Machine-Learning Classifier for Patients with Major Depressive Disorder: Multifeature Approach Based on a High-Order Minimum Spanning Tree Functional Brain Network

PubMed Central

Qin, Mengna; Chen, Junjie; Xu, Yong; Xiang, Jie

2017-01-01

High-order functional connectivity networks are rich in time information that can reflect dynamic changes in functional connectivity between brain regions. Accordingly, such networks are widely used to classify brain diseases. However, traditional methods for processing high-order functional connectivity networks generally include the clustering method, which reduces data dimensionality. As a result, such networks cannot be effectively interpreted in the context of neurology. Additionally, due to the large scale of high-order functional connectivity networks, it can be computationally very expensive to use complex network or graph theory to calculate certain topological properties. Here, we propose a novel method of generating a high-order minimum spanning tree functional connectivity network. This method increases the neurological significance of the high-order functional connectivity network, reduces network computing consumption, and produces a network scale that is conducive to subsequent network analysis. To ensure the quality of the topological information in the network structure, we used frequent subgraph mining technology to capture the discriminative subnetworks as features and combined this with quantifiable local network features. Then we applied a multikernel learning technique to the corresponding selected features to obtain the final classification results. We evaluated our proposed method using a data set containing 38 patients with major depressive disorder and 28 healthy controls. The experimental results showed a classification accuracy of up to 97.54%. PMID:29387141

Modulating Intrinsic Connectivity: Adjacent Subregions within Supplementary Motor Cortex, Dorsolateral Prefrontal Cortex, and Parietal Cortex Connect to Separate Functional Networks during Task and Also Connect during Rest

PubMed Central

Roth, Jennifer K.; Johnson, Marcia K.; Tokoglu, Fuyuze; Murphy, Isabella; Constable, R. Todd

2014-01-01

Supplementary motor area (SMA), the inferior frontal junction (IFJ), superior frontal junction (SFJ) and parietal cortex are active in many cognitive tasks. In a previous study, we found that subregions of each of these major areas were differentially active in component processes of executive function during working memory tasks. In the present study, each of these subregions was used as a seed in a whole brain functional connectivity analysis of working memory and resting state data. These regions show functional connectivity to different networks, thus supporting the parcellation of these major regions into functional subregions. Many regions showing significant connectivity during the working memory residual data (with task events regressed from the data) were also significantly connected during rest suggesting that these network connections to subregions within major regions of cortex are intrinsic. For some of these connections, task demands modulate activity in these intrinsic networks. Approximately half of the connections significant during task were significant during rest, indicating that some of the connections are intrinsic while others are recruited only in the service of the task. Furthermore, the network connections to traditional ‘task positive’ and ‘task negative’ (a.k.a ‘default mode’) regions shift from positive connectivity to negative connectivity depending on task demands. These findings demonstrate that such task-identified subregions are part of distinct networks, and that these networks have different patterns of connectivity for task as they do during rest, engaging connections both to task positive and task negative regions. These results have implications for understanding the parcellation of commonly active regions into more specific functional networks. PMID:24637793

Altered Brain Functional Connectivity in Betel Quid-Dependent Chewers.

PubMed

Huang, Xiaojun; Pu, Weidan; Liu, Haihong; Li, Xinmin; Greenshaw, Andrew J; Dursun, Serdar M; Xue, Zhimin; Liu, Zhening

2017-01-01

Betel quid (BQ) is a common psychoactive substance worldwide with particularly high usage in many Asian countries. This study aimed to explore the effect of BQ use on functional connectivity by comparing global functional brain networks and their subset between BQ chewers and healthy controls (HCs). Resting-state functional magnetic resonance imaging (fMRI) was obtained from 24 betel quid-dependent (BQD) male chewers and 27 healthy male individuals on a 3.0T scanner. We used independent component analysis (ICA) to determine components that represent the brain's functional networks and their spatial aspects of functional connectivity. Two sample t -tests were used to identify the functional connectivity differences in each network between these two groups. Seventeen networks were identified by ICA. Nine of them showed connectivity differences between BQD and HCs (two sample t -tests, p  < 0.001 uncorrected). We found increased functional connectivity in the orbitofrontal, bilateral frontoparietal, frontotemporal, occipital/parietal, frontotemporal/cerebellum, and temporal/limbic networks, and decreased connectivity in the parietal and medial frontal/anterior cingulate networks in the BQD compared to the HCs. The betel quid dependence scale scores were positively related to the increased functional connectivity in the orbitofrontal ( r  = 0.39, p  = 0.03) while negatively related to the decreased functional connectivity in medial frontal/anterior cingulate networks ( r  = -0.35, p  = 0.02). Our findings provide further evidence that BQ chewing may lead to brain functional connectivity changes, which may play a key role in the psychological and physiological effects of BQ.

Dissociated functional connectivity profiles for motor and attention deficits in acute right-hemisphere stroke

PubMed Central

Ramsey, Lenny; Rengachary, Jennifer; Zinn, Kristi; Siegel, Joshua S.; Metcalf, Nicholas V.; Strube, Michael J.; Snyder, Abraham Z.; Corbetta, Maurizio; Shulman, Gordon L.

2016-01-01

Strokes often cause multiple behavioural deficits that are correlated at the population level. Here, we show that motor and attention deficits are selectively associated with abnormal patterns of resting state functional connectivity in the dorsal attention and motor networks. We measured attention and motor deficits in 44 right hemisphere-damaged patients with a first-time stroke at 1–2 weeks post-onset. The motor battery included tests that evaluated deficits in both upper and lower extremities. The attention battery assessed both spatial and non-spatial attention deficits. Summary measures for motor and attention deficits were identified through principal component analyses on the raw behavioural scores. Functional connectivity in structurally normal cortex was estimated based on the temporal correlation of blood oxygenation level-dependent signals measured at rest with functional magnetic resonance imaging. Any correlation between motor and attention deficits and between functional connectivity in the dorsal attention network and motor networks that might spuriously affect the relationship between each deficit and functional connectivity was statistically removed. We report a double dissociation between abnormal functional connectivity patterns and attention and motor deficits, respectively. Attention deficits were significantly more correlated with abnormal interhemispheric functional connectivity within the dorsal attention network than motor networks, while motor deficits were significantly more correlated with abnormal interhemispheric functional connectivity patterns within the motor networks than dorsal attention network. These findings indicate that functional connectivity patterns in structurally normal cortex following a stroke link abnormal physiology in brain networks to the corresponding behavioural deficits. PMID:27225794

Network-Level Structure-Function Relationships in Human Neocortex

PubMed Central

Mišić, Bratislav; Betzel, Richard F.; de Reus, Marcel A.; van den Heuvel, Martijn P.; Berman, Marc G.; McIntosh, Anthony R.; Sporns, Olaf

2016-01-01

The dynamics of spontaneous fluctuations in neural activity are shaped by underlying patterns of anatomical connectivity. While numerous studies have demonstrated edge-wise correspondence between structural and functional connections, much less is known about how large-scale coherent functional network patterns emerge from the topology of structural networks. In the present study, we deploy a multivariate statistical technique, partial least squares, to investigate the association between spatially extended structural networks and functional networks. We find multiple statistically robust patterns, reflecting reliable combinations of structural and functional subnetworks that are optimally associated with one another. Importantly, these patterns generally do not show a one-to-one correspondence between structural and functional edges, but are instead distributed and heterogeneous, with many functional relationships arising from nonoverlapping sets of anatomical connections. We also find that structural connections between high-degree hubs are disproportionately represented, suggesting that these connections are particularly important in establishing coherent functional networks. Altogether, these results demonstrate that the network organization of the cerebral cortex supports the emergence of diverse functional network configurations that often diverge from the underlying anatomical substrate. PMID:27102654

Functional organization of intrinsic connectivity networks in Chinese-chess experts.

PubMed

Duan, Xujun; Long, Zhiliang; Chen, Huafu; Liang, Dongmei; Qiu, Lihua; Huang, Xiaoqi; Liu, Timon Cheng-Yi; Gong, Qiyong

2014-04-16

The functional architecture of the human brain has been extensively described in terms of functional connectivity networks, detected from the low-frequency coherent neuronal fluctuations during a resting state condition. Accumulating evidence suggests that the overall organization of functional connectivity networks is associated with individual differences in cognitive performance and prior experience. Such an association raises the question of how cognitive expertise exerts an influence on the topological properties of large-scale functional networks. To address this question, we examined the overall organization of brain functional networks in 20 grandmaster and master level Chinese-chess players (GM/M) and twenty novice players, by means of resting-state functional connectivity and graph theoretical analyses. We found that, relative to novices, functional connectivity was increased in GM/Ms between basal ganglia, thalamus, hippocampus, and several parietal and temporal areas, suggesting the influence of cognitive expertise on intrinsic connectivity networks associated with learning and memory. Furthermore, we observed economical small-world topology in the whole-brain functional connectivity networks in both groups, but GM/Ms exhibited significantly increased values of normalized clustering coefficient which resulted in increased small-world topology. These findings suggest an association between the functional organization of brain networks and individual differences in cognitive expertise, which might provide further evidence of the mechanisms underlying expert behavior. Copyright © 2014 Elsevier B.V. All rights reserved.

Resting-State Network Topology Differentiates Task Signals across the Adult Life Span.

PubMed

Chan, Micaela Y; Alhazmi, Fahd H; Park, Denise C; Savalia, Neil K; Wig, Gagan S

2017-03-08

Brain network connectivity differs across individuals. For example, older adults exhibit less segregated resting-state subnetworks relative to younger adults (Chan et al., 2014). It has been hypothesized that individual differences in network connectivity impact the recruitment of brain areas during task execution. While recent studies have described the spatial overlap between resting-state functional correlation (RSFC) subnetworks and task-evoked activity, it is unclear whether individual variations in the connectivity pattern of a brain area (topology) relates to its activity during task execution. We report data from 238 cognitively normal participants (humans), sampled across the adult life span (20-89 years), to reveal that RSFC-based network organization systematically relates to the recruitment of brain areas across two functionally distinct tasks (visual and semantic). The functional activity of brain areas (network nodes) were characterized according to their patterns of RSFC: nodes with relatively greater connections to nodes in their own functional system ("non-connector" nodes) exhibited greater activity than nodes with relatively greater connections to nodes in other systems ("connector" nodes). This "activation selectivity" was specific to those brain systems that were central to each of the tasks. Increasing age was accompanied by less differentiated network topology and a corresponding reduction in activation selectivity (or differentiation) across relevant network nodes. The results provide evidence that connectional topology of brain areas quantified at rest relates to the functional activity of those areas during task. Based on these findings, we propose a novel network-based theory for previous reports of the "dedifferentiation" in brain activity observed in aging. SIGNIFICANCE STATEMENT Similar to other real-world networks, the organization of brain networks impacts their function. As brain network connectivity patterns differ across individuals, we hypothesized that individual differences in network connectivity would relate to differences in brain activity. Using functional MRI in a group of individuals sampled across the adult life span (20-89 years), we measured correlations at rest and related the functional connectivity patterns to measurements of functional activity during two independent tasks. Brain activity varied in relation to connectivity patterns revealed by large-scale network analysis. This relationship tracked the differences in connectivity patterns accompanied by older age, providing important evidence for a link between the topology of areal connectivity measured at rest and the functional recruitment of these areas during task performance. Copyright © 2017 Chan et al.

Dynamic Functional Connectivity States Between the Dorsal and Ventral Sensorimotor Networks Revealed by Dynamic Conditional Correlation Analysis of Resting-State Functional Magnetic Resonance Imaging.

PubMed

Syed, Maleeha F; Lindquist, Martin A; Pillai, Jay J; Agarwal, Shruti; Gujar, Sachin K; Choe, Ann S; Caffo, Brian; Sair, Haris I

2017-12-01

Functional connectivity in resting-state functional magnetic resonance imaging (rs-fMRI) has received substantial attention since the initial findings of Biswal et al. Traditional network correlation metrics assume that the functional connectivity in the brain remains stationary over time. However, recent studies have shown that robust temporal fluctuations of functional connectivity among as well as within functional networks exist, challenging this assumption. In this study, these dynamic correlation differences were investigated between the dorsal and ventral sensorimotor networks by applying the dynamic conditional correlation model to rs-fMRI data of 20 healthy subjects. k-Means clustering was used to determine an optimal number of discrete connectivity states (k = 10) of the sensorimotor system across all subjects. Our analysis confirms the existence of differences in dynamic correlation between the dorsal and ventral networks, with highest connectivity found within the ventral motor network.

Disrupted Brain Functional Organization in Epilepsy Revealed by Graph Theory Analysis.

PubMed

Song, Jie; Nair, Veena A; Gaggl, Wolfgang; Prabhakaran, Vivek

2015-06-01

The human brain is a complex and dynamic system that can be modeled as a large-scale brain network to better understand the reorganizational changes secondary to epilepsy. In this study, we developed a brain functional network model using graph theory methods applied to resting-state fMRI data acquired from a group of epilepsy patients and age- and gender-matched healthy controls. A brain functional network model was constructed based on resting-state functional connectivity. A minimum spanning tree combined with proportional thresholding approach was used to obtain sparse connectivity matrices for each subject, which formed the basis of brain networks. We examined the brain reorganizational changes in epilepsy thoroughly at the level of the whole brain, the functional network, and individual brain regions. At the whole-brain level, local efficiency was significantly decreased in epilepsy patients compared with the healthy controls. However, global efficiency was significantly increased in epilepsy due to increased number of functional connections between networks (although weakly connected). At the functional network level, there were significant proportions of newly formed connections between the default mode network and other networks and between the subcortical network and other networks. There was a significant proportion of decreasing connections between the cingulo-opercular task control network and other networks. Individual brain regions from different functional networks, however, showed a distinct pattern of reorganizational changes in epilepsy. These findings suggest that epilepsy alters brain efficiency in a consistent pattern at the whole-brain level, yet alters brain functional networks and individual brain regions differently.

Test-retest reliability of functional connectivity networks during naturalistic fMRI paradigms.

PubMed

Wang, Jiahui; Ren, Yudan; Hu, Xintao; Nguyen, Vinh Thai; Guo, Lei; Han, Junwei; Guo, Christine Cong

2017-04-01

Functional connectivity analysis has become a powerful tool for probing the human brain function and its breakdown in neuropsychiatry disorders. So far, most studies adopted resting-state paradigm to examine functional connectivity networks in the brain, thanks to its low demand and high tolerance that are essential for clinical studies. However, the test-retest reliability of resting-state connectivity measures is moderate, potentially due to its low behavioral constraint. On the other hand, naturalistic neuroimaging paradigms, an emerging approach for cognitive neuroscience with high ecological validity, could potentially improve the reliability of functional connectivity measures. To test this hypothesis, we characterized the test-retest reliability of functional connectivity measures during a natural viewing condition, and benchmarked it against resting-state connectivity measures acquired within the same functional magnetic resonance imaging (fMRI) session. We found that the reliability of connectivity and graph theoretical measures of brain networks is significantly improved during natural viewing conditions over resting-state conditions, with an average increase of almost 50% across various connectivity measures. Not only sensory networks for audio-visual processing become more reliable, higher order brain networks, such as default mode and attention networks, but also appear to show higher reliability during natural viewing. Our results support the use of natural viewing paradigms in estimating functional connectivity of brain networks, and have important implications for clinical application of fMRI. Hum Brain Mapp 38:2226-2241, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Mutual connectivity analysis (MCA) using generalized radial basis function neural networks for nonlinear functional connectivity network recovery in resting-state functional MRI

NASA Astrophysics Data System (ADS)

D'Souza, Adora M.; Abidin, Anas Zainul; Nagarajan, Mahesh B.; Wismüller, Axel

2016-03-01

We investigate the applicability of a computational framework, called mutual connectivity analysis (MCA), for directed functional connectivity analysis in both synthetic and resting-state functional MRI data. This framework comprises of first evaluating non-linear cross-predictability between every pair of time series prior to recovering the underlying network structure using community detection algorithms. We obtain the non-linear cross-prediction score between time series using Generalized Radial Basis Functions (GRBF) neural networks. These cross-prediction scores characterize the underlying functionally connected networks within the resting brain, which can be extracted using non-metric clustering approaches, such as the Louvain method. We first test our approach on synthetic models with known directional influence and network structure. Our method is able to capture the directional relationships between time series (with an area under the ROC curve = 0.92 +/- 0.037) as well as the underlying network structure (Rand index = 0.87 +/- 0.063) with high accuracy. Furthermore, we test this method for network recovery on resting-state fMRI data, where results are compared to the motor cortex network recovered from a motor stimulation sequence, resulting in a strong agreement between the two (Dice coefficient = 0.45). We conclude that our MCA approach is effective in analyzing non-linear directed functional connectivity and in revealing underlying functional network structure in complex systems.

Mutual Connectivity Analysis (MCA) Using Generalized Radial Basis Function Neural Networks for Nonlinear Functional Connectivity Network Recovery in Resting-State Functional MRI.

PubMed

DSouza, Adora M; Abidin, Anas Zainul; Nagarajan, Mahesh B; Wismüller, Axel

2016-03-29

We investigate the applicability of a computational framework, called mutual connectivity analysis (MCA), for directed functional connectivity analysis in both synthetic and resting-state functional MRI data. This framework comprises of first evaluating non-linear cross-predictability between every pair of time series prior to recovering the underlying network structure using community detection algorithms. We obtain the non-linear cross-prediction score between time series using Generalized Radial Basis Functions (GRBF) neural networks. These cross-prediction scores characterize the underlying functionally connected networks within the resting brain, which can be extracted using non-metric clustering approaches, such as the Louvain method. We first test our approach on synthetic models with known directional influence and network structure. Our method is able to capture the directional relationships between time series (with an area under the ROC curve = 0.92 ± 0.037) as well as the underlying network structure (Rand index = 0.87 ± 0.063) with high accuracy. Furthermore, we test this method for network recovery on resting-state fMRI data, where results are compared to the motor cortex network recovered from a motor stimulation sequence, resulting in a strong agreement between the two (Dice coefficient = 0.45). We conclude that our MCA approach is effective in analyzing non-linear directed functional connectivity and in revealing underlying functional network structure in complex systems.

Reduced functional connectivity within and between ‘social’ resting state networks in autism spectrum conditions

PubMed Central

Stoyanova, Raliza S.; Baron-Cohen, Simon; Calder, Andrew J.

2013-01-01

Individuals with Autism Spectrum Conditions (ASC) have difficulties in social interaction and communication, which is reflected in hypoactivation of brain regions engaged in social processing, such as medial prefrontal cortex (mPFC), amygdala and insula. Resting state studies in ASC have identified reduced connectivity of the default mode network (DMN), which includes mPFC, suggesting that other resting state networks incorporating ‘social’ brain regions may also be abnormal. Using Seed-based Connectivity and Group Independent Component Analysis (ICA) approaches, we looked at resting functional connectivity in ASC between specific ‘social’ brain regions, as well as within and between whole networks incorporating these regions. We found reduced functional connectivity within the DMN in individuals with ASC, using both ICA and seed-based approaches. Two further networks identified by ICA, the salience network, incorporating the insula and a medial temporal lobe network, incorporating the amygdala, showed reduced inter-network connectivity. This was underlined by reduced seed-based connectivity between the insula and amygdala. The results demonstrate significantly reduced functional connectivity within and between resting state networks incorporating ‘social’ brain regions. This reduced connectivity may result in difficulties in communication and integration of information across these networks, which could contribute to the impaired processing of social signals in ASC. PMID:22563003

Resting-State Functional Connectivity in Individuals with Down Syndrome and Williams Syndrome Compared with Typically Developing Controls.

PubMed

Vega, Jennifer N; Hohman, Timothy J; Pryweller, Jennifer R; Dykens, Elisabeth M; Thornton-Wells, Tricia A

2015-10-01

The emergence of resting-state functional connectivity (rsFC) analysis, which examines temporal correlations of low-frequency (<0.1 Hz) blood oxygen level-dependent signal fluctuations between brain regions, has dramatically improved our understanding of the functional architecture of the typically developing (TD) human brain. This study examined rsFC in Down syndrome (DS) compared with another neurodevelopmental disorder, Williams syndrome (WS), and TD. Ten subjects with DS, 18 subjects with WS, and 40 subjects with TD each participated in a 3-Tesla MRI scan. We tested for group differences (DS vs. TD, DS vs. WS, and WS vs. TD) in between- and within-network rsFC connectivity for seven functional networks. For the DS group, we also examined associations between rsFC and other cognitive and genetic risk factors. In DS compared with TD, we observed higher levels of between-network connectivity in 6 out 21 network pairs but no differences in within-network connectivity. Participants with WS showed lower levels of within-network connectivity and no significant differences in between-network connectivity relative to DS. Finally, our comparison between WS and TD controls revealed lower within-network connectivity in multiple networks and higher between-network connectivity in one network pair relative to TD controls. While preliminary due to modest sample sizes, our findings suggest a global difference in between-network connectivity in individuals with neurodevelopmental disorders compared with controls and that such a difference is exacerbated across many brain regions in DS. However, this alteration in DS does not appear to extend to within-network connections, and therefore, the altered between-network connectivity must be interpreted within the framework of an intact intra-network pattern of activity. In contrast, WS shows markedly lower levels of within-network connectivity in the default mode network and somatomotor network relative to controls. These findings warrant further investigation using a task-based procedure that may help disentangle the relationship between brain function and cognitive performance across the spectrum of neurodevelopmental disorders.

Progressively Disrupted Brain Functional Connectivity Network in Subcortical Ischemic Vascular Cognitive Impairment Patients.

PubMed

Sang, Linqiong; Chen, Lin; Wang, Li; Zhang, Jingna; Zhang, Ye; Li, Pengyue; Li, Chuanming; Qiu, Mingguo

2018-01-01

Cognitive impairment caused by subcortical ischemic vascular disease (SIVD) has been elucidated by many neuroimaging studies. However, little is known regarding the changes in brain functional connectivity networks in relation to the severity of cognitive impairment in SIVD. In the present study, 20 subcortical ischemic vascular cognitive impairment no dementia patients (SIVCIND) and 20 dementia patients (SIVaD) were enrolled; additionally, 19 normal controls were recruited. Each participant underwent a resting-state functional MRI scan. Whole-brain functional networks were analyzed with graph theory and network-based statistics (NBS) to study the functional organization of networks and find alterations in functional connectivity among brain regions. After adjustments for age, gender, and duration of formal education, there were significant group differences for two network functional organization indices, global efficiency and local efficiency, which decreased (NC > SIVCIND > SIVaD) as cognitive impairment worsened. Between-group differences in functional connectivity (NBS corrected, p  < 0.01) mainly involved the orbitofrontal, parietal, and temporal cortices, as well as the basal ganglia. The brain connectivity network was progressively disrupted as cognitive impairment worsened, with an increased number of decreased connections between brain regions. We also observed more reductions in nodal efficiency in the prefrontal and temporal cortices for SIVaD than for SIVCIND. These findings indicated a progressively disrupted pattern of the brain functional connectivity network with increased cognitive impairment and showed promise for the development of reliable biomarkers of network metric changes related to cognitive impairment caused by SIVD.

Modulation of steady state functional connectivity in the default mode and working memory networks by cognitive load.

PubMed

Newton, Allen T; Morgan, Victoria L; Rogers, Baxter P; Gore, John C

2011-10-01

Interregional correlations between blood oxygen level dependent (BOLD) magnetic resonance imaging (fMRI) signals in the resting state have been interpreted as measures of connectivity across the brain. Here we investigate whether such connectivity in the working memory and default mode networks is modulated by changes in cognitive load. Functional connectivity was measured in a steady-state verbal identity N-back task for three different conditions (N = 1, 2, and 3) as well as in the resting state. We found that as cognitive load increases, the functional connectivity within both the working memory the default mode network increases. To test whether functional connectivity between the working memory and the default mode networks changed, we constructed maps of functional connectivity to the working memory network as a whole and found that increasingly negative correlations emerged in a dorsal region of the posterior cingulate cortex. These results provide further evidence that low frequency fluctuations in BOLD signals reflect variations in neural activity and suggests interaction between the default mode network and other cognitive networks. Copyright © 2010 Wiley-Liss, Inc.

EEG-based functional networks evoked by acupuncture at ST 36: A data-driven thresholding study

NASA Astrophysics Data System (ADS)

Li, Huiyan; Wang, Jiang; Yi, Guosheng; Deng, Bin; Zhou, Hexi

2017-10-01

This paper investigates how acupuncture at ST 36 modulates the brain functional network. 20 channel EEG signals from 15 healthy subjects are respectively recorded before, during and after acupuncture. The correlation between two EEG channels is calculated by using Pearson’s coefficient. A data-driven approach is applied to determine the threshold, which is performed by considering the connected set, connected edge and network connectivity. Based on such thresholding approach, the functional network in each acupuncture period is built with graph theory, and the associated functional connectivity is determined. We show that acupuncturing at ST 36 increases the connectivity of the EEG-based functional network, especially for the long distance ones between two hemispheres. The properties of the functional network in five EEG sub-bands are also characterized. It is found that the delta and gamma bands are affected more obviously by acupuncture than the other sub-bands. These findings highlight the modulatory effects of acupuncture on the EEG-based functional connectivity, which is helpful for us to understand how it participates in the cortical or subcortical activities. Further, the data-driven threshold provides an alternative approach to infer the functional connectivity under other physiological conditions.

Network topology and functional connectivity disturbances precede the onset of Huntington’s disease

PubMed Central

Harrington, Deborah L.; Rubinov, Mikail; Durgerian, Sally; Mourany, Lyla; Reece, Christine; Koenig, Katherine; Bullmore, Ed; Long, Jeffrey D.; Paulsen, Jane S.

2015-01-01

Cognitive, motor and psychiatric changes in prodromal Huntington’s disease have nurtured the emergent need for early interventions. Preventive clinical trials for Huntington’s disease, however, are limited by a shortage of suitable measures that could serve as surrogate outcomes. Measures of intrinsic functional connectivity from resting-state functional magnetic resonance imaging are of keen interest. Yet recent studies suggest circumscribed abnormalities in resting-state functional magnetic resonance imaging connectivity in prodromal Huntington’s disease, despite the spectrum of behavioural changes preceding a manifest diagnosis. The present study used two complementary analytical approaches to examine whole-brain resting-state functional magnetic resonance imaging connectivity in prodromal Huntington’s disease. Network topology was studied using graph theory and simple functional connectivity amongst brain regions was explored using the network-based statistic. Participants consisted of gene-negative controls (n = 16) and prodromal Huntington’s disease individuals (n = 48) with various stages of disease progression to examine the influence of disease burden on intrinsic connectivity. Graph theory analyses showed that global network interconnectivity approximated a random network topology as proximity to diagnosis neared and this was associated with decreased connectivity amongst highly-connected rich-club network hubs, which integrate processing from diverse brain regions. However, functional segregation within the global network (average clustering) was preserved. Functional segregation was also largely maintained at the local level, except for the notable decrease in the diversity of anterior insula intermodular-interconnections (participation coefficient), irrespective of disease burden. In contrast, network-based statistic analyses revealed patterns of weakened frontostriatal connections and strengthened frontal-posterior connections that evolved as disease burden increased. These disturbances were often related to long-range connections involving peripheral nodes and interhemispheric connections. A strong association was found between weaker connectivity and decreased rich-club organization, indicating that whole-brain simple connectivity partially expressed disturbances in the communication of highly-connected hubs. However, network topology and network-based statistic connectivity metrics did not correlate with key markers of executive dysfunction (Stroop Test, Trail Making Test) in prodromal Huntington’s disease, which instead were related to whole-brain connectivity disturbances in nodes (right inferior parietal, right thalamus, left anterior cingulate) that exhibited multiple aberrant connections and that mediate executive control. Altogether, our results show for the first time a largely disease burden-dependent functional reorganization of whole-brain networks in prodromal Huntington’s disease. Both analytic approaches provided a unique window into brain reorganization that was not related to brain atrophy or motor symptoms. Longitudinal studies currently in progress will chart the course of functional changes to determine the most sensitive markers of disease progression. PMID:26059655

Network topology and functional connectivity disturbances precede the onset of Huntington's disease.

PubMed

Harrington, Deborah L; Rubinov, Mikail; Durgerian, Sally; Mourany, Lyla; Reece, Christine; Koenig, Katherine; Bullmore, Ed; Long, Jeffrey D; Paulsen, Jane S; Rao, Stephen M

2015-08-01

Cognitive, motor and psychiatric changes in prodromal Huntington's disease have nurtured the emergent need for early interventions. Preventive clinical trials for Huntington's disease, however, are limited by a shortage of suitable measures that could serve as surrogate outcomes. Measures of intrinsic functional connectivity from resting-state functional magnetic resonance imaging are of keen interest. Yet recent studies suggest circumscribed abnormalities in resting-state functional magnetic resonance imaging connectivity in prodromal Huntington's disease, despite the spectrum of behavioural changes preceding a manifest diagnosis. The present study used two complementary analytical approaches to examine whole-brain resting-state functional magnetic resonance imaging connectivity in prodromal Huntington's disease. Network topology was studied using graph theory and simple functional connectivity amongst brain regions was explored using the network-based statistic. Participants consisted of gene-negative controls (n = 16) and prodromal Huntington's disease individuals (n = 48) with various stages of disease progression to examine the influence of disease burden on intrinsic connectivity. Graph theory analyses showed that global network interconnectivity approximated a random network topology as proximity to diagnosis neared and this was associated with decreased connectivity amongst highly-connected rich-club network hubs, which integrate processing from diverse brain regions. However, functional segregation within the global network (average clustering) was preserved. Functional segregation was also largely maintained at the local level, except for the notable decrease in the diversity of anterior insula intermodular-interconnections (participation coefficient), irrespective of disease burden. In contrast, network-based statistic analyses revealed patterns of weakened frontostriatal connections and strengthened frontal-posterior connections that evolved as disease burden increased. These disturbances were often related to long-range connections involving peripheral nodes and interhemispheric connections. A strong association was found between weaker connectivity and decreased rich-club organization, indicating that whole-brain simple connectivity partially expressed disturbances in the communication of highly-connected hubs. However, network topology and network-based statistic connectivity metrics did not correlate with key markers of executive dysfunction (Stroop Test, Trail Making Test) in prodromal Huntington's disease, which instead were related to whole-brain connectivity disturbances in nodes (right inferior parietal, right thalamus, left anterior cingulate) that exhibited multiple aberrant connections and that mediate executive control. Altogether, our results show for the first time a largely disease burden-dependent functional reorganization of whole-brain networks in prodromal Huntington's disease. Both analytic approaches provided a unique window into brain reorganization that was not related to brain atrophy or motor symptoms. Longitudinal studies currently in progress will chart the course of functional changes to determine the most sensitive markers of disease progression. © The Author (2015). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Resting-state networks associated with cognitive processing show more age-related decline than those associated with emotional processing.

PubMed

Nashiro, Kaoru; Sakaki, Michiko; Braskie, Meredith N; Mather, Mara

2017-06-01

Correlations in activity across disparate brain regions during rest reveal functional networks in the brain. Although previous studies largely agree that there is an age-related decline in the "default mode network," how age affects other resting-state networks, such as emotion-related networks, is still controversial. Here we used a dual-regression approach to investigate age-related alterations in resting-state networks. The results revealed age-related disruptions in functional connectivity in all 5 identified cognitive networks, namely the default mode network, cognitive-auditory, cognitive-speech (or speech-related somatosensory), and right and left frontoparietal networks, whereas such age effects were not observed in the 3 identified emotion networks. In addition, we observed age-related decline in functional connectivity in 3 visual and 3 motor/visuospatial networks. Older adults showed greater functional connectivity in regions outside 4 out of the 5 identified cognitive networks, consistent with the dedifferentiation effect previously observed in task-based functional magnetic resonance imaging studies. Both reduced within-network connectivity and increased out-of-network connectivity were correlated with poor cognitive performance, providing potential biomarkers for cognitive aging. Copyright © 2017 Elsevier Inc. All rights reserved.

Thalamocortical functional connectivity in Lennox-Gastaut syndrome is abnormally enhanced in executive-control and default-mode networks.

PubMed

Warren, Aaron E L; Abbott, David F; Jackson, Graeme D; Archer, John S

2017-12-01

To identify abnormal thalamocortical circuits in the severe epilepsy of Lennox-Gastaut syndrome (LGS) that may explain the shared electroclinical phenotype and provide potential treatment targets. Twenty patients with a diagnosis of LGS (mean age = 28.5 years) and 26 healthy controls (mean age = 27.6 years) were compared using task-free functional magnetic resonance imaging (MRI). The thalamus was parcellated according to functional connectivity with 10 cortical networks derived using group-level independent component analysis. For each cortical network, we assessed between-group differences in thalamic functional connectivity strength using nonparametric permutation-based tests. Anatomical locations were identified by quantifying spatial overlap with a histologically informed thalamic MRI atlas. In both groups, posterior thalamic regions showed functional connectivity with visual, auditory, and sensorimotor networks, whereas anterior, medial, and dorsal thalamic regions were connected with networks of distributed association cortex (including the default-mode, anterior-salience, and executive-control networks). Four cortical networks (left and right executive-control network; ventral and dorsal default-mode network) showed significantly enhanced thalamic functional connectivity strength in patients relative to controls. Abnormal connectivity was maximal in mediodorsal and ventrolateral thalamic nuclei. Specific thalamocortical circuits are affected in LGS. Functional connectivity is abnormally enhanced between the mediodorsal and ventrolateral thalamus and the default-mode and executive-control networks, thalamocortical circuits that normally support diverse cognitive processes. In contrast, thalamic regions connecting with primary and sensory cortical networks appear to be less affected. Our previous neuroimaging studies show that epileptic activity in LGS is expressed via the default-mode and executive-control networks. Results of the present study suggest that the mediodorsal and ventrolateral thalamus may be candidate targets for modulating abnormal network behavior underlying LGS, potentially via emerging thalamic neurostimulation therapies. Wiley Periodicals, Inc. © 2017 International League Against Epilepsy.

Hyperconnective and hypoconnective cortical and subcortical functional networks in multiple system atrophy.

PubMed

Rosskopf, Johannes; Gorges, Martin; Müller, Hans-Peter; Pinkhardt, Elmar H; Ludolph, Albert C; Kassubek, Jan

2018-04-01

In multiple system atrophy (MSA), the organization of the functional brain connectivity within cortical and subcortical networks and its clinical correlates remains to be investigated. Whole-brain based 'resting-state' fMRI data were obtained from 22 MSA patients (11 MSA-C, 11 MSA-P) and 22 matched healthy controls, together with standardized clinical assessment and video-oculographic recordings (EyeLink ® ). MSA patients vs. controls showed significantly higher ponto-cerebellar functional connectivity and lower default mode network connectivity (p < .05, corrected). No differences were observed in the motor network and in the control network. The higher the ponto-cerebellar network functional connectivity was, the more pronounced was smooth pursuit impairment. This functional connectivity analysis supports a network-dependent combination of hyper- and hypoconnectivity states in MSA, in agreement with adaptive compensatory responses (hyperconnectivity) and a function disconnection syndrome (hypoconnectivity) that may occur in a consecutive sequence. Copyright © 2018 Elsevier Ltd. All rights reserved.

Altered Functional Connectivity of the Default Mode Network in Low-Empathy Subjects

PubMed Central

Kim, Seung Jun; Kim, Sung-Eun; Kim, Hyo Eun; Han, Kiwan; Jeong, Bumseok; Kim, Jae-Jin; Namkoong, Kee

2017-01-01

Empathy is the ability to identify with or make a vicariously experience of another person's feelings or thoughts based on memory and/or self-referential mental simulation. The default mode network in particular is related to self-referential empathy. In order to elucidate the possible neural mechanisms underlying empathy, we investigated the functional connectivity of the default mode network in subjects from a general population. Resting state functional magnetic resonance imaging data were acquired from 19 low-empathy subjects and 18 medium-empathy subjects. An independent component analysis was used to identify the default mode network, and differences in functional connectivity strength were compared between the two groups. The low-empathy group showed lower functional connectivity of the medial prefrontal cortex and anterior cingulate cortex (Brodmann areas 9 and 32) within the default mode network, compared to the medium-empathy group. The results of the present study suggest that empathy is related to functional connectivity of the medial prefrontal cortex/anterior cingulate cortex within the default mode network. Functional decreases in connectivity among low-empathy subjects may reflect an impairment of self-referential mental simulation. PMID:28792155

Random matrix theory for analyzing the brain functional network in attention deficit hyperactivity disorder

NASA Astrophysics Data System (ADS)

Wang, Rong; Wang, Li; Yang, Yong; Li, Jiajia; Wu, Ying; Lin, Pan

2016-11-01

Attention deficit hyperactivity disorder (ADHD) is the most common childhood neuropsychiatric disorder and affects approximately 6 -7 % of children worldwide. Here, we investigate the statistical properties of undirected and directed brain functional networks in ADHD patients based on random matrix theory (RMT), in which the undirected functional connectivity is constructed based on correlation coefficient and the directed functional connectivity is measured based on cross-correlation coefficient and mutual information. We first analyze the functional connectivity and the eigenvalues of the brain functional network. We find that ADHD patients have increased undirected functional connectivity, reflecting a higher degree of linear dependence between regions, and increased directed functional connectivity, indicating stronger causality and more transmission of information among brain regions. More importantly, we explore the randomness of the undirected and directed functional networks using RMT. We find that for ADHD patients, the undirected functional network is more orderly than that for normal subjects, which indicates an abnormal increase in undirected functional connectivity. In addition, we find that the directed functional networks are more random, which reveals greater disorder in causality and more chaotic information flow among brain regions in ADHD patients. Our results not only further confirm the efficacy of RMT in characterizing the intrinsic properties of brain functional networks but also provide insights into the possibilities RMT offers for improving clinical diagnoses and treatment evaluations for ADHD patients.

Brain functional network abnormality extends beyond the sensorimotor network in brachial plexus injury patients.

PubMed

Feng, Jun-Tao; Liu, Han-Qiu; Hua, Xu-Yun; Gu, Yu-Dong; Xu, Jian-Guang; Xu, Wen-Dong

2016-12-01

Brachial plexus injury (BPI) is a type of severe peripheral nerve trauma that leads to central remodeling in the brain, as revealed by functional MRI analysis. However, previously reported remodeling is mostly restricted to sensorimotor areas of the brain. Whether this disturbance in the sensorimotor network leads to larger-scale functional remodeling remains unknown. We sought to explore the higher-level brain functional abnormality pattern of BPI patients from a large-scale network function connectivity dimension in 15 right-handed BPI patients. Resting-state functional MRI data were collected and analyzed using independent component analysis methods. Five components of interest were recognized and compared between patients and healthy subjects. Patients showed significantly altered brain local functional activities in the bilateral fronto-parietal network (FPN), sensorimotor network (SMN), and executive-control network (ECN) compared with healthy subjects. Moreover, functional connectivity between SMN and ECN were significantly less in patients compared with healthy subjects, and connectivity strength between ECN and SMN was negatively correlated with patients' residual function of the affected limb. Functional connectivity between SMN and right FPN were also significantly less than in controls, although connectivity between ECN and default mode network (DMN) was greater than in controls. These data suggested that brain functional disturbance in BPI patients extends beyond the sensorimotor network and cascades serial remodeling in the brain, which significantly correlates with residual hand function of the paralyzed limb. Furthermore, functional remodeling in these higher-level functional networks may lead to cognitive alterations in complex tasks.

Influence of cerebrovascular disease on brain networks in prodromal and clinical Alzheimer's disease.

PubMed

Chong, Joanna Su Xian; Liu, Siwei; Loke, Yng Miin; Hilal, Saima; Ikram, Mohammad Kamran; Xu, Xin; Tan, Boon Yeow; Venketasubramanian, Narayanaswamy; Chen, Christopher Li-Hsian; Zhou, Juan

2017-11-01

Network-sensitive neuroimaging methods have been used to characterize large-scale brain network degeneration in Alzheimer's disease and its prodrome. However, few studies have investigated the combined effect of Alzheimer's disease and cerebrovascular disease on brain network degeneration. Our study sought to examine the intrinsic functional connectivity and structural covariance network changes in 235 prodromal and clinical Alzheimer's disease patients with and without cerebrovascular disease. We focused particularly on two higher-order cognitive networks-the default mode network and the executive control network. We found divergent functional connectivity and structural covariance patterns in Alzheimer's disease patients with and without cerebrovascular disease. Alzheimer's disease patients without cerebrovascular disease, but not Alzheimer's disease patients with cerebrovascular disease, showed reductions in posterior default mode network functional connectivity. By comparison, while both groups exhibited parietal reductions in executive control network functional connectivity, only Alzheimer's disease patients with cerebrovascular disease showed increases in frontal executive control network connectivity. Importantly, these distinct executive control network changes were recapitulated in prodromal Alzheimer's disease patients with and without cerebrovascular disease. Across Alzheimer's disease patients with and without cerebrovascular disease, higher default mode network functional connectivity z-scores correlated with greater hippocampal volumes while higher executive control network functional connectivity z-scores correlated with greater white matter changes. In parallel, only Alzheimer's disease patients without cerebrovascular disease showed increased default mode network structural covariance, while only Alzheimer's disease patients with cerebrovascular disease showed increased executive control network structural covariance compared to controls. Our findings demonstrate the differential neural network structural and functional changes in Alzheimer's disease with and without cerebrovascular disease, suggesting that the underlying pathology of Alzheimer's disease patients with cerebrovascular disease might differ from those without cerebrovascular disease and reflect a combination of more severe cerebrovascular disease and less severe Alzheimer's disease network degeneration phenotype. © The Author (2017). Published by Oxford University Press on behalf of the Guarantors of Brain.

Brain network dysregulation, emotion, and complaints after mild traumatic brain injury.

PubMed

van der Horn, Harm J; Liemburg, Edith J; Scheenen, Myrthe E; de Koning, Myrthe E; Marsman, Jan-Bernard C; Spikman, Jacoba M; van der Naalt, Joukje

2016-04-01

To assess the role of brain networks in emotion regulation and post-traumatic complaints in the sub-acute phase after non-complicated mild traumatic brain injury (mTBI). Fifty-four patients with mTBI (34 with and 20 without complaints) and 20 healthy controls (group-matched for age, sex, education, and handedness) were included. Resting-state fMRI was performed at four weeks post-injury. Static and dynamic functional connectivity were studied within and between the default mode, executive (frontoparietal and bilateral frontal network), and salience network. The hospital anxiety and depression scale (HADS) was used to measure anxiety (HADS-A) and depression (HADS-D). Regarding within-network functional connectivity, none of the selected brain networks were different between groups. Regarding between-network interactions, patients with complaints exhibited lower functional connectivity between the bilateral frontal and salience network compared to patients without complaints. In the total patient group, higher HADS-D scores were related to lower functional connectivity between the bilateral frontal network and both the right frontoparietal and salience network, and to higher connectivity between the right frontoparietal and salience network. Furthermore, whereas higher HADS-D scores were associated with lower connectivity within the parietal midline areas of the bilateral frontal network, higher HADS-A scores were related to lower connectivity within medial prefrontal areas of the bilateral frontal network. Functional interactions of the executive and salience networks were related to emotion regulation and complaints after mTBI, with a key role for the bilateral frontal network. These findings may have implications for future studies on the effect of psychological interventions. © 2016 Wiley Periodicals, Inc.

Decreased Functional Brain Connectivity in Adolescents with Internet Addiction

PubMed Central

Hong, Soon-Beom; Zalesky, Andrew; Cocchi, Luca; Fornito, Alex; Choi, Eun-Jung; Kim, Ho-Hyun; Suh, Jeong-Eun; Kim, Chang-Dai; Kim, Jae-Won; Yi, Soon-Hyung

2013-01-01

Background Internet addiction has become increasingly recognized as a mental disorder, though its neurobiological basis is unknown. This study used functional neuroimaging to investigate whole-brain functional connectivity in adolescents diagnosed with internet addiction. Based on neurobiological changes seen in other addiction related disorders, it was predicted that connectivity disruptions in adolescents with internet addiction would be most prominent in cortico-striatal circuitry. Methods Participants were 12 adolescents diagnosed with internet addiction and 11 healthy comparison subjects. Resting-state functional magnetic resonance images were acquired, and group differences in brain functional connectivity were analyzed using the network-based statistic. We also analyzed network topology, testing for between-group differences in key graph-based network measures. Results Adolescents with internet addiction showed reduced functional connectivity spanning a distributed network. The majority of impaired connections involved cortico-subcortical circuits (∼24% with prefrontal and ∼27% with parietal cortex). Bilateral putamen was the most extensively involved subcortical brain region. No between-group difference was observed in network topological measures, including the clustering coefficient, characteristic path length, or the small-worldness ratio. Conclusions Internet addiction is associated with a widespread and significant decrease of functional connectivity in cortico-striatal circuits, in the absence of global changes in brain functional network topology. PMID:23451272

A new class of methods for functional connectivity estimation

NASA Astrophysics Data System (ADS)

Lin, Wutu

Measuring functional connectivity from neural recordings is important in understanding processing in cortical networks. The covariance-based methods are the current golden standard for functional connectivity estimation. However, the link between the pair-wise correlations and the physiological connections inside the neural network is unclear. Therefore, the power of inferring physiological basis from functional connectivity estimation is limited. To build a stronger tie and better understand the relationship between functional connectivity and physiological neural network, we need (1) a realistic model to simulate different types of neural recordings with known ground truth for benchmarking; (2) a new functional connectivity method that produce estimations closely reflecting the physiological basis. In this thesis, (1) I tune a spiking neural network model to match with human sleep EEG data, (2) introduce a new class of methods for estimating connectivity from different kinds of neural signals and provide theory proof for its superiority, (3) apply it to simulated fMRI data as an application.

Bimanual Motor Coordination in Older Adults Is Associated with Increased Functional Brain Connectivity – A Graph-Theoretical Analysis

PubMed Central

Heitger, Marcus H.; Goble, Daniel J.; Dhollander, Thijs; Dupont, Patrick; Caeyenberghs, Karen; Leemans, Alexander; Sunaert, Stefan; Swinnen, Stephan P.

2013-01-01

In bimanual coordination, older and younger adults activate a common cerebral network but the elderly also have additional activation in a secondary network of brain areas to master task performance. It remains unclear whether the functional connectivity within these primary and secondary motor networks differs between the old and the young and whether task difficulty modulates connectivity. We applied graph-theoretical network analysis (GTNA) to task-driven fMRI data in 16 elderly and 16 young participants using a bimanual coordination task including in-phase and anti-phase flexion/extension wrist movements. Network nodes for the GTNA comprised task-relevant brain areas as defined by fMRI activation foci. The elderly matched the motor performance of the young but showed an increased functional connectivity in both networks across a wide range of connectivity metrics, i.e., higher mean connectivity degree, connection strength, network density and efficiency, together with shorter mean communication path length between the network nodes and also a lower betweenness centrality. More difficult movements showed an increased connectivity in both groups. The network connectivity of both groups had “small world” character. The present findings indicate (a) that bimanual coordination in the aging brain is associated with a higher functional connectivity even between areas also activated in young adults, independently from task difficulty, and (b) that adequate motor coordination in the context of task-driven bimanual control in older adults may not be solely due to additional neural recruitment but also to aging-related changes of functional relationships between brain regions. PMID:23637982

Influence of cerebrovascular disease on brain networks in prodromal and clinical Alzheimer’s disease

PubMed Central

Chong, Joanna Su Xian; Liu, Siwei; Loke, Yng Miin; Hilal, Saima; Ikram, Mohammad Kamran; Xu, Xin; Tan, Boon Yeow; Venketasubramanian, Narayanaswamy; Chen, Christopher Li-Hsian

2017-01-01

Abstract Network-sensitive neuroimaging methods have been used to characterize large-scale brain network degeneration in Alzheimer’s disease and its prodrome. However, few studies have investigated the combined effect of Alzheimer’s disease and cerebrovascular disease on brain network degeneration. Our study sought to examine the intrinsic functional connectivity and structural covariance network changes in 235 prodromal and clinical Alzheimer’s disease patients with and without cerebrovascular disease. We focused particularly on two higher-order cognitive networks—the default mode network and the executive control network. We found divergent functional connectivity and structural covariance patterns in Alzheimer’s disease patients with and without cerebrovascular disease. Alzheimer’s disease patients without cerebrovascular disease, but not Alzheimer’s disease patients with cerebrovascular disease, showed reductions in posterior default mode network functional connectivity. By comparison, while both groups exhibited parietal reductions in executive control network functional connectivity, only Alzheimer’s disease patients with cerebrovascular disease showed increases in frontal executive control network connectivity. Importantly, these distinct executive control network changes were recapitulated in prodromal Alzheimer’s disease patients with and without cerebrovascular disease. Across Alzheimer’s disease patients with and without cerebrovascular disease, higher default mode network functional connectivity z-scores correlated with greater hippocampal volumes while higher executive control network functional connectivity z-scores correlated with greater white matter changes. In parallel, only Alzheimer’s disease patients without cerebrovascular disease showed increased default mode network structural covariance, while only Alzheimer’s disease patients with cerebrovascular disease showed increased executive control network structural covariance compared to controls. Our findings demonstrate the differential neural network structural and functional changes in Alzheimer’s disease with and without cerebrovascular disease, suggesting that the underlying pathology of Alzheimer’s disease patients with cerebrovascular disease might differ from those without cerebrovascular disease and reflect a combination of more severe cerebrovascular disease and less severe Alzheimer’s disease network degeneration phenotype. PMID:29053778

Default mode network connectivity as a function of familial and environmental risk for psychotic disorder.

PubMed

Peeters, Sanne C T; van de Ven, Vincent; Gronenschild, Ed H B M; Patel, Ameera X; Habets, Petra; Goebel, Rainer; van Os, Jim; Marcelis, Machteld

2015-01-01

Research suggests that altered interregional connectivity in specific networks, such as the default mode network (DMN), is associated with cognitive and psychotic symptoms in schizophrenia. In addition, frontal and limbic connectivity alterations have been associated with trauma, drug use and urban upbringing, though these environmental exposures have never been examined in relation to DMN functional connectivity in psychotic disorder. Resting-state functional MRI scans were obtained from 73 patients with psychotic disorder, 83 non-psychotic siblings of patients with psychotic disorder and 72 healthy controls. Posterior cingulate cortex (PCC) seed-based correlation analysis was used to estimate functional connectivity within the DMN. DMN functional connectivity was examined in relation to group (familial risk), group × environmental exposure (to cannabis, developmental trauma and urbanicity) and symptomatology. There was a significant association between group and PCC connectivity with the inferior parietal lobule (IPL), the precuneus (PCu) and the medial prefrontal cortex (MPFC). Compared to controls, patients and siblings had increased PCC connectivity with the IPL, PCu and MPFC. In the IPL and PCu, the functional connectivity of siblings was intermediate to that of controls and patients. No significant associations were found between DMN connectivity and (subclinical) psychotic/cognitive symptoms. In addition, there were no significant interactions between group and environmental exposures in the model of PCC functional connectivity. Increased functional connectivity in individuals with (increased risk for) psychotic disorder may reflect trait-related network alterations. The within-network "connectivity at rest" intermediate phenotype was not associated with (subclinical) psychotic or cognitive symptoms. The association between familial risk and DMN connectivity was not conditional on environmental exposure.

Stimulus-Elicited Connectivity Influences Resting-State Connectivity Years Later in Human Development: A Prospective Study.

PubMed

Gabard-Durnam, Laurel Joy; Gee, Dylan Grace; Goff, Bonnie; Flannery, Jessica; Telzer, Eva; Humphreys, Kathryn Leigh; Lumian, Daniel Stephen; Fareri, Dominic Stephen; Caldera, Christina; Tottenham, Nim

2016-04-27

Although the functional architecture of the brain is indexed by resting-state connectivity networks, little is currently known about the mechanisms through which these networks assemble into stable mature patterns. The current study posits and tests the long-term phasic molding hypothesis that resting-state networks are gradually shaped by recurring stimulus-elicited connectivity across development by examining how both stimulus-elicited and resting-state functional connections of the human brain emerge over development at the systems level. Using a sequential design following 4- to 18-year-olds over a 2 year period, we examined the predictive associations between stimulus-elicited and resting-state connectivity in amygdala-cortical circuitry as an exemplar case (given this network's protracted development across these ages). Age-related changes in amygdala functional connectivity converged on the same regions of medial prefrontal cortex (mPFC) and inferior frontal gyrus when elicited by emotional stimuli and when measured at rest. Consistent with the long-term phasic molding hypothesis, prospective analyses for both connections showed that the magnitude of an individual's stimulus-elicited connectivity unidirectionally predicted resting-state functional connectivity 2 years later. For the amygdala-mPFC connection, only stimulus-elicited connectivity during childhood and the transition to adolescence shaped future resting-state connectivity, consistent with a sensitive period ending with adolescence for the amygdala-mPFC circuit. Together, these findings suggest that resting-state functional architecture may arise from phasic patterns of functional connectivity elicited by environmental stimuli over the course of development on the order of years. A fundamental issue in understanding the ontogeny of brain function is how resting-state (intrinsic) functional networks emerge and relate to stimulus-elicited functional connectivity. Here, we posit and test the long-term phasic molding hypothesis that resting-state network development is influenced by recurring stimulus-elicited connectivity through prospective examination of the developing human amygdala-cortical functional connections. Our results provide critical insight into how early environmental events sculpt functional network architecture across development and highlight childhood as a potential developmental period of heightened malleability for the amygdala-medial prefrontal cortex circuit. These findings have implications for how both positive and adverse experiences influence the developing brain and motivate future investigations of whether this molding mechanism reflects a general phenomenon of brain development. Copyright © 2016 the authors 0270-6474/16/364772-14$15.00/0.

Stimulus-Elicited Connectivity Influences Resting-State Connectivity Years Later in Human Development: A Prospective Study

PubMed Central

Gee, Dylan Grace; Goff, Bonnie; Flannery, Jessica; Telzer, Eva; Humphreys, Kathryn Leigh; Lumian, Daniel Stephen; Fareri, Dominic Stephen; Caldera, Christina; Tottenham, Nim

2016-01-01

Although the functional architecture of the brain is indexed by resting-state connectivity networks, little is currently known about the mechanisms through which these networks assemble into stable mature patterns. The current study posits and tests the long-term phasic molding hypothesis that resting-state networks are gradually shaped by recurring stimulus-elicited connectivity across development by examining how both stimulus-elicited and resting-state functional connections of the human brain emerge over development at the systems level. Using a sequential design following 4- to 18-year-olds over a 2 year period, we examined the predictive associations between stimulus-elicited and resting-state connectivity in amygdala-cortical circuitry as an exemplar case (given this network's protracted development across these ages). Age-related changes in amygdala functional connectivity converged on the same regions of medial prefrontal cortex (mPFC) and inferior frontal gyrus when elicited by emotional stimuli and when measured at rest. Consistent with the long-term phasic molding hypothesis, prospective analyses for both connections showed that the magnitude of an individual's stimulus-elicited connectivity unidirectionally predicted resting-state functional connectivity 2 years later. For the amygdala-mPFC connection, only stimulus-elicited connectivity during childhood and the transition to adolescence shaped future resting-state connectivity, consistent with a sensitive period ending with adolescence for the amygdala-mPFC circuit. Together, these findings suggest that resting-state functional architecture may arise from phasic patterns of functional connectivity elicited by environmental stimuli over the course of development on the order of years. SIGNIFICANCE STATEMENT A fundamental issue in understanding the ontogeny of brain function is how resting-state (intrinsic) functional networks emerge and relate to stimulus-elicited functional connectivity. Here, we posit and test the long-term phasic molding hypothesis that resting-state network development is influenced by recurring stimulus-elicited connectivity through prospective examination of the developing human amygdala-cortical functional connections. Our results provide critical insight into how early environmental events sculpt functional network architecture across development and highlight childhood as a potential developmental period of heightened malleability for the amygdala-medial prefrontal cortex circuit. These findings have implications for how both positive and adverse experiences influence the developing brain and motivate future investigations of whether this molding mechanism reflects a general phenomenon of brain development. PMID:27122035

Increased resting state functional connectivity in the fronto-parietal and default mode network in anorexia nervosa

PubMed Central

Boehm, Ilka; Geisler, Daniel; King, Joseph A.; Ritschel, Franziska; Seidel, Maria; Deza Araujo, Yacila; Petermann, Juliane; Lohmeier, Heidi; Weiss, Jessika; Walter, Martin; Roessner, Veit; Ehrlich, Stefan

2014-01-01

The etiology of anorexia nervosa (AN) is poorly understood. Results from functional brain imaging studies investigating the neural profile of AN using cognitive and emotional task paradigms are difficult to reconcile. Task-related imaging studies often require a high level of compliance and can only partially explore the distributed nature and complexity of brain function. In this study, resting state functional connectivity imaging was used to investigate well-characterized brain networks potentially relevant to understand the neural mechanisms underlying the symptomatology and etiology of AN. Resting state functional magnetic resonance imaging data was obtained from 35 unmedicated female acute AN patients and 35 closely matched healthy controls female participants (HC) and decomposed using spatial group independent component analyses (ICA). Using validated templates, we identified components covering the fronto-parietal “control” network, the default mode network (DMN), the salience network, the visual and the sensory-motor network. Group comparison revealed an increased functional connectivity between the angular gyrus and the other parts of the fronto-parietal network in patients with AN in comparison to HC. Connectivity of the angular gyrus was positively associated with self-reported persistence in HC. In the DMN, AN patients also showed an increased functional connectivity strength in the anterior insula in comparison to HC. Anterior insula connectivity was associated with self-reported problems with interoceptive awareness. This study, with one of the largest sample to date, shows that acute AN is associated with abnormal brain connectivity in two major resting state networks (RSN). The finding of an increased functional connectivity in the fronto-parietal network adds novel support for the notion of AN as a disorder of excessive cognitive control, whereas the elevated functional connectivity of the anterior insula with the DMN may reflect the high levels of self- and body-focused ruminations when AN patients are at rest. PMID:25324749

Exploration of Functional Connectivity During Preferred Music Stimulation in Patients with Disorders of Consciousness

PubMed Central

Heine, Lizette; Castro, Maïté; Martial, Charlotte; Tillmann, Barbara; Laureys, Steven; Perrin, Fabien

2015-01-01

Preferred music is a highly emotional and salient stimulus, which has previously been shown to increase the probability of auditory cognitive event-related responses in patients with disorders of consciousness (DOC). To further investigate whether and how music modifies the functional connectivity of the brain in DOC, five patients were assessed with both a classical functional connectivity scan (control condition), and a scan while they were exposed to their preferred music (music condition). Seed-based functional connectivity (left or right primary auditory cortex), and mean network connectivity of three networks linked to conscious sound perception were assessed. The auditory network showed stronger functional connectivity with the left precentral gyrus and the left dorsolateral prefrontal cortex during music as compared to the control condition. Furthermore, functional connectivity of the external network was enhanced during the music condition in the temporo-parietal junction. Although caution should be taken due to small sample size, these results suggest that preferred music exposure might have effects on patients auditory network (implied in rhythm and music perception) and on cerebral regions linked to autobiographical memory. PMID:26617542

Methylphenidate Modulates Functional Network Connectivity to Enhance Attention

PubMed Central

Zhang, Sheng; Hsu, Wei-Ting; Scheinost, Dustin; Finn, Emily S.; Shen, Xilin; Constable, R. Todd; Li, Chiang-Shan R.; Chun, Marvin M.

2016-01-01

Recent work has demonstrated that human whole-brain functional connectivity patterns measured with fMRI contain information about cognitive abilities, including sustained attention. To derive behavioral predictions from connectivity patterns, our group developed a connectome-based predictive modeling (CPM) approach (Finn et al., 2015; Rosenberg et al., 2016). Previously using CPM, we defined a high-attention network, comprising connections positively correlated with performance on a sustained attention task, and a low-attention network, comprising connections negatively correlated with performance. Validating the networks as generalizable biomarkers of attention, models based on network strength at rest predicted attention-deficit/hyperactivity disorder (ADHD) symptoms in an independent group of individuals (Rosenberg et al., 2016). To investigate whether these networks play a causal role in attention, here we examined their strength in healthy adults given methylphenidate (Ritalin), a common ADHD treatment, compared with unmedicated controls. As predicted, individuals given methylphenidate showed patterns of connectivity associated with better sustained attention: higher high-attention and lower low-attention network strength than controls. There was significant overlap between the high-attention network and a network with greater strength in the methylphenidate group, and between the low-attention network and a network with greater strength in the control group. Network strength also predicted behavior on a stop-signal task, such that participants with higher go response rates showed higher high-attention and lower low-attention network strength. These results suggest that methylphenidate acts by modulating functional brain networks related to sustained attention, and that changing whole-brain connectivity patterns may help improve attention. SIGNIFICANCE STATEMENT Recent work identified a promising neuromarker of sustained attention based on whole-brain functional connectivity networks. To investigate the causal role of these networks in attention, we examined their response to a dose of methylphenidate, a common and effective treatment for attention-deficit/hyperactivity disorder, in healthy adults. As predicted, individuals on methylphenidate showed connectivity signatures of better sustained attention: higher high-attention and lower low-attention network strength than controls. These results suggest that methylphenidate acts by modulating strength in functional brain networks related to attention, and that changing whole-brain connectivity patterns may improve attention. PMID:27629707

Methylphenidate Modulates Functional Network Connectivity to Enhance Attention.

PubMed

Rosenberg, Monica D; Zhang, Sheng; Hsu, Wei-Ting; Scheinost, Dustin; Finn, Emily S; Shen, Xilin; Constable, R Todd; Li, Chiang-Shan R; Chun, Marvin M

2016-09-14

Recent work has demonstrated that human whole-brain functional connectivity patterns measured with fMRI contain information about cognitive abilities, including sustained attention. To derive behavioral predictions from connectivity patterns, our group developed a connectome-based predictive modeling (CPM) approach (Finn et al., 2015; Rosenberg et al., 2016). Previously using CPM, we defined a high-attention network, comprising connections positively correlated with performance on a sustained attention task, and a low-attention network, comprising connections negatively correlated with performance. Validating the networks as generalizable biomarkers of attention, models based on network strength at rest predicted attention-deficit/hyperactivity disorder (ADHD) symptoms in an independent group of individuals (Rosenberg et al., 2016). To investigate whether these networks play a causal role in attention, here we examined their strength in healthy adults given methylphenidate (Ritalin), a common ADHD treatment, compared with unmedicated controls. As predicted, individuals given methylphenidate showed patterns of connectivity associated with better sustained attention: higher high-attention and lower low-attention network strength than controls. There was significant overlap between the high-attention network and a network with greater strength in the methylphenidate group, and between the low-attention network and a network with greater strength in the control group. Network strength also predicted behavior on a stop-signal task, such that participants with higher go response rates showed higher high-attention and lower low-attention network strength. These results suggest that methylphenidate acts by modulating functional brain networks related to sustained attention, and that changing whole-brain connectivity patterns may help improve attention. Recent work identified a promising neuromarker of sustained attention based on whole-brain functional connectivity networks. To investigate the causal role of these networks in attention, we examined their response to a dose of methylphenidate, a common and effective treatment for attention-deficit/hyperactivity disorder, in healthy adults. As predicted, individuals on methylphenidate showed connectivity signatures of better sustained attention: higher high-attention and lower low-attention network strength than controls. These results suggest that methylphenidate acts by modulating strength in functional brain networks related to attention, and that changing whole-brain connectivity patterns may improve attention. Copyright © 2016 the authors 0270-6474/16/369547-11$15.00/0.

Age differences in the functional interactions among the default, frontoparietal control, and dorsal attention networks.

PubMed

Grady, Cheryl; Sarraf, Saman; Saverino, Cristina; Campbell, Karen

2016-05-01

Older adults typically show weaker functional connectivity (FC) within brain networks compared with young adults, but stronger functional connections between networks. Our primary aim here was to use a graph theoretical approach to identify age differences in the FC of 3 networks-default mode network (DMN), dorsal attention network, and frontoparietal control (FPC)-during rest and task conditions and test the hypothesis that age differences in the FPC would influence age differences in the other networks, consistent with its role as a cognitive "switch." At rest, older adults showed lower clustering values compared with the young, and both groups showed more between-network connections involving the FPC than the other 2 networks, but this difference was greater in the older adults. Connectivity within the DMN was reduced in older compared with younger adults. Consistent with our hypothesis, between-network connections of the FPC at rest predicted the age-related reduction in connectivity within the DMN. There was no age difference in within-network FC during the task (after removing the specific task effect), but between-network connections were greater in older adults than in young adults for the FPC and dorsal attention network. In addition, age reductions were found in almost all the graph metrics during the task condition, including clustering and modularity. Finally, age differences in between-network connectivity of the FPC during both rest and task predicted cognitive performance. These findings provide additional evidence of less within-network but greater between-network FC in older adults during rest but also show that these age differences can be altered by the residual influence of task demands on background connectivity. Our results also support a role for the FPC as the regulator of other brain networks in the service of cognition. Critically, the link between age differences in inter-network connections of the FPC and DMN connectivity, and the link between FPC connectivity and performance, support the hypothesis that FC of the FPC influences the expression of age differences in other networks, as well as differences in cognitive function. Copyright © 2016 Elsevier Inc. All rights reserved.

Sparse dictionary learning of resting state fMRI networks.

PubMed

Eavani, Harini; Filipovych, Roman; Davatzikos, Christos; Satterthwaite, Theodore D; Gur, Raquel E; Gur, Ruben C

2012-07-02

Research in resting state fMRI (rsfMRI) has revealed the presence of stable, anti-correlated functional subnetworks in the brain. Task-positive networks are active during a cognitive process and are anti-correlated with task-negative networks, which are active during rest. In this paper, based on the assumption that the structure of the resting state functional brain connectivity is sparse, we utilize sparse dictionary modeling to identify distinct functional sub-networks. We propose two ways of formulating the sparse functional network learning problem that characterize the underlying functional connectivity from different perspectives. Our results show that the whole-brain functional connectivity can be concisely represented with highly modular, overlapping task-positive/negative pairs of sub-networks.

Track-weighted functional connectivity (TW-FC): a tool for characterizing the structural-functional connections in the brain.

PubMed

Calamante, Fernando; Masterton, Richard A J; Tournier, Jacques-Donald; Smith, Robert E; Willats, Lisa; Raffelt, David; Connelly, Alan

2013-04-15

MRI provides a powerful tool for studying the functional and structural connections in the brain non-invasively. The technique of functional connectivity (FC) exploits the intrinsic temporal correlations of slow spontaneous signal fluctuations to characterise brain functional networks. In addition, diffusion MRI fibre-tracking can be used to study the white matter structural connections. In recent years, there has been considerable interest in combining these two techniques to provide an overall structural-functional description of the brain. In this work we applied the recently proposed super-resolution track-weighted imaging (TWI) methodology to demonstrate how whole-brain fibre-tracking data can be combined with FC data to generate a track-weighted (TW) FC map of FC networks. The method was applied to data from 8 healthy volunteers, and illustrated with (i) FC networks obtained using a seeded connectivity-based analysis (seeding in the precuneus/posterior cingulate cortex, PCC, known to be part of the default mode network), and (ii) with FC networks generated using independent component analysis (in particular, the default mode, attention, visual, and sensory-motor networks). TW-FC maps showed high intensity in white matter structures connecting the nodes of the FC networks. For example, the cingulum bundles show the strongest TW-FC values in the PCC seeded-based analysis, due to their major role in the connection between medial frontal cortex and precuneus/posterior cingulate cortex; similarly the superior longitudinal fasciculus was well represented in the attention network, the optic radiations in the visual network, and the corticospinal tract and corpus callosum in the sensory-motor network. The TW-FC maps highlight the white matter connections associated with a given FC network, and their intensity in a given voxel reflects the functional connectivity of the part of the nodes of the network linked by the structural connections traversing that voxel. They therefore contain a different (and novel) image contrast from that of the images used to generate them. The results shown in this study illustrate the potential of the TW-FC approach for the fusion of structural and functional data into a single quantitative image. This technique could therefore have important applications in neuroscience and neurology, such as for voxel-based comparison studies. Copyright © 2012 Elsevier Inc. All rights reserved.

Dynamic functional connectivity analysis reveals transient states of dysconnectivity in schizophrenia.

PubMed

Damaraju, E; Allen, E A; Belger, A; Ford, J M; McEwen, S; Mathalon, D H; Mueller, B A; Pearlson, G D; Potkin, S G; Preda, A; Turner, J A; Vaidya, J G; van Erp, T G; Calhoun, V D

2014-01-01

Schizophrenia is a psychotic disorder characterized by functional dysconnectivity or abnormal integration between distant brain regions. Recent functional imaging studies have implicated large-scale thalamo-cortical connectivity as being disrupted in patients. However, observed connectivity differences in schizophrenia have been inconsistent between studies, with reports of hyperconnectivity and hypoconnectivity between the same brain regions. Using resting state eyes-closed functional imaging and independent component analysis on a multi-site data that included 151 schizophrenia patients and 163 age- and gender matched healthy controls, we decomposed the functional brain data into 100 components and identified 47 as functionally relevant intrinsic connectivity networks. We subsequently evaluated group differences in functional network connectivity, both in a static sense, computed as the pairwise Pearson correlations between the full network time courses (5.4 minutes in length), and a dynamic sense, computed using sliding windows (44 s in length) and k-means clustering to characterize five discrete functional connectivity states. Static connectivity analysis revealed that compared to healthy controls, patients show significantly stronger connectivity, i.e., hyperconnectivity, between the thalamus and sensory networks (auditory, motor and visual), as well as reduced connectivity (hypoconnectivity) between sensory networks from all modalities. Dynamic analysis suggests that (1), on average, schizophrenia patients spend much less time than healthy controls in states typified by strong, large-scale connectivity, and (2), that abnormal connectivity patterns are more pronounced during these connectivity states. In particular, states exhibiting cortical-subcortical antagonism (anti-correlations) and strong positive connectivity between sensory networks are those that show the group differences of thalamic hyperconnectivity and sensory hypoconnectivity. Group differences are weak or absent during other connectivity states. Dynamic analysis also revealed hypoconnectivity between the putamen and sensory networks during the same states of thalamic hyperconnectivity; notably, this finding cannot be observed in the static connectivity analysis. Finally, in post-hoc analyses we observed that the relationships between sub-cortical low frequency power and connectivity with sensory networks is altered in patients, suggesting different functional interactions between sub-cortical nuclei and sensorimotor cortex during specific connectivity states. While important differences between patients with schizophrenia and healthy controls have been identified, one should interpret the results with caution given the history of medication in patients. Taken together, our results support and expand current knowledge regarding dysconnectivity in schizophrenia, and strongly advocate the use of dynamic analyses to better account for and understand functional connectivity differences.

Dynamic functional connectivity analysis reveals transient states of dysconnectivity in schizophrenia

PubMed Central

Damaraju, E.; Allen, E.A.; Belger, A.; Ford, J.M.; McEwen, S.; Mathalon, D.H.; Mueller, B.A.; Pearlson, G.D.; Potkin, S.G.; Preda, A.; Turner, J.A.; Vaidya, J.G.; van Erp, T.G.; Calhoun, V.D.

2014-01-01

Schizophrenia is a psychotic disorder characterized by functional dysconnectivity or abnormal integration between distant brain regions. Recent functional imaging studies have implicated large-scale thalamo-cortical connectivity as being disrupted in patients. However, observed connectivity differences in schizophrenia have been inconsistent between studies, with reports of hyperconnectivity and hypoconnectivity between the same brain regions. Using resting state eyes-closed functional imaging and independent component analysis on a multi-site data that included 151 schizophrenia patients and 163 age- and gender matched healthy controls, we decomposed the functional brain data into 100 components and identified 47 as functionally relevant intrinsic connectivity networks. We subsequently evaluated group differences in functional network connectivity, both in a static sense, computed as the pairwise Pearson correlations between the full network time courses (5.4 minutes in length), and a dynamic sense, computed using sliding windows (44 s in length) and k-means clustering to characterize five discrete functional connectivity states. Static connectivity analysis revealed that compared to healthy controls, patients show significantly stronger connectivity, i.e., hyperconnectivity, between the thalamus and sensory networks (auditory, motor and visual), as well as reduced connectivity (hypoconnectivity) between sensory networks from all modalities. Dynamic analysis suggests that (1), on average, schizophrenia patients spend much less time than healthy controls in states typified by strong, large-scale connectivity, and (2), that abnormal connectivity patterns are more pronounced during these connectivity states. In particular, states exhibiting cortical–subcortical antagonism (anti-correlations) and strong positive connectivity between sensory networks are those that show the group differences of thalamic hyperconnectivity and sensory hypoconnectivity. Group differences are weak or absent during other connectivity states. Dynamic analysis also revealed hypoconnectivity between the putamen and sensory networks during the same states of thalamic hyperconnectivity; notably, this finding cannot be observed in the static connectivity analysis. Finally, in post-hoc analyses we observed that the relationships between sub-cortical low frequency power and connectivity with sensory networks is altered in patients, suggesting different functional interactions between sub-cortical nuclei and sensorimotor cortex during specific connectivity states. While important differences between patients with schizophrenia and healthy controls have been identified, one should interpret the results with caution given the history of medication in patients. Taken together, our results support and expand current knowledge regarding dysconnectivity in schizophrenia, and strongly advocate the use of dynamic analyses to better account for and understand functional connectivity differences. PMID:25161896

Organization of brain networks governed by long-range connections index autistic traits in the general population

PubMed Central

2013-01-01

Background The dimensional approach to autism spectrum disorder (ASD) considers ASD as the extreme of a dimension traversing through the entire population. We explored the potential utility of electroencephalography (EEG) functional connectivity as a biomarker. We hypothesized that individual differences in autistic traits of typical subjects would involve a long-range connectivity diminution within the delta band. Methods Resting-state EEG functional connectivity was measured for 74 neurotypical subjects. All participants also provided a questionnaire (Social Responsiveness Scale, SRS) that was completed by an informant who knows the participant in social settings. We conducted multivariate regression between the SRS score and functional connectivity in all EEG frequency bands. We explored modulations of network graph metrics characterizing the optimality of a network using the SRS score. Results Our results show a decay in functional connectivity mainly within the delta and theta bands (the lower part of the EEG spectrum) associated with an increasing number of autistic traits. When inspecting the impact of autistic traits on the global organization of the functional network, we found that the optimal properties of the network are inversely related to the number of autistic traits, suggesting that the autistic dimension, throughout the entire population, modulates the efficiency of functional brain networks. Conclusions EEG functional connectivity at low frequencies and its associated network properties may be associated with some autistic traits in the general population. PMID:23806204

A method for functional network connectivity among spatially independent resting-state components in schizophrenia.

PubMed

Jafri, Madiha J; Pearlson, Godfrey D; Stevens, Michael; Calhoun, Vince D

2008-02-15

Functional connectivity of the brain has been studied by analyzing correlation differences in time courses among seed voxels or regions with other voxels of the brain in healthy individuals as well as in patients with brain disorders. The spatial extent of strongly temporally coherent brain regions co-activated during rest has also been examined using independent component analysis (ICA). However, the weaker temporal relationships among ICA component time courses, which we operationally define as a measure of functional network connectivity (FNC), have not yet been studied. In this study, we propose an approach for evaluating FNC and apply it to functional magnetic resonance imaging (fMRI) data collected from persons with schizophrenia and healthy controls. We examined the connectivity and latency among ICA component time courses to test the hypothesis that patients with schizophrenia would show increased functional connectivity and increased lag among resting state networks compared to controls. Resting state fMRI data were collected and the inter-relationships among seven selected resting state networks (identified using group ICA) were evaluated by correlating each subject's ICA time courses with one another. Patients showed higher correlation than controls among most of the dominant resting state networks. Patients also had slightly more variability in functional connectivity than controls. We present a novel approach for quantifying functional connectivity among brain networks identified with spatial ICA. Significant differences between patient and control connectivity in different networks were revealed possibly reflecting deficiencies in cortical processing in patients.

A Method for Functional Network Connectivity Among Spatially Independent Resting-State Components in Schizophrenia

PubMed Central

Jafri, Madiha J; Pearlson, Godfrey D; Stevens, Michael; Calhoun, Vince D

2011-01-01

Functional connectivity of the brain has been studied by analyzing correlation differences in time courses among seed voxels or regions with other voxels of the brain in patients versus controls. The spatial extent of strongly temporally coherent brain regions co-activated during rest has also been examined using independent component analysis (ICA). However, the weaker temporal relationships among ICA component time courses, which we operationally define as a measure of functional network connectivity (FNC), have not yet been studied. In this study, we propose an approach for evaluating FNC and apply it to functional magnetic resonance imaging (fMRI) data collected from persons with schizophrenia and healthy controls. We examined the connectivity and latency among ICA component time courses to test the hypothesis that patients with schizophrenia would show increased functional connectivity and increased lag among resting state networks compared to controls. Resting state fMRI data were collected and the inter-relationships among seven selected resting state networks (identified using group ICA) were evaluated by correlating each subject’s ICA time courses with one another. Patients showed higher correlation than controls among most of the dominant resting state networks. Patients also had slightly more variability in functional connectivity than controls. We present a novel approach for quantifying functional connectivity among brain networks identified with spatial ICA. Significant differences between patient and control connectivity in different networks were revealed possibly reflecting deficiencies in cortical processing in patients. PMID:18082428

Reduced integration and differentiation of the imitation network in autism: A combined functional connectivity magnetic resonance imaging and diffusion-weighted imaging study.

PubMed

Fishman, Inna; Datko, Michael; Cabrera, Yuliana; Carper, Ruth A; Müller, Ralph-Axel

2015-12-01

Converging evidence indicates that brain abnormalities in autism spectrum disorder (ASD) involve atypical network connectivity, but few studies have integrated functional with structural connectivity measures. This multimodal investigation examined functional and structural connectivity of the imitation network in children and adolescents with ASD, and its links with clinical symptoms. Resting state functional magnetic resonance imaging and diffusion-weighted imaging were performed in 35 participants with ASD and 35 typically developing controls, aged 8 to 17 years, matched for age, gender, intelligence quotient, and head motion. Within-network analyses revealed overall reduced functional connectivity (FC) between distributed imitation regions in the ASD group. Whole brain analyses showed that underconnectivity in ASD occurred exclusively in regions belonging to the imitation network, whereas overconnectivity was observed between imitation nodes and extraneous regions. Structurally, reduced fractional anisotropy and increased mean diffusivity were found in white matter tracts directly connecting key imitation regions with atypical FC in ASD. These differences in microstructural organization of white matter correlated with weaker FC and greater ASD symptomatology. Findings demonstrate atypical connectivity of the brain network supporting imitation in ASD, characterized by a highly specific pattern. This pattern of underconnectivity within, but overconnectivity outside the functional network is in contrast with typical development and suggests reduced network integration and differentiation in ASD. Our findings also indicate that atypical connectivity of the imitation network may contribute to ASD clinical symptoms, highlighting the role of this fundamental social cognition ability in the pathophysiology of ASD. © 2015 American Neurological Association.

Altered Functional Connectivity of the Default Mode Network in Low-Empathy Subjects.

PubMed

Kim, Seung Jun; Kim, Sung Eun; Kim, Hyo Eun; Han, Kiwan; Jeong, Bumseok; Kim, Jae Jin; Namkoong, Kee; Kim, Ji Woong

2017-09-01

Empathy is the ability to identify with or make a vicariously experience of another person's feelings or thoughts based on memory and/or self-referential mental simulation. The default mode network in particular is related to self-referential empathy. In order to elucidate the possible neural mechanisms underlying empathy, we investigated the functional connectivity of the default mode network in subjects from a general population. Resting state functional magnetic resonance imaging data were acquired from 19 low-empathy subjects and 18 medium-empathy subjects. An independent component analysis was used to identify the default mode network, and differences in functional connectivity strength were compared between the two groups. The low-empathy group showed lower functional connectivity of the medial prefrontal cortex and anterior cingulate cortex (Brodmann areas 9 and 32) within the default mode network, compared to the medium-empathy group. The results of the present study suggest that empathy is related to functional connectivity of the medial prefrontal cortex/anterior cingulate cortex within the default mode network. Functional decreases in connectivity among low-empathy subjects may reflect an impairment of self-referential mental simulation. © Copyright: Yonsei University College of Medicine 2017.

Resting state brain network function in major depression - Depression symptomatology, antidepressant treatment effects, future research.

PubMed

Brakowski, Janis; Spinelli, Simona; Dörig, Nadja; Bosch, Oliver Gero; Manoliu, Andrei; Holtforth, Martin Grosse; Seifritz, Erich

2017-09-01

The alterations of functional connectivity brain networks in major depressive disorder (MDD) have been subject of a large number of studies. Using different methodologies and focusing on diverse aspects of the disease, research shows heterogeneous results lacking integration. Disrupted network connectivity has been found in core MDD networks like the default mode network (DMN), the central executive network (CEN), and the salience network, but also in cerebellar and thalamic circuitries. Here we review literature published on resting state brain network function in MDD focusing on methodology, and clinical characteristics including symptomatology and antidepressant treatment related findings. There are relatively few investigations concerning the qualitative aspects of symptomatology of MDD, whereas most studies associate quantitative aspects with distinct resting state functional connectivity alterations. Such depression severity associated alterations are found in the DMN, frontal, cerebellar and thalamic brain regions as well as the insula and the subgenual anterior cingulate cortex. Similarly, different therapeutical options in MDD and their effects on brain function showed patchy results. Herein, pharmaceutical treatments reveal functional connectivity alterations throughout multiple brain regions notably the DMN, fronto-limbic, and parieto-temporal regions. Psychotherapeutical interventions show significant functional connectivity alterations in fronto-limbic networks, whereas electroconvulsive therapy and repetitive transcranial magnetic stimulation result in alterations of the subgenual anterior cingulate cortex, the DMN, the CEN and the dorsal lateral prefrontal cortex. While it appears clear that functional connectivity alterations are associated with the pathophysiology and treatment of MDD, future research should also generate a common strategy for data acquisition and analysis, as a least common denominator, to set the basis for comparability across studies and implementation of functional connectivity as a scientifically and clinically useful biomarker. Copyright © 2017 Elsevier Ltd. All rights reserved.

Distinct Aging Effects on Functional Networks in Good and Poor Cognitive Performers

PubMed Central

Lee, Annie; Tan, Mingzhen; Qiu, Anqi

2016-01-01

Brain network hubs are susceptible to normal aging processes and disruptions of their functional connectivity are detrimental to decline in cognitive functions in older adults. However, it remains unclear how the functional connectivity of network hubs cope with cognitive heterogeneity in an aging population. This study utilized cognitive and resting-state functional magnetic resonance imaging data, cluster analysis, and graph network analysis to examine age-related alterations in the network hubs’ functional connectivity of good and poor cognitive performers. Our results revealed that poor cognitive performers showed age-dependent disruptions in the functional connectivity of the right insula and posterior cingulate cortex (PCC), while good cognitive performers showed age-related disruptions in the functional connectivity of the left insula and PCC. Additionally, the left PCC had age-related declines in the functional connectivity with the left medial prefrontal cortex (mPFC) and anterior cingulate cortex (ACC). Most interestingly, good cognitive performers showed age-related declines in the functional connectivity of the left insula and PCC with their right homotopic structures. These results may provide insights of neuronal correlates for understanding individual differences in aging. In particular, our study suggests prominent protection roles of the left insula and PCC and bilateral ACC in good performers. PMID:27667972

Whole brain resting-state analysis reveals decreased functional connectivity in major depression.

PubMed

Veer, Ilya M; Beckmann, Christian F; van Tol, Marie-José; Ferrarini, Luca; Milles, Julien; Veltman, Dick J; Aleman, André; van Buchem, Mark A; van der Wee, Nic J; Rombouts, Serge A R B

2010-01-01

Recently, both increases and decreases in resting-state functional connectivity have been found in major depression. However, these studies only assessed functional connectivity within a specific network or between a few regions of interest, while comorbidity and use of medication was not always controlled for. Therefore, the aim of the current study was to investigate whole-brain functional connectivity, unbiased by a priori definition of regions or networks of interest, in medication-free depressive patients without comorbidity. We analyzed resting-state fMRI data of 19 medication-free patients with a recent diagnosis of major depression (within 6 months before inclusion) and no comorbidity, and 19 age- and gender-matched controls. Independent component analysis was employed on the concatenated data sets of all participants. Thirteen functionally relevant networks were identified, describing the entire study sample. Next, individual representations of the networks were created using a dual regression method. Statistical inference was subsequently done on these spatial maps using voxel-wise permutation tests. Abnormal functional connectivity was found within three resting-state networks in depression: (1) decreased bilateral amygdala and left anterior insula connectivity in an affective network, (2) reduced connectivity of the left frontal pole in a network associated with attention and working memory, and (3) decreased bilateral lingual gyrus connectivity within ventromedial visual regions. None of these effects were associated with symptom severity or gray matter density. We found abnormal resting-state functional connectivity not previously associated with major depression, which might relate to abnormal affect regulation and mild cognitive deficits, both associated with the symptomatology of the disorder.

Whole Brain Resting-State Analysis Reveals Decreased Functional Connectivity in Major Depression

PubMed Central

Veer, Ilya M.; Beckmann, Christian F.; van Tol, Marie-José; Ferrarini, Luca; Milles, Julien; Veltman, Dick J.; Aleman, André; van Buchem, Mark A.; van der Wee, Nic J.; Rombouts, Serge A.R.B.

2010-01-01

Recently, both increases and decreases in resting-state functional connectivity have been found in major depression. However, these studies only assessed functional connectivity within a specific network or between a few regions of interest, while comorbidity and use of medication was not always controlled for. Therefore, the aim of the current study was to investigate whole-brain functional connectivity, unbiased by a priori definition of regions or networks of interest, in medication-free depressive patients without comorbidity. We analyzed resting-state fMRI data of 19 medication-free patients with a recent diagnosis of major depression (within 6 months before inclusion) and no comorbidity, and 19 age- and gender-matched controls. Independent component analysis was employed on the concatenated data sets of all participants. Thirteen functionally relevant networks were identified, describing the entire study sample. Next, individual representations of the networks were created using a dual regression method. Statistical inference was subsequently done on these spatial maps using voxel-wise permutation tests. Abnormal functional connectivity was found within three resting-state networks in depression: (1) decreased bilateral amygdala and left anterior insula connectivity in an affective network, (2) reduced connectivity of the left frontal pole in a network associated with attention and working memory, and (3) decreased bilateral lingual gyrus connectivity within ventromedial visual regions. None of these effects were associated with symptom severity or gray matter density. We found abnormal resting-state functional connectivity not previously associated with major depression, which might relate to abnormal affect regulation and mild cognitive deficits, both associated with the symptomatology of the disorder. PMID:20941370

EEG functional connectivity is partially predicted by underlying white matter connectivity

PubMed Central

Chu, CJ; Tanaka, N; Diaz, J; Edlow, BL; Wu, O; Hämäläinen, M; Stufflebeam, S; Cash, SS; Kramer, MA.

2015-01-01

Over the past decade, networks have become a leading model to illustrate both the anatomical relationships (structural networks) and the coupling of dynamic physiology (functional networks) linking separate brain regions. The relationship between these two levels of description remains incompletely understood and an area of intense research interest. In particular, it is unclear how cortical currents relate to underlying brain structural architecture. In addition, although theory suggests that brain communication is highly frequency dependent, how structural connections influence overlying functional connectivity in different frequency bands has not been previously explored. Here we relate functional networks inferred from statistical associations between source imaging of EEG activity and underlying cortico-cortical structural brain connectivity determined by probabilistic white matter tractography. We evaluate spontaneous fluctuating cortical brain activity over a long time scale (minutes) and relate inferred functional networks to underlying structural connectivity for broadband signals, as well as in seven distinct frequency bands. We find that cortical networks derived from source EEG estimates partially reflect both direct and indirect underlying white matter connectivity in all frequency bands evaluated. In addition, we find that when structural support is absent, functional connectivity is significantly reduced for high frequency bands compared to low frequency bands. The association between cortical currents and underlying white matter connectivity highlights the obligatory interdependence of functional and structural networks in the human brain. The increased dependence on structural support for the coupling of higher frequency brain rhythms provides new evidence for how underlying anatomy directly shapes emergent brain dynamics at fast time scales. PMID:25534110

Retinotopic patterns of functional connectivity between V1 and large-scale brain networks during resting fixation

PubMed Central

Griffis, Joseph C.; Elkhetali, Abdurahman S.; Burge, Wesley K.; Chen, Richard H.; Bowman, Anthony D.; Szaflarski, Jerzy P.; Visscher, Kristina M.

2016-01-01

Psychophysical and neurobiological evidence suggests that central and peripheral vision are specialized for different functions. This specialization of function might be expected to lead to differences in the large-scale functional interactions of early cortical areas that represent central and peripheral visual space. Here, we characterize differences in whole-brain functional connectivity among sectors in primary visual cortex (V1) corresponding to central, near-peripheral, and far-peripheral vision during resting fixation. Importantly, our analyses reveal that eccentricity sectors in V1 have different functional connectivity with non-visual areas associated with large-scale brain networks. Regions associated with the fronto-parietal control network are most strongly connected with central sectors of V1, regions associated with the cingulo-opercular control network are most strongly connected with near-peripheral sectors of V1, and regions associated with the default mode and auditory networks are most strongly connected with far-peripheral sectors of V1. Additional analyses suggest that similar patterns are present during eyes-closed rest. These results suggest that different types of visual information may be prioritized by large-scale brain networks with distinct functional profiles, and provide insights into how the small-scale functional specialization within early visual regions such as V1 relates to the large-scale organization of functionally distinct whole-brain networks. PMID:27554527

Spinal Cord Injury Disrupts Resting-State Networks in the Human Brain.

PubMed

Hawasli, Ammar H; Rutlin, Jerrel; Roland, Jarod L; Murphy, Rory K J; Song, Sheng-Kwei; Leuthardt, Eric C; Shimony, Joshua S; Ray, Wilson Z

2018-03-15

Despite 253,000 spinal cord injury (SCI) patients in the United States, little is known about how SCI affects brain networks. Spinal MRI provides only structural information with no insight into functional connectivity. Resting-state functional MRI (RS-fMRI) quantifies network connectivity through the identification of resting-state networks (RSNs) and allows detection of functionally relevant changes during disease. Given the robust network of spinal cord afferents to the brain, we hypothesized that SCI produces meaningful changes in brain RSNs. RS-fMRIs and functional assessments were performed on 10 SCI subjects. Blood oxygen-dependent RS-fMRI sequences were acquired. Seed-based correlation mapping was performed using five RSNs: default-mode (DMN), dorsal-attention (DAN), salience (SAL), control (CON), and somatomotor (SMN). RSNs were compared with normal control subjects using false-discovery rate-corrected two way t tests. SCI reduced brain network connectivity within the SAL, SMN, and DMN and disrupted anti-correlated connectivity between CON and SMN. When divided into separate cohorts, complete but not incomplete SCI disrupted connectivity within SAL, DAN, SMN and DMN and between CON and SMN. Finally, connectivity changed over time after SCI: the primary motor cortex decreased connectivity with the primary somatosensory cortex, the visual cortex decreased connectivity with the primary motor cortex, and the visual cortex decreased connectivity with the sensory parietal cortex. These unique findings demonstrate the functional network plasticity that occurs in the brain as a result of injury to the spinal cord. Connectivity changes after SCI may serve as biomarkers to predict functional recovery following an SCI and guide future therapy.

Creativity and the default network: A functional connectivity analysis of the creative brain at rest☆

PubMed Central

Beaty, Roger E.; Benedek, Mathias; Wilkins, Robin W.; Jauk, Emanuel; Fink, Andreas; Silvia, Paul J.; Hodges, Donald A.; Koschutnig, Karl; Neubauer, Aljoscha C.

2014-01-01

The present research used resting-state functional magnetic resonance imaging (fMRI) to examine whether the ability to generate creative ideas corresponds to differences in the intrinsic organization of functional networks in the brain. We examined the functional connectivity between regions commonly implicated in neuroimaging studies of divergent thinking, including the inferior prefrontal cortex and the core hubs of the default network. Participants were prescreened on a battery of divergent thinking tests and assigned to high- and low-creative groups based on task performance. Seed-based functional connectivity analysis revealed greater connectivity between the left inferior frontal gyrus (IFG) and the entire default mode network in the high-creative group. The right IFG also showed greater functional connectivity with bilateral inferior parietal cortex and the left dorsolateral prefrontal cortex in the high-creative group. The results suggest that the ability to generate creative ideas is characterized by increased functional connectivity between the inferior prefrontal cortex and the default network, pointing to a greater cooperation between brain regions associated with cognitive control and low-level imaginative processes. PMID:25245940

Multivariate Classification of Major Depressive Disorder Using the Effective Connectivity and Functional Connectivity

PubMed Central

Geng, Xiangfei; Xu, Junhai; Liu, Baolin; Shi, Yonggang

2018-01-01

Major depressive disorder (MDD) is a mental disorder characterized by at least 2 weeks of low mood, which is present across most situations. Diagnosis of MDD using rest-state functional magnetic resonance imaging (fMRI) data faces many challenges due to the high dimensionality, small samples, noisy and individual variability. To our best knowledge, no studies aim at classification with effective connectivity and functional connectivity measures between MDD patients and healthy controls. In this study, we performed a data-driving classification analysis using the whole brain connectivity measures which included the functional connectivity from two brain templates and effective connectivity measures created by the default mode network (DMN), dorsal attention network (DAN), frontal-parietal network (FPN), and silence network (SN). Effective connectivity measures were extracted using spectral Dynamic Causal Modeling (spDCM) and transformed into a vectorial feature space. Linear Support Vector Machine (linear SVM), non-linear SVM, k-Nearest Neighbor (KNN), and Logistic Regression (LR) were used as the classifiers to identify the differences between MDD patients and healthy controls. Our results showed that the highest accuracy achieved 91.67% (p < 0.0001) when using 19 effective connections and 89.36% when using 6,650 functional connections. The functional connections with high discriminative power were mainly located within or across the whole brain resting-state networks while the discriminative effective connections located in several specific regions, such as posterior cingulate cortex (PCC), ventromedial prefrontal cortex (vmPFC), dorsal cingulate cortex (dACC), and inferior parietal lobes (IPL). To further compare the discriminative power of functional connections and effective connections, a classification analysis only using the functional connections from those four networks was conducted and the highest accuracy achieved 78.33% (p < 0.0001). Our study demonstrated that the effective connectivity measures might play a more important role than functional connectivity in exploring the alterations between patients and health controls and afford a better mechanistic interpretability. Moreover, our results showed a diagnostic potential of the effective connectivity for the diagnosis of MDD patients with high accuracies allowing for earlier prevention or intervention. PMID:29515348

Interhemispheric Functional Brain Connectivity in Neonates with Prenatal Alcohol Exposure: Preliminary Findings.

PubMed

Donald, Kirsten A; Ipser, Jonathan C; Howells, Fleur M; Roos, Annerine; Fouche, Jean-Paul; Riley, Edward P; Koen, Nastassja; Woods, Roger P; Biswal, Bharat; Zar, Heather J; Narr, Katherine L; Stein, Dan J

2016-01-01

Children exposed to alcohol in utero demonstrate reduced white matter microstructural integrity. While early evidence suggests altered functional brain connectivity in the lateralization of motor networks in school-age children with prenatal alcohol exposure (PAE), the specific effects of alcohol exposure on the establishment of intrinsic connectivity in early infancy have not been explored. Sixty subjects received functional imaging at 2 to 4 weeks of age for 6 to 8 minutes during quiet natural sleep. Thirteen alcohol-exposed (PAE) and 14 age-matched control (CTRL) participants with usable data were included in a multivariate model of connectivity between sensorimotor intrinsic functional connectivity networks. Seed-based analyses of group differences in interhemispheric connectivity of intrinsic motor networks were also conducted. The Dubowitz neurological assessment was performed at the imaging visit. Alcohol exposure was associated with significant increases in connectivity between somatosensory, motor networks, brainstem/thalamic, and striatal intrinsic networks. Reductions in interhemispheric connectivity of motor and somatosensory networks did not reach significance. Although results are preliminary, findings suggest PAE may disrupt the temporal coherence in blood oxygenation utilization in intrinsic networks underlying motor performance in newborn infants. Studies that employ longitudinal designs to investigate the effects of in utero alcohol exposure on the evolving resting-state networks will be key in establishing the distribution and timing of connectivity disturbances already described in older children. Copyright © 2016 by the Research Society on Alcoholism.

Information processing architecture of functionally defined clusters in the macaque cortex.

PubMed

Shen, Kelly; Bezgin, Gleb; Hutchison, R Matthew; Gati, Joseph S; Menon, Ravi S; Everling, Stefan; McIntosh, Anthony R

2012-11-28

Computational and empirical neuroimaging studies have suggested that the anatomical connections between brain regions primarily constrain their functional interactions. Given that the large-scale organization of functional networks is determined by the temporal relationships between brain regions, the structural limitations may extend to the global characteristics of functional networks. Here, we explored the extent to which the functional network community structure is determined by the underlying anatomical architecture. We directly compared macaque (Macaca fascicularis) functional connectivity (FC) assessed using spontaneous blood oxygen level-dependent functional magnetic resonance imaging (BOLD-fMRI) to directed anatomical connectivity derived from macaque axonal tract tracing studies. Consistent with previous reports, FC increased with increasing strength of anatomical connection, and FC was also present between regions that had no direct anatomical connection. We observed moderate similarity between the FC of each region and its anatomical connectivity. Notably, anatomical connectivity patterns, as described by structural motifs, were different within and across functional modules: partitioning of the functional network was supported by dense bidirectional anatomical connections within clusters and unidirectional connections between clusters. Together, our data directly demonstrate that the FC patterns observed in resting-state BOLD-fMRI are dictated by the underlying neuroanatomical architecture. Importantly, we show how this architecture contributes to the global organizational principles of both functional specialization and integration.

Dynamic reconfiguration of human brain functional networks through neurofeedback.

PubMed

Haller, Sven; Kopel, Rotem; Jhooti, Permi; Haas, Tanja; Scharnowski, Frank; Lovblad, Karl-Olof; Scheffler, Klaus; Van De Ville, Dimitri

2013-11-01

Recent fMRI studies demonstrated that functional connectivity is altered following cognitive tasks (e.g., learning) or due to various neurological disorders. We tested whether real-time fMRI-based neurofeedback can be a tool to voluntarily reconfigure brain network interactions. To disentangle learning-related from regulation-related effects, we first trained participants to voluntarily regulate activity in the auditory cortex (training phase) and subsequently asked participants to exert learned voluntary self-regulation in the absence of feedback (transfer phase without learning). Using independent component analysis (ICA), we found network reconfigurations (increases in functional network connectivity) during the neurofeedback training phase between the auditory target region and (1) the auditory pathway; (2) visual regions related to visual feedback processing; (3) insula related to introspection and self-regulation and (4) working memory and high-level visual attention areas related to cognitive effort. Interestingly, the auditory target region was identified as the hub of the reconfigured functional networks without a-priori assumptions. During the transfer phase, we again found specific functional connectivity reconfiguration between auditory and attention network confirming the specific effect of self-regulation on functional connectivity. Functional connectivity to working memory related networks was no longer altered consistent with the absent demand on working memory. We demonstrate that neurofeedback learning is mediated by widespread changes in functional connectivity. In contrast, applying learned self-regulation involves more limited and specific network changes in an auditory setup intended as a model for tinnitus. Hence, neurofeedback training might be used to promote recovery from neurological disorders that are linked to abnormal patterns of brain connectivity. Copyright © 2013 Elsevier Inc. All rights reserved.

Resting-state functional brain networks in first-episode psychosis: A 12-month follow-up study.

PubMed

Ganella, Eleni P; Seguin, Caio; Pantelis, Christos; Whittle, Sarah; Baune, Bernhard T; Olver, James; Amminger, G Paul; McGorry, Patrick D; Cropley, Vanessa; Zalesky, Andrew; Bartholomeusz, Cali F

2018-05-01

Schizophrenia is increasingly conceived as a disorder of brain network connectivity and organization. However, reports of network abnormalities during the early illness stage of psychosis are mixed. This study adopted a data-driven whole-brain approach to investigate functional connectivity and network architecture in a first-episode psychosis cohort relative to healthy controls and whether functional network properties changed abnormally over a 12-month period in first-episode psychosis. Resting-state functional connectivity was performed at two time points. At baseline, 29 first-episode psychosis individuals and 30 healthy controls were assessed, and at 12 months, 14 first-episode psychosis individuals and 20 healthy controls completed follow-up. Whole-brain resting-state functional connectivity networks were mapped for each individual and analyzed using graph theory to investigate whether network abnormalities associated with first-episode psychosis were evident and whether functional network properties changed abnormally over 12 months relative to controls. This study found no evidence of abnormal resting-state functional connectivity or topology in first-episode psychosis individuals relative to healthy controls at baseline or at 12-months follow-up. Furthermore, longitudinal changes in network properties over a 12-month period did not significantly differ between first-episode psychosis individuals and healthy control. Network measures did not significantly correlate with symptomatology, duration of illness or antipsychotic medication. This is the first study to show unaffected resting-state functional connectivity and topology in the early psychosis stage of illness. In light of previous literature, this suggests that a subgroup of first-episode psychosis individuals who have a neurotypical resting-state functional connectivity and topology may exist. Our preliminary longitudinal analyses indicate that there also does not appear to be deterioration in these network properties over a 12-month period. Future research in a larger sample is necessary to confirm our longitudinal findings.

Default Mode Network Connectivity as a Function of Familial and Environmental Risk for Psychotic Disorder

PubMed Central

Peeters, Sanne C. T.; van de Ven, Vincent; Gronenschild, Ed H. B. M; Patel, Ameera X.; Habets, Petra; Goebel, Rainer; van Os, Jim; Marcelis, Machteld

2015-01-01

Background Research suggests that altered interregional connectivity in specific networks, such as the default mode network (DMN), is associated with cognitive and psychotic symptoms in schizophrenia. In addition, frontal and limbic connectivity alterations have been associated with trauma, drug use and urban upbringing, though these environmental exposures have never been examined in relation to DMN functional connectivity in psychotic disorder. Methods Resting-state functional MRI scans were obtained from 73 patients with psychotic disorder, 83 non-psychotic siblings of patients with psychotic disorder and 72 healthy controls. Posterior cingulate cortex (PCC) seed-based correlation analysis was used to estimate functional connectivity within the DMN. DMN functional connectivity was examined in relation to group (familial risk), group × environmental exposure (to cannabis, developmental trauma and urbanicity) and symptomatology. Results There was a significant association between group and PCC connectivity with the inferior parietal lobule (IPL), the precuneus (PCu) and the medial prefrontal cortex (MPFC). Compared to controls, patients and siblings had increased PCC connectivity with the IPL, PCu and MPFC. In the IPL and PCu, the functional connectivity of siblings was intermediate to that of controls and patients. No significant associations were found between DMN connectivity and (subclinical) psychotic/cognitive symptoms. In addition, there were no significant interactions between group and environmental exposures in the model of PCC functional connectivity. Discussion Increased functional connectivity in individuals with (increased risk for) psychotic disorder may reflect trait-related network alterations. The within-network “connectivity at rest” intermediate phenotype was not associated with (subclinical) psychotic or cognitive symptoms. The association between familial risk and DMN connectivity was not conditional on environmental exposure. PMID:25790002

Impaired Long Distance Functional Connectivity and Weighted Network Architecture in Alzheimer's Disease

PubMed Central

Liu, Yong; Yu, Chunshui; Zhang, Xinqing; Liu, Jieqiong; Duan, Yunyun; Alexander-Bloch, Aaron F.; Liu, Bing; Jiang, Tianzi; Bullmore, Ed

2014-01-01

Alzheimer's disease (AD) is increasingly recognized as a disconnection syndrome, which leads to cognitive impairment due to the disruption of functional activity across large networks or systems of interconnected brain regions. We explored abnormal functional magnetic resonance imaging (fMRI) resting-state dynamics, functional connectivity, and weighted functional networks, in a sample of patients with severe AD (N = 18) and age-matched healthy volunteers (N = 21). We found that patients had reduced amplitude and regional homogeneity of low-frequency fMRI oscillations, and reduced the strength of functional connectivity, in several regions previously described as components of the default mode network, for example, medial posterior parietal cortex and dorsal medial prefrontal cortex. In patients with severe AD, functional connectivity was particularly attenuated between regions that were separated by a greater physical distance; and loss of long distance connectivity was associated with less efficient global and nodal network topology. This profile of functional abnormality in severe AD was consistent with the results of a comparable analysis of data on 2 additional groups of patients with mild AD (N = 17) and amnestic mild cognitive impairment (MCI; N = 18). A greater degree of cognitive impairment, measured by the mini-mental state examination across all patient groups, was correlated with greater attenuation of functional connectivity, particularly over long connection distances, for example, between anterior and posterior components of the default mode network, and greater reduction of global and nodal network efficiency. These results indicate that neurodegenerative disruption of fMRI oscillations and connectivity in AD affects long-distance connections to hub nodes, with the consequent loss of network efficiency. This profile was evident also to a lesser degree in the patients with less severe cognitive impairment, indicating that the potential of resting-state fMRI measures as biomarkers or predictors of disease progression in AD. PMID:23314940

Functional Connectivity of Cognitive Brain Networks in Schizophrenia during a Working Memory Task

PubMed Central

Godwin, Douglass; Ji, Andrew; Kandala, Sridhar; Mamah, Daniel

2017-01-01

Task-based connectivity studies facilitate the understanding of how the brain functions during cognition, which is commonly impaired in schizophrenia (SZ). Our aim was to investigate functional connectivity during a working memory task in SZ. We hypothesized that the task-negative (default mode) network and the cognitive control (frontoparietal) network would show dysconnectivity. Twenty-five SZ patient and 31 healthy control scans were collected using the customized 3T Siemens Skyra MRI scanner, previously used to collect data for the Human Connectome Project. Blood oxygen level dependent signal during the 0-back and 2-back conditions were extracted within a network-based parcelation scheme. Average functional connectivity was assessed within five brain networks: frontoparietal (FPN), default mode (DMN), cingulo-opercular (CON), dorsal attention (DAN), and ventral attention network; as well as between the DMN or FPN and other networks. For within-FPN connectivity, there was a significant interaction between n-back condition and group (p = 0.015), with decreased connectivity at 0-back in SZ subjects compared to controls. FPN-to-DMN connectivity also showed a significant condition × group effect (p = 0.003), with decreased connectivity at 0-back in SZ. Across groups, connectivity within the CON and DAN were increased during the 2-back condition, while DMN connectivity with either CON or DAN were decreased during the 2-back condition. Our findings support the role of the FPN, CON, and DAN in working memory and indicate that the pattern of FPN functional connectivity differs between SZ patients and control subjects during the course of a working memory task. PMID:29312020

Functional Connectivity of Cognitive Brain Networks in Schizophrenia during a Working Memory Task.

PubMed

Godwin, Douglass; Ji, Andrew; Kandala, Sridhar; Mamah, Daniel

2017-01-01

Task-based connectivity studies facilitate the understanding of how the brain functions during cognition, which is commonly impaired in schizophrenia (SZ). Our aim was to investigate functional connectivity during a working memory task in SZ. We hypothesized that the task-negative (default mode) network and the cognitive control (frontoparietal) network would show dysconnectivity. Twenty-five SZ patient and 31 healthy control scans were collected using the customized 3T Siemens Skyra MRI scanner, previously used to collect data for the Human Connectome Project. Blood oxygen level dependent signal during the 0-back and 2-back conditions were extracted within a network-based parcelation scheme. Average functional connectivity was assessed within five brain networks: frontoparietal (FPN), default mode (DMN), cingulo-opercular (CON), dorsal attention (DAN), and ventral attention network; as well as between the DMN or FPN and other networks. For within-FPN connectivity, there was a significant interaction between n -back condition and group ( p  = 0.015), with decreased connectivity at 0-back in SZ subjects compared to controls. FPN-to-DMN connectivity also showed a significant condition × group effect ( p  = 0.003), with decreased connectivity at 0-back in SZ. Across groups, connectivity within the CON and DAN were increased during the 2-back condition, while DMN connectivity with either CON or DAN were decreased during the 2-back condition. Our findings support the role of the FPN, CON, and DAN in working memory and indicate that the pattern of FPN functional connectivity differs between SZ patients and control subjects during the course of a working memory task.

Compensatory Motor Network Connectivity is Associated with Motor Sequence Learning after Subcortical Stroke

PubMed Central

Wadden, Katie P.; Woodward, Todd S.; Metzak, Paul D.; Lavigne, Katie M.; Lakhani, Bimal; Auriat, Angela M.; Boyd, Lara A.

2015-01-01

Following stroke, functional networks reorganize and the brain demonstrates widespread alterations in cortical activity. Implicit motor learning is preserved after stroke. However the manner in which brain reorganization occurs, and how it supports behaviour within the damaged brain remains unclear. In this functional magnetic resonance imaging (fMRI) study, we evaluated whole brain patterns of functional connectivity during the performance of an implicit tracking task at baseline and retention, following 5 days of practice. Following motor practice, a significant difference in connectivity within a motor network, consisting of bihemispheric activation of the sensory and motor cortices, parietal lobules, cerebellar and occipital lobules, was observed at retention. Healthy subjects demonstrated greater activity within this motor network during sequence learning compared to random practice. The stroke group did not show the same level of functional network integration, presumably due to the heterogeneity of functional reorganization following stroke. In a secondary analysis, a binary mask of the functional network activated from the aforementioned whole brain analyses was created to assess within-network connectivity, decreasing the spatial distribution and large variability of activation that exists within the lesioned brain. The stroke group demonstrated reduced clusters of connectivity within the masked brain regions as compared to the whole brain approach. Connectivity within this smaller motor network correlated with repeated sequence performance on the retention test. Increased functional integration within the motor network may be an important neurophysiological predictor of motor learning-related change in individuals with stroke. PMID:25757996

Decreased functional connectivity to posterior cingulate cortex in major depressive disorder.

PubMed

Yang, Rui; Gao, Chengge; Wu, Xiaoping; Yang, Junle; Li, Shengbin; Cheng, Hu

2016-09-30

The default mode network (DMN) and its interaction with other key networks such as the salience network and executive network are keys to understand psychiatric and neurological disorders including major depressive disorder (MDD). In this study, we combined independent component analysis and seed based connectivity analysis to study the posterior default mode network between 20 patients with MDD and 25 normal controls, as well as pre-treatment and post-treatment conditions of the patients. Both correlated and anti-correlated networks centered at the posterior cingulate cortex (PCC) were examined (PCC+ and PCC-). Our results showed aberrant functional connectivity of the PCC+ and PCC- networks between patients and normal controls. Specifically, normal controls exhibited significantly higher connectivity between the PCC and frontal/temporal regions for the PCC+ network and stronger connectivity strength between the PCC and the insula/middle frontal cortex for the PCC- network. The overall connectivity strength of the PCC+ and PCC- networks was also significantly lower in MDD. Because the PCC is a hub in the DMN that interacts with other networks, our result suggested a stronger interaction between the DMN and the salience network but a weak interaction between the DMN and the executive network in MDD. The treatment using sertraline did increase the functional connectivity strength, especially in the PCC+ network. Despite a large inter-subject variability in the overall connectivity strengths and change of the PCC network in response to the treatment, a high correlation between change of connectivity strength and the Hamilton depression score was observed for both the PCC+ and PCC- network. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Evidence for a Functional Hierarchy of Association Networks.

PubMed

Choi, Eun Young; Drayna, Garrett K; Badre, David

2018-05-01

Patient lesion and neuroimaging studies have identified a rostral-to-caudal functional gradient in the lateral frontal cortex (LFC) corresponding to higher-order (complex or abstract) to lower-order (simple or concrete) cognitive control. At the same time, monkey anatomical and human functional connectivity studies show that frontal regions are reciprocally connected with parietal and temporal regions, forming parallel and distributed association networks. Here, we investigated the link between the functional gradient of LFC regions observed during control tasks and the parallel, distributed organization of association networks. Whole-brain fMRI task activity corresponding to four orders of hierarchical control [Badre, D., & D'Esposito, M. Functional magnetic resonance imaging evidence for a hierarchical organization of the prefrontal cortex. Journal of Cognitive Neuroscience, 19, 2082-2099, 2007] was compared with a resting-state functional connectivity MRI estimate of cortical networks [Yeo, B. T., Krienen, F. M., Sepulcre, J., Sabuncu, M. R., Lashkari, D., Hollinshead, M., et al. The organization of the human cerebral cortex estimated by intrinsic functional connectivity. Journal of Neurophysiology, 106, 1125-1165, 2011]. Critically, at each order of control, activity in the LFC and parietal cortex overlapped onto a common association network that differed between orders. These results are consistent with a functional organization based on separable association networks that are recruited during hierarchical control. Furthermore, corticostriatal functional connectivity MRI showed that, consistent with their participation in functional networks, rostral-to-caudal LFC and caudal-to-rostral parietal regions had similar, order-specific corticostriatal connectivity that agreed with a striatal gating model of hierarchical rule use. Our results indicate that hierarchical cognitive control is subserved by parallel and distributed association networks, together forming multiple localized functional gradients in different parts of association cortex. As such, association networks, while connectionally organized in parallel, may be functionally organized in a hierarchy via dynamic interaction with the striatum.

Characterizing Individual Differences in Functional Connectivity Using Dual-Regression and Seed-Based Approaches

PubMed Central

Smith, David V.; Utevsky, Amanda V.; Bland, Amy R.; Clement, Nathan; Clithero, John A.; Harsch, Anne E. W.; Carter, R. McKell; Huettel, Scott A.

2014-01-01

A central challenge for neuroscience lies in relating inter-individual variability to the functional properties of specific brain regions. Yet, considerable variability exists in the connectivity patterns between different brain areas, potentially producing reliable group differences. Using sex differences as a motivating example, we examined two separate resting-state datasets comprising a total of 188 human participants. Both datasets were decomposed into resting-state networks (RSNs) using a probabilistic spatial independent components analysis (ICA). We estimated voxelwise functional connectivity with these networks using a dual-regression analysis, which characterizes the participant-level spatiotemporal dynamics of each network while controlling for (via multiple regression) the influence of other networks and sources of variability. We found that males and females exhibit distinct patterns of connectivity with multiple RSNs, including both visual and auditory networks and the right frontal-parietal network. These results replicated across both datasets and were not explained by differences in head motion, data quality, brain volume, cortisol levels, or testosterone levels. Importantly, we also demonstrate that dual-regression functional connectivity is better at detecting inter-individual variability than traditional seed-based functional connectivity approaches. Our findings characterize robust—yet frequently ignored—neural differences between males and females, pointing to the necessity of controlling for sex in neuroscience studies of individual differences. Moreover, our results highlight the importance of employing network-based models to study variability in functional connectivity. PMID:24662574

Verbal working memory-related functional connectivity alterations in boys with attention-deficit/hyperactivity disorder and the effects of methylphenidate.

PubMed

Wu, Zhao-Min; Bralten, Janita; An, Li; Cao, Qing-Jiu; Cao, Xiao-Hua; Sun, Li; Liu, Lu; Yang, Li; Mennes, Maarten; Zang, Yu-Feng; Franke, Barbara; Hoogman, Martine; Wang, Yu-Feng

2017-08-01

Few studies have investigated verbal working memory-related functional connectivity patterns in participants with attention-deficit/hyperactivity disorder (ADHD). Thus, we aimed to compare working memory-related functional connectivity patterns in healthy children and those with ADHD, and study effects of methylphenidate (MPH). Twenty-two boys with ADHD were scanned twice, under either MPH (single dose, 10 mg) or placebo, in a randomised, cross-over, counterbalanced placebo-controlled design. Thirty healthy boys were scanned once. We used fMRI during a numerical n-back task to examine functional connectivity patterns in case-control and MPH-placebo comparisons, using independent component analysis. There was no significant difference in behavioural performance between children with ADHD, treated with MPH or placebo, and healthy controls. Compared with controls, participants with ADHD under placebo showed increased functional connectivity within fronto-parietal and auditory networks, and decreased functional connectivity within the executive control network. MPH normalized the altered functional connectivity pattern and significantly enhanced functional connectivity within the executive control network, though in non-overlapping areas. Our study contributes to the identification of the neural substrates of working memory. Single dose of MPH normalized the altered brain functional connectivity network, but had no enhancing effect on (non-impaired) behavioural performance.

Structural Connectivity Relates to Perinatal Factors and Functional Impairment at 7 Years in Children Born Very Preterm

PubMed Central

Thompson, Deanne K.; Chen, Jian; Beare, Richard; Adamson, Christopher L.; Ellis, Rachel; Ahmadzai, Zohra M.; Kelly, Claire E.; Lee, Katherine J.; Zalesky, Andrew; Yang, Joseph Y.M.; Hunt, Rodney W.; Cheong, Jeanie L.Y.; Inder, Terrie E.; Doyle, Lex W.; Seal, Marc L.; Anderson, Peter J.

2016-01-01

Objective To use structural connectivity to (1) compare brain networks between typically and atypically developing (very preterm) children, (2) explore associations between potential perinatal developmental disturbances and brain networks, and (3) describe associations between brain networks and functional impairments in very preterm children. Methods 26 full-term and 107 very preterm 7-year-old children (born <30 weeks’ gestational age and/or <1250 g) underwent T1- and diffusion-weighted imaging. Global white matter fiber networks were produced using 80 cortical and subcortical nodes, and edges created using constrained spherical deconvolution-based tractography. Global graph theory metrics were analysed, and regional networks were identified using network-based statistics. Cognitive and motor function were assessed at 7 years of age. Results Compared with full-term children, very preterm children had reduced density, lower global efficiency and higher local efficiency. Those with lower gestational age at birth, infection or higher neonatal brain abnormality score had reduced connectivity. Reduced connectivity within a widespread network was predictive of impaired IQ, while reduced connectivity within the right parietal and temporal lobes was associated with motor impairment in very preterm children. Conclusions This study utilized an innovative structural connectivity pipeline to reveal that children born very preterm have less connected and less complex brain networks compared with typically developing term-born children. Adverse perinatal factors led to disturbances in white matter connectivity, which in turn are associated with impaired functional outcomes, highlighting novel structure-function relationships. PMID:27046108

A human brain network derived from coma-causing brainstem lesions.

PubMed

Fischer, David B; Boes, Aaron D; Demertzi, Athena; Evrard, Henry C; Laureys, Steven; Edlow, Brian L; Liu, Hesheng; Saper, Clifford B; Pascual-Leone, Alvaro; Fox, Michael D; Geerling, Joel C

2016-12-06

To characterize a brainstem location specific to coma-causing lesions, and its functional connectivity network. We compared 12 coma-causing brainstem lesions to 24 control brainstem lesions using voxel-based lesion-symptom mapping in a case-control design to identify a site significantly associated with coma. We next used resting-state functional connectivity from a healthy cohort to identify a network of regions functionally connected to this brainstem site. We further investigated the cortical regions of this network by comparing their spatial topography to that of known networks and by evaluating their functional connectivity in patients with disorders of consciousness. A small region in the rostral dorsolateral pontine tegmentum was significantly associated with coma-causing lesions. In healthy adults, this brainstem site was functionally connected to the ventral anterior insula (AI) and pregenual anterior cingulate cortex (pACC). These cortical areas aligned poorly with previously defined resting-state networks, better matching the distribution of von Economo neurons. Finally, connectivity between the AI and pACC was disrupted in patients with disorders of consciousness, and to a greater degree than other brain networks. Injury to a small region in the pontine tegmentum is significantly associated with coma. This brainstem site is functionally connected to 2 cortical regions, the AI and pACC, which become disconnected in disorders of consciousness. This network of brain regions may have a role in the maintenance of human consciousness. © 2016 American Academy of Neurology.

A human brain network derived from coma-causing brainstem lesions

PubMed Central

Boes, Aaron D.; Demertzi, Athena; Evrard, Henry C.; Laureys, Steven; Edlow, Brian L.; Liu, Hesheng; Saper, Clifford B.; Pascual-Leone, Alvaro; Geerling, Joel C.

2016-01-01

Objective: To characterize a brainstem location specific to coma-causing lesions, and its functional connectivity network. Methods: We compared 12 coma-causing brainstem lesions to 24 control brainstem lesions using voxel-based lesion-symptom mapping in a case-control design to identify a site significantly associated with coma. We next used resting-state functional connectivity from a healthy cohort to identify a network of regions functionally connected to this brainstem site. We further investigated the cortical regions of this network by comparing their spatial topography to that of known networks and by evaluating their functional connectivity in patients with disorders of consciousness. Results: A small region in the rostral dorsolateral pontine tegmentum was significantly associated with coma-causing lesions. In healthy adults, this brainstem site was functionally connected to the ventral anterior insula (AI) and pregenual anterior cingulate cortex (pACC). These cortical areas aligned poorly with previously defined resting-state networks, better matching the distribution of von Economo neurons. Finally, connectivity between the AI and pACC was disrupted in patients with disorders of consciousness, and to a greater degree than other brain networks. Conclusions: Injury to a small region in the pontine tegmentum is significantly associated with coma. This brainstem site is functionally connected to 2 cortical regions, the AI and pACC, which become disconnected in disorders of consciousness. This network of brain regions may have a role in the maintenance of human consciousness. PMID:27815400

Resting State Network Topology of the Ferret Brain

PubMed Central

Zhou, Zhe Charles; Salzwedel, Andrew P.; Radtke-Schuller, Susanne; Li, Yuhui; Sellers, Kristin K.; Gilmore, John H.; Shih, Yen-Yu Ian; Fröhlich, Flavio; Gao, Wei

2016-01-01

Resting state functional magnetic resonance imaging (rsfMRI) has emerged as a versatile tool for non-invasive measurement of functional connectivity patterns in the brain. RsfMRI brain dynamics in rodents, non-human primates, and humans share similar properties; however, little is known about the resting state functional connectivity patterns in the ferret, an animal model with high potential for developmental and cognitive translational study. To address this knowledge-gap, we performed rsfMRI on anesthetized ferrets using a 9.4 tesla MRI scanner, and subsequently performed group-level independent component analysis (gICA) to identify functionally connected brain networks. Group-level ICA analysis revealed distributed sensory, motor, and higher-order networks in the ferret brain. Subsequent connectivity analysis showed interconnected higher-order networks that constituted a putative default mode network (DMN), a network that exhibits altered connectivity in neuropsychiatric disorders. Finally, we assessed ferret brain topological efficiency using graph theory analysis and found that the ferret brain exhibits small-world properties. Overall, these results provide additional evidence for pan-species resting-state networks, further supporting ferret-based studies of sensory and cognitive function. PMID:27596024

Functional Connectivity of Insula, Basal Ganglia, and Prefrontal Executive Control Networks during Hypoglycemia in Type 1 Diabetes

PubMed Central

Simonson, Donald C.; Nickerson, Lisa D.; Flores, Veronica L.; Siracusa, Tamar; Hager, Brandon; Lyoo, In Kyoon; Renshaw, Perry F.; Jacobson, Alan M.

2015-01-01

Human brain networks mediating interoceptive, behavioral, and cognitive aspects of glycemic control are not well studied. Using group independent component analysis with dual-regression approach of functional magnetic resonance imaging data, we examined the functional connectivity changes of large-scale resting state networks during sequential euglycemic–hypoglycemic clamp studies in patients with type 1 diabetes and nondiabetic controls and how these changes during hypoglycemia were related to symptoms of hypoglycemia awareness and to concurrent glycosylated hemoglobin (HbA1c) levels. During hypoglycemia, diabetic patients showed increased functional connectivity of the right anterior insula and the prefrontal cortex within the executive control network, which was associated with higher HbA1c. Controls showed decreased functional connectivity of the right anterior insula with the cerebellum/basal ganglia network and of temporal regions within the temporal pole network and increased functional connectivity in the default mode and sensorimotor networks. Functional connectivity reductions in the right basal ganglia were correlated with increases of self-reported hypoglycemic symptoms in controls but not in patients. Resting state networks that showed different group functional connectivity during hypoglycemia may be most sensitive to glycemic environment, and their connectivity patterns may have adapted to repeated glycemic excursions present in type 1 diabetes. Our results suggest that basal ganglia and insula mediation of interoceptive awareness during hypoglycemia is altered in type 1 diabetes. These changes could be neuroplastic adaptations to frequent hypoglycemic experiences. Functional connectivity changes in the insula and prefrontal cognitive networks could also reflect an adaptation to changes in brain metabolic pathways associated with chronic hyperglycemia. SIGNIFICANCE STATEMENT The major factor limiting improved glucose control in type 1 diabetes is the significant increase in hypoglycemia associated with insulin treatment. Repeated exposure to hypoglycemia alters patients' ability to recognize the autonomic and neuroglycopenic symptoms associated with low plasma glucose levels. We examined brain resting state networks during the induction of hypoglycemia in diabetic and control subjects and found differences in networks involved in sensorimotor function, cognition, and interoceptive awareness that were related to chronic levels of glycemic control. These findings identify brain regions that are sensitive to variations in plasma glucose levels and may also provide a basis for understanding the mechanisms underlying the increased incidence of cognitive impairment and affective disorders seen in patients with diabetes. PMID:26245963

Electrophysiological signatures of atypical intrinsic brain connectivity networks in autism

NASA Astrophysics Data System (ADS)

Shou, Guofa; Mosconi, Matthew W.; Wang, Jun; Ethridge, Lauren E.; Sweeney, John A.; Ding, Lei

2017-08-01

Objective. Abnormal local and long-range brain connectivity have been widely reported in autism spectrum disorder (ASD), yet the nature of these abnormalities and their functional relevance at distinct cortical rhythms remains unknown. Investigations of intrinsic connectivity networks (ICNs) and their coherence across whole brain networks hold promise for determining whether patterns of functional connectivity abnormalities vary across frequencies and networks in ASD. In the present study, we aimed to probe atypical intrinsic brain connectivity networks in ASD from resting-state electroencephalography (EEG) data via characterizing the whole brain network. Approach. Connectivity within individual ICNs (measured by spectral power) and between ICNs (measured by coherence) were examined at four canonical frequency bands via a time-frequency independent component analysis on high-density EEG, which were recorded from 20 ASD and 20 typical developing (TD) subjects during an eyes-closed resting state. Main results. Among twelve identified electrophysiological ICNs, individuals with ASD showed hyper-connectivity in individual ICNs and hypo-connectivity between ICNs. Functional connectivity alterations in ASD were more severe in the frontal lobe and the default mode network (DMN) and at low frequency bands. These functional connectivity measures also showed abnormal age-related associations in ICNs related to frontal, temporal and motor regions in ASD. Significance. Our findings suggest that ASD is characterized by the opposite directions of abnormalities (i.e. hypo- and hyper-connectivity) in the hierarchical structure of the whole brain network, with more impairments in the frontal lobe and the DMN at low frequency bands, which are critical for top-down control of sensory systems, as well as for both cognition and social skills.

Differential reward network functional connectivity in cannabis dependent and non-dependent users☆

PubMed Central

Filbey, Francesca M.; Dunlop, Joseph

2015-01-01

Background Emergent studies show that similar to other substances of abuse, cue-reactivity to cannabis is also associated with neural response in the brain’s reward pathway (Filbey et al., 2009). However, the inter-relatedness of brain regions during cue-reactivity in cannabis users remains unknown. Methods In this study, we conducted a series of investigations to determine functional connectivity during cue-reactivity in 71 cannabis users. First, we used psychophysiological interaction (PPI) analysis to examine coherent neural response to cannabis cues. Second, we evaluated whether these patterns of network functional connectivity differentiated dependent and non-dependent users. Finally, as an exploratory analysis, we determined the directionality of these connections via Granger connectivity analyses. Results PPI analyses showed reward network functional connectivity with the nucleus accumbens (NAc) seed region during cue exposure. Between-group contrasts found differential effects of dependence status. Dependent users (N = 31) had greater functional connectivity with amygdala and anterior cingulate gyrus (ACG) seeds while the non-dependent users (N = 24) had greater functional connectivity with the NAc, orbitofrontal cortex (OFC) and hippocampus seeds. Granger analyses showed that hippocampal and ACG activation preceded neural response in reward areas. Conclusions Both PPI and Granger analyses demonstrated strong functional coherence in reward regions during exposure to cannabis cues in current cannabis users. Functional connectivity (but not regional activation) in the reward network differentiated dependent from non-dependent cannabis users. Our findings suggest that repeated cannabis exposure causes observable changes in functional connectivity in the reward network and should be considered in intervention strategies. PMID:24838032

Structure-Function Network Mapping and Its Assessment via Persistent Homology

PubMed Central

2017-01-01

Understanding the relationship between brain structure and function is a fundamental problem in network neuroscience. This work deals with the general method of structure-function mapping at the whole-brain level. We formulate the problem as a topological mapping of structure-function connectivity via matrix function, and find a stable solution by exploiting a regularization procedure to cope with large matrices. We introduce a novel measure of network similarity based on persistent homology for assessing the quality of the network mapping, which enables a detailed comparison of network topological changes across all possible thresholds, rather than just at a single, arbitrary threshold that may not be optimal. We demonstrate that our approach can uncover the direct and indirect structural paths for predicting functional connectivity, and our network similarity measure outperforms other currently available methods. We systematically validate our approach with (1) a comparison of regularized vs. non-regularized procedures, (2) a null model of the degree-preserving random rewired structural matrix, (3) different network types (binary vs. weighted matrices), and (4) different brain parcellation schemes (low vs. high resolutions). Finally, we evaluate the scalability of our method with relatively large matrices (2514x2514) of structural and functional connectivity obtained from 12 healthy human subjects measured non-invasively while at rest. Our results reveal a nonlinear structure-function relationship, suggesting that the resting-state functional connectivity depends on direct structural connections, as well as relatively parsimonious indirect connections via polysynaptic pathways. PMID:28046127

Altered neural connectivity during response inhibition in adolescents with attention-deficit/hyperactivity disorder and their unaffected siblings

PubMed Central

van Rooij, Daan; Hartman, Catharina A.; Mennes, Maarten; Oosterlaan, Jaap; Franke, Barbara; Rommelse, Nanda; Heslenfeld, Dirk; Faraone, Stephen V.; Buitelaar, Jan K.; Hoekstra, Pieter J.

2015-01-01

Introduction Response inhibition is one of the executive functions impaired in attention-deficit/hyperactivity disorder (ADHD). Increasing evidence indicates that altered functional and structural neural connectivity are part of the neurobiological basis of ADHD. Here, we investigated if adolescents with ADHD show altered functional connectivity during response inhibition compared to their unaffected siblings and healthy controls. Methods Response inhibition was assessed using the stop signal paradigm. Functional connectivity was assessed using psycho-physiological interaction analyses applied to BOLD time courses from seed regions within inferior- and superior frontal nodes of the response inhibition network. Resulting networks were compared between adolescents with ADHD (N = 185), their unaffected siblings (N = 111), and controls (N = 125). Results Control subjects showed stronger functional connectivity than the other two groups within the response inhibition network, while subjects with ADHD showed relatively stronger connectivity between default mode network (DMN) nodes. Stronger connectivity within the response inhibition network was correlated with lower ADHD severity, while stronger connectivity with the DMN was correlated with increased ADHD severity. Siblings showed connectivity patterns similar to controls during successful inhibition and to ADHD subjects during failed inhibition. Additionally, siblings showed decreased connectivity with the primary motor areas as compared to both participants with ADHD and controls. Discussion Subjects with ADHD fail to integrate activation within the response inhibition network and to inhibit connectivity with task-irrelevant regions. Unaffected siblings show similar alterations only during failed stop trials, as well as unique suppression of motor areas, suggesting compensatory strategies. These findings support the role of altered functional connectivity in understanding the neurobiology and familial transmission of ADHD. PMID:25610797

Altered neural connectivity during response inhibition in adolescents with attention-deficit/hyperactivity disorder and their unaffected siblings.

PubMed

van Rooij, Daan; Hartman, Catharina A; Mennes, Maarten; Oosterlaan, Jaap; Franke, Barbara; Rommelse, Nanda; Heslenfeld, Dirk; Faraone, Stephen V; Buitelaar, Jan K; Hoekstra, Pieter J

2015-01-01

Response inhibition is one of the executive functions impaired in attention-deficit/hyperactivity disorder (ADHD). Increasing evidence indicates that altered functional and structural neural connectivity are part of the neurobiological basis of ADHD. Here, we investigated if adolescents with ADHD show altered functional connectivity during response inhibition compared to their unaffected siblings and healthy controls. Response inhibition was assessed using the stop signal paradigm. Functional connectivity was assessed using psycho-physiological interaction analyses applied to BOLD time courses from seed regions within inferior- and superior frontal nodes of the response inhibition network. Resulting networks were compared between adolescents with ADHD (N = 185), their unaffected siblings (N = 111), and controls (N = 125). Control subjects showed stronger functional connectivity than the other two groups within the response inhibition network, while subjects with ADHD showed relatively stronger connectivity between default mode network (DMN) nodes. Stronger connectivity within the response inhibition network was correlated with lower ADHD severity, while stronger connectivity with the DMN was correlated with increased ADHD severity. Siblings showed connectivity patterns similar to controls during successful inhibition and to ADHD subjects during failed inhibition. Additionally, siblings showed decreased connectivity with the primary motor areas as compared to both participants with ADHD and controls. Subjects with ADHD fail to integrate activation within the response inhibition network and to inhibit connectivity with task-irrelevant regions. Unaffected siblings show similar alterations only during failed stop trials, as well as unique suppression of motor areas, suggesting compensatory strategies. These findings support the role of altered functional connectivity in understanding the neurobiology and familial transmission of ADHD.

A proposal of fuzzy connective with learning function and its application to fuzzy retrieval system

NASA Technical Reports Server (NTRS)

Hayashi, Isao; Naito, Eiichi; Ozawa, Jun; Wakami, Noboru

1993-01-01

A new fuzzy connective and a structure of network constructed by fuzzy connectives are proposed to overcome a drawback of conventional fuzzy retrieval systems. This network represents a retrieval query and the fuzzy connectives in networks have a learning function to adjust its parameters by data from a database and outputs of a user. The fuzzy retrieval systems employing this network are also constructed. Users can retrieve results even with a query whose attributes do not exist in a database schema and can get satisfactory results for variety of thinkings by learning function.

Long-term intensive gymnastic training induced changes in intra- and inter-network functional connectivity: an independent component analysis.

PubMed

Huang, Huiyuan; Wang, Junjing; Seger, Carol; Lu, Min; Deng, Feng; Wu, Xiaoyan; He, Yuan; Niu, Chen; Wang, Jun; Huang, Ruiwang

2018-01-01

Long-term intensive gymnastic training can induce brain structural and functional reorganization. Previous studies have identified structural and functional network differences between world class gymnasts (WCGs) and non-athletes at the whole-brain level. However, it is still unclear how interactions within and between functional networks are affected by long-term intensive gymnastic training. We examined both intra- and inter-network functional connectivity of gymnasts relative to non-athletes using resting-state fMRI (R-fMRI). R-fMRI data were acquired from 13 WCGs and 14 non-athlete controls. Group-independent component analysis (ICA) was adopted to decompose the R-fMRI data into spatial independent components and associated time courses. An automatic component identification method was used to identify components of interest associated with resting-state networks (RSNs). We identified nine RSNs, the basal ganglia network (BG), sensorimotor network (SMN), cerebellum (CB), anterior and posterior default mode networks (aDMN/pDMN), left and right fronto-parietal networks (lFPN/rFPN), primary visual network (PVN), and extrastriate visual network (EVN). Statistical analyses revealed that the intra-network functional connectivity was significantly decreased within the BG, aDMN, lFPN, and rFPN, but increased within the EVN in the WCGs compared to the controls. In addition, the WCGs showed uniformly decreased inter-network functional connectivity between SMN and BG, CB, and PVN, BG and PVN, and pDMN and rFPN compared to the controls. We interpret this generally weaker intra- and inter-network functional connectivity in WCGs during the resting state as a result of greater efficiency in the WCGs' brain associated with long-term motor skill training.

Analyzing the association between functional connectivity of the brain and intellectual performance

PubMed Central

Pamplona, Gustavo S. P.; Santos Neto, Gérson S.; Rosset, Sara R. E.; Rogers, Baxter P.; Salmon, Carlos E. G.

2015-01-01

Measurements of functional connectivity support the hypothesis that the brain is composed of distinct networks with anatomically separated nodes but common functionality. A few studies have suggested that intellectual performance may be associated with greater functional connectivity in the fronto-parietal network and enhanced global efficiency. In this fMRI study, we performed an exploratory analysis of the relationship between the brain's functional connectivity and intelligence scores derived from the Portuguese language version of the Wechsler Adult Intelligence Scale (WAIS-III) in a sample of 29 people, born and raised in Brazil. We examined functional connectivity between 82 regions, including graph theoretic properties of the overall network. Some previous findings were extended to the Portuguese-speaking population, specifically the presence of small-world organization of the brain and relationships of intelligence with connectivity of frontal, pre-central, parietal, occipital, fusiform and supramarginal gyrus, and caudate nucleus. Verbal comprehension was associated with global network efficiency, a new finding. PMID:25713528

Abnormal functional connectivity of hippocampus during episodic memory retrieval processing network in amnestic mild cognitive impairment.

PubMed

Bai, Feng; Zhang, Zhijun; Watson, David R; Yu, Hui; Shi, Yongmei; Yuan, Yonggui; Zang, Yufeng; Zhu, Chaozhe; Qian, Yun

2009-06-01

Functional connectivity magnetic resonance imaging technique has revealed the importance of distributed network structures in higher cognitive processes in the human brain. The hippocampus has a key role in a distributed network supporting memory encoding and retrieval. Hippocampal dysfunction is a recurrent finding in memory disorders of aging such as amnestic mild cognitive impairment (aMCI) in which learning- and memory-related cognitive abilities are the predominant impairment. The functional connectivity method provides a novel approach in our attempts to better understand the changes occurring in this structure in aMCI patients. Functional connectivity analysis was used to examine episodic memory retrieval networks in vivo in twenty 28 aMCI patients and 23 well-matched control subjects, specifically between the hippocampal structures and other brain regions. Compared with control subjects, aMCI patients showed significantly lower hippocampus functional connectivity in a network involving prefrontal lobe, temporal lobe, parietal lobe, and cerebellum, and higher functional connectivity to more diffuse areas of the brain than normal aging control subjects. In addition, those regions associated with increased functional connectivity with the hippocampus demonstrated a significantly negative correlation to episodic memory performance. aMCI patients displayed altered patterns of functional connectivity during memory retrieval. The degree of this disturbance appears to be related to level of impairment of processes involved in memory function. Because aMCI is a putative prodromal syndrome to Alzheimer's disease (AD), these early changes in functional connectivity involving the hippocampus may yield important new data to predict whether a patient will eventually develop AD.

Complex network analysis of brain functional connectivity under a multi-step cognitive task

NASA Astrophysics Data System (ADS)

Cai, Shi-Min; Chen, Wei; Liu, Dong-Bai; Tang, Ming; Chen, Xun

2017-01-01

Functional brain network has been widely studied to understand the relationship between brain organization and behavior. In this paper, we aim to explore the functional connectivity of brain network under a multi-step cognitive task involving consecutive behaviors, and further understand the effect of behaviors on the brain organization. The functional brain networks are constructed based on a high spatial and temporal resolution fMRI dataset and analyzed via complex network based approach. We find that at voxel level the functional brain network shows robust small-worldness and scale-free characteristics, while its assortativity and rich-club organization are slightly restricted to the order of behaviors performed. More interestingly, the functional connectivity of brain network in activated ROIs strongly correlates with behaviors and is obviously restricted to the order of behaviors performed. These empirical results suggest that the brain organization has the generic properties of small-worldness and scale-free characteristics, and its diverse functional connectivity emerging from activated ROIs is strongly driven by these behavioral activities via the plasticity of brain.

Functional connectivity of hippocampal and prefrontal networks during episodic and spatial memory based on real-world environments.

PubMed

Robin, Jessica; Hirshhorn, Marnie; Rosenbaum, R Shayna; Winocur, Gordon; Moscovitch, Morris; Grady, Cheryl L

2015-01-01

Several recent studies have compared episodic and spatial memory in neuroimaging paradigms in order to understand better the contribution of the hippocampus to each of these tasks. In the present study, we build on previous findings showing common neural activation in default network areas during episodic and spatial memory tasks based on familiar, real-world environments (Hirshhorn et al. (2012) Neuropsychologia 50:3094-3106). Following previous demonstrations of the presence of functionally connected sub-networks within the default network, we performed seed-based functional connectivity analyses to determine how, depending on the task, the hippocampus and prefrontal cortex differentially couple with one another and with distinct whole-brain networks. We found evidence for a medial prefrontal-parietal network and a medial temporal lobe network, which were functionally connected to the prefrontal and hippocampal seeds, respectively, regardless of the nature of the memory task. However, these two networks were functionally connected with one another during the episodic memory task, but not during spatial memory tasks. Replicating previous reports of fractionation of the default network into stable sub-networks, this study also shows how these sub-networks may flexibly couple and uncouple with one another based on task demands. These findings support the hypothesis that episodic memory and spatial memory share a common medial temporal lobe-based neural substrate, with episodic memory recruiting additional prefrontal sub-networks. © 2014 Wiley Periodicals, Inc.

Creativity and the default network: A functional connectivity analysis of the creative brain at rest.

PubMed

Beaty, Roger E; Benedek, Mathias; Wilkins, Robin W; Jauk, Emanuel; Fink, Andreas; Silvia, Paul J; Hodges, Donald A; Koschutnig, Karl; Neubauer, Aljoscha C

2014-11-01

The present research used resting-state functional magnetic resonance imaging (fMRI) to examine whether the ability to generate creative ideas corresponds to differences in the intrinsic organization of functional networks in the brain. We examined the functional connectivity between regions commonly implicated in neuroimaging studies of divergent thinking, including the inferior prefrontal cortex and the core hubs of the default network. Participants were prescreened on a battery of divergent thinking tests and assigned to high- and low-creative groups based on task performance. Seed-based functional connectivity analysis revealed greater connectivity between the left inferior frontal gyrus (IFG) and the entire default mode network in the high-creative group. The right IFG also showed greater functional connectivity with bilateral inferior parietal cortex and the left dorsolateral prefrontal cortex in the high-creative group. The results suggest that the ability to generate creative ideas is characterized by increased functional connectivity between the inferior prefrontal cortex and the default network, pointing to a greater cooperation between brain regions associated with cognitive control and low-level imaginative processes. Copyright © 2014 The Authors. Published by Elsevier Ltd.. All rights reserved.

Explaining the heterogeneity of functional connectivity findings in multiple sclerosis: An empirically informed modeling study.

PubMed

Tewarie, Prejaas; Steenwijk, Martijn D; Brookes, Matthew J; Uitdehaag, Bernard M J; Geurts, Jeroen J G; Stam, Cornelis J; Schoonheim, Menno M

2018-06-01

To understand the heterogeneity of functional connectivity results reported in the literature, we analyzed the separate effects of grey and white matter damage on functional connectivity and networks in multiple sclerosis. For this, we employed a biophysical thalamo-cortical model consisting of interconnected cortical and thalamic neuronal populations, informed and amended by empirical diffusion MRI tractography data, to simulate functional data that mimic neurophysiological signals. Grey matter degeneration was simulated by decreasing within population connections and white matter degeneration by lowering between population connections, based on lesion predilection sites in multiple sclerosis. For all simulations, functional connectivity and functional network organization are quantified by phase synchronization and network integration, respectively. Modeling results showed that both cortical and thalamic grey matter damage induced a global increase in functional connectivity, whereas white matter damage induced an initially increased connectivity followed by a global decrease. Both white and especially grey matter damage, however, induced a decrease in network integration. These empirically informed simulations show that specific topology and timing of structural damage are nontrivial aspects in explaining functional abnormalities in MS. Insufficient attention to these aspects likely explains contradictory findings in multiple sclerosis functional imaging studies so far. © 2018 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

A global interaction network maps a wiring diagram of cellular function

PubMed Central

Costanzo, Michael; VanderSluis, Benjamin; Koch, Elizabeth N.; Baryshnikova, Anastasia; Pons, Carles; Tan, Guihong; Wang, Wen; Usaj, Matej; Hanchard, Julia; Lee, Susan D.; Pelechano, Vicent; Styles, Erin B.; Billmann, Maximilian; van Leeuwen, Jolanda; van Dyk, Nydia; Lin, Zhen-Yuan; Kuzmin, Elena; Nelson, Justin; Piotrowski, Jeff S.; Srikumar, Tharan; Bahr, Sondra; Chen, Yiqun; Deshpande, Raamesh; Kurat, Christoph F.; Li, Sheena C.; Li, Zhijian; Usaj, Mojca Mattiazzi; Okada, Hiroki; Pascoe, Natasha; Luis, Bryan-Joseph San; Sharifpoor, Sara; Shuteriqi, Emira; Simpkins, Scott W.; Snider, Jamie; Suresh, Harsha Garadi; Tan, Yizhao; Zhu, Hongwei; Malod-Dognin, Noel; Janjic, Vuk; Przulj, Natasa; Troyanskaya, Olga G.; Stagljar, Igor; Xia, Tian; Ohya, Yoshikazu; Gingras, Anne-Claude; Raught, Brian; Boutros, Michael; Steinmetz, Lars M.; Moore, Claire L.; Rosebrock, Adam P.; Caudy, Amy A.; Myers, Chad L.; Andrews, Brenda; Boone, Charles

2017-01-01

We generated a global genetic interaction network for Saccharomyces cerevisiae, constructing over 23 million double mutants, identifying ~550,000 negative and ~350,000 positive genetic interactions. This comprehensive network maps genetic interactions for essential gene pairs, highlighting essential genes as densely connected hubs. Genetic interaction profiles enabled assembly of a hierarchical model of cell function, including modules corresponding to protein complexes and pathways, biological processes, and cellular compartments. Negative interactions connected functionally related genes, mapped core bioprocesses, and identified pleiotropic genes, whereas positive interactions often mapped general regulatory connections among gene pairs, rather than shared functionality. The global network illustrates how coherent sets of genetic interactions connect protein complex and pathway modules to map a functional wiring diagram of the cell. PMID:27708008

Extrinsic and Intrinsic Brain Network Connectivity Maintains Cognition across the Lifespan Despite Accelerated Decay of Regional Brain Activation.

PubMed

Tsvetanov, Kamen A; Henson, Richard N A; Tyler, Lorraine K; Razi, Adeel; Geerligs, Linda; Ham, Timothy E; Rowe, James B

2016-03-16

The maintenance of wellbeing across the lifespan depends on the preservation of cognitive function. We propose that successful cognitive aging is determined by interactions both within and between large-scale functional brain networks. Such connectivity can be estimated from task-free functional magnetic resonance imaging (fMRI), also known as resting-state fMRI (rs-fMRI). However, common correlational methods are confounded by age-related changes in the neurovascular signaling. To estimate network interactions at the neuronal rather than vascular level, we used generative models that specified both the neural interactions and a flexible neurovascular forward model. The networks' parameters were optimized to explain the spectral dynamics of rs-fMRI data in 602 healthy human adults from population-based cohorts who were approximately uniformly distributed between 18 and 88 years (www.cam-can.com). We assessed directed connectivity within and between three key large-scale networks: the salience network, dorsal attention network, and default mode network. We found that age influences connectivity both within and between these networks, over and above the effects on neurovascular coupling. Canonical correlation analysis revealed that the relationship between network connectivity and cognitive function was age-dependent: cognitive performance relied on neural dynamics more strongly in older adults. These effects were driven partly by reduced stability of neural activity within all networks, as expressed by an accelerated decay of neural information. Our findings suggest that the balance of excitatory connectivity between networks, and the stability of intrinsic neural representations within networks, changes with age. The cognitive function of older adults becomes increasingly dependent on these factors. Maintaining cognitive function is critical to successful aging. To study the neural basis of cognitive function across the lifespan, we studied a large population-based cohort (n = 602, 18-88 years), separating neural connectivity from vascular components of fMRI signals. Cognitive ability was influenced by the strength of connection within and between functional brain networks, and this positive relationship increased with age. In older adults, there was more rapid decay of intrinsic neuronal activity in multiple regions of the brain networks, which related to cognitive performance. Our data demonstrate increased reliance on network flexibility to maintain cognitive function, in the presence of more rapid decay of neural activity. These insights will facilitate the development of new strategies to maintain cognitive ability. Copyright © 2016 Tsvetanov et al.

Extrinsic and Intrinsic Brain Network Connectivity Maintains Cognition across the Lifespan Despite Accelerated Decay of Regional Brain Activation

PubMed Central

Henson, Richard N.A.; Tyler, Lorraine K.; Razi, Adeel; Geerligs, Linda; Ham, Timothy E.; Rowe, James B.

2016-01-01

The maintenance of wellbeing across the lifespan depends on the preservation of cognitive function. We propose that successful cognitive aging is determined by interactions both within and between large-scale functional brain networks. Such connectivity can be estimated from task-free functional magnetic resonance imaging (fMRI), also known as resting-state fMRI (rs-fMRI). However, common correlational methods are confounded by age-related changes in the neurovascular signaling. To estimate network interactions at the neuronal rather than vascular level, we used generative models that specified both the neural interactions and a flexible neurovascular forward model. The networks' parameters were optimized to explain the spectral dynamics of rs-fMRI data in 602 healthy human adults from population-based cohorts who were approximately uniformly distributed between 18 and 88 years (www.cam-can.com). We assessed directed connectivity within and between three key large-scale networks: the salience network, dorsal attention network, and default mode network. We found that age influences connectivity both within and between these networks, over and above the effects on neurovascular coupling. Canonical correlation analysis revealed that the relationship between network connectivity and cognitive function was age-dependent: cognitive performance relied on neural dynamics more strongly in older adults. These effects were driven partly by reduced stability of neural activity within all networks, as expressed by an accelerated decay of neural information. Our findings suggest that the balance of excitatory connectivity between networks, and the stability of intrinsic neural representations within networks, changes with age. The cognitive function of older adults becomes increasingly dependent on these factors. SIGNIFICANCE STATEMENT Maintaining cognitive function is critical to successful aging. To study the neural basis of cognitive function across the lifespan, we studied a large population-based cohort (n = 602, 18–88 years), separating neural connectivity from vascular components of fMRI signals. Cognitive ability was influenced by the strength of connection within and between functional brain networks, and this positive relationship increased with age. In older adults, there was more rapid decay of intrinsic neuronal activity in multiple regions of the brain networks, which related to cognitive performance. Our data demonstrate increased reliance on network flexibility to maintain cognitive function, in the presence of more rapid decay of neural activity. These insights will facilitate the development of new strategies to maintain cognitive ability. PMID:26985024

Network analysis of mesoscale optical recordings to assess regional, functional connectivity.

PubMed

Lim, Diana H; LeDue, Jeffrey M; Murphy, Timothy H

2015-10-01

With modern optical imaging methods, it is possible to map structural and functional connectivity. Optical imaging studies that aim to describe large-scale neural connectivity often need to handle large and complex datasets. In order to interpret these datasets, new methods for analyzing structural and functional connectivity are being developed. Recently, network analysis, based on graph theory, has been used to describe and quantify brain connectivity in both experimental and clinical studies. We outline how to apply regional, functional network analysis to mesoscale optical imaging using voltage-sensitive-dye imaging and channelrhodopsin-2 stimulation in a mouse model. We include links to sample datasets and an analysis script. The analyses we employ can be applied to other types of fluorescence wide-field imaging, including genetically encoded calcium indicators, to assess network properties. We discuss the benefits and limitations of using network analysis for interpreting optical imaging data and define network properties that may be used to compare across preparations or other manipulations such as animal models of disease.

Self-reference, emotion inhibition and somatosensory disturbance: preliminary investigation of network perturbations in conversion disorder.

PubMed

Monsa, R; Peer, M; Arzy, S

2018-06-01

Conversion disorder (CD), or functional neurological disorder, is manifested as a neurological disturbance that is not macroscopically visible on clinical structural neuroimaging and is instead ascribed to underlying psychological stress. Known for many years in neuropsychiatry, a comprehensive explanation of the way in which psychological stress leads to a neurological deficit of a structural-like origin is still lacking. We applied whole-brain network-based data-driven analyses on resting-state functional magnetic resonance imaging, recorded in seven patients with acute-onset, stroke-like CD with unilateral paresis and hypoesthesia as compared with 15 age-matched healthy controls. We used a clustering analysis to measure functional connectivity (FC) strength within 10 different brain networks, as well as between these networks. Finally, we tested FC of specific brain regions that are known to be involved in CD. We found a significant increase in FC strength only within the default-mode network (DMN), which manages self-referential processing. Examination of inter-connectivity between networks showed a structure of disturbed connectivity, which included decreased connectivity between the DMN and limbic/salience network, increased connectivity between the limbic/salience network and body-related temporo-parieto-occipital junction network, decreased connectivity between the temporo-parieto-occipital junction and memory-related medial temporal lobe, and decreased connectivity between the medial temporal lobe and sensorimotor network. Region-specific FC analysis showed increased connectivity between the hippocampus and DMN. These preliminary results of disturbances in brain networks related to memory, emotions and self-referential processing, and networks involved in motor planning and execution, suggest a role of these cognitive functions in the psychopathology of CD. © 2018 EAN.

Network analysis of functional brain connectivity in borderline personality disorder using resting-state fMRI

PubMed Central

Xu, Tingting; Cullen, Kathryn R.; Mueller, Bryon; Schreiner, Mindy W.; Lim, Kelvin O.; Schulz, S. Charles; Parhi, Keshab K.

2016-01-01

Borderline personality disorder (BPD) is associated with symptoms such as affect dysregulation, impaired sense of self, and self-harm behaviors. Neuroimaging research on BPD has revealed structural and functional abnormalities in specific brain regions and connections. However, little is known about the topological organizations of brain networks in BPD. We collected resting-state functional magnetic resonance imaging (fMRI) data from 20 patients with BPD and 10 healthy controls, and constructed frequency-specific functional brain networks by correlating wavelet-filtered fMRI signals from 82 cortical and subcortical regions. We employed graph-theory based complex network analysis to investigate the topological properties of the brain networks, and employed network-based statistic to identify functional dysconnections in patients. In the 0.03–0.06 Hz frequency band, compared to controls, patients with BPD showed significantly larger measures of global network topology, including the size of largest connected graph component, clustering coefficient, small-worldness, and local efficiency, indicating increased local cliquishness of the functional brain network. Compared to controls, patients showed lower nodal centrality at several hub nodes but greater centrality at several non-hub nodes in the network. Furthermore, an interconnected subnetwork in 0.03–0.06 Hz frequency band was identified that showed significantly lower connectivity in patients. The links in the subnetwork were mainly long-distance connections between regions located at different lobes; and the mean connectivity of this subnetwork was negatively correlated with the increased global topology measures. Lastly, the key network measures showed high correlations with several clinical symptom scores, and classified BPD patients against healthy controls with high accuracy based on linear discriminant analysis. The abnormal topological properties and connectivity found in this study may add new knowledge to the current understanding of functional brain networks in BPD. However, due to limitation of small sample sizes, the results of the current study should be viewed as exploratory and need to be validated on large samples in future works. PMID:26977400

Network analysis of functional brain connectivity in borderline personality disorder using resting-state fMRI.

PubMed

Xu, Tingting; Cullen, Kathryn R; Mueller, Bryon; Schreiner, Mindy W; Lim, Kelvin O; Schulz, S Charles; Parhi, Keshab K

2016-01-01

Borderline personality disorder (BPD) is associated with symptoms such as affect dysregulation, impaired sense of self, and self-harm behaviors. Neuroimaging research on BPD has revealed structural and functional abnormalities in specific brain regions and connections. However, little is known about the topological organizations of brain networks in BPD. We collected resting-state functional magnetic resonance imaging (fMRI) data from 20 patients with BPD and 10 healthy controls, and constructed frequency-specific functional brain networks by correlating wavelet-filtered fMRI signals from 82 cortical and subcortical regions. We employed graph-theory based complex network analysis to investigate the topological properties of the brain networks, and employed network-based statistic to identify functional dysconnections in patients. In the 0.03-0.06 Hz frequency band, compared to controls, patients with BPD showed significantly larger measures of global network topology, including the size of largest connected graph component, clustering coefficient, small-worldness, and local efficiency, indicating increased local cliquishness of the functional brain network. Compared to controls, patients showed lower nodal centrality at several hub nodes but greater centrality at several non-hub nodes in the network. Furthermore, an interconnected subnetwork in 0.03-0.06 Hz frequency band was identified that showed significantly lower connectivity in patients. The links in the subnetwork were mainly long-distance connections between regions located at different lobes; and the mean connectivity of this subnetwork was negatively correlated with the increased global topology measures. Lastly, the key network measures showed high correlations with several clinical symptom scores, and classified BPD patients against healthy controls with high accuracy based on linear discriminant analysis. The abnormal topological properties and connectivity found in this study may add new knowledge to the current understanding of functional brain networks in BPD. However, due to limitation of small sample sizes, the results of the current study should be viewed as exploratory and need to be validated on large samples in future works.

Characterizing individual differences in functional connectivity using dual-regression and seed-based approaches.

PubMed

Smith, David V; Utevsky, Amanda V; Bland, Amy R; Clement, Nathan; Clithero, John A; Harsch, Anne E W; McKell Carter, R; Huettel, Scott A

2014-07-15

A central challenge for neuroscience lies in relating inter-individual variability to the functional properties of specific brain regions. Yet, considerable variability exists in the connectivity patterns between different brain areas, potentially producing reliable group differences. Using sex differences as a motivating example, we examined two separate resting-state datasets comprising a total of 188 human participants. Both datasets were decomposed into resting-state networks (RSNs) using a probabilistic spatial independent component analysis (ICA). We estimated voxel-wise functional connectivity with these networks using a dual-regression analysis, which characterizes the participant-level spatiotemporal dynamics of each network while controlling for (via multiple regression) the influence of other networks and sources of variability. We found that males and females exhibit distinct patterns of connectivity with multiple RSNs, including both visual and auditory networks and the right frontal-parietal network. These results replicated across both datasets and were not explained by differences in head motion, data quality, brain volume, cortisol levels, or testosterone levels. Importantly, we also demonstrate that dual-regression functional connectivity is better at detecting inter-individual variability than traditional seed-based functional connectivity approaches. Our findings characterize robust-yet frequently ignored-neural differences between males and females, pointing to the necessity of controlling for sex in neuroscience studies of individual differences. Moreover, our results highlight the importance of employing network-based models to study variability in functional connectivity. Copyright © 2014 Elsevier Inc. All rights reserved.

Functional network-based statistics in depression: Theory of mind subnetwork and importance of parietal region.

PubMed

Lai, Chien-Han; Wu, Yu-Te; Hou, Yuh-Ming

2017-08-01

The functional network analysis of whole brain is an emerging field for research in depression. We initiated this study to investigate which subnetwork is significantly altered within the functional connectome in major depressive disorder (MDD). The study enrolled 52 first-episode medication-naïve patients with MDD and 40 controls for functional network analysis. All participants received the resting-state functional imaging using a 3-Tesla magnetic resonance scanner. After preprocessing, we calculated the connectivity matrix of functional connectivity in whole brain for each subject. The network-based statistics of connectome was used to perform group comparisons between patients and controls. The correlations between functional connectivity and clinical parameters were also performed. MDD patients had significant alterations in the network involving "theory of mind" regions, such as the left precentral gyrus, left angular gyrus, bilateral rolandic operculums and left inferior frontal gyrus. The center node of significant network was the left angular gyrus. No significant correlations of functional connectivity within the subnetwork and clinical parameters were noted. Functional connectivity of "theory of mind" subnetwork may be the core issue for pathophysiology in MDD. In addition, the center role of parietal region should be emphasized in future study. Copyright © 2017. Published by Elsevier B.V.

Genomic connectivity networks based on the BrainSpan atlas of the developing human brain

NASA Astrophysics Data System (ADS)

Mahfouz, Ahmed; Ziats, Mark N.; Rennert, Owen M.; Lelieveldt, Boudewijn P. F.; Reinders, Marcel J. T.

2014-03-01

The human brain comprises systems of networks that span the molecular, cellular, anatomic and functional levels. Molecular studies of the developing brain have focused on elucidating networks among gene products that may drive cellular brain development by functioning together in biological pathways. On the other hand, studies of the brain connectome attempt to determine how anatomically distinct brain regions are connected to each other, either anatomically (diffusion tensor imaging) or functionally (functional MRI and EEG), and how they change over development. A global examination of the relationship between gene expression and connectivity in the developing human brain is necessary to understand how the genetic signature of different brain regions instructs connections to other regions. Furthermore, analyzing the development of connectivity networks based on the spatio-temporal dynamics of gene expression provides a new insight into the effect of neurodevelopmental disease genes on brain networks. In this work, we construct connectivity networks between brain regions based on the similarity of their gene expression signature, termed "Genomic Connectivity Networks" (GCNs). Genomic connectivity networks were constructed using data from the BrainSpan Transcriptional Atlas of the Developing Human Brain. Our goal was to understand how the genetic signatures of anatomically distinct brain regions relate to each other across development. We assessed the neurodevelopmental changes in connectivity patterns of brain regions when networks were constructed with genes implicated in the neurodevelopmental disorder autism (autism spectrum disorder; ASD). Using graph theory metrics to characterize the GCNs, we show that ASD-GCNs are relatively less connected later in development with the cerebellum showing a very distinct expression of ASD-associated genes compared to other brain regions.

Greater preference consistency during the Willingness-to-Pay task is related to higher resting state connectivity between the ventromedial prefrontal cortex and the ventral striatum.

PubMed

Mackey, Scott; Olafsson, Valur; Aupperle, Robin L; Lu, Kun; Fonzo, Greg A; Parnass, Jason; Liu, Thomas; Paulus, Martin P

2016-09-01

The significance of why a similar set of brain regions are associated with the default mode network and value-related neural processes remains to be clarified. Here, we examined i) whether brain regions exhibiting willingness-to-pay (WTP) task-related activity are intrinsically connected when the brain is at rest, ii) whether these regions overlap spatially with the default mode network, and iii) whether individual differences in choice behavior during the WTP task are reflected in functional brain connectivity at rest. Blood-oxygen-level dependent (BOLD) signal was measured by functional magnetic resonance imaging while subjects performed the WTP task and at rest with eyes open. Brain regions that tracked the value of bids during the WTP task were used as seed regions in an analysis of functional connectivity in the resting state data. The seed in the ventromedial prefrontal cortex was functionally connected to core regions of the WTP task-related network. Brain regions within the WTP task-related network, namely the ventral precuneus, ventromedial prefrontal and posterior cingulate cortex overlapped spatially with publically available maps of the default mode network. Also, those individuals with higher functional connectivity during rest between the ventromedial prefrontal cortex and the ventral striatum showed greater preference consistency during the WTP task. Thus, WTP task-related regions are an intrinsic network of the brain that corresponds spatially with the default mode network, and individual differences in functional connectivity within the WTP network at rest may reveal a priori biases in choice behavior.

Greater preference consistency during the Willingness-to-Pay task is related to higher resting state connectivity between the ventromedial prefrontal cortex and the ventral striatum

PubMed Central

Mackey, Scott; Olafsson, Valur; Aupperle, Robin; Lu, Kun; Fonzo, Greg; Parnass, Jason; Liu, Thomas; Paulus, Martin P.

2015-01-01

The significance of why a similar set of brain regions are associated with the default mode network and value-related neural processes remains to be clarified. Here, we examined i) whether brain regions exhibiting willingness-to-pay (WTP) task-related activity are intrinsically connected when the brain is at rest, ii) whether these regions overlap spatially with the default mode network, and iii) whether individual differences in choice behavior during the WTP task are reflected in functional brain connectivity at rest. Blood-oxygen-level dependent (BOLD) signal was measured by functional magnetic resonance imaging while subjects performed the WTP task and at rest with eyes open. Brain regions that tracked the value of bids during the WTP task were used as seed regions in an analysis of functional connectivity in the resting state data. The seed in the ventromedial prefrontal cortex was functionally connected to core regions of the WTP task-related network. Brain regions within the WTP task-related network, namely the ventral precuneus, ventromedial prefrontal and posterior cingulate cortex overlapped spatially with publically available maps of the default mode network. Also, those individuals with higher functional connectivity during rest between the ventromedial prefrontal cortex and the ventral striatum showed greater preference consistency during the WTP task. Thus, WTP task-related regions are an intrinsic network of the brain that corresponds spatially with the default mode network, and individual differences in functional connectivity within the WTP network at rest may reveal a priori biases in choice behavior. PMID:26271206

Altered Functional Connectivity of Insular Subregions in Alzheimer’s Disease

PubMed Central

Liu, Xingyun; Chen, Xiaodan; Zheng, Weimin; Xia, Mingrui; Han, Ying; Song, Haiqing; Li, Kuncheng; He, Yong; Wang, Zhiqun

2018-01-01

Recent researches have demonstrated that the insula is the crucial hub of the human brain networks and most vulnerable region of Alzheimer’s disease (AD). However, little is known about the changes of functional connectivity of insular subregions in the AD patients. In this study, we collected resting-state functional magnetic resonance imaging (fMRI) data including 32 AD patients and 38 healthy controls (HCs). By defining three subregions of insula, we mapped whole-brain resting-state functional connectivity (RSFC) and identified several distinct RSFC patterns of the insular subregions: For positive connectivity, three cognitive-related RSFC patterns were identified within insula that suggest anterior-to-posterior functional subdivisions: (1) an dorsal anterior zone of the insula that exhibits RSFC with executive control network (ECN); (2) a ventral anterior zone of insula, exhibits functional connectivity with the salience network (SN); (3) a posterior zone along the insula exhibits functional connectivity with the sensorimotor network (SMN). In addition, we found significant negative connectivities between the each insular subregion and several special default mode network (DMN) regions. Compared with controls, the AD patients demonstrated distinct disruption of positive RSFCs in the different network (ECN and SMN), suggesting the impairment of the functional integrity. There were no differences of the positive RSFCs in the SN between the two groups. On the other hand, several DMN regions showed increased negative RSFCs to the sub-region of insula in the AD patients, indicating compensatory plasticity. Furthermore, these abnormal insular subregions RSFCs are closely correlated with cognitive performances in the AD patients. Our findings suggested that different insular subregions presented distinct RSFC patterns with various functional networks, which are differently affected in the AD patients. PMID:29695961

Altered Functional Connectivity of Insular Subregions in Alzheimer's Disease.

PubMed

Liu, Xingyun; Chen, Xiaodan; Zheng, Weimin; Xia, Mingrui; Han, Ying; Song, Haiqing; Li, Kuncheng; He, Yong; Wang, Zhiqun

2018-01-01

Recent researches have demonstrated that the insula is the crucial hub of the human brain networks and most vulnerable region of Alzheimer's disease (AD). However, little is known about the changes of functional connectivity of insular subregions in the AD patients. In this study, we collected resting-state functional magnetic resonance imaging (fMRI) data including 32 AD patients and 38 healthy controls (HCs). By defining three subregions of insula, we mapped whole-brain resting-state functional connectivity (RSFC) and identified several distinct RSFC patterns of the insular subregions: For positive connectivity, three cognitive-related RSFC patterns were identified within insula that suggest anterior-to-posterior functional subdivisions: (1) an dorsal anterior zone of the insula that exhibits RSFC with executive control network (ECN); (2) a ventral anterior zone of insula, exhibits functional connectivity with the salience network (SN); (3) a posterior zone along the insula exhibits functional connectivity with the sensorimotor network (SMN). In addition, we found significant negative connectivities between the each insular subregion and several special default mode network (DMN) regions. Compared with controls, the AD patients demonstrated distinct disruption of positive RSFCs in the different network (ECN and SMN), suggesting the impairment of the functional integrity. There were no differences of the positive RSFCs in the SN between the two groups. On the other hand, several DMN regions showed increased negative RSFCs to the sub-region of insula in the AD patients, indicating compensatory plasticity. Furthermore, these abnormal insular subregions RSFCs are closely correlated with cognitive performances in the AD patients. Our findings suggested that different insular subregions presented distinct RSFC patterns with various functional networks, which are differently affected in the AD patients.

Learning Control Over Emotion Networks Through Connectivity-Based Neurofeedback.

PubMed

Koush, Yury; Meskaldji, Djalel-E; Pichon, Swann; Rey, Gwladys; Rieger, Sebastian W; Linden, David E J; Van De Ville, Dimitri; Vuilleumier, Patrik; Scharnowski, Frank

2017-02-01

Most mental functions are associated with dynamic interactions within functional brain networks. Thus, training individuals to alter functional brain networks might provide novel and powerful means to improve cognitive performance and emotions. Using a novel connectivity-neurofeedback approach based on functional magnetic resonance imaging (fMRI), we show for the first time that participants can learn to change functional brain networks. Specifically, we taught participants control over a key component of the emotion regulation network, in that they learned to increase top-down connectivity from the dorsomedial prefrontal cortex, which is involved in cognitive control, onto the amygdala, which is involved in emotion processing. After training, participants successfully self-regulated the top-down connectivity between these brain areas even without neurofeedback, and this was associated with concomitant increases in subjective valence ratings of emotional stimuli of the participants. Connectivity-based neurofeedback goes beyond previous neurofeedback approaches, which were limited to training localized activity within a brain region. It allows to noninvasively and nonpharmacologically change interconnected functional brain networks directly, thereby resulting in specific behavioral changes. Our results demonstrate that connectivity-based neurofeedback training of emotion regulation networks enhances emotion regulation capabilities. This approach can potentially lead to powerful therapeutic emotion regulation protocols for neuropsychiatric disorders. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Functional connectivity in the developing brain: A longitudinal study from 4 to 9 months of age

PubMed Central

Damaraju, E.; Caprihan, A.; Lowe, J.R.; Allen, E.A.; Calhoun, V.D.; Phillips, J.P.

2013-01-01

We characterize the development of intrinsic connectivity networks (ICNs) from 4 to 9 months of age with resting state magnetic resonance imaging performed on sleeping infants without sedative medication. Data is analyzed with independent component analysis (ICA). Using both low (30 components) and high (100 components) ICA model order decompositions, we find that the functional network connectivity (FNC) map is largely similar at both 4 and 9 months. However at 9 months the connectivity strength decreases within local networks and increases between more distant networks. The connectivity within the default-mode network, which contains both local and more distant nodes, also increases in strength with age. The low frequency power spectrum increases with age only in the posterior cingulate cortex and posterior default mode network. These findings are consistent with a general developmental pattern of increasing longer distance functional connectivity over the first year of life and raise questions regarding the developmental importance of the posterior cingulate at this age. PMID:23994454

Functional connectivity in the developing brain: a longitudinal study from 4 to 9months of age.

PubMed

Damaraju, E; Caprihan, A; Lowe, J R; Allen, E A; Calhoun, V D; Phillips, J P

2014-01-01

We characterize the development of intrinsic connectivity networks (ICNs) from 4 to 9months of age with resting state magnetic resonance imaging performed on sleeping infants without sedative medication. Data is analyzed with independent component analysis (ICA). Using both low (30 components) and high (100 components) ICA model order decompositions, we find that the functional network connectivity (FNC) map is largely similar at both 4 and 9months. However at 9months the connectivity strength decreases within local networks and increases between more distant networks. The connectivity within the default-mode network, which contains both local and more distant nodes, also increases in strength with age. The low frequency power spectrum increases with age only in the posterior cingulate cortex and posterior default mode network. These findings are consistent with a general developmental pattern of increasing longer distance functional connectivity over the first year of life and raise questions regarding the developmental importance of the posterior cingulate at this age. © 2013.

Psychophysiological whole-brain network clustering based on connectivity dynamics analysis in naturalistic conditions.

PubMed

Raz, Gal; Shpigelman, Lavi; Jacob, Yael; Gonen, Tal; Benjamini, Yoav; Hendler, Talma

2016-12-01

We introduce a novel method for delineating context-dependent functional brain networks whose connectivity dynamics are synchronized with the occurrence of a specific psychophysiological process of interest. In this method of context-related network dynamics analysis (CRNDA), a continuous psychophysiological index serves as a reference for clustering the whole-brain into functional networks. We applied CRNDA to fMRI data recorded during the viewing of a sadness-inducing film clip. The method reliably demarcated networks in which temporal patterns of connectivity related to the time series of reported emotional intensity. Our work successfully replicated the link between network connectivity and emotion rating in an independent sample group for seven of the networks. The demarcated networks have clear common functional denominators. Three of these networks overlap with distinct empathy-related networks, previously identified in distinct sets of studies. The other networks are related to sensorimotor processing, language, attention, and working memory. The results indicate that CRNDA, a data-driven method for network clustering that is sensitive to transient connectivity patterns, can productively and reliably demarcate networks that follow psychologically meaningful processes. Hum Brain Mapp 37:4654-4672, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Differential Effects of Left and Right Prefrontal High-Frequency Repetitive Transcranial Magnetic Stimulation on Resting-State Functional Magnetic Resonance Imaging in Healthy Individuals.

PubMed

Schluter, Renée S; Jansen, Jochem M; van Holst, Ruth J; van den Brink, Wim; Goudriaan, Anna E

2018-03-01

High-frequency repetitive transcranial magnetic stimulation (HF-rTMS) has gained great interest in multiple clinical and research fields and is believed to accomplish its effect by influencing neuronal networks. The dorsolateral prefrontal cortex (dlPFC) is frequently chosen as the cortical target for HF-rTMS. However, very little is known about the differential effect of HF-rTMS over the left and right dlPFC on intrinsic functional connectivity networks in patients or in healthy individuals. The current study assessed the differential effects of left or right HF-rTMS (corrected for sham) on intrinsic independent component analysis (ICA)-defined functional connectivity networks in a sample of 45 healthy individuals. All subjects had a first scanning session in which baseline functional connectivity was assessed. During the second session, individuals received one session of left, right, or sham dlPFC HF-rTMS (60 5-sec trains of 10 Hz at 110% motor threshold). The sham condition was used to correct for time and placebo effects. ICAs were performed to assess baseline differences and stimulation effects on within- and between-network functional connectivity. Stimulation of the left dlPFC resulted in decreased functional connectivity in the salience network, whereas right dlPFC stimulation resulted in increased functional connectivity within this network. No differences between left or right dlPFC stimulation were found in between-network connectivity. These results suggest that left and right HF-rTMS may have differential effects, and more research is needed on the clinical consequences.

White Matter Connectivity of the Thalamus Delineates the Functional Architecture of Competing Thalamocortical Systems

PubMed Central

O'Muircheartaigh, Jonathan; Keller, Simon S.; Barker, Gareth J.; Richardson, Mark P.

2015-01-01

There is an increasing awareness of the involvement of thalamic connectivity on higher level cortical functioning in the human brain. This is reflected by the influence of thalamic stimulation on cortical activity and behavior as well as apparently cortical lesion syndromes occurring as a function of small thalamic insults. Here, we attempt to noninvasively test the correspondence of structural and functional connectivity of the human thalamus using diffusion-weighted and resting-state functional MRI. Using a large sample of 102 adults, we apply tensor independent component analysis to diffusion MRI tractography data to blindly parcellate bilateral thalamus according to diffusion tractography-defined structural connectivity. Using resting-state functional MRI collected in the same subjects, we show that the resulting structurally defined thalamic regions map to spatially distinct, and anatomically predictable, whole-brain functional networks in the same subjects. Although there was significant variability in the functional connectivity patterns, the resulting 51 structural and functional patterns could broadly be reduced to a subset of 7 similar core network types. These networks were distinct from typical cortical resting-state networks. Importantly, these networks were distributed across the brain and, in a subset, map extremely well to known thalamocortico-basal-ganglial loops. PMID:25899706

Top-down and bottom-up attention-to-memory: mapping functional connectivity in two distinct networks that underlie cued and uncued recognition memory.

PubMed

Burianová, Hana; Ciaramelli, Elisa; Grady, Cheryl L; Moscovitch, Morris

2012-11-15

The objective of this study was to examine the functional connectivity of brain regions active during cued and uncued recognition memory to test the idea that distinct networks would underlie these memory processes, as predicted by the attention-to-memory (AtoM) hypothesis. The AtoM hypothesis suggests that dorsal parietal cortex (DPC) allocates effortful top-down attention to memory retrieval during cued retrieval, whereas ventral parietal cortex (VPC) mediates spontaneous bottom-up capture of attention by memory during uncued retrieval. To identify networks associated with these two processes, we conducted a functional connectivity analysis of a left DPC and a left VPC region, both identified by a previous analysis of task-related regional activations. We hypothesized that the two parietal regions would be functionally connected with distinct neural networks, reflecting their engagement in the differential mnemonic processes. We found two spatially dissociated networks that overlapped only in the precuneus. During cued trials, DPC was functionally connected with dorsal attention areas, including the superior parietal lobules, right precuneus, and premotor cortex, as well as relevant memory areas, such as the left hippocampus and the middle frontal gyri. During uncued trials, VPC was functionally connected with ventral attention areas, including the supramarginal gyrus, cuneus, and right fusiform gyrus, as well as the parahippocampal gyrus. In addition, activity in the DPC network was associated with faster response times for cued retrieval. This is the first study to show a dissociation of the functional connectivity of posterior parietal regions during episodic memory retrieval, characterized by a top-down AtoM network involving DPC and a bottom-up AtoM network involving VPC. Copyright © 2012 Elsevier Inc. All rights reserved.

Brain Connectivity and Visual Attention

PubMed Central

Parks, Emily L.

2013-01-01

Abstract Emerging hypotheses suggest that efficient cognitive functioning requires the integration of separate, but interconnected cortical networks in the brain. Although task-related measures of brain activity suggest that a frontoparietal network is associated with the control of attention, little is known regarding how components within this distributed network act together or with other networks to achieve various attentional functions. This review considers both functional and structural studies of brain connectivity, as complemented by behavioral and task-related neuroimaging data. These studies show converging results: The frontal and parietal cortical regions are active together, over time, and identifiable frontoparietal networks are active in relation to specific task demands. However, the spontaneous, low-frequency fluctuations of brain activity that occur in the resting state, without specific task demands, also exhibit patterns of connectivity that closely resemble the task-related, frontoparietal attention networks. Both task-related and resting-state networks exhibit consistent relations to behavioral measures of attention. Further, anatomical structure, particularly white matter pathways as defined by diffusion tensor imaging, places constraints on intrinsic functional connectivity. Lastly, connectivity analyses applied to investigate cognitive differences across individuals in both healthy and diseased states suggest that disconnection of attentional networks is linked to deficits in cognitive functioning, and in extreme cases, to disorders of attention. Thus, comprehensive theories of visual attention and their clinical translation depend on the continued integration of behavioral, task-related neuroimaging, and brain connectivity measures. PMID:23597177

Sex differences in normal age trajectories of functional brain networks.

PubMed

Scheinost, Dustin; Finn, Emily S; Tokoglu, Fuyuze; Shen, Xilin; Papademetris, Xenophon; Hampson, Michelle; Constable, R Todd

2015-04-01

Resting-state functional magnetic resonance image (rs-fMRI) is increasingly used to study functional brain networks. Nevertheless, variability in these networks due to factors such as sex and aging is not fully understood. This study explored sex differences in normal age trajectories of resting-state networks (RSNs) using a novel voxel-wise measure of functional connectivity, the intrinsic connectivity distribution (ICD). Males and females showed differential patterns of changing connectivity in large-scale RSNs during normal aging from early adulthood to late middle-age. In some networks, such as the default-mode network, males and females both showed decreases in connectivity with age, albeit at different rates. In other networks, such as the fronto-parietal network, males and females showed divergent connectivity trajectories with age. Main effects of sex and age were found in many of the same regions showing sex-related differences in aging. Finally, these sex differences in aging trajectories were robust to choice of preprocessing strategy, such as global signal regression. Our findings resolve some discrepancies in the literature, especially with respect to the trajectory of connectivity in the default mode, which can be explained by our observed interactions between sex and aging. Overall, results indicate that RSNs show different aging trajectories for males and females. Characterizing effects of sex and age on RSNs are critical first steps in understanding the functional organization of the human brain. © 2014 Wiley Periodicals, Inc.

Network discovery with DCM

PubMed Central

Friston, Karl J.; Li, Baojuan; Daunizeau, Jean; Stephan, Klaas E.

2011-01-01

This paper is about inferring or discovering the functional architecture of distributed systems using Dynamic Causal Modelling (DCM). We describe a scheme that recovers the (dynamic) Bayesian dependency graph (connections in a network) using observed network activity. This network discovery uses Bayesian model selection to identify the sparsity structure (absence of edges or connections) in a graph that best explains observed time-series. The implicit adjacency matrix specifies the form of the network (e.g., cyclic or acyclic) and its graph-theoretical attributes (e.g., degree distribution). The scheme is illustrated using functional magnetic resonance imaging (fMRI) time series to discover functional brain networks. Crucially, it can be applied to experimentally evoked responses (activation studies) or endogenous activity in task-free (resting state) fMRI studies. Unlike conventional approaches to network discovery, DCM permits the analysis of directed and cyclic graphs. Furthermore, it eschews (implausible) Markovian assumptions about the serial independence of random fluctuations. The scheme furnishes a network description of distributed activity in the brain that is optimal in the sense of having the greatest conditional probability, relative to other networks. The networks are characterised in terms of their connectivity or adjacency matrices and conditional distributions over the directed (and reciprocal) effective connectivity between connected nodes or regions. We envisage that this approach will provide a useful complement to current analyses of functional connectivity for both activation and resting-state studies. PMID:21182971

Network diffusion accurately models the relationship between structural and functional brain connectivity networks

PubMed Central

Abdelnour, Farras; Voss, Henning U.; Raj, Ashish

2014-01-01

The relationship between anatomic connectivity of large-scale brain networks and their functional connectivity is of immense importance and an area of active research. Previous attempts have required complex simulations which model the dynamics of each cortical region, and explore the coupling between regions as derived by anatomic connections. While much insight is gained from these non-linear simulations, they can be computationally taxing tools for predicting functional from anatomic connectivities. Little attention has been paid to linear models. Here we show that a properly designed linear model appears to be superior to previous non-linear approaches in capturing the brain’s long-range second order correlation structure that governs the relationship between anatomic and functional connectivities. We derive a linear network of brain dynamics based on graph diffusion, whereby the diffusing quantity undergoes a random walk on a graph. We test our model using subjects who underwent diffusion MRI and resting state fMRI. The network diffusion model applied to the structural networks largely predicts the correlation structures derived from their fMRI data, to a greater extent than other approaches. The utility of the proposed approach is that it can routinely be used to infer functional correlation from anatomic connectivity. And since it is linear, anatomic connectivity can also be inferred from functional data. The success of our model confirms the linearity of ensemble average signals in the brain, and implies that their long-range correlation structure may percolate within the brain via purely mechanistic processes enacted on its structural connectivity pathways. PMID:24384152

Motor deficits correlate with resting state motor network connectivity in patients with brain tumours

PubMed Central

Mikell, Charles B.; Youngerman, Brett E.; Liston, Conor; Sisti, Michael B.; Bruce, Jeffrey N.; Small, Scott A.; McKhann, Guy M.

2012-01-01

While a tumour in or abutting primary motor cortex leads to motor weakness, how tumours elsewhere in the frontal or parietal lobes affect functional connectivity in a weak patient is less clear. We hypothesized that diminished functional connectivity in a distributed network of motor centres would correlate with motor weakness in subjects with brain masses. Furthermore, we hypothesized that interhemispheric connections would be most vulnerable to subtle disruptions in functional connectivity. We used task-free functional magnetic resonance imaging connectivity to probe motor networks in control subjects and patients with brain tumours (n = 22). Using a control dataset, we developed a method for automated detection of key nodes in the motor network, including the primary motor cortex, supplementary motor area, premotor area and superior parietal lobule, based on the anatomic location of the hand-motor knob in the primary motor cortex. We then calculated functional connectivity between motor network nodes in control subjects, as well as patients with and without brain masses. We used this information to construct weighted, undirected graphs, which were then compared to variables of interest, including performance on a motor task, the grooved pegboard. Strong connectivity was observed within the identified motor networks between all nodes bilaterally, and especially between the primary motor cortex and supplementary motor area. Reduced connectivity was observed in subjects with motor weakness versus subjects with normal strength (P < 0.001). This difference was driven mostly by decreases in interhemispheric connectivity between the primary motor cortices (P < 0.05) and between the left primary motor cortex and the right premotor area (P < 0.05), as well as other premotor area connections. In the subjects without motor weakness, however, performance on the grooved pegboard did not relate to interhemispheric connectivity, but rather was inversely correlated with connectivity between the left premotor area and left supplementary motor area, for both the left and the right hands (P < 0.01). Finally, two subjects who experienced severe weakness following surgery for their brain tumours were followed longitudinally, and the subject who recovered showed reconstitution of her motor network at follow-up. The subject who was persistently weak did not reconstitute his motor network. Motor weakness in subjects with brain tumours that do not involve primary motor structures is associated with decreased connectivity within motor functional networks, particularly interhemispheric connections. Motor networks become weaker as the subjects become weaker, and may become strong again during motor recovery. PMID:22408270

Resting state network topology of the ferret brain.

PubMed

Zhou, Zhe Charles; Salzwedel, Andrew P; Radtke-Schuller, Susanne; Li, Yuhui; Sellers, Kristin K; Gilmore, John H; Shih, Yen-Yu Ian; Fröhlich, Flavio; Gao, Wei

2016-12-01

Resting state functional magnetic resonance imaging (rsfMRI) has emerged as a versatile tool for non-invasive measurement of functional connectivity patterns in the brain. RsfMRI brain dynamics in rodents, non-human primates, and humans share similar properties; however, little is known about the resting state functional connectivity patterns in the ferret, an animal model with high potential for developmental and cognitive translational study. To address this knowledge-gap, we performed rsfMRI on anesthetized ferrets using a 9.4T MRI scanner, and subsequently performed group-level independent component analysis (gICA) to identify functionally connected brain networks. Group-level ICA analysis revealed distributed sensory, motor, and higher-order networks in the ferret brain. Subsequent connectivity analysis showed interconnected higher-order networks that constituted a putative default mode network (DMN), a network that exhibits altered connectivity in neuropsychiatric disorders. Finally, we assessed ferret brain topological efficiency using graph theory analysis and found that the ferret brain exhibits small-world properties. Overall, these results provide additional evidence for pan-species resting-state networks, further supporting ferret-based studies of sensory and cognitive function. Copyright © 2016 Elsevier Inc. All rights reserved.

PTEN Loss Increases the Connectivity of Fast Synaptic Motifs and Functional Connectivity in a Developing Hippocampal Network.

PubMed

Barrows, Caitlynn M; McCabe, Matthew P; Chen, Hongmei; Swann, John W; Weston, Matthew C

2017-09-06

Changes in synaptic strength and connectivity are thought to be a major mechanism through which many gene variants cause neurological disease. Hyperactivation of the PI3K-mTOR signaling network, via loss of function of repressors such as PTEN, causes epilepsy in humans and animal models, and altered mTOR signaling may contribute to a broad range of neurological diseases. Changes in synaptic transmission have been reported in animal models of PTEN loss; however, the full extent of these changes, and their effect on network function, is still unknown. To better understand the scope of these changes, we recorded from pairs of mouse hippocampal neurons cultured in a two-neuron microcircuit configuration that allowed us to characterize all four major connection types within the hippocampus. Loss of PTEN caused changes in excitatory and inhibitory connectivity, and these changes were postsynaptic, presynaptic, and transynaptic, suggesting that disruption of PTEN has the potential to affect most connection types in the hippocampal circuit. Given the complexity of the changes at the synaptic level, we measured changes in network behavior after deleting Pten from neurons in an organotypic hippocampal slice network. Slices containing Pten -deleted neurons showed increased recruitment of neurons into network bursts. Importantly, these changes were not confined to Pten -deleted neurons, but involved the entire network, suggesting that the extensive changes in synaptic connectivity rewire the entire network in such a way that promotes a widespread increase in functional connectivity. SIGNIFICANCE STATEMENT Homozygous deletion of the Pten gene in neuronal subpopulations in the mouse serves as a valuable model of epilepsy caused by mTOR hyperactivation. To better understand how gene deletions lead to altered neuronal activity, we investigated the synaptic and network effects that occur 1 week after Pten deletion. PTEN loss increased the connectivity of all four types of hippocampal synaptic connections, including two forms of increased inhibition of inhibition, and increased network functional connectivity. These data suggest that single gene mutations that cause neurological diseases such as epilepsy may affect a surprising range of connection types. Moreover, given the robustness of homeostatic plasticity, these diverse effects on connection types may be necessary to cause network phenotypes such as increased synchrony. Copyright © 2017 the authors 0270-6474/17/378595-17$15.00/0.

PTEN Loss Increases the Connectivity of Fast Synaptic Motifs and Functional Connectivity in a Developing Hippocampal Network

PubMed Central

McCabe, Matthew P.; Chen, Hongmei; Swann, John W.

2017-01-01

Changes in synaptic strength and connectivity are thought to be a major mechanism through which many gene variants cause neurological disease. Hyperactivation of the PI3K-mTOR signaling network, via loss of function of repressors such as PTEN, causes epilepsy in humans and animal models, and altered mTOR signaling may contribute to a broad range of neurological diseases. Changes in synaptic transmission have been reported in animal models of PTEN loss; however, the full extent of these changes, and their effect on network function, is still unknown. To better understand the scope of these changes, we recorded from pairs of mouse hippocampal neurons cultured in a two-neuron microcircuit configuration that allowed us to characterize all four major connection types within the hippocampus. Loss of PTEN caused changes in excitatory and inhibitory connectivity, and these changes were postsynaptic, presynaptic, and transynaptic, suggesting that disruption of PTEN has the potential to affect most connection types in the hippocampal circuit. Given the complexity of the changes at the synaptic level, we measured changes in network behavior after deleting Pten from neurons in an organotypic hippocampal slice network. Slices containing Pten-deleted neurons showed increased recruitment of neurons into network bursts. Importantly, these changes were not confined to Pten-deleted neurons, but involved the entire network, suggesting that the extensive changes in synaptic connectivity rewire the entire network in such a way that promotes a widespread increase in functional connectivity. SIGNIFICANCE STATEMENT Homozygous deletion of the Pten gene in neuronal subpopulations in the mouse serves as a valuable model of epilepsy caused by mTOR hyperactivation. To better understand how gene deletions lead to altered neuronal activity, we investigated the synaptic and network effects that occur 1 week after Pten deletion. PTEN loss increased the connectivity of all four types of hippocampal synaptic connections, including two forms of increased inhibition of inhibition, and increased network functional connectivity. These data suggest that single gene mutations that cause neurological diseases such as epilepsy may affect a surprising range of connection types. Moreover, given the robustness of homeostatic plasticity, these diverse effects on connection types may be necessary to cause network phenotypes such as increased synchrony. PMID:28751459

Exploring the Associations Between Intrinsic Brain Connectivity and Creative Ability Using Functional Connectivity Strength and Connectome Analysis.

PubMed

Gao, Zhenni; Zhang, Delong; Liang, Aiying; Liang, Bishan; Wang, Zengjian; Cai, Yuxuan; Li, Junchao; Gao, Mengxia; Liu, Xiaojin; Chang, Song; Jiao, Bingqing; Huang, Ruiwang; Liu, Ming

2017-11-01

The present study aimed to explore the association between resting-state functional connectivity and creativity ability. Toward this end, the figural Torrance Tests of Creative Thinking (TTCT) scores were collected from 180 participants. Based on the figural TTCT measures, we collected resting-state functional magnetic resonance imaging data for participants with two different levels of creativity ability (a high-creativity group [HG, n = 22] and a low-creativity group [LG, n = 20]). For the aspect of group difference, this study combined voxel-wise functional connectivity strength (FCS) and seed-based functional connectivity to identify brain regions with group-change functional connectivity. Furthermore, the connectome properties of the identified regions and their associations with creativity were investigated using the permutation test, discriminative analysis, and brain-behavior correlation analysis. The results indicated that there were 4 regions with group differences in FCS, and these regions were linked to 30 other regions, demonstrating different functional connectivity between the groups. Together, these regions form a creativity-related network, and we observed higher network efficiency in the HG compared with the LG. The regions involved in the creativity network were widely distributed across the modality-specific/supramodality cerebral cortex, subcortex, and cerebellum. Notably, properties of regions in the supramodality networks (i.e., the default mode network and attention network) carried creativity-level discriminative information and were significantly correlated with the creativity performance. Together, these findings demonstrate a link between intrinsic brain connectivity and creative ability, which should provide new insights into the neural basis of creativity.

Spontaneous eyelid closures link vigilance fluctuation with fMRI dynamic connectivity states

PubMed Central

Wang, Chenhao; Ong, Ju Lynn; Patanaik, Amiya; Chee, Michael W. L.

2016-01-01

Fluctuations in resting-state functional connectivity occur but their behavioral significance remains unclear, largely because correlating behavioral state with dynamic functional connectivity states (DCS) engages probes that disrupt the very behavioral state we seek to observe. Observing spontaneous eyelid closures following sleep deprivation permits nonintrusive arousal monitoring. During periods of low arousal dominated by eyelid closures, sliding-window correlation analysis uncovered a DCS associated with reduced within-network functional connectivity of default mode and dorsal/ventral attention networks, as well as reduced anticorrelation between these networks. Conversely, during periods when participants’ eyelids were wide open, a second DCS was associated with less decoupling between the visual network and higher-order cognitive networks that included dorsal/ventral attention and default mode networks. In subcortical structures, eyelid closures were associated with increased connectivity between the striatum and thalamus with the ventral attention network, and greater anticorrelation with the dorsal attention network. When applied to task-based fMRI data, these two DCS predicted interindividual differences in frequency of behavioral lapsing and intraindividual temporal fluctuations in response speed. These findings with participants who underwent a night of total sleep deprivation were replicated in an independent dataset involving partially sleep-deprived participants. Fluctuations in functional connectivity thus appear to be clearly associated with changes in arousal. PMID:27512040

Independent functional connectivity networks underpin food and monetary reward sensitivity in excess weight.

PubMed

Verdejo-Román, Juan; Fornito, Alex; Soriano-Mas, Carles; Vilar-López, Raquel; Verdejo-García, Antonio

2017-02-01

Overvaluation of palatable food is a primary driver of obesity, and is associated with brain regions of the reward system. However, it remains unclear if this network is specialized in food reward, or generally involved in reward processing. We used functional magnetic resonance imaging (fMRI) to characterize functional connectivity during processing of food and monetary rewards. Thirty-nine adults with excess weight and 37 adults with normal weight performed the Willingness to Pay for Food task and the Monetary Incentive Delay task in the fMRI scanner. A data-driven graph approach was applied to compare whole-brain, task-related functional connectivity between groups. Excess weight was associated with decreased functional connectivity during the processing of food rewards in a network involving primarily frontal and striatal areas, and increased functional connectivity during the processing of monetary rewards in a network involving principally frontal and parietal areas. These two networks were topologically and anatomically distinct, and were independently associated with BMI. The processing of food and monetary rewards involve segregated neural networks, and both are altered in individuals with excess weight. Copyright © 2016 Elsevier Inc. All rights reserved.

Multimodal investigation of triple network connectivity in patients with 22q11DS and association with executive functions.

PubMed

Padula, Maria C; Schaer, Marie; Scariati, Elisa; Maeder, Johanna; Schneider, Maude; Eliez, Stephan

2017-04-01

Large-scale brain networks play a prominent role in cognitive abilities and their activity is impaired in psychiatric disorders, such as schizophrenia. Patients with 22q11.2 deletion syndrome (22q11DS) are at high risk of developing schizophrenia and present similar cognitive impairments, including executive functions deficits. Thus, 22q11DS represents a model for the study of neural biomarkers associated with schizophrenia. In this study, we investigated structural and functional connectivity within and between the Default Mode (DMN), the Central Executive (CEN), and the Saliency network (SN) in 22q11DS using resting-state fMRI and DTI. Furthermore, we investigated if triple network impairments were related to executive dysfunctions or the presence of psychotic symptoms. Sixty-three patients with 22q11DS and sixty-eighty controls (age 6-33 years) were included in the study. Structural connectivity between main nodes of DMN, CEN, and SN was computed using probabilistic tractography. Functional connectivity was computed as the partial correlation between the time courses extracted from each node. Structural and functional connectivity measures were then correlated to executive functions and psychotic symptom scores. Our results showed mainly reduced structural connectivity within the CEN, DMN, and SN, in patients with 22q11DS compared with controls as well as reduced between-network connectivity. Functional connectivity appeared to be more preserved, with impairments being evident only within the DMN. Structural connectivity impairments were also related to executive dysfunctions. These findings show an association between triple network structural alterations and executive deficits in patients with the microdeletion, suggesting that 22q11DS and schizophrenia share common psychopathological mechanisms. Hum Brain Mapp 38:2177-2189, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Behavioral Interpretations of Intrinsic Connectivity Networks

ERIC Educational Resources Information Center

Laird, Angela R.; Fox, P. Mickle; Eickhoff, Simon B.; Turner, Jessica A.; Ray, Kimberly L.; McKay, D. Reese; Glahn, David C.; Beckmann, Christian F.; Smith, Stephen M.; Fox, Peter T.

2011-01-01

An increasingly large number of neuroimaging studies have investigated functionally connected networks during rest, providing insight into human brain architecture. Assessment of the functional qualities of resting state networks has been limited by the task-independent state, which results in an inability to relate these networks to specific…

Functional resting-state networks are differentially affected in schizophrenia

PubMed Central

Woodward, Neil D.; Rogers, Baxter; Heckers, Stephan

2011-01-01

Neurobiological theories posit that schizophrenia relates to disturbances in connectivity between brain regions. Resting-state functional magnetic resonance imaging is a powerful tool for examining functional connectivity and has revealed several canonical brain networks, including the default mode, dorsal attention, executive control, and salience networks. The purpose of this study was to examine changes in these networks in schizophrenia. 42 patients with schizophrenia and 61 healthy subjects completed a RS-fMRI scanning session. Seed-based region-of-interest correlation analysis was used to identify the default mode, dorsal attention, executive control, and salience networks. Compared to healthy subjects, individuals with schizophrenia demonstrated greater connectivity between the posterior cingulate cortex, a key hub of the default mode, and the left inferior gyrus, left middle frontal gyrus, and left middle temporal gyrus. Interestingly, these regions were more strongly connected to the executive control network in healthy control subjects. In contrast to the default mode, patients demonstrated less connectivity in the executive control and dorsal attention networks. No differences were observed in the salience network. The results indicate that resting-state networks are differentially affected in schizophrenia. The alterations are characterized by reduced segregation between the default mode and executive control networks in the prefrontal cortex and temporal lobe, and reduced connectivity in the dorsal attention and executive control networks. The changes suggest that the process of functional specialization is altered in schizophrenia. Further work is needed to determine if the alterations are related to disturbances in white matter connectivity, neurodevelopmental abnormalities, and genetic risk for schizophrenia. PMID:21458238

Intrinsic Amygdala-Cortical Functional Connectivity Predicts Social Network Size in Humans

PubMed Central

Bickart, Kevin C.; Hollenbeck, Mark C.; Barrett, Lisa Feldman; Dickerson, Bradford C.

2012-01-01

Using resting-state functional MRI data from two independent samples of healthy adults, we parsed the amygdala’s intrinsic connectivity into three partially-distinct large-scale networks that strongly resemble the known anatomical organization of amygdala connectivity in rodents and monkeys. Moreover, in a third independent sample, we discovered that people who fostered and maintained larger and more complex social networks not only had larger amygdala volumes, but also amygdalae with stronger intrinsic connectivity within two of these networks, one putatively subserving perceptual abilities and one subserving affiliative behaviors. Our findings were anatomically specific to amygdalar circuitry in that individual differences in social network size and complexity could not be explained by the strength of intrinsic connectivity between nodes within two networks that do not typically involve the amygdala (i.e., the mentalizing and mirror networks), and were behaviorally specific in that amygdala connectivity did not correlate with other self-report measures of sociality. PMID:23077058

Aberrant cerebellar connectivity in motor and association networks in schizophrenia

PubMed Central

Shinn, Ann K.; Baker, Justin T.; Lewandowski, Kathryn E.; Öngür, Dost; Cohen, Bruce M.

2015-01-01

Schizophrenia is a devastating illness characterized by disturbances in multiple domains. The cerebellum is involved in both motor and non-motor functions, and the “cognitive dysmetria” and “dysmetria of thought” models propose that abnormalities of the cerebellum may contribute to schizophrenia signs and symptoms. The cerebellum and cerebral cortex are reciprocally connected via a modular, closed-loop network architecture, but few schizophrenia neuroimaging studies have taken into account the topographical and functional heterogeneity of the cerebellum. In this study, using a previously defined 17-network cerebral cortical parcellation system as the basis for our functional connectivity seeds, we systematically investigated connectivity abnormalities within the cerebellum of 44 schizophrenia patients and 28 healthy control participants. We found selective alterations in cerebro-cerebellar functional connectivity. Specifically, schizophrenia patients showed decreased cerebro-cerebellar functional connectivity in higher level association networks (ventral attention, salience, control, and default mode networks) relative to healthy control participants. Schizophrenia patients also showed increased cerebro-cerebellar connectivity in somatomotor and default mode networks, with the latter showing no overlap with the regions found to be hypoconnected within the same default mode network. Finally, we found evidence to suggest that somatomotor and default mode networks may be inappropriately linked in schizophrenia. The relationship of these dysconnectivities to schizophrenia symptoms, such as neurological soft signs and altered sense of agency, is discussed. We conclude that the cerebellum ought to be considered for analysis in all future studies of network abnormalities in SZ, and further suggest the cerebellum as a potential target for further elucidation, and possibly treatment, of the underlying mechanisms and network abnormalities producing symptoms of schizophrenia. PMID:25852520

Risperidone Effects on Brain Dynamic Connectivity-A Prospective Resting-State fMRI Study in Schizophrenia.

PubMed

Lottman, Kristin K; Kraguljac, Nina V; White, David M; Morgan, Charity J; Calhoun, Vince D; Butt, Allison; Lahti, Adrienne C

2017-01-01

Resting-state functional connectivity studies in schizophrenia evaluating average connectivity over the entire experiment have reported aberrant network integration, but findings are variable. Examining time-varying (dynamic) functional connectivity may help explain some inconsistencies. We assessed dynamic network connectivity using resting-state functional MRI in patients with schizophrenia, while unmedicated ( n  = 34), after 1 week ( n  = 29) and 6 weeks of treatment with risperidone ( n  = 24), as well as matched controls at baseline ( n  = 35) and after 6 weeks ( n  = 19). After identifying 41 independent components (ICs) comprising resting-state networks, sliding window analysis was performed on IC timecourses using an optimal window size validated with linear support vector machines. Windowed correlation matrices were then clustered into three discrete connectivity states (a relatively sparsely connected state, a relatively abundantly connected state, and an intermediately connected state). In unmedicated patients, static connectivity was increased between five pairs of ICs and decreased between two pairs of ICs when compared to controls, dynamic connectivity showed increased connectivity between the thalamus and somatomotor network in one of the three states. State statistics indicated that, in comparison to controls, unmedicated patients had shorter mean dwell times and fraction of time spent in the sparsely connected state, and longer dwell times and fraction of time spent in the intermediately connected state. Risperidone appeared to normalize mean dwell times after 6 weeks, but not fraction of time. Results suggest that static connectivity abnormalities in schizophrenia may partly be related to altered brain network temporal dynamics rather than consistent dysconnectivity within and between functional networks and demonstrate the importance of implementing complementary data analysis techniques.

Functional network connectivity underlying food processing: disturbed salience and visual processing in overweight and obese adults.

PubMed

Kullmann, Stephanie; Pape, Anna-Antonia; Heni, Martin; Ketterer, Caroline; Schick, Fritz; Häring, Hans-Ulrich; Fritsche, Andreas; Preissl, Hubert; Veit, Ralf

2013-05-01

In order to adequately explore the neurobiological basis of eating behavior of humans and their changes with body weight, interactions between brain areas or networks need to be investigated. In the current functional magnetic resonance imaging study, we examined the modulating effects of stimulus category (food vs. nonfood), caloric content of food, and body weight on the time course and functional connectivity of 5 brain networks by means of independent component analysis in healthy lean and overweight/obese adults. These functional networks included motor sensory, default-mode, extrastriate visual, temporal visual association, and salience networks. We found an extensive modulation elicited by food stimuli in the 2 visual and salience networks, with a dissociable pattern in the time course and functional connectivity between lean and overweight/obese subjects. Specifically, only in lean subjects, the temporal visual association network was modulated by the stimulus category and the salience network by caloric content, whereas overweight and obese subjects showed a generalized augmented response in the salience network. Furthermore, overweight/obese subjects showed changes in functional connectivity in networks important for object recognition, motivational salience, and executive control. These alterations could potentially lead to top-down deficiencies driving the overconsumption of food in the obese population.

Reduced brain resting-state network specificity in infants compared with adults.

PubMed

Wylie, Korey P; Rojas, Donald C; Ross, Randal G; Hunter, Sharon K; Maharajh, Keeran; Cornier, Marc-Andre; Tregellas, Jason R

2014-01-01

Infant resting-state networks do not exhibit the same connectivity patterns as those of young children and adults. Current theories of brain development emphasize developmental progression in regional and network specialization. We compared infant and adult functional connectivity, predicting that infants would exhibit less regional specificity and greater internetwork communication compared with adults. Functional magnetic resonance imaging at rest was acquired in 12 healthy, term infants and 17 adults. Resting-state networks were extracted, using independent components analysis, and the resulting components were then compared between the adult and infant groups. Adults exhibited stronger connectivity in the posterior cingulate cortex node of the default mode network, but infants had higher connectivity in medial prefrontal cortex/anterior cingulate cortex than adults. Adult connectivity was typically higher than infant connectivity within structures previously associated with the various networks, whereas infant connectivity was frequently higher outside of these structures. Internetwork communication was significantly higher in infants than in adults. We interpret these findings as consistent with evidence suggesting that resting-state network development is associated with increasing spatial specificity, possibly reflecting the corresponding functional specialization of regions and their interconnections through experience.

Spatial-temporal-spectral EEG patterns of BOLD functional network connectivity dynamics

NASA Astrophysics Data System (ADS)

Lamoš, Martin; Mareček, Radek; Slavíček, Tomáš; Mikl, Michal; Rektor, Ivan; Jan, Jiří

2018-06-01

Objective. Growing interest in the examination of large-scale brain network functional connectivity dynamics is accompanied by an effort to find the electrophysiological correlates. The commonly used constraints applied to spatial and spectral domains during electroencephalogram (EEG) data analysis may leave part of the neural activity unrecognized. We propose an approach that blindly reveals multimodal EEG spectral patterns that are related to the dynamics of the BOLD functional network connectivity. Approach. The blind decomposition of EEG spectrogram by parallel factor analysis has been shown to be a useful technique for uncovering patterns of neural activity. The simultaneously acquired BOLD fMRI data were decomposed by independent component analysis. Dynamic functional connectivity was computed on the component’s time series using a sliding window correlation, and between-network connectivity states were then defined based on the values of the correlation coefficients. ANOVA tests were performed to assess the relationships between the dynamics of between-network connectivity states and the fluctuations of EEG spectral patterns. Main results. We found three patterns related to the dynamics of between-network connectivity states. The first pattern has dominant peaks in the alpha, beta, and gamma bands and is related to the dynamics between the auditory, sensorimotor, and attentional networks. The second pattern, with dominant peaks in the theta and low alpha bands, is related to the visual and default mode network. The third pattern, also with peaks in the theta and low alpha bands, is related to the auditory and frontal network. Significance. Our previous findings revealed a relationship between EEG spectral pattern fluctuations and the hemodynamics of large-scale brain networks. In this study, we suggest that the relationship also exists at the level of functional connectivity dynamics among large-scale brain networks when no standard spatial and spectral constraints are applied on the EEG data.

Characterizing structure connectivity correlation with the default mode network in Alzheimer's patients and normal controls

NASA Astrophysics Data System (ADS)

Guo, Jia; Xu, Peng; Song, Chao; Yao, Li; Zhao, Xiaojie

2012-03-01

Magnetic resonance diffusion tensor imaging (DTI) is a kind of effective measure to do non-invasive investigation on brain fiber structure at present. Studies of fiber tracking based on DTI showed that there was structural connection of white matter fiber among the nodes of resting-state functional network, denoting that the connection of white matter was the basis of gray matter regions in functional network. Nevertheless, relationship between these structure connectivity regions and functional network has not been clearly indicated. Moreover, research of fMRI found that activation of default mode network (DMN) in Alzheimer's disease (AD) was significantly descended, especially in hippocampus and posterior cingulated cortex (PCC). The relationship between this change of DMN activity and structural connection among functional networks needs further research. In this study, fast marching tractography (FMT) algorithm was adopted to quantitative calculate fiber connectivity value between regions, and hippocampus and PCC which were two important regions in DMN related with AD were selected to compute white matter connection region between them in elderly normal control (NC) and AD patient. The fiber connectivity value was extracted to do the correlation analysis with activity intensity of DMN. Results showed that, between PCC and hippocampus of NC, there exited region with significant high connectivity value of white matter fiber whose performance has relatively strong correlation with the activity of DMN, while there was no significant white matter connection region between them for AD patient which might be related with reduced network activation in these two regions of AD.

Dynamics of networks of excitatory and inhibitory neurons in response to time-dependent inputs.

PubMed

Ledoux, Erwan; Brunel, Nicolas

2011-01-01

We investigate the dynamics of recurrent networks of excitatory (E) and inhibitory (I) neurons in the presence of time-dependent inputs. The dynamics is characterized by the network dynamical transfer function, i.e., how the population firing rate is modulated by sinusoidal inputs at arbitrary frequencies. Two types of networks are studied and compared: (i) a Wilson-Cowan type firing rate model; and (ii) a fully connected network of leaky integrate-and-fire (LIF) neurons, in a strong noise regime. We first characterize the region of stability of the "asynchronous state" (a state in which population activity is constant in time when external inputs are constant) in the space of parameters characterizing the connectivity of the network. We then systematically characterize the qualitative behaviors of the dynamical transfer function, as a function of the connectivity. We find that the transfer function can be either low-pass, or with a single or double resonance, depending on the connection strengths and synaptic time constants. Resonances appear when the system is close to Hopf bifurcations, that can be induced by two separate mechanisms: the I-I connectivity and the E-I connectivity. Double resonances can appear when excitatory delays are larger than inhibitory delays, due to the fact that two distinct instabilities exist with a finite gap between the corresponding frequencies. In networks of LIF neurons, changes in external inputs and external noise are shown to be able to change qualitatively the network transfer function. Firing rate models are shown to exhibit the same diversity of transfer functions as the LIF network, provided delays are present. They can also exhibit input-dependent changes of the transfer function, provided a suitable static non-linearity is incorporated.

A Longitudinal Study on Resting State Functional Connectivity in Behavioral Variant Frontotemporal Dementia and Alzheimer's Disease.

PubMed

Hafkemeijer, Anne; Möller, Christiane; Dopper, Elise G P; Jiskoot, Lize C; van den Berg-Huysmans, Annette A; van Swieten, John C; van der Flier, Wiesje M; Vrenken, Hugo; Pijnenburg, Yolande A L; Barkhof, Frederik; Scheltens, Philip; van der Grond, Jeroen; Rombouts, Serge A R B

2017-01-01

Alzheimer's disease (AD) and behavioral variant frontotemporal dementia (bvFTD) are the most common types of early-onset dementia. We applied longitudinal resting state functional magnetic resonance imaging (fMRI) to delineate functional brain connections relevant for disease progression and diagnostic accuracy. We used two-center resting state fMRI data of 20 AD patients (65.1±8.0 years), 12 bvFTD patients (64.7±5.4 years), and 22 control subjects (63.8±5.0 years) at baseline and 1.8-year follow-up. We used whole-network and voxel-based network-to-region analyses to study group differences in functional connectivity at baseline and follow-up, and longitudinal changes in connectivity within and between groups. At baseline, connectivity between paracingulate gyrus and executive control network, between cuneal cortex and medial visual network, and between paracingulate gyrus and salience network was higher in AD compared with controls. These differences were also present after 1.8 years. At follow-up, connectivity between angular gyrus and right frontoparietal network, and between paracingulate gyrus and default mode network was lower in bvFTD compared with controls, and lower compared with AD between anterior cingulate gyrus and executive control network, and between lateral occipital cortex and medial visual network. Over time, connectivity decreased in AD between precuneus and right frontoparietal network and in bvFTD between inferior frontal gyrus and left frontoparietal network. Longitudinal changes in connectivity between supramarginal gyrus and right frontoparietal network differ between both patient groups and controls. We found disease-specific brain regions with longitudinal connectivity changes. This suggests the potential of longitudinal resting state fMRI to delineate regions relevant for disease progression and for diagnostic accuracy, although no group differences in longitudinal changes in the direct comparison of AD and bvFTD were found.

Markov models for fMRI correlation structure: Is brain functional connectivity small world, or decomposable into networks?

PubMed

Varoquaux, G; Gramfort, A; Poline, J B; Thirion, B

2012-01-01

Correlations in the signal observed via functional Magnetic Resonance Imaging (fMRI), are expected to reveal the interactions in the underlying neural populations through hemodynamic response. In particular, they highlight distributed set of mutually correlated regions that correspond to brain networks related to different cognitive functions. Yet graph-theoretical studies of neural connections give a different picture: that of a highly integrated system with small-world properties: local clustering but with short pathways across the complete structure. We examine the conditional independence properties of the fMRI signal, i.e. its Markov structure, to find realistic assumptions on the connectivity structure that are required to explain the observed functional connectivity. In particular we seek a decomposition of the Markov structure into segregated functional networks using decomposable graphs: a set of strongly-connected and partially overlapping cliques. We introduce a new method to efficiently extract such cliques on a large, strongly-connected graph. We compare methods learning different graph structures from functional connectivity by testing the goodness of fit of the model they learn on new data. We find that summarizing the structure as strongly-connected networks can give a good description only for very large and overlapping networks. These results highlight that Markov models are good tools to identify the structure of brain connectivity from fMRI signals, but for this purpose they must reflect the small-world properties of the underlying neural systems. Copyright © 2012 Elsevier Ltd. All rights reserved.

Structural and functional cerebral correlates of hypnotic suggestibility.

PubMed

Huber, Alexa; Lui, Fausta; Duzzi, Davide; Pagnoni, Giuseppe; Porro, Carlo Adolfo

2014-01-01

Little is known about the neural bases of hypnotic suggestibility, a cognitive trait referring to the tendency to respond to hypnotic suggestions. In the present magnetic resonance imaging study, we performed regression analyses to assess hypnotic suggestibility-related differences in local gray matter volume, using voxel-based morphometry, and in waking resting state functional connectivity of 10 resting state networks, in 37 healthy women. Hypnotic suggestibility was positively correlated with gray matter volume in portions of the left superior and medial frontal gyri, roughly overlapping with the supplementary and pre-supplementary motor area, and negatively correlated with gray matter volume in the left superior temporal gyrus and insula. In the functional connectivity analysis, hypnotic suggestibility was positively correlated with functional connectivity between medial posterior areas, including bilateral posterior cingulate cortex and precuneus, and both the lateral visual network and the left fronto-parietal network; a positive correlation was also found with functional connectivity between the executive-control network and a right postcentral/parietal area. In contrast, hypnotic suggestibility was negatively correlated with functional connectivity between the right fronto-parietal network and the right lateral thalamus. These findings demonstrate for the first time a correlation between hypnotic suggestibility, the structural features of specific cortical regions, and the functional connectivity during the normal resting state of brain structures involved in imagery and self-monitoring activity.

Resting State fMRI Functional Connectivity-Based Classification Using a Convolutional Neural Network Architecture

PubMed Central

Meszlényi, Regina J.; Buza, Krisztian; Vidnyánszky, Zoltán

2017-01-01

Machine learning techniques have become increasingly popular in the field of resting state fMRI (functional magnetic resonance imaging) network based classification. However, the application of convolutional networks has been proposed only very recently and has remained largely unexplored. In this paper we describe a convolutional neural network architecture for functional connectome classification called connectome-convolutional neural network (CCNN). Our results on simulated datasets and a publicly available dataset for amnestic mild cognitive impairment classification demonstrate that our CCNN model can efficiently distinguish between subject groups. We also show that the connectome-convolutional network is capable to combine information from diverse functional connectivity metrics and that models using a combination of different connectivity descriptors are able to outperform classifiers using only one metric. From this flexibility follows that our proposed CCNN model can be easily adapted to a wide range of connectome based classification or regression tasks, by varying which connectivity descriptor combinations are used to train the network. PMID:29089883

Resting State fMRI Functional Connectivity-Based Classification Using a Convolutional Neural Network Architecture.

PubMed

Meszlényi, Regina J; Buza, Krisztian; Vidnyánszky, Zoltán

2017-01-01

Machine learning techniques have become increasingly popular in the field of resting state fMRI (functional magnetic resonance imaging) network based classification. However, the application of convolutional networks has been proposed only very recently and has remained largely unexplored. In this paper we describe a convolutional neural network architecture for functional connectome classification called connectome-convolutional neural network (CCNN). Our results on simulated datasets and a publicly available dataset for amnestic mild cognitive impairment classification demonstrate that our CCNN model can efficiently distinguish between subject groups. We also show that the connectome-convolutional network is capable to combine information from diverse functional connectivity metrics and that models using a combination of different connectivity descriptors are able to outperform classifiers using only one metric. From this flexibility follows that our proposed CCNN model can be easily adapted to a wide range of connectome based classification or regression tasks, by varying which connectivity descriptor combinations are used to train the network.

Aging and functional brain networks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tomasi D.; Tomasi, D.; Volkow, N.D.

2011-07-11

Aging is associated with changes in human brain anatomy and function and cognitive decline. Recent studies suggest the aging decline of major functional connectivity hubs in the 'default-mode' network (DMN). Aging effects on other networks, however, are largely unknown. We hypothesized that aging would be associated with a decline of short- and long-range functional connectivity density (FCD) hubs in the DMN. To test this hypothesis, we evaluated resting-state data sets corresponding to 913 healthy subjects from a public magnetic resonance imaging database using functional connectivity density mapping (FCDM), a voxelwise and data-driven approach, together with parallel computing. Aging was associatedmore » with pronounced long-range FCD decreases in DMN and dorsal attention network (DAN) and with increases in somatosensory and subcortical networks. Aging effects in these networks were stronger for long-range than for short-range FCD and were also detected at the level of the main functional hubs. Females had higher short- and long-range FCD in DMN and lower FCD in the somatosensory network than males, but the gender by age interaction effects were not significant for any of the networks or hubs. These findings suggest that long-range connections may be more vulnerable to aging effects than short-range connections and that, in addition to the DMN, the DAN is also sensitive to aging effects, which could underlie the deterioration of attention processes that occurs with aging.« less

Postoperative seizure freedom does not normalize altered connectivity in temporal lobe epilepsy.

PubMed

Maccotta, Luigi; Lopez, Mayra A; Adeyemo, Babatunde; Ances, Beau M; Day, Brian K; Eisenman, Lawrence N; Dowling, Joshua L; Leuthardt, Eric C; Schlaggar, Bradley L; Hogan, Robert Edward

2017-11-01

Specific changes in the functional connectivity of brain networks occur in patients with epilepsy. Yet whether such changes reflect a stable disease effect or one that is a function of active seizure burden remains unclear. Here, we longitudinally assessed the connectivity of canonical cognitive functional networks in patients with intractable temporal lobe epilepsy (TLE), both before and after patients underwent epilepsy surgery and achieved seizure freedom. Seventeen patients with intractable TLE who underwent epilepsy surgery with Engel class I outcome and 17 matched healthy controls took part in the study. The functional connectivity of a set of cognitive functional networks derived from typical cognitive tasks was assessed in patients, preoperatively and postoperatively, as well as in controls, using stringent methods of artifact reduction. Preoperatively, functional networks in TLE patients differed significantly from healthy controls, with differences that largely, but not exclusively, involved the default mode and temporal/auditory subnetworks. However, undergoing epilepsy surgery and achieving seizure freedom did not lead to significant changes in network connectivity, with postoperative functional network abnormalities closely mirroring the preoperative state. This result argues for a stable chronic effect of the disease on brain connectivity, with changes that are largely "burned in" by the time a patient with intractable TLE undergoes epilepsy surgery, which typically occurs years after the initial diagnosis. The result has potential implications for the treatment of intractable epilepsy, suggesting that delaying surgical intervention that may achieve seizure freedom may lead to functional network changes that are no longer reversible by the time of epilepsy surgery. Wiley Periodicals, Inc. © 2017 International League Against Epilepsy.

Brain functional connectivity network studies of acupuncture: a systematic review on resting-state fMRI.

PubMed

Cai, Rong-Lin; Shen, Guo-Ming; Wang, Hao; Guan, Yuan-Yuan

2018-01-01

Functional magnetic resonance imaging (fMRI) is a novel method for studying the changes of brain networks due to acupuncture treatment. In recent years, more and more studies have focused on the brain functional connectivity network of acupuncture stimulation. To offer an overview of the different influences of acupuncture on the brain functional connectivity network from studies using resting-state fMRI. The authors performed a systematic search according to PRISMA guidelines. The database PubMed was searched from January 1, 2006 to December 31, 2016 with restriction to human studies in English language. Electronic searches were conducted in PubMed using the keywords "acupuncture" and "neuroimaging" or "resting-state fMRI" or "functional connectivity". Selection of included articles, data extraction and methodological quality assessments were respectively conducted by two review authors. Forty-four resting-state fMRI studies were included in this systematic review according to inclusion criteria. Thirteen studies applied manual acupuncture vs. sham, four studies applied electro-acupuncture vs. sham, two studies also compared transcutaneous electrical acupoint stimulation vs. sham, and nine applied sham acupoint as control. Nineteen studies with a total number of 574 healthy subjects selected to perform fMRI only considered healthy adult volunteers. The brain functional connectivity of the patients had varying degrees of change. Compared with sham acupuncture, verum acupuncture could increase default mode network and sensorimotor network connectivity with pain-, affective- and memory-related brain areas. It has significantly greater connectivity of genuine acupuncture between the periaqueductal gray, anterior cingulate cortex, left posterior cingulate cortex, right anterior insula, limbic/paralimbic and precuneus compared with sham acupuncture. Some research had also shown that acupuncture could adjust the limbic-paralimbic-neocortical network, brainstem, cerebellum, subcortical and hippocampus brain areas. It can be presumed that the functional connectivity network is closely related to the mechanism of acupuncture, and central integration plays a critical role in the acupuncture mechanism. Copyright © 2017 Shanghai Changhai Hospital. Published by Elsevier B.V. All rights reserved.

Healthy brain connectivity predicts atrophy progression in non-fluent variant of primary progressive aphasia.

PubMed

Mandelli, Maria Luisa; Vilaplana, Eduard; Brown, Jesse A; Hubbard, H Isabel; Binney, Richard J; Attygalle, Suneth; Santos-Santos, Miguel A; Miller, Zachary A; Pakvasa, Mikhail; Henry, Maya L; Rosen, Howard J; Henry, Roland G; Rabinovici, Gil D; Miller, Bruce L; Seeley, William W; Gorno-Tempini, Maria Luisa

2016-10-01

Neurodegeneration has been hypothesized to follow predetermined large-scale networks through the trans-synaptic spread of toxic proteins from a syndrome-specific epicentre. To date, no longitudinal neuroimaging study has tested this hypothesis in vivo in frontotemporal dementia spectrum disorders. The aim of this study was to demonstrate that longitudinal progression of atrophy in non-fluent/agrammatic variant primary progressive aphasia spreads over time from a syndrome-specific epicentre to additional regions, based on their connectivity to the epicentre in healthy control subjects. The syndrome-specific epicentre of the non-fluent/agrammatic variant of primary progressive aphasia was derived in a group of 10 mildly affected patients (clinical dementia rating equal to 0) using voxel-based morphometry. From this region, the inferior frontal gyrus (pars opercularis), we derived functional and structural connectivity maps in healthy controls (n = 30) using functional magnetic resonance imaging at rest and diffusion-weighted imaging tractography. Graph theory analysis was applied to derive functional network features. Atrophy progression was calculated using voxel-based morphometry longitudinal analysis on 34 non-fluent/agrammatic patients. Correlation analyses were performed to compare volume changes in patients with connectivity measures of the healthy functional and structural speech/language network. The default mode network was used as a control network. From the epicentre, the healthy functional connectivity network included the left supplementary motor area and the prefrontal, inferior parietal and temporal regions, which were connected through the aslant, superior longitudinal and arcuate fasciculi. Longitudinal grey and white matter changes were found in the left language-related regions and in the right inferior frontal gyrus. Functional connectivity strength in the healthy speech/language network, but not in the default network, correlated with longitudinal grey matter changes in the non-fluent/agrammatic variant of primary progressive aphasia. Graph theoretical analysis of the speech/language network showed that regions with shorter functional paths to the epicentre exhibited greater longitudinal atrophy. The network contained three modules, including a left inferior frontal gyrus/supplementary motor area, which was most strongly connected with the epicentre. The aslant tract was the white matter pathway connecting these two regions and showed the most significant correlation between fractional anisotropy and white matter longitudinal atrophy changes. This study showed that the pattern of longitudinal atrophy progression in the non-fluent/agrammatic variant of primary progressive aphasia relates to the strength of connectivity in pre-determined functional and structural large-scale speech production networks. These findings support the hypothesis that the spread of neurodegeneration occurs by following specific anatomical and functional neuronal network architectures. © The Author (2016). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Structural and functional connectivity of the human brain in autism spectrum disorders and attention-deficit/hyperactivity disorder: A rich club organization study

PubMed Central

Ray, Siddharth; Miller, Meghan; Karalunas, Sarah; Robertson, C.J.; Grayson, David; Cary, Paul; Hawkey, Elizabeth; Painter, Julia G.; Kriz, Daniel; Fombonne, Eric; Nigg, Joel T.; Fair, Damien A.

2015-01-01

Attention deficit hyperactive disorder (ADHD) and Autism spectrum disorders (ASD) are two of the most common and vexing neurodevelopmental disorders among children. Although the two disorders share many behavioral and neuropsychological characteristics, most MRI studies examine only one of the disorders at a time. Using graph theory combined with structural and functional connectivity, we examined the large-scale network organization among three groups of children: a group with ADHD (8-12 years, n = 20), a group with ASD (7-13 years, n = 16), and typically developing controls (TD) (8-12 years, n = 20). We apply the concept of the rich-club organization, whereby central, highly connected hub regions are also highly connected to themselves. We examine the brain into two different network domains: (1) inside a rich-club network phenomena, and (2) outside a rich-club network phenomena. ASD and ADHD populations had markedly different patterns of rich club and non rich-club connections in both functional and structural data. The ASD group exhibited higher connectivity in structural and functional networks but only inside the rich-club networks. These findings were replicated using the autism brain imaging data exchange (ABIDE) dataset with ASD (n = 85) and TD (n = 101). The ADHD group exhibited a lower generalized fractional anisotropy (GFA) and functional connectivity inside the rich-club networks, but a higher number of axonal fibers and correlation coefficient values outside the rich-club. Despite some shared biological features and frequent comorbity, these data suggest ADHD and ASD exhibit distinct large-scale connectivity patterns in middle childhood. PMID:25116862

Functional Connectivity in Multiple Cortical Networks Is Associated with Performance Across Cognitive Domains in Older Adults.

PubMed

Shaw, Emily E; Schultz, Aaron P; Sperling, Reisa A; Hedden, Trey

2015-10-01

Intrinsic functional connectivity MRI has become a widely used tool for measuring integrity in large-scale cortical networks. This study examined multiple cortical networks using Template-Based Rotation (TBR), a method that applies a priori network and nuisance component templates defined from an independent dataset to test datasets of interest. A priori templates were applied to a test dataset of 276 older adults (ages 65-90) from the Harvard Aging Brain Study to examine the relationship between multiple large-scale cortical networks and cognition. Factor scores derived from neuropsychological tests represented processing speed, executive function, and episodic memory. Resting-state BOLD data were acquired in two 6-min acquisitions on a 3-Tesla scanner and processed with TBR to extract individual-level metrics of network connectivity in multiple cortical networks. All results controlled for data quality metrics, including motion. Connectivity in multiple large-scale cortical networks was positively related to all cognitive domains, with a composite measure of general connectivity positively associated with general cognitive performance. Controlling for the correlations between networks, the frontoparietal control network (FPCN) and executive function demonstrated the only significant association, suggesting specificity in this relationship. Further analyses found that the FPCN mediated the relationships of the other networks with cognition, suggesting that this network may play a central role in understanding individual variation in cognition during aging.

The Human Thalamus Is an Integrative Hub for Functional Brain Networks

PubMed Central

Bertolero, Maxwell A.

2017-01-01

The thalamus is globally connected with distributed cortical regions, yet the functional significance of this extensive thalamocortical connectivity remains largely unknown. By performing graph-theoretic analyses on thalamocortical functional connectivity data collected from human participants, we found that most thalamic subdivisions display network properties that are capable of integrating multimodal information across diverse cortical functional networks. From a meta-analysis of a large dataset of functional brain-imaging experiments, we further found that the thalamus is involved in multiple cognitive functions. Finally, we found that focal thalamic lesions in humans have widespread distal effects, disrupting the modular organization of cortical functional networks. This converging evidence suggests that the human thalamus is a critical hub region that could integrate diverse information being processed throughout the cerebral cortex as well as maintain the modular structure of cortical functional networks. SIGNIFICANCE STATEMENT The thalamus is traditionally viewed as a passive relay station of information from sensory organs or subcortical structures to the cortex. However, the thalamus has extensive connections with the entire cerebral cortex, which can also serve to integrate information processing between cortical regions. In this study, we demonstrate that multiple thalamic subdivisions display network properties that are capable of integrating information across multiple functional brain networks. Moreover, the thalamus is engaged by tasks requiring multiple cognitive functions. These findings support the idea that the thalamus is involved in integrating information across cortical networks. PMID:28450543

Errors on interrupter tasks presented during spatial and verbal working memory performance are linearly linked to large-scale functional network connectivity in high temporal resolution resting state fMRI.

PubMed

Magnuson, Matthew Evan; Thompson, Garth John; Schwarb, Hillary; Pan, Wen-Ju; McKinley, Andy; Schumacher, Eric H; Keilholz, Shella Dawn

2015-12-01

The brain is organized into networks composed of spatially separated anatomical regions exhibiting coherent functional activity over time. Two of these networks (the default mode network, DMN, and the task positive network, TPN) have been implicated in the performance of a number of cognitive tasks. To directly examine the stable relationship between network connectivity and behavioral performance, high temporal resolution functional magnetic resonance imaging (fMRI) data were collected during the resting state, and behavioral data were collected from 15 subjects on different days, exploring verbal working memory, spatial working memory, and fluid intelligence. Sustained attention performance was also evaluated in a task interleaved between resting state scans. Functional connectivity within and between the DMN and TPN was related to performance on these tasks. Decreased TPN resting state connectivity was found to significantly correlate with fewer errors on an interrupter task presented during a spatial working memory paradigm and decreased DMN/TPN anti-correlation was significantly correlated with fewer errors on an interrupter task presented during a verbal working memory paradigm. A trend for increased DMN resting state connectivity to correlate to measures of fluid intelligence was also observed. These results provide additional evidence of the relationship between resting state networks and behavioral performance, and show that such results can be observed with high temporal resolution fMRI. Because cognitive scores and functional connectivity were collected on nonconsecutive days, these results highlight the stability of functional connectivity/cognitive performance coupling.

Altered default mode, fronto-parietal and salience networks in adolescents with Internet addiction.

PubMed

Wang, Lubin; Shen, Hui; Lei, Yu; Zeng, Ling-Li; Cao, Fenglin; Su, Linyan; Yang, Zheng; Yao, Shuqiao; Hu, Dewen

2017-07-01

Internet addiction (IA) is a condition characterized by loss of control over Internet use, leading to a variety of negative psychosocial consequences. Recent neuroimaging studies have begun to identify IA-related changes in specific brain regions and connections. However, whether and how the interactions within and between the large-scale brain networks are disrupted in individuals with IA remain largely unexplored. Using group independent component analysis, we extracted five intrinsic connectivity networks (ICNs) from the resting-state fMRI data of 26 adolescents with IA and 43 controls, including the anterior and posterior default mode network (DMN), left and right fronto-parietal network (FPN), and salience network (SN). We then examined the possible group differences in the functional connectivity within each ICN and between the ICNs. We found that, compared with controls, IA subjects showed: (1) reduced inter-hemispheric functional connectivity of the right FPN, whereas increased intra-hemispheric functional connectivity of the left FPN; (2) reduced functional connectivity in the dorsal medial prefrontal cortex (mPFC) of the anterior DMN; (3) reduced functional connectivity between the SN and anterior DMN. Our findings suggest that IA is associated with imbalanced interactions among the DMN, FPN and SN, which may serve as system-level neural underpinnings for the uncontrollable Internet-using behaviors. Copyright © 2017 Elsevier Ltd. All rights reserved.

Intrinsic and task-evoked network architectures of the human brain

PubMed Central

Cole, Michael W.; Bassett, Danielle S.; Power, Jonathan D.; Braver, Todd S.; Petersen, Steven E.

2014-01-01

Summary Many functional network properties of the human brain have been identified during rest and task states, yet it remains unclear how the two relate. We identified a whole-brain network architecture present across dozens of task states that was highly similar to the resting-state network architecture. The most frequent functional connectivity strengths across tasks closely matched the strengths observed at rest, suggesting this is an “intrinsic”, standard architecture of functional brain organization. Further, a set of small but consistent changes common across tasks suggests the existence of a task-general network architecture distinguishing task states from rest. These results indicate the brain’s functional network architecture during task performance is shaped primarily by an intrinsic network architecture that is also present during rest, and secondarily by evoked task-general and task-specific network changes. This establishes a strong relationship between resting-state functional connectivity and task-evoked functional connectivity – areas of neuroscientific inquiry typically considered separately. PMID:24991964

Community structure in networks of functional connectivity: resolving functional organization in the rat brain with pharmacological MRI.

PubMed

Schwarz, Adam J; Gozzi, Alessandro; Bifone, Angelo

2009-08-01

In the study of functional connectivity, fMRI data can be represented mathematically as a network of nodes and links, where image voxels represent the nodes and the connections between them reflect a degree of correlation or similarity in their response. Here we show that, within this framework, functional imaging data can be partitioned into 'communities' of tightly interconnected voxels corresponding to maximum modularity within the overall network. We evaluated this approach systematically in application to networks constructed from pharmacological MRI (phMRI) of the rat brain in response to acute challenge with three different compounds with distinct mechanisms of action (d-amphetamine, fluoxetine, and nicotine) as well as vehicle (physiological saline). This approach resulted in bilaterally symmetric sub-networks corresponding to meaningful anatomical and functional connectivity pathways consistent with the purported mechanism of action of each drug. Interestingly, common features across all three networks revealed two groups of tightly coupled brain structures that responded as functional units independent of the specific neurotransmitter systems stimulated by the drug challenge, including a network involving the prefrontal cortex and sub-cortical regions extending from the striatum to the amygdala. This finding suggests that each of these networks includes general underlying features of the functional organization of the rat brain.

Opportunities and methodological challenges in EEG and MEG resting state functional brain network research.

PubMed

van Diessen, E; Numan, T; van Dellen, E; van der Kooi, A W; Boersma, M; Hofman, D; van Lutterveld, R; van Dijk, B W; van Straaten, E C W; Hillebrand, A; Stam, C J

2015-08-01

Electroencephalogram (EEG) and magnetoencephalogram (MEG) recordings during resting state are increasingly used to study functional connectivity and network topology. Moreover, the number of different analysis approaches is expanding along with the rising interest in this research area. The comparison between studies can therefore be challenging and discussion is needed to underscore methodological opportunities and pitfalls in functional connectivity and network studies. In this overview we discuss methodological considerations throughout the analysis pipeline of recording and analyzing resting state EEG and MEG data, with a focus on functional connectivity and network analysis. We summarize current common practices with their advantages and disadvantages; provide practical tips, and suggestions for future research. Finally, we discuss how methodological choices in resting state research can affect the construction of functional networks. When taking advantage of current best practices and avoid the most obvious pitfalls, functional connectivity and network studies can be improved and enable a more accurate interpretation and comparison between studies. Copyright © 2014 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Changes of intranetwork and internetwork functional connectivity in Alzheimer’s disease and mild cognitive impairment

NASA Astrophysics Data System (ADS)

Zhu, Haoze; Zhou, Peng; Alcauter, Sarael; Chen, Yuanyuan; Cao, Hongbao; Tian, Miao; Ming, Dong; Qi, Hongzhi; Wang, Xuemin; Zhao, Xin; He, Feng; Ni, Hongyan; Gao, Wei

2016-08-01

Objective. Alzheimer’s disease (AD) is a serious neurodegenerative disorder characterized by deficits of working memory, attention, language and many other cognitive functions. Although different stages of the disease are relatively well characterized by clinical criteria, stage-specific pathological changes in the brain remain relatively poorly understood, especially at the level of large-scale functional networks. In this study, we aimed to characterize the potential disruptions of large-scale functional brain networks based on a sample including amnestic mild cognition impairment (aMCI) and AD patients to help delineate the underlying stage-dependent AD pathology. Approach. We sought to identify the neural connectivity mechanisms of aMCI and AD through examination of both intranetwork and internetwork interactions among four of the brain’s key networks, namely dorsal attention network (DAN), default mode network (DMN), executive control network (ECN) and salience network (SAL). We analyzed functional connectivity based on resting-state functional magnetic resonance imaging (rs-fMRI) data from 25 Alzheimer’s disease patients, 20 aMCI patients and 35 elderly normal controls (NC). Main results. Intranetwork functional disruptions within the DAN and ECN were detected in both aMCI and AD patients. Disrupted intranetwork connectivity of DMN and anti-correlation between DAN and DMN were observed in AD patients. Moreover, aMCI-specific alterations in the internetwork functional connectivity of SAL were observed. Significance. Our results confirmed previous findings that AD pathology was related to dysconnectivity both within and between resting-state networks but revealed more spatial details. Moreover, the SAL network, reportedly flexibly coupling either with the DAN or DMN networks during different brain states, demonstrated interesting alterations specifically in the early stage of the disease.

Altered topography of intrinsic functional connectivity in childhood risk for social anxiety

PubMed Central

Taber-Thomas, Bradley C.; Morales, Santiago; Hillary, Frank G.; Pérez-Edgar, Koraly E.

2016-01-01

Background Extreme shyness in childhood arising from behavioral inhibition (BI) is among the strongest risk factors for developing social anxiety. Although no imaging studies of intrinsic brain networks in BI children have been reported, adults with a history of BI exhibit altered functioning of frontolimbic circuits and enhanced processing of salient, personally-relevant information. BI in childhood may be marked by increased coupling of salience (insula) and default (ventromedial prefrontal cortex) network hubs. Methods We tested this potential relation in 42 children ages 9 to 12, oversampled for high-BI. Participants provided resting-state functional magnetic resonance imaging. A novel topographical pattern analysis of salience network intrinsic functional connectivity was conducted, and the impact of salience-default coupling on the relation between BI and social anxiety symptoms was assessed via moderation analysis. Results High-BI children exhibit altered salience network topography, marked by reduced insula connectivity to dorsal anterior cingulate and increased insula connectivity to ventromedial prefrontal cortex. Whole-brain analyses revealed increased connectivity of salience, executive, and sensory networks with default network hubs in children higher in BI. Finally, the relation between insula-ventromedial prefrontal connectivity and social anxiety symptoms was strongest among the highest BI children. Conclusions BI is associated with an increase in connectivity to default network hubs that may bias processing toward personally-relevant information during development. These altered patterns of connectivity point to potential biomarkers of the neural profile of risk for anxiety in childhood. PMID:27093074

Connectivity Strength-Weighted Sparse Group Representation-Based Brain Network Construction for MCI Classification

PubMed Central

Yu, Renping; Zhang, Han; An, Le; Chen, Xiaobo; Wei, Zhihui; Shen, Dinggang

2017-01-01

Brain functional network analysis has shown great potential in understanding brain functions and also in identifying biomarkers for brain diseases, such as Alzheimer's disease (AD) and its early stage, mild cognitive impairment (MCI). In these applications, accurate construction of biologically meaningful brain network is critical. Sparse learning has been widely used for brain network construction; however, its l1-norm penalty simply penalizes each edge of a brain network equally, without considering the original connectivity strength which is one of the most important inherent linkwise characters. Besides, based on the similarity of the linkwise connectivity, brain network shows prominent group structure (i.e., a set of edges sharing similar attributes). In this article, we propose a novel brain functional network modeling framework with a “connectivity strength-weighted sparse group constraint.” In particular, the network modeling can be optimized by considering both raw connectivity strength and its group structure, without losing the merit of sparsity. Our proposed method is applied to MCI classification, a challenging task for early AD diagnosis. Experimental results based on the resting-state functional MRI, from 50 MCI patients and 49 healthy controls, show that our proposed method is more effective (i.e., achieving a significantly higher classification accuracy, 84.8%) than other competing methods (e.g., sparse representation, accuracy = 65.6%). Post hoc inspection of the informative features further shows more biologically meaningful brain functional connectivities obtained by our proposed method. PMID:28150897

Quantifying Individual Brain Connectivity with Functional Principal Component Analysis for Networks.

PubMed

Petersen, Alexander; Zhao, Jianyang; Carmichael, Owen; Müller, Hans-Georg

2016-09-01

In typical functional connectivity studies, connections between voxels or regions in the brain are represented as edges in a network. Networks for different subjects are constructed at a given graph density and are summarized by some network measure such as path length. Examining these summary measures for many density values yields samples of connectivity curves, one for each individual. This has led to the adoption of basic tools of functional data analysis, most commonly to compare control and disease groups through the average curves in each group. Such group differences, however, neglect the variability in the sample of connectivity curves. In this article, the use of functional principal component analysis (FPCA) is demonstrated to enrich functional connectivity studies by providing increased power and flexibility for statistical inference. Specifically, individual connectivity curves are related to individual characteristics such as age and measures of cognitive function, thus providing a tool to relate brain connectivity with these variables at the individual level. This individual level analysis opens a new perspective that goes beyond previous group level comparisons. Using a large data set of resting-state functional magnetic resonance imaging scans, relationships between connectivity and two measures of cognitive function-episodic memory and executive function-were investigated. The group-based approach was implemented by dichotomizing the continuous cognitive variable and testing for group differences, resulting in no statistically significant findings. To demonstrate the new approach, FPCA was implemented, followed by linear regression models with cognitive scores as responses, identifying significant associations of connectivity in the right middle temporal region with both cognitive scores.

Modulation of Brain Resting-State Networks by Sad Mood Induction

PubMed Central

Harrison, Ben J.; Pujol, Jesus; Ortiz, Hector; Fornito, Alex; Pantelis, Christos; Yücel, Murat

2008-01-01

Background There is growing interest in the nature of slow variations of the blood oxygen level-dependent (BOLD) signal observed in functional MRI resting-state studies. In humans, these slow BOLD variations are thought to reflect an underlying or intrinsic form of brain functional connectivity in discrete neuroanatomical systems. While these ‘resting-state networks’ may be relatively enduring phenomena, other evidence suggest that dynamic changes in their functional connectivity may also emerge depending on the brain state of subjects during scanning. Methodology/Principal Findings In this study, we examined healthy subjects (n = 24) with a mood induction paradigm during two continuous fMRI recordings to assess the effects of a change in self-generated mood state (neutral to sad) on the functional connectivity of these resting-state networks (n = 24). Using independent component analysis, we identified five networks that were common to both experimental states, each showing dominant signal fluctuations in the very low frequency domain (∼0.04 Hz). Between the two states, we observed apparent increases and decreases in the overall functional connectivity of these networks. Primary findings included increased connectivity strength of a paralimbic network involving the dorsal anterior cingulate and anterior insula cortices with subjects' increasing sadness and decreased functional connectivity of the ‘default mode network’. Conclusions/Significance These findings support recent studies that suggest the functional connectivity of certain resting-state networks may, in part, reflect a dynamic image of the current brain state. In our study, this was linked to changes in subjective mood. PMID:18350136

Resting-State Connectivity of the Left Frontal Cortex to the Default Mode and Dorsal Attention Network Supports Reserve in Mild Cognitive Impairment.

PubMed

Franzmeier, Nicolai; Göttler, Jens; Grimmer, Timo; Drzezga, Alexander; Áraque-Caballero, Miguel A; Simon-Vermot, Lee; Taylor, Alexander N W; Bürger, Katharina; Catak, Cihan; Janowitz, Daniel; Müller, Claudia; Duering, Marco; Sorg, Christian; Ewers, Michael

2017-01-01

Reserve refers to the phenomenon of relatively preserved cognition in disproportion to the extent of neuropathology, e.g., in Alzheimer's disease. A putative functional neural substrate underlying reserve is global functional connectivity of the left lateral frontal cortex (LFC, Brodmann Area 6/44). Resting-state fMRI-assessed global LFC-connectivity is associated with protective factors (education) and better maintenance of memory in mild cognitive impairment (MCI). Since the LFC is a hub of the fronto-parietal control network that regulates the activity of other networks, the question arises whether LFC-connectivity to specific networks rather than the whole-brain may underlie reserve. We assessed resting-state fMRI in 24 MCI and 16 healthy controls (HC) and in an independent validation sample (23 MCI/32 HC). Seed-based LFC-connectivity to seven major resting-state networks (i.e., fronto-parietal, limbic, dorsal-attention, somatomotor, default-mode, ventral-attention, visual) was computed, reserve was quantified as residualized memory performance after accounting for age and hippocampal atrophy. In both samples of MCI, LFC-activity was anti-correlated with the default-mode network (DMN), but positively correlated with the dorsal-attention network (DAN). Greater education predicted stronger LFC-DMN-connectivity (anti-correlation) and LFC-DAN-connectivity. Stronger LFC-DMN and LFC-DAN-connectivity each predicted higher reserve, consistently in both MCI samples. No associations were detected for LFC-connectivity to other networks. These novel results extend our previous findings on global functional connectivity of the LFC, showing that LFC-connectivity specifically to the DAN and DMN, two core memory networks, enhances reserve in the memory domain in MCI.

Distinct hippocampal functional networks revealed by tractography-based parcellation.

PubMed

Adnan, Areeba; Barnett, Alexander; Moayedi, Massieh; McCormick, Cornelia; Cohn, Melanie; McAndrews, Mary Pat

2016-07-01

Recent research suggests the anterior and posterior hippocampus form part of two distinct functional neural networks. Here we investigate the structural underpinnings of this functional connectivity difference using diffusion-weighted imaging-based parcellation. Using this technique, we substantiated that the hippocampus can be parcellated into distinct anterior and posterior segments. These structurally defined segments did indeed show different patterns of resting state functional connectivity, in that the anterior segment showed greater connectivity with temporal and orbitofrontal cortex, whereas the posterior segment was more highly connected to medial and lateral parietal cortex. Furthermore, we showed that the posterior hippocampal connectivity to memory processing regions, including the dorsolateral prefrontal cortex, parahippocampal, inferior temporal and fusiform gyri and the precuneus, predicted interindividual relational memory performance. These findings provide important support for the integration of structural and functional connectivity in understanding the brain networks underlying episodic memory.

Three subsystems of the inferior parietal cortex are differently affected in mild cognitive impairment.

PubMed

Liang, Peipeng; Wang, Zhiqun; Yang, Yanhui; Li, Kuncheng

2012-01-01

The Inferior parietal cortex (IPC), including the intraparietal sulcus (IPS), angular gyrus (AG), and supramarginal gyrus (SG), plays an important role in episodic memory, and is considered to be one of the specific neuroimaging markers in predicting the conversion of mild cognitive impairment (MCI) to Alzheimer's disease (AD). However, it is still unclear whether the connectivity of the IPC is impaired in MCI patients. In the present study, we used resting state fMRI to examine the functional connectivity of the three subdivisions of the IPC in MCI patients after controlling the impact of regional grey matter atrophy. It was found that, using IPS, AG, and SG as seeds of functional connectivity, three canonical functional networks could be correspondingly traced, i.e., executive control network (ECN), default mode network (DMN), and salience network (SN), and the three networks are differently altered in MCI patients. In contrast to the healthy controls, it was found that in MCI patients: 1) AG connectivity was significantly reduced within the DMN; 2) IPS showed decreased connectivity with the right inferior frontal gyrus while showing increased connectivity with the left frontal regions within the ECN; and 3) SG displayed decreased connectivity with a distribution of regions including the frontal and parietal regions, and increased connectivity with some sub-cortical areas within the SN. Moreover, the connectivity within the three networks was correlated with episodic memory and general cognitive impairment in MCI patients. These results extend well beyond the DMN, and further suggest that MCI is associated with alteration of large-scale functional brain networks.

Multimodal Classification of Schizophrenia Patients with MEG and fMRI Data Using Static and Dynamic Connectivity Measures

PubMed Central

Cetin, Mustafa S.; Houck, Jon M.; Rashid, Barnaly; Agacoglu, Oktay; Stephen, Julia M.; Sui, Jing; Canive, Jose; Mayer, Andy; Aine, Cheryl; Bustillo, Juan R.; Calhoun, Vince D.

2016-01-01

Mental disorders like schizophrenia are currently diagnosed by physicians/psychiatrists through clinical assessment and their evaluation of patient's self-reported experiences as the illness emerges. There is great interest in identifying biological markers of prognosis at the onset of illness, rather than relying on the evolution of symptoms across time. Functional network connectivity, which indicates a subject's overall level of “synchronicity” of activity between brain regions, demonstrates promise in providing individual subject predictive power. Many previous studies reported functional connectivity changes during resting-state using only functional magnetic resonance imaging (fMRI). Nevertheless, exclusive reliance on fMRI to generate such networks may limit the inference of the underlying dysfunctional connectivity, which is hypothesized to be a factor in patient symptoms, as fMRI measures connectivity via hemodynamics. Therefore, combination of connectivity assessments using fMRI and magnetoencephalography (MEG), which more directly measures neuronal activity, may provide improved classification of schizophrenia than either modality alone. Moreover, recent evidence indicates that metrics of dynamic connectivity may also be critical for understanding pathology in schizophrenia. In this work, we propose a new framework for extraction of important disease related features and classification of patients with schizophrenia based on using both fMRI and MEG to investigate functional network components in the resting state. Results of this study show that the integration of fMRI and MEG provides important information that captures fundamental characteristics of functional network connectivity in schizophrenia and is helpful for prediction of schizophrenia patient group membership. Combined fMRI/MEG methods, using static functional network connectivity analyses, improved classification accuracy relative to use of fMRI or MEG methods alone (by 15 and 12.45%, respectively), while combined fMRI/MEG methods using dynamic functional network connectivity analyses improved classification up to 5.12% relative to use of fMRI alone and up to 17.21% relative to use of MEG alone. PMID:27807403

Functional connectivity mapping of regions associated with self- and other-processing.

PubMed

Murray, Ryan J; Debbané, Martin; Fox, Peter T; Bzdok, Danilo; Eickhoff, Simon B

2015-04-01

Neuroscience literature increasingly suggests a conceptual self composed of interacting neural regions, rather than independent local activations, yet such claims have yet to be investigated. We, thus, combined task-dependent meta-analytic connectivity modeling (MACM) with task-independent resting-state (RS) connectivity analysis to delineate the neural network of the self, across both states. Given psychological evidence implicating the self's interdependence on social information, we also delineated the neural network underlying conceptual other-processing. To elucidate the relation between the self-/other-networks and their function, we mined the MACM metadata to generate a cognitive-behavioral profile for an empirically identified region specific to conceptual self, the pregenual anterior cingulate (pACC), and conceptual other, posterior cingulate/precuneus (PCC/PC). Mining of 7,200 published, task-dependent, neuroimaging studies, using healthy human subjects, yielded 193 studies activating the self-related seed and were conjoined with RS connectivity analysis to delineate a differentiated self-network composed of the pACC (seed) and anterior insula, relative to other functional connectivity. Additionally, 106 studies activating the other-related seed were conjoined with RS connectivity analysis to delineate a differentiated other-network of PCC/PC (seed) and angular gyrus/temporoparietal junction, relative to self-functional connectivity. The self-network seed related to emotional conflict resolution and motivational processing, whereas the other-network seed related to socially oriented processing and contextual information integration. Notably, our findings revealed shared RS connectivity between ensuing self-/other-networks within the ventromedial prefrontal cortex and medial orbitofrontal cortex, suggesting self-updating via integration of self-relevant social information. We, therefore, present initial neurobiological evidence corroborating the increasing claims of an intricate self-network, the architecture of which may promote social value processing. © 2014 Wiley Periodicals, Inc.

Common and distinct brain networks underlying verbal and visual creativity.

PubMed

Zhu, Wenfeng; Chen, Qunlin; Xia, Lingxiang; Beaty, Roger E; Yang, Wenjing; Tian, Fang; Sun, Jiangzhou; Cao, Guikang; Zhang, Qinglin; Chen, Xu; Qiu, Jiang

2017-04-01

Creativity is imperative to the progression of human civilization, prosperity, and well-being. Past creative researches tends to emphasize the default mode network (DMN) or the frontoparietal network (FPN) somewhat exclusively. However, little is known about how these networks interact to contribute to creativity and whether common or distinct brain networks are responsible for visual and verbal creativity. Here, we use functional connectivity analysis of resting-state functional magnetic resonance imaging data to investigate visual and verbal creativity-related regions and networks in 282 healthy subjects. We found that functional connectivity within the bilateral superior parietal cortex of the FPN was negatively associated with visual and verbal creativity. The strength of connectivity between the DMN and FPN was positively related to both creative domains. Visual creativity was negatively correlated with functional connectivity within the precuneus of the pDMN and right middle frontal gyrus of the FPN, and verbal creativity was negatively correlated with functional connectivity within the medial prefrontal cortex of the aDMN. Critically, the FPN mediated the relationship between the aDMN and verbal creativity, and it also mediated the relationship between the pDMN and visual creativity. Taken together, decreased within-network connectivity of the FPN and DMN may allow for flexible between-network coupling in the highly creative brain. These findings provide indirect evidence for the cooperative role of the default and executive control networks in creativity, extending past research by revealing common and distinct brain systems underlying verbal and visual creative cognition. Hum Brain Mapp 38:2094-2111, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Atypical within- and between-hemisphere motor network functional connections in children with developmental coordination disorder and attention-deficit/hyperactivity disorder.

PubMed

McLeod, Kevin R; Langevin, Lisa Marie; Dewey, Deborah; Goodyear, Bradley G

2016-01-01

Developmental coordination disorder (DCD) and attention-deficit hyperactivity disorder (ADHD) are highly comorbid neurodevelopmental disorders; however, the neural mechanisms of this comorbidity are poorly understood. Previous research has demonstrated that children with DCD and ADHD have altered brain region communication, particularly within the motor network. The structure and function of the motor network in a typically developing brain exhibits hemispheric dominance. It is plausible that functional deficits observed in children with DCD and ADHD are associated with neurodevelopmental alterations in within- and between-hemisphere motor network functional connection strength that disrupt this hemispheric dominance. We used resting-state functional magnetic resonance imaging to examine functional connections of the left and right primary and sensory motor (SM1) cortices in children with DCD, ADHD and DCD + ADHD, relative to typically developing children. Our findings revealed that children with DCD, ADHD and DCD + ADHD exhibit atypical within- and between-hemisphere functional connection strength between SM1 and regions of the basal ganglia, as well as the cerebellum. Our findings further support the assertion that development of atypical motor network connections represents common and distinct neural mechanisms underlying DCD and ADHD. In children with DCD and DCD + ADHD (but not ADHD), a significant correlation was observed between clinical assessment of motor function and the strength of functional connections between right SM1 and anterior cingulate cortex, supplementary motor area, and regions involved in visuospatial processing. This latter finding suggests that behavioral phenotypes associated with atypical motor network development differ between individuals with DCD and those with ADHD.

On the integrity of functional brain networks in schizophrenia, Parkinson's disease, and advanced age: Evidence from connectivity-based single-subject classification.

PubMed

Pläschke, Rachel N; Cieslik, Edna C; Müller, Veronika I; Hoffstaedter, Felix; Plachti, Anna; Varikuti, Deepthi P; Goosses, Mareike; Latz, Anne; Caspers, Svenja; Jockwitz, Christiane; Moebus, Susanne; Gruber, Oliver; Eickhoff, Claudia R; Reetz, Kathrin; Heller, Julia; Südmeyer, Martin; Mathys, Christian; Caspers, Julian; Grefkes, Christian; Kalenscher, Tobias; Langner, Robert; Eickhoff, Simon B

2017-12-01

Previous whole-brain functional connectivity studies achieved successful classifications of patients and healthy controls but only offered limited specificity as to affected brain systems. Here, we examined whether the connectivity patterns of functional systems affected in schizophrenia (SCZ), Parkinson's disease (PD), or normal aging equally translate into high classification accuracies for these conditions. We compared classification performance between pre-defined networks for each group and, for any given network, between groups. Separate support vector machine classifications of 86 SCZ patients, 80 PD patients, and 95 older adults relative to their matched healthy/young controls, respectively, were performed on functional connectivity in 12 task-based, meta-analytically defined networks using 25 replications of a nested 10-fold cross-validation scheme. Classification performance of the various networks clearly differed between conditions, as those networks that best classified one disease were usually non-informative for the other. For SCZ, but not PD, emotion-processing, empathy, and cognitive action control networks distinguished patients most accurately from controls. For PD, but not SCZ, networks subserving autobiographical or semantic memory, motor execution, and theory-of-mind cognition yielded the best classifications. In contrast, young-old classification was excellent based on all networks and outperformed both clinical classifications. Our pattern-classification approach captured associations between clinical and developmental conditions and functional network integrity with a higher level of specificity than did previous whole-brain analyses. Taken together, our results support resting-state connectivity as a marker of functional dysregulation in specific networks known to be affected by SCZ and PD, while suggesting that aging affects network integrity in a more global way. Hum Brain Mapp 38:5845-5858, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Identifying Dynamic Functional Connectivity Changes in Dementia with Lewy Bodies Based on Product Hidden Markov Models.

PubMed

Sourty, Marion; Thoraval, Laurent; Roquet, Daniel; Armspach, Jean-Paul; Foucher, Jack; Blanc, Frédéric

2016-01-01

Exploring time-varying connectivity networks in neurodegenerative disorders is a recent field of research in functional MRI. Dementia with Lewy bodies (DLB) represents 20% of the neurodegenerative forms of dementia. Fluctuations of cognition and vigilance are the key symptoms of DLB. To date, no dynamic functional connectivity (DFC) investigations of this disorder have been performed. In this paper, we refer to the concept of connectivity state as a piecewise stationary configuration of functional connectivity between brain networks. From this concept, we propose a new method for group-level as well as for subject-level studies to compare and characterize connectivity state changes between a set of resting-state networks (RSNs). Dynamic Bayesian networks, statistical and graph theory-based models, enable one to learn dependencies between interacting state-based processes. Product hidden Markov models (PHMM), an instance of dynamic Bayesian networks, are introduced here to capture both statistical and temporal aspects of DFC of a set of RSNs. This analysis was based on sliding-window cross-correlations between seven RSNs extracted from a group independent component analysis performed on 20 healthy elderly subjects and 16 patients with DLB. Statistical models of DFC differed in patients compared to healthy subjects for the occipito-parieto-frontal network, the medial occipital network and the right fronto-parietal network. In addition, pairwise comparisons of DFC of RSNs revealed a decrease of dependency between these two visual networks (occipito-parieto-frontal and medial occipital networks) and the right fronto-parietal control network. The analysis of DFC state changes thus pointed out networks related to the cognitive functions that are known to be impaired in DLB: visual processing as well as attentional and executive functions. Besides this context, product HMM applied to RSNs cross-correlations offers a promising new approach to investigate structural and temporal aspects of brain DFC.

Connectomic markers of symptom severity in sport-related concussion: Whole-brain analysis of resting-state fMRI.

PubMed

Churchill, Nathan W; Hutchison, Michael G; Graham, Simon J; Schweizer, Tom A

2018-01-01

Concussion is associated with significant adverse effects within the first week post-injury, including physical complaints and altered cognition, sleep and mood. It is currently unknown whether these subjective disturbances have reliable functional brain correlates. Resting-state functional magnetic resonance imaging (rs-fMRI) has been used to measure functional connectivity of individuals after traumatic brain injury, but less is known about the relationship between functional connectivity and symptom assessments after a sport concussion. In this study, rs-fMRI was used to evaluate whole-brain functional connectivity for seventy (70) university-level athletes, including 35 with acute concussion and 35 healthy matched controls. Univariate analyses showed that greater symptom severity was mainly associated with lower pairwise connectivity in frontal, temporal and insular regions, along with higher connectivity in a sparser set of cerebellar regions. A novel multivariate approach also extracted two components that showed reliable covariation with symptom severity: (1) a network of frontal, temporal and insular regions where connectivity was negatively correlated with symptom severity (replicating the univariate findings); and (2) a network with anti-correlated elements of the default-mode network and sensorimotor system, where connectivity was positively correlated with symptom severity. These findings support the presence of connectomic signatures of symptom complaints following a sport-related concussion, including both increased and decreased functional connectivity within distinct functional brain networks.

Functional connectivity changes in second language vocabulary learning.

PubMed

Ghazi Saidi, Ladan; Perlbarg, Vincent; Marrelec, Guillaume; Pélégrini-Issac, Mélani; Benali, Habib; Ansaldo, Ana-Inés

2013-01-01

Functional connectivity changes in the language network (Price, 2010), and in a control network involved in second language (L2) processing (Abutalebi & Green, 2007) were examined in a group of Persian (L1) speakers learning French (L2) words. Measures of network integration that characterize the global integrative state of a network (Marrelec, Bellec et al., 2008) were gathered, in the shallow and consolidation phases of L2 vocabulary learning. Functional connectivity remained unchanged across learning phases for L1, whereas total, between- and within-network integration levels decreased as proficiency for L2 increased. The results of this study provide the first functional connectivity evidence regarding the dynamic role of the language processing and cognitive control networks in L2 learning (Abutalebi, Cappa, & Perani, 2005; Altarriba & Heredia, 2008; Leonard et al., 2011; Parker-Jones et al., 2011). Thus, increased proficiency results in a higher degree of automaticity and lower cognitive effort (Segalowitz & Hulstijn, 2005). Copyright © 2012 Elsevier Inc. All rights reserved.

A Multivariate Granger Causality Concept towards Full Brain Functional Connectivity.

PubMed

Schmidt, Christoph; Pester, Britta; Schmid-Hertel, Nicole; Witte, Herbert; Wismüller, Axel; Leistritz, Lutz

2016-01-01

Detecting changes of spatially high-resolution functional connectivity patterns in the brain is crucial for improving the fundamental understanding of brain function in both health and disease, yet still poses one of the biggest challenges in computational neuroscience. Currently, classical multivariate Granger Causality analyses of directed interactions between single process components in coupled systems are commonly restricted to spatially low- dimensional data, which requires a pre-selection or aggregation of time series as a preprocessing step. In this paper we propose a new fully multivariate Granger Causality approach with embedded dimension reduction that makes it possible to obtain a representation of functional connectivity for spatially high-dimensional data. The resulting functional connectivity networks may consist of several thousand vertices and thus contain more detailed information compared to connectivity networks obtained from approaches based on particular regions of interest. Our large scale Granger Causality approach is applied to synthetic and resting state fMRI data with a focus on how well network community structure, which represents a functional segmentation of the network, is preserved. It is demonstrated that a number of different community detection algorithms, which utilize a variety of algorithmic strategies and exploit topological features differently, reveal meaningful information on the underlying network module structure.

BRAIN NETWORKS. Correlated gene expression supports synchronous activity in brain networks.

PubMed

Richiardi, Jonas; Altmann, Andre; Milazzo, Anna-Clare; Chang, Catie; Chakravarty, M Mallar; Banaschewski, Tobias; Barker, Gareth J; Bokde, Arun L W; Bromberg, Uli; Büchel, Christian; Conrod, Patricia; Fauth-Bühler, Mira; Flor, Herta; Frouin, Vincent; Gallinat, Jürgen; Garavan, Hugh; Gowland, Penny; Heinz, Andreas; Lemaître, Hervé; Mann, Karl F; Martinot, Jean-Luc; Nees, Frauke; Paus, Tomáš; Pausova, Zdenka; Rietschel, Marcella; Robbins, Trevor W; Smolka, Michael N; Spanagel, Rainer; Ströhle, Andreas; Schumann, Gunter; Hawrylycz, Mike; Poline, Jean-Baptiste; Greicius, Michael D

2015-06-12

During rest, brain activity is synchronized between different regions widely distributed throughout the brain, forming functional networks. However, the molecular mechanisms supporting functional connectivity remain undefined. We show that functional brain networks defined with resting-state functional magnetic resonance imaging can be recapitulated by using measures of correlated gene expression in a post mortem brain tissue data set. The set of 136 genes we identify is significantly enriched for ion channels. Polymorphisms in this set of genes significantly affect resting-state functional connectivity in a large sample of healthy adolescents. Expression levels of these genes are also significantly associated with axonal connectivity in the mouse. The results provide convergent, multimodal evidence that resting-state functional networks correlate with the orchestrated activity of dozens of genes linked to ion channel activity and synaptic function. Copyright © 2015, American Association for the Advancement of Science.

Preferential degradation of cognitive networks differentiates Alzheimer's disease from ageing.

PubMed

Chhatwal, Jasmeer P; Schultz, Aaron P; Johnson, Keith A; Hedden, Trey; Jaimes, Sehily; Benzinger, Tammie L S; Jack, Clifford; Ances, Beau M; Ringman, John M; Marcus, Daniel S; Ghetti, Bernardino; Farlow, Martin R; Danek, Adrian; Levin, Johannes; Yakushev, Igor; Laske, Christoph; Koeppe, Robert A; Galasko, Douglas R; Xiong, Chengjie; Masters, Colin L; Schofield, Peter R; Kinnunen, Kirsi M; Salloway, Stephen; Martins, Ralph N; McDade, Eric; Cairns, Nigel J; Buckles, Virginia D; Morris, John C; Bateman, Randall; Sperling, Reisa A

2018-05-01

Converging evidence from structural, metabolic and functional connectivity MRI suggests that neurodegenerative diseases, such as Alzheimer's disease, target specific neural networks. However, age-related network changes commonly co-occur with neuropathological cascades, limiting efforts to disentangle disease-specific alterations in network function from those associated with normal ageing. Here we elucidate the differential effects of ageing and Alzheimer's disease pathology through simultaneous analyses of two functional connectivity MRI datasets: (i) young participants harbouring highly-penetrant mutations leading to autosomal-dominant Alzheimer's disease from the Dominantly Inherited Alzheimer's Network (DIAN), an Alzheimer's disease cohort in which age-related comorbidities are minimal and likelihood of progression along an Alzheimer's disease trajectory is extremely high; and (ii) young and elderly participants from the Harvard Aging Brain Study, a cohort in which imaging biomarkers of amyloid burden and neurodegeneration can be used to disambiguate ageing alone from preclinical Alzheimer's disease. Consonant with prior reports, we observed the preferential degradation of cognitive (especially the default and dorsal attention networks) over motor and sensory networks in early autosomal-dominant Alzheimer's disease, and found that this distinctive degradation pattern was magnified in more advanced stages of disease. Importantly, a nascent form of the pattern observed across the autosomal-dominant Alzheimer's disease spectrum was also detectable in clinically normal elderly with clear biomarker evidence of Alzheimer's disease pathology (preclinical Alzheimer's disease). At the more granular level of individual connections between node pairs, we observed that connections within cognitive networks were preferentially targeted in Alzheimer's disease (with between network connections relatively spared), and that connections between positively coupled nodes (correlations) were preferentially degraded as compared to connections between negatively coupled nodes (anti-correlations). In contrast, ageing in the absence of Alzheimer's disease biomarkers was characterized by a far less network-specific degradation across cognitive and sensory networks, of between- and within-network connections, and of connections between positively and negatively coupled nodes. We go on to demonstrate that formalizing the differential patterns of network degradation in ageing and Alzheimer's disease may have the practical benefit of yielding connectivity measurements that highlight early Alzheimer's disease-related connectivity changes over those due to age-related processes. Together, the contrasting patterns of connectivity in Alzheimer's disease and ageing add to prior work arguing against Alzheimer's disease as a form of accelerated ageing, and suggest multi-network composite functional connectivity MRI metrics may be useful in the detection of early Alzheimer's disease-specific alterations co-occurring with age-related connectivity changes. More broadly, our findings are consistent with a specific pattern of network degradation associated with the spreading of Alzheimer's disease pathology within targeted neural networks.

Large-Scale Hypoconnectivity Between Resting-State Functional Networks in Unmedicated Adolescent Major Depressive Disorder.

PubMed

Sacchet, Matthew D; Ho, Tiffany C; Connolly, Colm G; Tymofiyeva, Olga; Lewinn, Kaja Z; Han, Laura Km; Blom, Eva H; Tapert, Susan F; Max, Jeffrey E; Frank, Guido Kw; Paulus, Martin P; Simmons, Alan N; Gotlib, Ian H; Yang, Tony T

2016-11-01

Major depressive disorder (MDD) often emerges during adolescence, a critical period of brain development. Recent resting-state fMRI studies of adults suggest that MDD is associated with abnormalities within and between resting-state networks (RSNs). Here we tested whether adolescent MDD is characterized by abnormalities in interactions among RSNs. Participants were 55 unmedicated adolescents diagnosed with MDD and 56 matched healthy controls. Functional connectivity was mapped using resting-state fMRI. We used the network-based statistic (NBS) to compare large-scale connectivity between groups and also compared the groups on graph metrics. We further assessed whether group differences identified using nodes defined from functionally defined RSNs were also evident when using anatomically defined nodes. In addition, we examined relations between network abnormalities and depression severity and duration. Finally, we compared intranetwork connectivity between groups and assessed the replication of previously reported MDD-related abnormalities in connectivity. The NBS indicated that, compared with controls, depressed adolescents exhibited reduced connectivity (p<0.024, corrected) between a specific set of RSNs, including components of the attention, central executive, salience, and default mode networks. The NBS did not identify group differences in network connectivity when using anatomically defined nodes. Longer duration of depression was significantly correlated with reduced connectivity in this set of network interactions (p=0.020, corrected), specifically with reduced connectivity between components of the dorsal attention network. The dorsal attention network was also characterized by reduced intranetwork connectivity in the MDD group. Finally, we replicated previously reported abnormal connectivity in individuals with MDD. In summary, adolescents with MDD show hypoconnectivity between large-scale brain networks compared with healthy controls. Given that connectivity among these networks typically increases during adolescent neurodevelopment, these results suggest that adolescent depression is associated with abnormalities in neural systems that are still developing during this critical period.

Large-Scale Hypoconnectivity Between Resting-State Functional Networks in Unmedicated Adolescent Major Depressive Disorder

PubMed Central

Sacchet, Matthew D; Ho, Tiffany C; Connolly, Colm G; Tymofiyeva, Olga; Lewinn, Kaja Z; Han, Laura KM; Blom, Eva H; Tapert, Susan F; Max, Jeffrey E; Frank, Guido KW; Paulus, Martin P; Simmons, Alan N; Gotlib, Ian H; Yang, Tony T

2016-01-01

Major depressive disorder (MDD) often emerges during adolescence, a critical period of brain development. Recent resting-state fMRI studies of adults suggest that MDD is associated with abnormalities within and between resting-state networks (RSNs). Here we tested whether adolescent MDD is characterized by abnormalities in interactions among RSNs. Participants were 55 unmedicated adolescents diagnosed with MDD and 56 matched healthy controls. Functional connectivity was mapped using resting-state fMRI. We used the network-based statistic (NBS) to compare large-scale connectivity between groups and also compared the groups on graph metrics. We further assessed whether group differences identified using nodes defined from functionally defined RSNs were also evident when using anatomically defined nodes. In addition, we examined relations between network abnormalities and depression severity and duration. Finally, we compared intranetwork connectivity between groups and assessed the replication of previously reported MDD-related abnormalities in connectivity. The NBS indicated that, compared with controls, depressed adolescents exhibited reduced connectivity (p<0.024, corrected) between a specific set of RSNs, including components of the attention, central executive, salience, and default mode networks. The NBS did not identify group differences in network connectivity when using anatomically defined nodes. Longer duration of depression was significantly correlated with reduced connectivity in this set of network interactions (p=0.020, corrected), specifically with reduced connectivity between components of the dorsal attention network. The dorsal attention network was also characterized by reduced intranetwork connectivity in the MDD group. Finally, we replicated previously reported abnormal connectivity in individuals with MDD. In summary, adolescents with MDD show hypoconnectivity between large-scale brain networks compared with healthy controls. Given that connectivity among these networks typically increases during adolescent neurodevelopment, these results suggest that adolescent depression is associated with abnormalities in neural systems that are still developing during this critical period. PMID:27238621

Exploring time- and frequency- dependent functional connectivity and brain networks during deception with single-trial event-related potentials

NASA Astrophysics Data System (ADS)

Gao, Jun-Feng; Yang, Yong; Huang, Wen-Tao; Lin, Pan; Ge, Sheng; Zheng, Hong-Mei; Gu, Ling-Yun; Zhou, Hui; Li, Chen-Hong; Rao, Ni-Ni

2016-11-01

To better characterize the cognitive processes and mechanisms that are associated with deception, wavelet coherence was employed to evaluate functional connectivity between different brain regions. Two groups of subjects were evaluated for this purpose: 32 participants were required to either tell the truth or to lie when facing certain stimuli, and their electroencephalogram signals on 12 electrodes were recorded. The experimental results revealed that deceptive responses elicited greater connectivity strength than truthful responses, particularly in the θ band on specific electrode pairs primarily involving connections between the prefrontal/frontal and central regions and between the prefrontal/frontal and left parietal regions. These results indicate that these brain regions play an important role in executing lying responses. Additionally, three time- and frequency-dependent functional connectivity networks were proposed to thoroughly reflect the functional coupling of brain regions that occurs during lying. Furthermore, the wavelet coherence values for the connections shown in the networks were extracted as features for support vector machine training. High classification accuracy suggested that the proposed network effectively characterized differences in functional connectivity between the two groups of subjects over a specific time-frequency area and hence could be a sensitive measurement for identifying deception.

Functional Brain Networks: Does the Choice of Dependency Estimator and Binarization Method Matter?

NASA Astrophysics Data System (ADS)

Jalili, Mahdi

2016-07-01

The human brain can be modelled as a complex networked structure with brain regions as individual nodes and their anatomical/functional links as edges. Functional brain networks are constructed by first extracting weighted connectivity matrices, and then binarizing them to minimize the noise level. Different methods have been used to estimate the dependency values between the nodes and to obtain a binary network from a weighted connectivity matrix. In this work we study topological properties of EEG-based functional networks in Alzheimer’s Disease (AD). To estimate the connectivity strength between two time series, we use Pearson correlation, coherence, phase order parameter and synchronization likelihood. In order to binarize the weighted connectivity matrices, we use Minimum Spanning Tree (MST), Minimum Connected Component (MCC), uniform threshold and density-preserving methods. We find that the detected AD-related abnormalities highly depend on the methods used for dependency estimation and binarization. Topological properties of networks constructed using coherence method and MCC binarization show more significant differences between AD and healthy subjects than the other methods. These results might explain contradictory results reported in the literature for network properties specific to AD symptoms. The analysis method should be seriously taken into account in the interpretation of network-based analysis of brain signals.

Structural and Functional Cerebral Correlates of Hypnotic Suggestibility

PubMed Central

Huber, Alexa; Lui, Fausta; Duzzi, Davide; Pagnoni, Giuseppe; Porro, Carlo Adolfo

2014-01-01

Little is known about the neural bases of hypnotic suggestibility, a cognitive trait referring to the tendency to respond to hypnotic suggestions. In the present magnetic resonance imaging study, we performed regression analyses to assess hypnotic suggestibility-related differences in local gray matter volume, using voxel-based morphometry, and in waking resting state functional connectivity of 10 resting state networks, in 37 healthy women. Hypnotic suggestibility was positively correlated with gray matter volume in portions of the left superior and medial frontal gyri, roughly overlapping with the supplementary and pre-supplementary motor area, and negatively correlated with gray matter volume in the left superior temporal gyrus and insula. In the functional connectivity analysis, hypnotic suggestibility was positively correlated with functional connectivity between medial posterior areas, including bilateral posterior cingulate cortex and precuneus, and both the lateral visual network and the left fronto-parietal network; a positive correlation was also found with functional connectivity between the executive-control network and a right postcentral/parietal area. In contrast, hypnotic suggestibility was negatively correlated with functional connectivity between the right fronto-parietal network and the right lateral thalamus. These findings demonstrate for the first time a correlation between hypnotic suggestibility, the structural features of specific cortical regions, and the functional connectivity during the normal resting state of brain structures involved in imagery and self-monitoring activity. PMID:24671130

Individual diversity of functional brain network economy.

PubMed

Hahn, Andreas; Kranz, Georg S; Sladky, Ronald; Ganger, Sebastian; Windischberger, Christian; Kasper, Siegfried; Lanzenberger, Rupert

2015-04-01

On average, brain network economy represents a trade-off between communication efficiency, robustness, and connection cost, although an analogous understanding on an individual level is largely missing. Evaluating resting-state networks of 42 healthy participants with seven Tesla functional magnetic resonance imaging and graph theory revealed that not even half of all possible connections were common across subjects. The strongest similarities among individuals were observed for interhemispheric and/or short-range connections, which may relate to the essential feature of the human brain to develop specialized systems within each hemisphere. Despite this marked variability in individual network architecture, all subjects exhibited equal small-world properties. Furthermore, interdependency between four major network economy metrics was observed across healthy individuals. The characteristic path length was associated with the clustering coefficient (peak correlation r=0.93), the response to network attacks (r=-0.97), and the physical connection cost in three-dimensional space (r=-0.62). On the other hand, clustering was negatively related to attack response (r=-0.75) and connection cost (r=-0.59). Finally, increased connection cost was associated with better response to attacks (r=0.65). This indicates that functional brain networks with high global information transfer also exhibit strong network resilience. However, it seems that these advantages come at the cost of decreased local communication efficiency and increased physical connection cost. Except for wiring length, the results were replicated on a subsample at three Tesla (n=20). These findings highlight the finely tuned interrelationships between different parameters of brain network economy. Moreover, the understanding of the individual diversity of functional brain network economy may provide further insights in the vulnerability to mental and neurological disorders.

Common Dimensional Reward Deficits Across Mood and Psychotic Disorders: A Connectome-Wide Association Study.

PubMed

Sharma, Anup; Wolf, Daniel H; Ciric, Rastko; Kable, Joseph W; Moore, Tyler M; Vandekar, Simon N; Katchmar, Natalie; Daldal, Aylin; Ruparel, Kosha; Davatzikos, Christos; Elliott, Mark A; Calkins, Monica E; Shinohara, Russell T; Bassett, Danielle S; Satterthwaite, Theodore D

2017-07-01

Anhedonia is central to multiple psychiatric disorders and causes substantial disability. A dimensional conceptualization posits that anhedonia severity is related to a transdiagnostic continuum of reward deficits in specific neural networks. Previous functional connectivity studies related to anhedonia have focused on case-control comparisons in specific disorders, using region-specific seed-based analyses. Here, the authors explore the entire functional connectome in relation to reward responsivity across a population of adults with heterogeneous psychopathology. In a sample of 225 adults from five diagnostic groups (major depressive disorder, N=32; bipolar disorder, N=50; schizophrenia, N=51; psychosis risk, N=39; and healthy control subjects, N=53), the authors conducted a connectome-wide analysis examining the relationship between a dimensional measure of reward responsivity (the reward sensitivity subscale of the Behavioral Activation Scale) and resting-state functional connectivity using multivariate distance-based matrix regression. The authors identified foci of dysconnectivity associated with reward responsivity in the nucleus accumbens, the default mode network, and the cingulo-opercular network. Follow-up analyses revealed dysconnectivity among specific large-scale functional networks and their connectivity with the nucleus accumbens. Reward deficits were associated with decreased connectivity between the nucleus accumbens and the default mode network and increased connectivity between the nucleus accumbens and the cingulo-opercular network. In addition, impaired reward responsivity was associated with default mode network hyperconnectivity and diminished connectivity between the default mode network and the cingulo-opercular network. These results emphasize the centrality of the nucleus accumbens in the pathophysiology of reward deficits and suggest that dissociable patterns of connectivity among large-scale networks are critical to the neurobiology of reward dysfunction across clinical diagnostic categories.

Integration of Network Topological and Connectivity Properties for Neuroimaging Classification

PubMed Central

Jie, Biao; Gao, Wei; Wang, Qian; Wee, Chong-Yaw

2014-01-01

Rapid advances in neuroimaging techniques have provided an efficient and noninvasive way for exploring the structural and functional connectivity of the human brain. Quantitative measurement of abnormality of brain connectivity in patients with neurodegenerative diseases, such as mild cognitive impairment (MCI) and Alzheimer’s disease (AD), have also been widely reported, especially at a group level. Recently, machine learning techniques have been applied to the study of AD and MCI, i.e., to identify the individuals with AD/MCI from the healthy controls (HCs). However, most existing methods focus on using only a single property of a connectivity network, although multiple network properties, such as local connectivity and global topological properties, can potentially be used. In this paper, by employing multikernel based approach, we propose a novel connectivity based framework to integrate multiple properties of connectivity network for improving the classification performance. Specifically, two different types of kernels (i.e., vector-based kernel and graph kernel) are used to quantify two different yet complementary properties of the network, i.e., local connectivity and global topological properties. Then, multikernel learning (MKL) technique is adopted to fuse these heterogeneous kernels for neuroimaging classification. We test the performance of our proposed method on two different data sets. First, we test it on the functional connectivity networks of 12 MCI and 25 HC subjects. The results show that our method achieves significant performance improvement over those using only one type of network property. Specifically, our method achieves a classification accuracy of 91.9%, which is 10.8% better than those by single network-property-based methods. Then, we test our method for gender classification on a large set of functional connectivity networks with 133 infants scanned at birth, 1 year, and 2 years, also demonstrating very promising results. PMID:24108708

The intrinsic resting state voice network in Parkinson's disease

PubMed Central

New, Anneliese B.; Parkinson, Amy L.; Eickhoff, Claudia R.; Reetz, Kathrin; Hoffstaedter, Felix; Mathys, Christian; Sudmeyer, Martin; Michely, Jochen; Caspers, Julian; Grefkes, Christian; Larson, Charles R.; Ramig, Loraine O.; Fox, Peter T.; Eickhoff, Simon B.

2015-01-01

Abstract Over 90 percent of patients with Parkinson's disease experience speech‐motor impairment, namely, hypokinetic dysarthria characterized by reduced pitch and loudness. Resting‐state functional connectivity analysis of blood oxygen level‐dependent functional magnetic resonance imaging is a useful measure of intrinsic neural functioning. We utilized resting‐state functional connectivity modeling to analyze the intrinsic connectivity in patients with Parkinson's disease within a vocalization network defined by a previous meta‐analysis of speech (Brown et al., 2009). Functional connectivity of this network was assessed in 56 patients with Parkinson's disease and 56 gender‐, age‐, and movement‐matched healthy controls. We also had item 5 and 18 of the UPDRS, and the PDQ‐39 Communication subscale available for correlation with the voice network connectivity strength in patients. The within‐group analyses of connectivity patterns demonstrated a lack of subcortical–cortical connectivity in patients with Parkinson's disease. At the cortical level, we found robust (homotopic) interhemispheric connectivity but only inconsistent evidence for many intrahemispheric connections. When directly contrasted to the control group, we found a significant reduction of connections between the left thalamus and putamen, and cortical motor areas, as well as reduced right superior temporal gyrus connectivity. Furthermore, most symptom measures correlated with right putamen, left cerebellum, left superior temporal gyrus, right premotor, and left Rolandic operculum connectivity in the voice network. The results reflect the importance of (right) subcortical nodes and the superior temporal gyrus in Parkinson's disease, enhancing our understanding of the neurobiological underpinnings of vocalization impairment in Parkinson's disease. Hum Brain Mapp 36:1951–1962, 2015. © 2015 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.. PMID:25627959

Aberrant within- and between-network connectivity of the mirror neuron system network and the mentalizing network in first episode psychosis.

PubMed

Choe, Eugenie; Lee, Tae Young; Kim, Minah; Hur, Ji-Won; Yoon, Youngwoo Bryan; Cho, Kang-Ik K; Kwon, Jun Soo

2018-03-26

It has been suggested that the mentalizing network and the mirror neuron system network support important social cognitive processes that are impaired in schizophrenia. However, the integrity and interaction of these two networks have not been sufficiently studied, and their effects on social cognition in schizophrenia remain unclear. Our study included 26 first-episode psychosis (FEP) patients and 26 healthy controls. We utilized resting-state functional connectivity to examine the a priori-defined mirror neuron system network and the mentalizing network and to assess the within- and between-network connectivities of the networks in FEP patients. We also assessed the correlation between resting-state functional connectivity measures and theory of mind performance. FEP patients showed altered within-network connectivity of the mirror neuron system network, and aberrant between-network connectivity between the mirror neuron system network and the mentalizing network. The within-network connectivity of the mirror neuron system network was noticeably correlated with theory of mind task performance in FEP patients. The integrity and interaction of the mirror neuron system network and the mentalizing network may be altered during the early stages of psychosis. Additionally, this study suggests that alterations in the integrity of the mirror neuron system network are highly related to deficient theory of mind in schizophrenia, and this problem would be present from the early stage of psychosis. Copyright © 2018 Elsevier B.V. All rights reserved.

Interferon-α acutely impairs whole-brain functional connectivity network architecture - A preliminary study.

PubMed

Dipasquale, Ottavia; Cooper, Ella A; Tibble, Jeremy; Voon, Valerie; Baglio, Francesca; Baselli, Giuseppe; Cercignani, Mara; Harrison, Neil A

2016-11-01

Interferon-alpha (IFN-α) is a key mediator of antiviral immune responses used to treat Hepatitis C infection. Though clinically effective, IFN-α rapidly impairs mood, motivation and cognition, effects that can appear indistinguishable from major depression and provide powerful empirical support for the inflammation theory of depression. Though inflammation has been shown to modulate activity within discrete brain regions, how it affects distributed information processing and the architecture of whole brain functional connectivity networks have not previously been investigated. Here we use a graph theoretic analysis of resting state functional magnetic resonance imaging (rfMRI) to investigate acute effects of systemic interferon-alpha (IFN-α) on whole brain functional connectivity architecture and its relationship to IFN-α-induced mood change. Twenty-two patients with Hepatitis-C infection, initiating IFN-α-based therapy were scanned at baseline and 4h after their first IFN-α dose. The whole brain network was parcellated into 110 cortical and sub-cortical nodes based on the Oxford-Harvard Atlas and effects assessed on higher-level graph metrics, including node degree, betweenness centrality, global and local efficiency. IFN-α was associated with a significant reduction in global network connectivity (node degree) (p=0.033) and efficiency (p=0.013), indicating a global reduction of information transfer among the nodes forming the whole brain network. Effects were similar for highly connected (hub) and non-hub nodes, with no effect on betweenness centrality (p>0.1). At a local level, we identified regions with reduced efficiency of information exchange and a sub-network with decreased functional connectivity after IFN-α. Changes in local and particularly global functional connectivity correlated with associated changes in mood measured on the Profile of Mood States (POMS) questionnaire. IFN-α rapidly induced a profound shift in whole brain network structure, impairing global functional connectivity and the efficiency of parallel information exchange. Correlations with multiple indices of mood change support a role for global changes in brain functional connectivity architecture in coordinated behavioral responses to IFN-α. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

Abnormalities of Intrinsic Functional Connectivity in Autism Spectrum Disorders

PubMed Central

Monk, Christopher S.; Peltier, Scott J.; Wiggins, Jillian Lee; Weng, Shih-Jen; Carrasco, Melisa; Risi, Susan; Lord, Catherine

2009-01-01

Autism spectrum disorders (ASD) impact social functioning and communication, and individuals with these disorders often have restrictive and repetitive behaviors. Accumulating data indicate that ASD is associated with alterations of neural circuitry. Functional MRI (FMRI) studies have focused on connectivity in the context of psychological tasks. However, even in the absence of a task, the brain exhibits a high degree of functional connectivity, known as intrinsic or resting connectivity. Notably, the default network, which includes the posterior cingulate cortex, retro-splenial, lateral parietal cortex/angular gyrus, medial prefrontal cortex, superior frontal gyrus, temporal lobe, and parahippocampal gyrus, is strongly active when there is no task. Altered intrinsic connectivity within the default network may underlie offline processing that may actuate ASD impairments. Using FMRI, we sought to evaluate intrinsic connectivity within the default network in ASD. Relative to controls, the ASD group showed weaker connectivity between the posterior cingulate cortex and superior frontal gyrus and stronger connectivity between the posterior cingulate cortex and both the right temporal lobe and right parahippocampal gyrus. Moreover, poorer social functioning in the ASD group was correlated with weaker connectivity between the posterior cingulate cortex and the superior frontal gyrus. In addition, more severe restricted and repetitive behaviors in ASD were correlated with stronger connectivity between the posterior cingulate cortex and right parahippocampal gyrus. These findings indicate that ASD subjects show altered intrinsic connectivity within the default network, and connectivity between these structures is associated with specific ASD symptoms. PMID:19409498

Further evidence of alerted default network connectivity and association with theory of mind ability in schizophrenia.

PubMed

Mothersill, Omar; Tangney, Noreen; Morris, Derek W; McCarthy, Hazel; Frodl, Thomas; Gill, Michael; Corvin, Aiden; Donohoe, Gary

2017-06-01

Resting-state functional magnetic resonance imaging (rs-fMRI) has repeatedly shown evidence of altered functional connectivity of large-scale networks in schizophrenia. The relationship between these connectivity changes and behaviour (e.g. symptoms, neuropsychological performance) remains unclear. Functional connectivity in 27 patients with schizophrenia or schizoaffective disorder, and 25 age and gender matched healthy controls was examined using rs-fMRI. Based on seed regions from previous studies, we examined functional connectivity of the default, cognitive control, affective and attention networks. Effects of symptom severity and theory of mind performance on functional connectivity were also examined. Patients showed increased connectivity between key nodes of the default network including the precuneus and medial prefrontal cortex compared to controls (p<0.01, FWE-corrected). Increasing positive symptoms and increasing theory of mind performance were both associated with altered connectivity of default regions within the patient group (p<0.01, FWE-corrected). This study confirms previous findings of default hyper-connectivity in schizophrenia spectrum patients and reveals an association between altered default connectivity and positive symptom severity. As a novel find, this study also shows that default connectivity is correlated to and predictive of theory of mind performance. Extending these findings by examining the effects of emerging social cognition treatments on both default connectivity and theory of mind performance is now an important goal for research. Copyright © 2016 Elsevier B.V. All rights reserved.

Resilience of developing brain networks to interictal epileptiform discharges is associated with cognitive outcome.

PubMed

Ibrahim, George M; Cassel, Daniel; Morgan, Benjamin R; Smith, Mary Lou; Otsubo, Hiroshi; Ochi, Ayako; Taylor, Margot; Rutka, James T; Snead, O Carter; Doesburg, Sam

2014-10-01

The effects of interictal epileptiform discharges on neurocognitive development in children with medically-intractable epilepsy are poorly understood. Such discharges may have a deleterious effect on the brain's intrinsic connectivity networks, which reflect the organization of functional networks at rest, and in turn on neurocognitive development. Using a combined functional magnetic resonance imaging-magnetoencephalography approach, we examine the effects of interictal epileptiform discharges on intrinsic connectivity networks and neurocognitive outcome. Functional magnetic resonance imaging was used to determine the location of regions comprising various intrinsic connectivity networks in 26 children (7-17 years), and magnetoencephalography data were reconstructed from these locations. Inter-regional phase synchronization was then calculated across interictal epileptiform discharges and graph theoretical analysis was applied to measure event-related changes in network topology in the peri-discharge period. The magnitude of change in network topology (network resilience/vulnerability) to interictal epileptiform discharges was associated with neurocognitive outcomes and functional magnetic resonance imaging networks using dual regression. Three main findings are reported: (i) large-scale network changes precede and follow interictal epileptiform discharges; (ii) the resilience of network topologies to interictal discharges is associated with stronger resting-state network connectivity; and (iii) vulnerability to interictal discharges is associated with worse neurocognitive outcomes. By combining the spatial resolution of functional magnetic resonance imaging with the temporal resolution of magnetoencephalography, we describe the effects of interictal epileptiform discharges on neurophysiological synchrony in intrinsic connectivity networks and establish the impact of interictal disruption of functional networks on cognitive outcome in children with epilepsy. The association between interictal discharges, network changes and neurocognitive outcomes suggests that it is of clinical importance to suppress discharges to foster more typical brain network development in children with focal epilepsy. © The Author (2014). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

The Longitudinal Trajectory of Default Mode Network Connectivity in Healthy Older Adults Varies As a Function of Age and Is Associated with Changes in Episodic Memory and Processing Speed.

PubMed

Staffaroni, Adam M; Brown, Jesse A; Casaletto, Kaitlin B; Elahi, Fanny M; Deng, Jersey; Neuhaus, John; Cobigo, Yann; Mumford, Paige S; Walters, Samantha; Saloner, Rowan; Karydas, Anna; Coppola, Giovanni; Rosen, Howie J; Miller, Bruce L; Seeley, William W; Kramer, Joel H

2018-03-14

The default mode network (DMN) supports memory functioning and may be sensitive to preclinical Alzheimer's pathology. Little is known, however, about the longitudinal trajectory of this network's intrinsic functional connectivity (FC). In this study, we evaluated longitudinal FC in 111 cognitively normal older human adults (ages 49-87, 46 women/65 men), 92 of whom had at least three task-free fMRI scans ( n = 353 total scans). Whole-brain FC and three DMN subnetworks were assessed: (1) within-DMN, (2) between anterior and posterior DMN, and (3) between medial temporal lobe network and posterior DMN. Linear mixed-effects models demonstrated significant baseline age × time interactions, indicating a nonlinear trajectory. There was a trend toward increasing FC between ages 50-66 and significantly accelerating declines after age 74. A similar interaction was observed for whole-brain FC. APOE status did not predict baseline connectivity or change in connectivity. After adjusting for network volume, changes in within-DMN connectivity were specifically associated with changes in episodic memory and processing speed but not working memory or executive functions. The relationship with processing speed was attenuated after covarying for white matter hyperintensities (WMH) and whole-brain FC, whereas within-DMN connectivity remained associated with memory above and beyond WMH and whole-brain FC. Whole-brain and DMN FC exhibit a nonlinear trajectory, with more rapid declines in older age and possibly increases in connectivity early in the aging process. Within-DMN connectivity is a marker of episodic memory performance even among cognitively healthy older adults. SIGNIFICANCE STATEMENT Default mode network and whole-brain connectivity, measured using task-free fMRI, changed nonlinearly as a function of age, with some suggestion of early increases in connectivity. For the first time, longitudinal changes in DMN connectivity were shown to correlate with changes in episodic memory, whereas volume changes in relevant brain regions did not. This relationship was not accounted for by white matter hyperintensities or mean whole-brain connectivity. Functional connectivity may be an early biomarker of changes in aging but should be used with caution given its nonmonotonic nature, which could complicate interpretation. Future studies investigating longitudinal network changes should consider whole-brain changes in connectivity. Copyright © 2018 the authors 0270-6474/18/382810-09$15.00/0.

Linking Inter-Individual Variability in Functional Brain Connectivity to Cognitive Ability in Elderly Individuals

PubMed Central

Li, Rui; Yin, Shufei; Zhu, Xinyi; Ren, Weicong; Yu, Jing; Wang, Pengyun; Zheng, Zhiwei; Niu, Ya-Nan; Huang, Xin; Li, Juan

2017-01-01

Increasing evidence suggests that functional brain connectivity is an important determinant of cognitive aging. However, the fundamental concept of inter-individual variations in functional connectivity in older individuals is not yet completely understood. It is essential to evaluate the extent to which inter-individual variability in connectivity impacts cognitive performance at an older age. In the current study, we aimed to characterize individual variability of functional connectivity in the elderly and to examine its significance to individual cognition. We mapped inter-individual variability of functional connectivity by analyzing whole-brain functional connectivity magnetic resonance imaging data obtained from a large sample of cognitively normal older adults. Our results demonstrated a gradual increase in variability in primary regions of the visual, sensorimotor, and auditory networks to specific subcortical structures, particularly the hippocampal formation, and the prefrontal and parietal cortices, which largely constitute the default mode and fronto-parietal networks, to the cerebellum. Further, the inter-individual variability of the functional connectivity correlated significantly with the degree of cognitive relevance. Regions with greater connectivity variability demonstrated more connections that correlated with cognitive performance. These results also underscored the crucial function of the long-range and inter-network connections in individual cognition. Thus, individual connectivity–cognition variability mapping findings may provide important information for future research on cognitive aging and neurocognitive diseases. PMID:29209203

Function-specific and Enhanced Brain Structural Connectivity Mapping via Joint Modeling of Diffusion and Functional MRI.

PubMed

Chu, Shu-Hsien; Parhi, Keshab K; Lenglet, Christophe

2018-03-16

A joint structural-functional brain network model is presented, which enables the discovery of function-specific brain circuits, and recovers structural connections that are under-estimated by diffusion MRI (dMRI). Incorporating information from functional MRI (fMRI) into diffusion MRI to estimate brain circuits is a challenging task. Usually, seed regions for tractography are selected from fMRI activation maps to extract the white matter pathways of interest. The proposed method jointly analyzes whole brain dMRI and fMRI data, allowing the estimation of complete function-specific structural networks instead of interactively investigating the connectivity of individual cortical/sub-cortical areas. Additionally, tractography techniques are prone to limitations, which can result in erroneous pathways. The proposed framework explicitly models the interactions between structural and functional connectivity measures thereby improving anatomical circuit estimation. Results on Human Connectome Project (HCP) data demonstrate the benefits of the approach by successfully identifying function-specific anatomical circuits, such as the language and resting-state networks. In contrast to correlation-based or independent component analysis (ICA) functional connectivity mapping, detailed anatomical connectivity patterns are revealed for each functional module. Results on a phantom (Fibercup) also indicate improvements in structural connectivity mapping by rejecting false-positive connections with insufficient support from fMRI, and enhancing under-estimated connectivity with strong functional correlation.

Whole-brain functional connectivity during acquisition of novel grammar: Distinct functional networks depend on language learning abilities.

PubMed

Kepinska, Olga; de Rover, Mischa; Caspers, Johanneke; Schiller, Niels O

2017-03-01

In an effort to advance the understanding of brain function and organisation accompanying second language learning, we investigate the neural substrates of novel grammar learning in a group of healthy adults, consisting of participants with high and average language analytical abilities (LAA). By means of an Independent Components Analysis, a data-driven approach to functional connectivity of the brain, the fMRI data collected during a grammar-learning task were decomposed into maps representing separate cognitive processes. These included the default mode, task-positive, working memory, visual, cerebellar and emotional networks. We further tested for differences within the components, representing individual differences between the High and Average LAA learners. We found high analytical abilities to be coupled with stronger contributions to the task-positive network from areas adjacent to bilateral Broca's region, stronger connectivity within the working memory network and within the emotional network. Average LAA participants displayed stronger engagement within the task-positive network from areas adjacent to the right-hemisphere homologue of Broca's region and typical to lower level processing (visual word recognition), and increased connectivity within the default mode network. The significance of each of the identified networks for the grammar learning process is presented next to a discussion on the established markers of inter-individual learners' differences. We conclude that in terms of functional connectivity, the engagement of brain's networks during grammar acquisition is coupled with one's language learning abilities. Copyright © 2016 Elsevier B.V. All rights reserved.

Brain Network Analysis from High-Resolution EEG Signals

NASA Astrophysics Data System (ADS)

de Vico Fallani, Fabrizio; Babiloni, Fabio

Over the last decade, there has been a growing interest in the detection of the functional connectivity in the brain from different neuroelectromagnetic and hemodynamic signals recorded by several neuro-imaging devices such as the functional Magnetic Resonance Imaging (fMRI) scanner, electroencephalography (EEG) and magnetoencephalography (MEG) apparatus. Many methods have been proposed and discussed in the literature with the aim of estimating the functional relationships among different cerebral structures. However, the necessity of an objective comprehension of the network composed by the functional links of different brain regions is assuming an essential role in the Neuroscience. Consequently, there is a wide interest in the development and validation of mathematical tools that are appropriate to spot significant features that could describe concisely the structure of the estimated cerebral networks. The extraction of salient characteristics from brain connectivity patterns is an open challenging topic, since often the estimated cerebral networks have a relative large size and complex structure. Recently, it was realized that the functional connectivity networks estimated from actual brain-imaging technologies (MEG, fMRI and EEG) can be analyzed by means of the graph theory. Since a graph is a mathematical representation of a network, which is essentially reduced to nodes and connections between them, the use of a theoretical graph approach seems relevant and useful as firstly demonstrated on a set of anatomical brain networks. In those studies, the authors have employed two characteristic measures, the average shortest path L and the clustering index C, to extract respectively the global and local properties of the network structure. They have found that anatomical brain networks exhibit many local connections (i.e. a high C) and few random long distance connections (i.e. a low L). These values identify a particular model that interpolate between a regular lattice and a random structure. Such a model has been designated as "small-world" network in analogy with the concept of the small-world phenomenon observed more than 30 years ago in social systems. In a similar way, many types of functional brain networks have been analyzed according to this mathematical approach. In particular, several studies based on different imaging techniques (fMRI, MEG and EEG) have found that the estimated functional networks showed small-world characteristics. In the functional brain connectivity context, these properties have been demonstrated to reflect an optimal architecture for the information processing and propagation among the involved cerebral structures. However, the performance of cognitive and motor tasks as well as the presence of neural diseases has been demonstrated to affect such a small-world topology, as revealed by the significant changes of L and C. Moreover, some functional brain networks have been mostly found to be very unlike the random graphs in their degree-distribution, which gives information about the allocation of the functional links within the connectivity pattern. It was demonstrated that the degree distributions of these networks follow a power-law trend. For this reason those networks are called "scale-free". They still exhibit the small-world phenomenon but tend to contain few nodes that act as highly connected "hubs". Scale-free networks are known to show resistance to failure, facility of synchronization and fast signal processing. Hence, it would be important to see whether the scaling properties of the functional brain networks are altered under various pathologies or experimental tasks. The present Chapter proposes a theoretical graph approach in order to evaluate the functional connectivity patterns obtained from high-resolution EEG signals. In this way, the "Brain Network Analysis" (in analogy with the Social Network Analysis that has emerged as a key technique in modern sociology) represents an effective methodology improving the comprehension of the complex interactions in the brain.

The CB1 Neutral Antagonist Tetrahydrocannabivarin Reduces Default Mode Network and Increases Executive Control Network Resting State Functional Connectivity in Healthy Volunteers.

PubMed

Rzepa, Ewelina; Tudge, Luke; McCabe, Ciara

2015-09-10

The cannabinoid cannabinoid type 1 (CB1) neutral antagonist tetrahydrocannabivarin (THCv) has been suggested as a possible treatment for obesity, but without the depressogenic side-effects of inverse antagonists such as Rimonabant. However, how THCv might affect the resting state functional connectivity of the human brain is as yet unknown. We examined the effects of a single 10mg oral dose of THCv and placebo in 20 healthy volunteers in a randomized, within-subject, double-blind design. Using resting state functional magnetic resonance imaging and seed-based connectivity analyses, we selected the amygdala, insula, orbitofrontal cortex, and dorsal medial prefrontal cortex (dmPFC) as regions of interest. Mood and subjective experience were also measured before and after drug administration using self-report scales. Our results revealed, as expected, no significant differences in the subjective experience with a single dose of THCv. However, we found reduced resting state functional connectivity between the amygdala seed region and the default mode network and increased resting state functional connectivity between the amygdala seed region and the dorsal anterior cingulate cortex and between the dmPFC seed region and the inferior frontal gyrus/medial frontal gyrus. We also found a positive correlation under placebo for the amygdala-precuneus connectivity with the body mass index, although this correlation was not apparent under THCv. Our findings are the first to show that treatment with the CB1 neutral antagonist THCv decreases resting state functional connectivity in the default mode network and increases connectivity in the cognitive control network and dorsal visual stream network. This effect profile suggests possible therapeutic activity of THCv for obesity, where functional connectivity has been found to be altered in these regions. © The Author 2015. Published by Oxford University Press on behalf of CINP.

Structural disconnection is responsible for increased functional connectivity in multiple sclerosis.

PubMed

Patel, Kevin R; Tobyne, Sean; Porter, Daria; Bireley, John Daniel; Smith, Victoria; Klawiter, Eric

2018-06-01

Increased synchrony within neuroanatomical networks is often observed in neurophysiologic studies of human brain disease. Most often, this phenomenon is ascribed to a compensatory process in the face of injury, though evidence supporting such accounts is limited. Given the known dependence of resting-state functional connectivity (rsFC) on underlying structural connectivity (SC), we examine an alternative hypothesis: that topographical changes in SC, specifically particular patterns of disconnection, contribute to increased network rsFC. We obtain measures of rsFC using fMRI and SC using probabilistic tractography in 50 healthy and 28 multiple sclerosis subjects. Using a computational model of neuronal dynamics, we simulate BOLD using healthy subject SC to couple regions. We find that altering the model by introducing structural disconnection patterns observed in those multiple sclerosis subjects with high network rsFC generates simulations with high rsFC as well, suggesting that disconnection itself plays a role in producing high network functional connectivity. We then examine SC data in individuals. In multiple sclerosis subjects with high network rsFC, we find a preferential disconnection between the relevant network and wider system. We examine the significance of such network isolation by introducing random disconnection into the model. As observed empirically, simulated network rsFC increases with removal of connections bridging a community with the remainder of the brain. We thus show that structural disconnection known to occur in multiple sclerosis contributes to network rsFC changes in multiple sclerosis and further that community isolation is responsible for elevated network functional connectivity.

Connectivity strength-weighted sparse group representation-based brain network construction for MCI classification.

PubMed

Yu, Renping; Zhang, Han; An, Le; Chen, Xiaobo; Wei, Zhihui; Shen, Dinggang

2017-05-01

Brain functional network analysis has shown great potential in understanding brain functions and also in identifying biomarkers for brain diseases, such as Alzheimer's disease (AD) and its early stage, mild cognitive impairment (MCI). In these applications, accurate construction of biologically meaningful brain network is critical. Sparse learning has been widely used for brain network construction; however, its l 1 -norm penalty simply penalizes each edge of a brain network equally, without considering the original connectivity strength which is one of the most important inherent linkwise characters. Besides, based on the similarity of the linkwise connectivity, brain network shows prominent group structure (i.e., a set of edges sharing similar attributes). In this article, we propose a novel brain functional network modeling framework with a "connectivity strength-weighted sparse group constraint." In particular, the network modeling can be optimized by considering both raw connectivity strength and its group structure, without losing the merit of sparsity. Our proposed method is applied to MCI classification, a challenging task for early AD diagnosis. Experimental results based on the resting-state functional MRI, from 50 MCI patients and 49 healthy controls, show that our proposed method is more effective (i.e., achieving a significantly higher classification accuracy, 84.8%) than other competing methods (e.g., sparse representation, accuracy = 65.6%). Post hoc inspection of the informative features further shows more biologically meaningful brain functional connectivities obtained by our proposed method. Hum Brain Mapp 38:2370-2383, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Functional Connectivity Between Anterior Insula and Key Nodes of Frontoparietal Executive Control and Salience Networks Distinguish Bipolar Depression From Unipolar Depression and Healthy Control Subjects.

PubMed

Ellard, Kristen K; Zimmerman, Jared P; Kaur, Navneet; Van Dijk, Koene R A; Roffman, Joshua L; Nierenberg, Andrew A; Dougherty, Darin D; Deckersbach, Thilo; Camprodon, Joan A

2018-05-01

Patients with bipolar depression are characterized by dysregulation across the full spectrum of mood, differentiating them from patients with unipolar depression. The ability to switch neural resources among the default mode network, salience network, and executive control network (ECN) has been proposed as a key mechanism for adaptive mood regulation. The anterior insula is implicated in the modulation of functional network switching. Differential connectivity between anterior insula and functional networks may provide insights into pathophysiological differences between bipolar and unipolar mood disorders, with implications for diagnosis and treatment. Resting-state functional magnetic resonance imaging data were collected from 98 subjects (35 unipolar, 24 bipolar, and 39 healthy control subjects). Pearson correlations were computed between bilateral insula seed regions and a priori defined target regions from the default mode network, salience network, and ECN. After r-to-z transformation, a one-way multivariate analysis of covariance was conducted to identify significant differences in connectivity between groups. Post hoc pairwise comparisons were conducted and Bonferroni corrections were applied. Receiver-operating characteristics were computed to assess diagnostic sensitivity. Patients with bipolar depression evidenced significantly altered right anterior insula functional connectivity with the inferior parietal lobule of the ECN relative to patients with unipolar depression and control subjects. Right anterior insula-inferior parietal lobule connectivity significantly discriminated patients with bipolar depression. Impaired functional connectivity between the anterior insula and the inferior parietal lobule of the ECN distinguishes patients with bipolar depression from those with unipolar depression and healthy control subjects. This finding highlights a pathophysiological mechanism with potential as a therapeutic target and a clinical biomarker for bipolar disorder, exhibiting reasonable sensitivity and specificity. Copyright © 2018 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

Ecological connectivity networks in rapidly expanding cities.

PubMed

Nor, Amal Najihah M; Corstanje, Ron; Harris, Jim A; Grafius, Darren R; Siriwardena, Gavin M

2017-06-01

Urban expansion increases fragmentation of the landscape. In effect, fragmentation decreases connectivity, causes green space loss and impacts upon the ecology and function of green space. Restoration of the functionality of green space often requires restoring the ecological connectivity of this green space within the city matrix. However, identifying ecological corridors that integrate different structural and functional connectivity of green space remains vague. Assessing connectivity for developing an ecological network by using efficient models is essential to improve these networks under rapid urban expansion. This paper presents a novel methodological approach to assess and model connectivity for the Eurasian tree sparrow ( Passer montanus ) and Yellow-vented bulbul ( Pycnonotus goiavier ) in three cities (Kuala Lumpur, Malaysia; Jakarta, Indonesia and Metro Manila, Philippines). The approach identifies potential priority corridors for ecological connectivity networks. The study combined circuit models, connectivity analysis and least-cost models to identify potential corridors by integrating structure and function of green space patches to provide reliable ecological connectivity network models in the cities. Relevant parameters such as landscape resistance and green space structure (vegetation density, patch size and patch distance) were derived from an expert and literature-based approach based on the preference of bird behaviour. The integrated models allowed the assessment of connectivity for both species using different measures of green space structure revealing the potential corridors and least-cost pathways for both bird species at the patch sites. The implementation of improvements to the identified corridors could increase the connectivity of green space. This study provides examples of how combining models can contribute to the improvement of ecological networks in rapidly expanding cities and demonstrates the usefulness of such models for biodiversity conservation and urban planning.

Age differences in the intrinsic functional connectivity of default network subsystems

PubMed Central

Campbell, Karen L.; Grigg, Omer; Saverino, Cristina; Churchill, Nathan; Grady, Cheryl L.

2013-01-01

Recent work suggests that the default mode network (DMN) includes two core regions, the ventromedial prefrontal cortex and posterior cingulate cortex (PCC), and several unique subsystems that are functionally distinct. These include a medial temporal lobe (MTL) subsystem, active during remembering and future projection, and a dorsomedial prefrontal cortex (dmPFC) subsystem, active during self-reference. The PCC has been further subdivided into ventral (vPCC) and dorsal (dPCC) regions that are more strongly connected with the DMN and cognitive control networks, respectively. The goal of this study was to examine age differences in resting state functional connectivity within these subsystems. After applying a rigorous procedure to reduce the effects of head motion, we used a multivariate technique to identify both common and unique patterns of functional connectivity in the MTL vs. the dmPFC, and in vPCC vs. dPCC. All four areas had robust functional connectivity with other DMN regions, and each also showed distinct connectivity patterns in both age groups. Young and older adults had equivalent functional connectivity in the MTL subsystem. Older adults showed weaker connectivity in the vPCC and dmPFC subsystems, particularly with other DMN areas, but stronger connectivity than younger adults in the dPCC subsystem, which included areas involved in cognitive control. Our data provide evidence for distinct subsystems involving DMN nodes, which are maintained with age. Nevertheless, there are age differences in the strength of functional connectivity within these subsystems, supporting prior evidence that DMN connectivity is particularly vulnerable to age, whereas connectivity involving cognitive control regions is relatively maintained. These results suggest an age difference in the integrated activity among brain networks that can have implications for cognition in older adults. PMID:24294203

Age differences in the intrinsic functional connectivity of default network subsystems.

PubMed

Campbell, Karen L; Grigg, Omer; Saverino, Cristina; Churchill, Nathan; Grady, Cheryl L

2013-01-01

Recent work suggests that the default mode network (DMN) includes two core regions, the ventromedial prefrontal cortex and posterior cingulate cortex (PCC), and several unique subsystems that are functionally distinct. These include a medial temporal lobe (MTL) subsystem, active during remembering and future projection, and a dorsomedial prefrontal cortex (dmPFC) subsystem, active during self-reference. The PCC has been further subdivided into ventral (vPCC) and dorsal (dPCC) regions that are more strongly connected with the DMN and cognitive control networks, respectively. The goal of this study was to examine age differences in resting state functional connectivity within these subsystems. After applying a rigorous procedure to reduce the effects of head motion, we used a multivariate technique to identify both common and unique patterns of functional connectivity in the MTL vs. the dmPFC, and in vPCC vs. dPCC. All four areas had robust functional connectivity with other DMN regions, and each also showed distinct connectivity patterns in both age groups. Young and older adults had equivalent functional connectivity in the MTL subsystem. Older adults showed weaker connectivity in the vPCC and dmPFC subsystems, particularly with other DMN areas, but stronger connectivity than younger adults in the dPCC subsystem, which included areas involved in cognitive control. Our data provide evidence for distinct subsystems involving DMN nodes, which are maintained with age. Nevertheless, there are age differences in the strength of functional connectivity within these subsystems, supporting prior evidence that DMN connectivity is particularly vulnerable to age, whereas connectivity involving cognitive control regions is relatively maintained. These results suggest an age difference in the integrated activity among brain networks that can have implications for cognition in older adults.

Functional network integrity presages cognitive decline in preclinical Alzheimer disease.

PubMed

Buckley, Rachel F; Schultz, Aaron P; Hedden, Trey; Papp, Kathryn V; Hanseeuw, Bernard J; Marshall, Gad; Sepulcre, Jorge; Smith, Emily E; Rentz, Dorene M; Johnson, Keith A; Sperling, Reisa A; Chhatwal, Jasmeer P

2017-07-04

To examine the utility of resting-state functional connectivity MRI (rs-fcMRI) measurements of network integrity as a predictor of future cognitive decline in preclinical Alzheimer disease (AD). A total of 237 clinically normal older adults (aged 63-90 years, Clinical Dementia Rating 0) underwent baseline β-amyloid (Aβ) imaging with Pittsburgh compound B PET and structural and rs-fcMRI. We identified 7 networks for analysis, including 4 cognitive networks (default, salience, dorsal attention, and frontoparietal control) and 3 noncognitive networks (primary visual, extrastriate visual, motor). Using linear and curvilinear mixed models, we used baseline connectivity in these networks to predict longitudinal changes in preclinical Alzheimer cognitive composite (PACC) performance, both alone and interacting with Aβ burden. Median neuropsychological follow-up was 3 years. Baseline connectivity in the default, salience, and control networks predicted longitudinal PACC decline, unlike connectivity in the dorsal attention and all noncognitive networks. Default, salience, and control network connectivity was also synergistic with Aβ burden in predicting decline, with combined higher Aβ and lower connectivity predicting the steepest curvilinear decline in PACC performance. In clinically normal older adults, lower functional connectivity predicted more rapid decline in PACC scores over time, particularly when coupled with increased Aβ burden. Among examined networks, default, salience, and control networks were the strongest predictors of rate of change in PACC scores, with the inflection point of greatest decline beyond the fourth year of follow-up. These results suggest that rs-fcMRI may be a useful predictor of early, AD-related cognitive decline in clinical research settings. © 2017 American Academy of Neurology.

Low-rank network decomposition reveals structural characteristics of small-world networks

NASA Astrophysics Data System (ADS)

Barranca, Victor J.; Zhou, Douglas; Cai, David

2015-12-01

Small-world networks occur naturally throughout biological, technological, and social systems. With their prevalence, it is particularly important to prudently identify small-world networks and further characterize their unique connection structure with respect to network function. In this work we develop a formalism for classifying networks and identifying small-world structure using a decomposition of network connectivity matrices into low-rank and sparse components, corresponding to connections within clusters of highly connected nodes and sparse interconnections between clusters, respectively. We show that the network decomposition is independent of node indexing and define associated bounded measures of connectivity structure, which provide insight into the clustering and regularity of network connections. While many existing network characterizations rely on constructing benchmark networks for comparison or fail to describe the structural properties of relatively densely connected networks, our classification relies only on the intrinsic network structure and is quite robust with respect to changes in connection density, producing stable results across network realizations. Using this framework, we analyze several real-world networks and reveal new structural properties, which are often indiscernible by previously established characterizations of network connectivity.

Control networks and hubs.

PubMed

Gratton, Caterina; Sun, Haoxin; Petersen, Steven E

2018-03-01

Executive control functions are associated with frontal, parietal, cingulate, and insular brain regions that interact through distributed large-scale networks. Here, we discuss how fMRI functional connectivity can shed light on the organization of control networks and how they interact with other parts of the brain. In the first section of our review, we present convergent evidence from fMRI functional connectivity, activation, and lesion studies that there are multiple dissociable control networks in the brain with distinct functional properties. In the second section, we discuss how graph theoretical concepts can help illuminate the mechanisms by which control networks interact with other brain regions to carry out goal-directed functions, focusing on the role of specialized hub regions for mediating cross-network interactions. Again, we use a combination of functional connectivity, lesion, and task activation studies to bolster this claim. We conclude that a large-scale network perspective provides important neurobiological constraints on the neural underpinnings of executive control, which will guide future basic and translational research into executive function and its disruption in disease. © 2017 Society for Psychophysiological Research.

Trade-off of cerebello-cortical and cortico-cortical functional networks for planning in 6-year-old children.

PubMed

Kipping, Judy A; Margulies, Daniel S; Eickhoff, Simon B; Lee, Annie; Qiu, Anqi

2018-08-01

Childhood is a critical period for the development of cognitive planning. There is a lack of knowledge on its neural mechanisms in children. This study aimed to examine cerebello-cortical and cortico-cortical functional connectivity in association with planning skills in 6-year-olds (n = 76). We identified the cerebello-cortical and cortico-cortical functional networks related to cognitive planning using activation likelihood estimation (ALE) meta-analysis on existing functional imaging studies on spatial planning, and data-driven independent component analysis (ICA) of children's resting-state functional MRI (rs-fMRI). We investigated associations of cerebello-cortical and cortico-cortical functional connectivity with planning ability in 6-year-olds, as assessed using the Stockings of Cambridge task. Long-range functional connectivity of two cerebellar networks (lobules VI and lateral VIIa) with the prefrontal and premotor cortex were greater in children with poorer planning ability. In contrast, cortico-cortical association networks were not associated with the performance of planning in children. These results highlighted the key contribution of the lateral cerebello-frontal functional connectivity, but not cortico-cortical association functional connectivity, for planning ability in 6-year-olds. Our results suggested that brain adaptation to the acquisition of planning ability during childhood is partially achieved through the engagement of the cerebello-cortical functional connectivity. Copyright © 2018 Elsevier Inc. All rights reserved.

Functional connectivity associated with social networks in older adults: A resting-state fMRI study.

PubMed

Pillemer, Sarah; Holtzer, Roee; Blumen, Helena M

2017-06-01

Poor social networks and decreased levels of social support are associated with worse mood, health, and cognition in younger and older adults. Yet, we know very little about the brain substrates associated with social networks and social support, particularly in older adults. This study examined functional brain substrates associated with social networks using the Social Network Index (SNI) and resting-state functional magnetic resonance imaging (fMRI). Resting-state fMRI data from 28 non-demented older adults were analyzed with independent components analyses. As expected, four established resting-state networks-previously linked to motor, vision, speech, and other language functions-correlated with the quality (SNI-1: total number of high-contact roles of a respondent) and quantity (SNI-2: total number of individuals in a respondent's social network) of social networks: a sensorimotor, a visual, a vestibular/insular, and a left frontoparietal network. Moreover, SNI-1 was associated with greater functional connectivity in the lateral prefrontal regions of the left frontoparietal network, while SNI-2 was associated with greater functional connectivity in the medial prefrontal regions of this network. Thus, lateral prefrontal regions may be particularly linked to the quality of social networks while medial prefrontal regions may be particularly linked to the quantity of social networks.

Preliminary findings of altered functional connectivity of the default mode network linked to functional outcomes one year after pediatric traumatic brain injury.

PubMed

Stephens, Jaclyn A; Salorio, Cynthia F; Barber, Anita D; Risen, Sarah R; Mostofsky, Stewart H; Suskauer, Stacy J

2017-07-10

This study examined functional connectivity of the default mode network (DMN) and examined brain-behavior relationships in a pilot cohort of children with chronic mild to moderate traumatic brain injury (TBI). Compared to uninjured peers, children with TBI demonstrated less anti-correlated functional connectivity between DMN and right Brodmann Area 40 (BA 40). In children with TBI, more anomalous less anti-correlated) connectivity between DMN and right BA 40 was linked to poorer performance on response inhibition tasks. Collectively, these preliminary findings suggest that functional connectivity between DMN and BA 40 may relate to longterm functional outcomes in chronic pediatric TBI.

Different alterations in brain functional networks according to direct and indirect topological connections in patients with schizophrenia.

PubMed

Park, Chang-Hyun; Lee, Seungyup; Kim, Taewon; Won, Wang Yeon; Lee, Kyoung-Uk

2017-10-01

Schizophrenia displays connectivity deficits in the brain, but the literature has shown inconsistent findings about alterations in global efficiency of brain functional networks. We supposed that such inconsistency at the whole brain level may be due to a mixture of different portions of global efficiency at sub-brain levels. Accordingly, we considered measuring portions of global efficiency in two aspects: spatial portions by considering sub-brain networks and topological portions by considering contributions to global efficiency according to direct and indirect topological connections. We proposed adjacency and indirect adjacency as new network parameters attributable to direct and indirect topological connections, respectively, and applied them to graph-theoretical analysis of brain functional networks constructed from resting state fMRI data of 22 patients with schizophrenia and 22 healthy controls. Group differences in the network parameters were observed not for whole brain and hemispheric networks, but for regional networks. Alterations in adjacency and indirect adjacency were in opposite directions, such that adjacency increased, but indirect adjacency decreased in patients with schizophrenia. Furthermore, over connections in frontal and parietal regions, increased adjacency was associated with more severe negative symptoms, while decreased adjacency was associated with more severe positive symptoms of schizophrenia. This finding indicates that connectivity deficits associated with positive and negative symptoms of schizophrenia may involve topologically different paths in the brain. In patients with schizophrenia, although changes in global efficiency may not be clearly shown, different alterations in brain functional networks according to direct and indirect topological connections could be revealed at the regional level. Copyright © 2017 Elsevier B.V. All rights reserved.

Motor network disruption in essential tremor: a functional and effective connectivity study.

PubMed

Buijink, Arthur W G; van der Stouwe, A M Madelein; Broersma, Marja; Sharifi, Sarvi; Groot, Paul F C; Speelman, Johannes D; Maurits, Natasha M; van Rootselaar, Anne-Fleur

2015-10-01

Although involvement of the cerebello-thalamo-cortical network has often been suggested in essential tremor, the source of oscillatory activity remains largely unknown. To elucidate mechanisms of tremor generation, it is of crucial importance to study the dynamics within the cerebello-thalamo-cortical network. Using a combination of electromyography and functional magnetic resonance imaging, it is possible to record the peripheral manifestation of tremor simultaneously with brain activity related to tremor generation. Our first aim was to study the intrinsic activity of regions within the cerebello-thalamo-cortical network using dynamic causal modelling to estimate effective connectivity driven by the concurrently recorded tremor signal. Our second aim was to objectify how the functional integrity of the cerebello-thalamo-cortical network is affected in essential tremor. We investigated the functional connectivity between cerebellar and cortical motor regions showing activations during a motor task. Twenty-two essential tremor patients and 22 healthy controls were analysed. For the effective connectivity analysis, a network of tremor-signal related regions was constructed, consisting of the left primary motor cortex, premotor cortex, supplementary motor area, left thalamus, and right cerebellar motor regions lobule V and lobule VIII. A measure of variation in tremor severity over time, derived from the electromyogram, was included as modulatory input on intrinsic connections and on the extrinsic cerebello-thalamic connections, giving a total of 128 models. Bayesian model selection and random effects Bayesian model averaging were used. Separate seed-based functional connectivity analyses for the left primary motor cortex, left supplementary motor area and right cerebellar lobules IV, V, VI and VIII were performed. We report two novel findings that support an important role for the cerebellar system in the pathophysiology of essential tremor. First, in the effective connectivity analysis, tremor variation during the motor task has an excitatory effect on both the extrinsic connection from cerebellar lobule V to the thalamus, and the intrinsic activity of cerebellar lobule V and thalamus. Second, the functional integrity of the motor network is affected in essential tremor, with a decrease in functional connectivity between cortical and cerebellar motor regions. This decrease in functional connectivity, related to the motor task, correlates with an increase in clinical tremor severity. Interestingly, increased functional connectivity between right cerebellar lobules I-IV and the left thalamus correlates with an increase in clinical tremor severity. In conclusion, our findings suggest that cerebello-dentato-thalamic activity and cerebello-cortical connectivity is disturbed in essential tremor, supporting previous evidence of functional cerebellar changes in essential tremor. © The Author (2015). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Multilayer motif analysis of brain networks

NASA Astrophysics Data System (ADS)

Battiston, Federico; Nicosia, Vincenzo; Chavez, Mario; Latora, Vito

2017-04-01

In the last decade, network science has shed new light both on the structural (anatomical) and on the functional (correlations in the activity) connectivity among the different areas of the human brain. The analysis of brain networks has made possible to detect the central areas of a neural system and to identify its building blocks by looking at overabundant small subgraphs, known as motifs. However, network analysis of the brain has so far mainly focused on anatomical and functional networks as separate entities. The recently developed mathematical framework of multi-layer networks allows us to perform an analysis of the human brain where the structural and functional layers are considered together. In this work, we describe how to classify the subgraphs of a multiplex network, and we extend the motif analysis to networks with an arbitrary number of layers. We then extract multi-layer motifs in brain networks of healthy subjects by considering networks with two layers, anatomical and functional, respectively, obtained from diffusion and functional magnetic resonance imaging. Results indicate that subgraphs in which the presence of a physical connection between brain areas (links at the structural layer) coexists with a non-trivial positive correlation in their activities are statistically overabundant. Finally, we investigate the existence of a reinforcement mechanism between the two layers by looking at how the probability to find a link in one layer depends on the intensity of the connection in the other one. Showing that functional connectivity is non-trivially constrained by the underlying anatomical network, our work contributes to a better understanding of the interplay between the structure and function in the human brain.

Altered intrinsic and extrinsic connectivity in schizophrenia.

PubMed

Zhou, Yuan; Zeidman, Peter; Wu, Shihao; Razi, Adeel; Chen, Cheng; Yang, Liuqing; Zou, Jilin; Wang, Gaohua; Wang, Huiling; Friston, Karl J

2018-01-01

Schizophrenia is a disorder characterized by functional dysconnectivity among distributed brain regions. However, it is unclear how causal influences among large-scale brain networks are disrupted in schizophrenia. In this study, we used dynamic causal modeling (DCM) to assess the hypothesis that there is aberrant directed (effective) connectivity within and between three key large-scale brain networks (the dorsal attention network, the salience network and the default mode network) in schizophrenia during a working memory task. Functional MRI data during an n-back task from 40 patients with schizophrenia and 62 healthy controls were analyzed. Using hierarchical modeling of between-subject effects in DCM with Parametric Empirical Bayes, we found that intrinsic (within-region) and extrinsic (between-region) effective connectivity involving prefrontal regions were abnormal in schizophrenia. Specifically, in patients (i) inhibitory self-connections in prefrontal regions of the dorsal attention network were decreased across task conditions; (ii) extrinsic connectivity between regions of the default mode network was increased; specifically, from posterior cingulate cortex to the medial prefrontal cortex; (iii) between-network extrinsic connections involving the prefrontal cortex were altered; (iv) connections within networks and between networks were correlated with the severity of clinical symptoms and impaired cognition beyond working memory. In short, this study revealed the predominance of reduced synaptic efficacy of prefrontal efferents and afferents in the pathophysiology of schizophrenia.

PreSMA stimulation changes task-free functional connectivity in the fronto-basal-ganglia that correlates with response inhibition efficiency

PubMed Central

Xu, Benjamin; Sandrini, Marco; Wang, Wen-tung; Smith, Jason F.; Sarlls, Joelle E.; Awosika, Oluwole; Butman, John A.; Horwitz, Barry; Cohen, Leonardo G.

2016-01-01

Previous work using transcranial magnetic stimulation (TMS) demonstrated that the right pre-supplementary motor area (preSMA), a node in the fronto-basal-ganglia network, is critical for response inhibition. However, TMS influences interconnected regions, raising the possibility of a link between the preSMA activity and the functional connectivity within the network. To understand this relationship, we applied single-pulse TMS to the right preSMA during functional magnetic resonance imaging when the subjects were at rest to examine changes in neural activity and functional connectivity within the network in relation to the efficiency of response inhibition evaluated with a stop-signal task. The results showed that preSMA-TMS increased activation in the right inferior-frontal cortex (rIFC) and basal ganglia and modulated their task-free functional connectivity. Both the TMS-induced changes in the basal-ganglia activation and the functional connectivity between rIFC and left striatum, and of the overall network correlated with the efficiency of response inhibition and with the white-matter microstructure along the preSMA – rIFC pathway. These results suggest that the task-free functional and structural connectivity between the rIFCop and basal ganglia are critical to the efficiency of response inhibition. PMID:27144466

Discriminant analysis of resting-state functional connectivity patterns on the Grassmann manifold

NASA Astrophysics Data System (ADS)

Fan, Yong; Liu, Yong; Jiang, Tianzi; Liu, Zhening; Hao, Yihui; Liu, Haihong

2010-03-01

The functional networks, extracted from fMRI images using independent component analysis, have been demonstrated informative for distinguishing brain states of cognitive functions and neurological diseases. In this paper, we propose a novel algorithm for discriminant analysis of functional networks encoded by spatial independent components. The functional networks of each individual are used as bases for a linear subspace, referred to as a functional connectivity pattern, which facilitates a comprehensive characterization of temporal signals of fMRI data. The functional connectivity patterns of different individuals are analyzed on the Grassmann manifold by adopting a principal angle based subspace distance. In conjunction with a support vector machine classifier, a forward component selection technique is proposed to select independent components for constructing the most discriminative functional connectivity pattern. The discriminant analysis method has been applied to an fMRI based schizophrenia study with 31 schizophrenia patients and 31 healthy individuals. The experimental results demonstrate that the proposed method not only achieves a promising classification performance for distinguishing schizophrenia patients from healthy controls, but also identifies discriminative functional networks that are informative for schizophrenia diagnosis.

Functional connectivity changes detected with magnetoencephalography after mild traumatic brain injury

PubMed Central

Dimitriadis, Stavros I.; Zouridakis, George; Rezaie, Roozbeh; Babajani-Feremi, Abbas; Papanicolaou, Andrew C.

2015-01-01

Mild traumatic brain injury (mTBI) may affect normal cognition and behavior by disrupting the functional connectivity networks that mediate efficient communication among brain regions. In this study, we analyzed brain connectivity profiles from resting state Magnetoencephalographic (MEG) recordings obtained from 31 mTBI patients and 55 normal controls. We used phase-locking value estimates to compute functional connectivity graphs to quantify frequency-specific couplings between sensors at various frequency bands. Overall, normal controls showed a dense network of strong local connections and a limited number of long-range connections that accounted for approximately 20% of all connections, whereas mTBI patients showed networks characterized by weak local connections and strong long-range connections that accounted for more than 60% of all connections. Comparison of the two distinct general patterns at different frequencies using a tensor representation for the connectivity graphs and tensor subspace analysis for optimal feature extraction showed that mTBI patients could be separated from normal controls with 100% classification accuracy in the alpha band. These encouraging findings support the hypothesis that MEG-based functional connectivity patterns may be used as biomarkers that can provide more accurate diagnoses, help guide treatment, and monitor effectiveness of intervention in mTBI. PMID:26640764

Efficiency of weak brain connections support general cognitive functioning.

PubMed

Santarnecchi, Emiliano; Galli, Giulia; Polizzotto, Nicola Riccardo; Rossi, Alessandro; Rossi, Simone

2014-09-01

Brain network topology provides valuable information on healthy and pathological brain functioning. Novel approaches for brain network analysis have shown an association between topological properties and cognitive functioning. Under the assumption that "stronger is better", the exploration of brain properties has generally focused on the connectivity patterns of the most strongly correlated regions, whereas the role of weaker brain connections has remained obscure for years. Here, we assessed whether the different strength of connections between brain regions may explain individual differences in intelligence. We analyzed-functional connectivity at rest in ninety-eight healthy individuals of different age, and correlated several connectivity measures with full scale, verbal, and performance Intelligent Quotients (IQs). Our results showed that the variance in IQ levels was mostly explained by the distributed communication efficiency of brain networks built using moderately weak, long-distance connections, with only a smaller contribution of stronger connections. The variability in individual IQs was associated with the global efficiency of a pool of regions in the prefrontal lobes, hippocampus, temporal pole, and postcentral gyrus. These findings challenge the traditional view of a prominent role of strong functional brain connections in brain topology, and highlight the importance of both strong and weak connections in determining the functional architecture responsible for human intelligence variability. Copyright © 2014 Wiley Periodicals, Inc.

Changes in functional and structural brain connectome along the Alzheimer's disease continuum.

PubMed

Filippi, Massimo; Basaia, Silvia; Canu, Elisa; Imperiale, Francesca; Magnani, Giuseppe; Falautano, Monica; Comi, Giancarlo; Falini, Andrea; Agosta, Federica

2018-05-09

The aim of this study was two-fold: (i) to investigate structural and functional brain network architecture in patients with Alzheimer's disease (AD) and amnestic mild cognitive impairment (aMCI), stratified in converters (c-aMCI) and non-converters (nc-aMCI) to AD; and to assess the relationship between healthy brain network functional connectivity and the topography of brain atrophy in patients along the AD continuum. Ninety-four AD patients, 47 aMCI patients (25 c-aMCI within 36 months) and 53 age- and sex-matched healthy controls were studied. Graph analysis and connectomics assessed global and local, structural and functional topological network properties and regional connectivity. Healthy topological features of brain regions were assessed based on their connectivity with the point of maximal atrophy (epicenter) in AD and aMCI patients. Brain network graph analysis properties were severely altered in AD patients. Structural brain network was already altered in c-aMCI patients relative to healthy controls in particular in the temporal and parietal brain regions, while functional connectivity did not change. Structural connectivity alterations distinguished c-aMCI from nc-aMCI cases. In both AD and c-aMCI, the point of maximal atrophy was located in left hippocampus (disease-epicenter). Brain regions most strongly connected with the disease-epicenter in the healthy functional connectome were also the most atrophic in both AD and c-aMCI patients. Progressive degeneration in the AD continuum is associated with an early breakdown of anatomical brain connections and follows the strongest connections with the disease-epicenter. These findings support the hypothesis that the topography of brain connectional architecture can modulate the spread of AD through the brain.

Atypical cross talk between mentalizing and mirror neuron networks in autism spectrum disorder.

PubMed

Fishman, Inna; Keown, Christopher L; Lincoln, Alan J; Pineda, Jaime A; Müller, Ralph-Axel

2014-07-01

Converging evidence indicates that brain abnormalities in autism spectrum disorder (ASD) involve atypical network connectivity, but it is unclear whether altered connectivity is especially prominent in brain networks that participate in social cognition. To investigate whether adolescents with ASD show altered functional connectivity in 2 brain networks putatively impaired in ASD and involved in social processing, theory of mind (ToM) and mirror neuron system (MNS). Cross-sectional study using resting-state functional magnetic resonance imaging involving 25 adolescents with ASD between the ages of 11 and 18 years and 25 typically developing adolescents matched for age, handedness, and nonverbal IQ. Statistical parametric maps testing the degree of whole-brain functional connectivity and social functioning measures. Relative to typically developing controls, participants with ASD showed a mixed pattern of both over- and underconnectivity in the ToM network, which was associated with greater social impairment. Increased connectivity in the ASD group was detected primarily between the regions of the MNS and ToM, and was correlated with sociocommunicative measures, suggesting that excessive ToM-MNS cross talk might be associated with social impairment. In a secondary analysis comparing a subset of the 15 participants with ASD with the most severe symptomology and a tightly matched subset of 15 typically developing controls, participants with ASD showed exclusive overconnectivity effects in both ToM and MNS networks, which were also associated with greater social dysfunction. Adolescents with ASD showed atypically increased functional connectivity involving the mentalizing and mirror neuron systems, largely reflecting greater cross talk between the 2. This finding is consistent with emerging evidence of reduced network segregation in ASD and challenges the prevailing theory of general long-distance underconnectivity in ASD. This excess ToM-MNS connectivity may reflect immature or aberrant developmental processes in 2 brain networks involved in understanding of others, a domain of impairment in ASD. Further, robust links with sociocommunicative symptoms of ASD implicate atypically increased ToM-MNS connectivity in social deficits observed in ASD.

Dynamic functional connectivity reveals altered variability in functional connectivity among patients with major depressive disorder.

PubMed

Demirtaş, Murat; Tornador, Cristian; Falcón, Carles; López-Solà, Marina; Hernández-Ribas, Rosa; Pujol, Jesús; Menchón, José M; Ritter, Petra; Cardoner, Narcis; Soriano-Mas, Carles; Deco, Gustavo

2016-08-01

Resting-state fMRI (RS-fMRI) has become a useful tool to investigate the connectivity structure of mental health disorders. In the case of major depressive disorder (MDD), recent studies regarding the RS-fMRI have found abnormal connectivity in several regions of the brain, particularly in the default mode network (DMN). Thus, the relevance of the DMN to self-referential thoughts and ruminations has made the use of the resting-state approach particularly important for MDD. The majority of such research has relied on the grand averaged functional connectivity measures based on the temporal correlations between the BOLD time series of various brain regions. We, in our study, investigated the variations in the functional connectivity over time at global and local level using RS-fMRI BOLD time series of 27 MDD patients and 27 healthy control subjects. We found that global synchronization and temporal stability were significantly increased in the MDD patients. Furthermore, the participants with MDD showed significantly increased overall average (static) functional connectivity (sFC) but decreased variability of functional connectivity (vFC) within specific networks. Static FC increased to predominance among the regions pertaining to the default mode network (DMN), while the decreased variability of FC was observed in the connections between the DMN and the frontoparietal network. Hum Brain Mapp 37:2918-2930, 2016. © 2016 Wiley Periodicals, Inc. © 2016 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

Improved Diagnostic Accuracy of Alzheimer's Disease by Combining Regional Cortical Thickness and Default Mode Network Functional Connectivity: Validated in the Alzheimer's Disease Neuroimaging Initiative Set.

PubMed

Park, Ji Eun; Park, Bumwoo; Kim, Sang Joon; Kim, Ho Sung; Choi, Choong Gon; Jung, Seung Chai; Oh, Joo Young; Lee, Jae-Hong; Roh, Jee Hoon; Shim, Woo Hyun

2017-01-01

To identify potential imaging biomarkers of Alzheimer's disease by combining brain cortical thickness (CThk) and functional connectivity and to validate this model's diagnostic accuracy in a validation set. Data from 98 subjects was retrospectively reviewed, including a study set (n = 63) and a validation set from the Alzheimer's Disease Neuroimaging Initiative (n = 35). From each subject, data for CThk and functional connectivity of the default mode network was extracted from structural T1-weighted and resting-state functional magnetic resonance imaging. Cortical regions with significant differences between patients and healthy controls in the correlation of CThk and functional connectivity were identified in the study set. The diagnostic accuracy of functional connectivity measures combined with CThk in the identified regions was evaluated against that in the medial temporal lobes using the validation set and application of a support vector machine. Group-wise differences in the correlation of CThk and default mode network functional connectivity were identified in the superior temporal ( p < 0.001) and supramarginal gyrus ( p = 0.007) of the left cerebral hemisphere. Default mode network functional connectivity combined with the CThk of those two regions were more accurate than that combined with the CThk of both medial temporal lobes (91.7% vs. 75%). Combining functional information with CThk of the superior temporal and supramarginal gyri in the left cerebral hemisphere improves diagnostic accuracy, making it a potential imaging biomarker for Alzheimer's disease.

Phenotypic Variability in Resting-State Functional Connectivity: Current Status

PubMed Central

Gordon, Evan M.

2013-01-01

Abstract We reviewed the extant literature with the goal of assessing the extent to which resting-state functional connectivity is associated with phenotypic variability in healthy and disordered populations. A large corpus of work has accumulated to date (125 studies), supporting the association between intrinsic functional connectivity and individual differences in a wide range of domains—not only in cognitive, perceptual, motoric, and linguistic performance, but also in behavioral traits (e.g., impulsiveness, risky decision making, personality, and empathy) and states (e.g., anxiety and psychiatric symptoms) that are distinguished by cognitive and affective functioning, and in neurological conditions with cognitive and motor sequelae. Further, intrinsic functional connectivity is sensitive to remote (e.g., early-life stress) and enduring (e.g., duration of symptoms) life experience, and it exhibits plasticity in response to recent experience (e.g., learning and adaptation) and pharmacological treatment. The most pervasive associations were observed with the default network; associations were also widespread between the cingulo-opercular network and both cognitive and affective behaviors, while the frontoparietal network was associated primarily with cognitive functions. Associations of somatomotor, frontotemporal, auditory, and amygdala networks were relatively restricted to the behaviors linked to their respective putative functions. Surprisingly, visual network associations went beyond visual function to include a variety of behavioral traits distinguished by affective function. Together, the reviewed evidence sets the stage for testing causal hypothesis about the functional role of intrinsic connectivity and augments its potential as a biomarker for healthy and disordered brain function. PMID:23294010

Altered functional and effective connectivity in anticorrelated intrinsic networks in children with benign childhood epilepsy with centrotemporal spikes.

PubMed

Luo, Cheng; Yang, Fei; Deng, Jiayan; Zhang, Yaodan; Hou, Changyue; Huang, Yue; Cao, Weifang; Wang, Jianjun; Xiao, Ruhui; Zeng, Nanlin; Wang, Xiaoming; Yao, Dezhong

2016-06-01

There are 2 intrinsic networks in the human brain: the task positive network (TPN) and task negative network (alternately termed the default mode network, DMN) in which inverse correlations have been observed during resting state and event-related functional magnetic resonance imaging (fMRI). The antagonism between the 2 networks might indicate a dynamic interaction in the brain that is associated with development.To evaluate the alterations in the relations of the 2 networks in children with benign childhood epilepsy with centrotemporal spikes (BECTS), resting state fMRI was performed in 17 patients with BECTS and 17 healthy controls. The functional and effective connectivities of 29 nodes in the TPN and DMN were analyzed. Positive functional connectivity (FC) within the networks and negative FC between the 2 networks were observed in both groups.The patients exhibited increased FC within both networks, particularly in the frontoparietal nodes such as the left superior frontal cortex, and enhanced antagonism between the 2 networks, suggesting abnormal functional integration of the nodes of the 2 networks in the patients. Granger causality analysis revealed a significant difference in the degree of outflow to inflow in the left superior frontal cortex and the left ventral occipital lobe.The alterations observed in the combined functional and effective connectivity analyses might indicate an association of an abnormal ability to integrate information between the DMN and TPN and the epileptic neuropathology of BECTS and provide preliminary evidence supporting the occurrence of abnormal development in children with BECTS.

Mapping higher-order relations between brain structure and function with embedded vector representations of connectomes.

PubMed

Rosenthal, Gideon; Váša, František; Griffa, Alessandra; Hagmann, Patric; Amico, Enrico; Goñi, Joaquín; Avidan, Galia; Sporns, Olaf

2018-06-05

Connectomics generates comprehensive maps of brain networks, represented as nodes and their pairwise connections. The functional roles of nodes are defined by their direct and indirect connectivity with the rest of the network. However, the network context is not directly accessible at the level of individual nodes. Similar problems in language processing have been addressed with algorithms such as word2vec that create embeddings of words and their relations in a meaningful low-dimensional vector space. Here we apply this approach to create embedded vector representations of brain networks or connectome embeddings (CE). CE can characterize correspondence relations among brain regions, and can be used to infer links that are lacking from the original structural diffusion imaging, e.g., inter-hemispheric homotopic connections. Moreover, we construct predictive deep models of functional and structural connectivity, and simulate network-wide lesion effects using the face processing system as our application domain. We suggest that CE offers a novel approach to revealing relations between connectome structure and function.

Decomposition of metabolic network into functional modules based on the global connectivity structure of reaction graph.

PubMed

Ma, Hong-Wu; Zhao, Xue-Ming; Yuan, Ying-Jin; Zeng, An-Ping

2004-08-12

Metabolic networks are organized in a modular, hierarchical manner. Methods for a rational decomposition of the metabolic network into relatively independent functional subsets are essential to better understand the modularity and organization principle of a large-scale, genome-wide network. Network decomposition is also necessary for functional analysis of metabolism by pathway analysis methods that are often hampered by the problem of combinatorial explosion due to the complexity of metabolic network. Decomposition methods proposed in literature are mainly based on the connection degree of metabolites. To obtain a more reasonable decomposition, the global connectivity structure of metabolic networks should be taken into account. In this work, we use a reaction graph representation of a metabolic network for the identification of its global connectivity structure and for decomposition. A bow-tie connectivity structure similar to that previously discovered for metabolite graph is found also to exist in the reaction graph. Based on this bow-tie structure, a new decomposition method is proposed, which uses a distance definition derived from the path length between two reactions. An hierarchical classification tree is first constructed from the distance matrix among the reactions in the giant strong component of the bow-tie structure. These reactions are then grouped into different subsets based on the hierarchical tree. Reactions in the IN and OUT subsets of the bow-tie structure are subsequently placed in the corresponding subsets according to a 'majority rule'. Compared with the decomposition methods proposed in literature, ours is based on combined properties of the global network structure and local reaction connectivity rather than, primarily, on the connection degree of metabolites. The method is applied to decompose the metabolic network of Escherichia coli. Eleven subsets are obtained. More detailed investigations of the subsets show that reactions in the same subset are really functionally related. The rational decomposition of metabolic networks, and subsequent studies of the subsets, make it more amenable to understand the inherent organization and functionality of metabolic networks at the modular level. http://genome.gbf.de/bioinformatics/

Fetal functional imaging portrays heterogeneous development of emerging human brain networks

PubMed Central

Jakab, András; Schwartz, Ernst; Kasprian, Gregor; Gruber, Gerlinde M.; Prayer, Daniela; Schöpf, Veronika; Langs, Georg

2014-01-01

The functional connectivity architecture of the adult human brain enables complex cognitive processes, and exhibits a remarkably complex structure shared across individuals. We are only beginning to understand its heterogeneous structure, ranging from a strongly hierarchical organization in sensorimotor areas to widely distributed networks in areas such as the parieto-frontal cortex. Our study relied on the functional magnetic resonance imaging (fMRI) data of 32 fetuses with no detectable morphological abnormalities. After adapting functional magnetic resonance acquisition, motion correction, and nuisance signal reduction procedures of resting-state functional data analysis to fetuses, we extracted neural activity information for major cortical and subcortical structures. Resting fMRI networks were observed for increasing regional functional connectivity from 21st to 38th gestational weeks (GWs) with a network-based statistical inference approach. The overall connectivity network, short range, and interhemispheric connections showed sigmoid expansion curve peaking at the 26–29 GW. In contrast, long-range connections exhibited linear increase with no periods of peaking development. Region-specific increase of functional signal synchrony followed a sequence of occipital (peak: 24.8 GW), temporal (peak: 26 GW), frontal (peak: 26.4 GW), and parietal expansion (peak: 27.5 GW). We successfully adapted functional neuroimaging and image post-processing approaches to correlate macroscopical scale activations in the fetal brain with gestational age. This in vivo study reflects the fact that the mid-fetal period hosts events that cause the architecture of the brain circuitry to mature, which presumably manifests in increasing strength of intra- and interhemispheric functional macro connectivity. PMID:25374531

Fetal functional imaging portrays heterogeneous development of emerging human brain networks.

PubMed

Jakab, András; Schwartz, Ernst; Kasprian, Gregor; Gruber, Gerlinde M; Prayer, Daniela; Schöpf, Veronika; Langs, Georg

2014-01-01

The functional connectivity architecture of the adult human brain enables complex cognitive processes, and exhibits a remarkably complex structure shared across individuals. We are only beginning to understand its heterogeneous structure, ranging from a strongly hierarchical organization in sensorimotor areas to widely distributed networks in areas such as the parieto-frontal cortex. Our study relied on the functional magnetic resonance imaging (fMRI) data of 32 fetuses with no detectable morphological abnormalities. After adapting functional magnetic resonance acquisition, motion correction, and nuisance signal reduction procedures of resting-state functional data analysis to fetuses, we extracted neural activity information for major cortical and subcortical structures. Resting fMRI networks were observed for increasing regional functional connectivity from 21st to 38th gestational weeks (GWs) with a network-based statistical inference approach. The overall connectivity network, short range, and interhemispheric connections showed sigmoid expansion curve peaking at the 26-29 GW. In contrast, long-range connections exhibited linear increase with no periods of peaking development. Region-specific increase of functional signal synchrony followed a sequence of occipital (peak: 24.8 GW), temporal (peak: 26 GW), frontal (peak: 26.4 GW), and parietal expansion (peak: 27.5 GW). We successfully adapted functional neuroimaging and image post-processing approaches to correlate macroscopical scale activations in the fetal brain with gestational age. This in vivo study reflects the fact that the mid-fetal period hosts events that cause the architecture of the brain circuitry to mature, which presumably manifests in increasing strength of intra- and interhemispheric functional macro connectivity.

Cognitive performance in mid-stage Parkinson's disease: functional connectivity under chronic antiparkinson treatment.

PubMed

Vancea, Roxana; Simonyan, Kristina; Petracca, Maria; Brys, Miroslaw; Di Rocco, Alessandro; Ghilardi, Maria Felice; Inglese, Matilde

2017-09-23

Cognitive impairment in Parkinson's disease (PD) is related to the reorganization of brain topology. Although drug challenge studies have proven how levodopa treatment can modulate functional connectivity in brain circuits, the role of chronic dopaminergic therapy on cognitive status and functional connectivity has never been investigated. We sought to characterize brain functional topology in mid-stage PD patients under chronic antiparkinson treatment and explore the presence of correlation between reorganization of brain architecture and specific cognitive deficits. We explored networks topology and functional connectivity in 16 patients with PD and 16 matched controls through a graph theoretical analysis of resting state-functional MRI data, and evaluated the relationships between network metrics and cognitive performance. PD patients showed a preserved small-world network topology but a lower clustering coefficient in comparison with healthy controls. Locally, PD patients showed lower degree of connectivity and local efficiency in many hubs corresponding to functionally relevant areas. Four disconnected subnetworks were also identified in regions responsible for executive control, sensory-motor control and planning, motor coordination and visual elaboration. Executive functions and information processing speed were directly correlated with degree of connectivity and local efficiency in frontal, parietal and occipital areas. While functional reorganization appears in both motor and cognitive areas, the clinical expression of network imbalance seems to be partially compensated by the chronic levodopa treatment with regards to the motor but not to the cognitive performance. In a context of reduced network segregation, the presence of higher local efficiency in hubs regions correlates with a better cognitive performance.

Causal effect of disconnection lesions on interhemispheric functional connectivity in rhesus monkeys

PubMed Central

O’Reilly, Jill X.; Croxson, Paula L.; Jbabdi, Saad; Sallet, Jerome; Noonan, MaryAnn P.; Mars, Rogier B.; Browning, Philip G.F.; Wilson, Charles R. E.; Mitchell, Anna S.; Miller, Karla L.; Rushworth, Matthew F. S.; Baxter, Mark G.

2013-01-01

In the absence of external stimuli or task demands, correlations in spontaneous brain activity (functional connectivity) reflect patterns of anatomical connectivity. Hence, resting-state functional connectivity has been used as a proxy measure for structural connectivity and as a biomarker for brain changes in disease. To relate changes in functional connectivity to physiological changes in the brain, it is important to understand how correlations in functional connectivity depend on the physical integrity of brain tissue. The causal nature of this relationship has been called into question by patient data suggesting that decreased structural connectivity does not necessarily lead to decreased functional connectivity. Here we provide evidence for a causal but complex relationship between structural connectivity and functional connectivity: we tested interhemispheric functional connectivity before and after corpus callosum section in rhesus monkeys. We found that forebrain commissurotomy severely reduced interhemispheric functional connectivity, but surprisingly, this effect was greatly mitigated if the anterior commissure was left intact. Furthermore, intact structural connections increased their functional connectivity in line with the hypothesis that the inputs to each node are normalized. We conclude that functional connectivity is likely driven by corticocortical white matter connections but with complex network interactions such that a near-normal pattern of functional connectivity can be maintained by just a few indirect structural connections. These surprising results highlight the importance of network-level interactions in functional connectivity and may cast light on various paradoxical findings concerning changes in functional connectivity in disease states. PMID:23924609

Network organization is globally atypical in autism: A graph theory study of intrinsic functional connectivity.

PubMed

Keown, Christopher L; Datko, Michael C; Chen, Colleen P; Maximo, José Omar; Jahedi, Afrooz; Müller, Ralph-Axel

2017-01-01

Despite abundant evidence of brain network anomalies in autism spectrum disorder (ASD), findings have varied from broad functional underconnectivity to broad overconnectivity. Rather than pursuing overly simplifying general hypotheses ('under' vs. 'over'), we tested the hypothesis of atypical network distribution in ASD (i.e., participation of unusual loci in distributed functional networks). We used a selective high-quality data subset from the ABIDE datashare (including 111 ASD and 174 typically developing [TD] participants) and several graph theory metrics. Resting state functional MRI data were preprocessed and analyzed for detection of low-frequency intrinsic signal correlations. Groups were tightly matched for available demographics and head motion. As hypothesized, the Rand Index (reflecting how similar network organization was to a normative set of networks) was significantly lower in ASD than TD participants. This was accounted for by globally reduced cohesion and density, but increased dispersion of networks. While differences in hub architecture did not survive correction, rich club connectivity (among the hubs) was increased in the ASD group. Our findings support the model of reduced network integration (connectivity with networks) and differentiation (or segregation; based on connectivity outside network boundaries) in ASD. While the findings applied at the global level, they were not equally robust across all networks and in one case (greater cohesion within ventral attention network in ASD) even reversed.

Mapping the changed hubs and corresponding functional connectivity in idiopathic restless legs syndrome.

PubMed

Liu, Chunyan; Wang, Jiaojian; Hou, Yue; Qi, Zhigang; Wang, Li; Zhan, Shuqin; Wang, Rong; Wang, Yuping

2018-05-01

The hubs of the brain network play a key role in integrating and transferring information between different functional modules. However, whether the changed pattern in functional network hubs contributes to the onset of leg discomfort symptoms in restless legs syndrome (RLS) patients remains unclear. Using resting-state functional magnetic resonance imaging (rs-fMRI) and graph theory methods, we investigated whether alterations of hubs can be detected in RLS. First, we constructed the whole-brain voxelwise functional connectivity and calculated a functional connectivity strength (FCS) map in each of 16 drug-naive idiopathic RLS patients and 26 gender- and age-matched healthy control (HC) subjects. Next, a two-sample t test was applied to compare the FCS maps between HC and RLS patients, and to identify significant changes in FCS in RLS patients. To further elucidate the corresponding changes in the functional connectivity patterns of the aberrant hubs in RLS patients, whole-brain resting-state functional connectivity analyses for the hub areas were performed. The hub analysis revealed decreased FCS in the cuneus, fusiform gyrus, paracentral lobe, and precuneus, and increased FCS in the superior frontal gyrus and thalamus in idiopathic drug-naive RLS patients. Subsequent functional connectivity analyses revealed decreased functional connectivity in sensorimotor and visual processing networks and increased functional connectivity in the affective cognitive network and cerebellar-thalamic circuit. Furthermore, the mean FCS value in the superior frontal gyrus was significantly correlated with Hamilton Anxiety Rating Scale scores in RLS patients, and the mean FCS value in the fusiform gyrus was significantly correlated with Hamilton Depression Rating Scale scores. These findings may provide novel insight into the pathophysiology of RLS. Copyright © 2018 Elsevier B.V. All rights reserved.

Constructing fMRI connectivity networks: a whole brain functional parcellation method for node definition.

PubMed

Maggioni, Eleonora; Tana, Maria Gabriella; Arrigoni, Filippo; Zucca, Claudio; Bianchi, Anna Maria

2014-05-15

Functional Magnetic Resonance Imaging (fMRI) is used for exploring brain functionality, and recently it was applied for mapping the brain connection patterns. To give a meaningful neurobiological interpretation to the connectivity network, it is fundamental to properly define the network framework. In particular, the choice of the network nodes may affect the final connectivity results and the consequent interpretation. We introduce a novel method for the intra subject topological characterization of the nodes of fMRI brain networks, based on a whole brain parcellation scheme. The proposed whole brain parcellation algorithm divides the brain into clusters that are homogeneous from the anatomical and functional point of view, each of which constitutes a node. The functional parcellation described is based on the Tononi's cluster index, which measures instantaneous correlation in terms of intrinsic and extrinsic statistical dependencies. The method performance and reliability were first tested on simulated data, then on a real fMRI dataset acquired on healthy subjects during visual stimulation. Finally, the proposed algorithm was applied to epileptic patients' fMRI data recorded during seizures, to verify its usefulness as preparatory step for effective connectivity analysis. For each patient, the nodes of the network involved in ictal activity were defined according to the proposed parcellation scheme and Granger Causality Analysis (GCA) was applied to infer effective connectivity. We showed that the algorithm 1) performed well on simulated data, 2) was able to produce reliable inter subjects results and 3) led to a detailed definition of the effective connectivity pattern. Copyright © 2014 Elsevier B.V. All rights reserved.

Combined Functional and Causal Connectivity Analyses of Language Networks in Children: A Feasibility Study

ERIC Educational Resources Information Center

Wilke, Marko; Lidzba, Karen; Krageloh-Mann, Ingeborg

2009-01-01

Instead of assessing activation in distinct brain regions, approaches to investigating the networks underlying distinct brain functions have come into the focus of neuroscience research. Here, we provide a completely data-driven framework for assessing functional and causal connectivity in functional magnetic resonance imaging (fMRI) data,…

Relationships between cortical myeloarchitecture and electrophysiological networks

PubMed Central

Hunt, Benjamin A. E.; Tewarie, Prejaas K.; Mougin, Olivier E.; Geades, Nicolas; Singh, Krish D.; Morris, Peter G.; Gowland, Penny A.; Brookes, Matthew J.

2016-01-01

The human brain relies upon the dynamic formation and dissolution of a hierarchy of functional networks to support ongoing cognition. However, how functional connectivities underlying such networks are supported by cortical microstructure remains poorly understood. Recent animal work has demonstrated that electrical activity promotes myelination. Inspired by this, we test a hypothesis that gray-matter myelin is related to electrophysiological connectivity. Using ultra-high field MRI and the principle of structural covariance, we derive a structural network showing how myelin density differs across cortical regions and how separate regions can exhibit similar myeloarchitecture. Building upon recent evidence that neural oscillations mediate connectivity, we use magnetoencephalography to elucidate networks that represent the major electrophysiological pathways of communication in the brain. Finally, we show that a significant relationship exists between our functional and structural networks; this relationship differs as a function of neural oscillatory frequency and becomes stronger when integrating oscillations over frequency bands. Our study sheds light on the way in which cortical microstructure supports functional networks. Further, it paves the way for future investigations of the gray-matter structure/function relationship and its breakdown in pathology. PMID:27830650

Resting state brain networks and their implications in neurodegenerative disease

NASA Astrophysics Data System (ADS)

Sohn, William S.; Yoo, Kwangsun; Kim, Jinho; Jeong, Yong

2012-10-01

Neurons are the basic units of the brain, and form network by connecting via synapses. So far, there have been limited ways to measure the brain networks. Recently, various imaging modalities are widely used for this purpose. In this paper, brain network mapping using resting state fMRI will be introduced with several applications including neurodegenerative disease such as Alzheimer's disease, frontotemporal lobar degeneration and Parkinson's disease. The resting functional connectivity using intrinsic functional connectivity in mouse is useful since we can take advantage of perturbation or stimulation of certain nodes of the network. The study of brain connectivity will open a new era in understanding of brain and diseases thus will be an essential foundation for future research.

Brain Functional Connectivity in Small Cell Lung Cancer Population after Chemotherapy Treatment: an ICA fMRI Study

NASA Astrophysics Data System (ADS)

Bromis, K.; Kakkos, I.; Gkiatis, K.; Karanasiou, I. S.; Matsopoulos, G. K.

2017-11-01

Previous neurocognitive assessments in Small Cell Lung Cancer (SCLC) population, highlight the presence of neurocognitive impairments (mainly in attention processing and executive functioning) in this type of cancer. The majority of these studies, associate these deficits with the Prophylactic Cranial Irradiation (PCI) that patients undergo in order to avoid brain metastasis. However, there is not much evidence exploring cognitive impairments induced by chemotherapy in SCLC patients. For this reason, we aimed to investigate the underlying processes that may potentially affect cognition by examining brain functional connectivity in nineteen SCLC patients after chemotherapy treatment, while additionally including fourteen healthy participants as control group. Independent Component Analysis (ICA) is a functional connectivity measure aiming to unravel the temporal correlation between brain regions, which are called brain networks. We focused on two brain networks related to the aforementioned cognitive functions, the Default Mode Network (DMN) and the Task-Positive Network (TPN). Permutation tests were performed between the two groups to assess the differences and control for familywise errors in the statistical parametric maps. ICA analysis showed functional connectivity disruptions within both of the investigated networks. These results, propose a detrimental effect of chemotherapy on brain functioning in the SCLC population.

Complex networks of functional connectivity in a wetland reconnected to its floodplain

USGS Publications Warehouse

Larsen, Laurel G.; Newman, Susan; Saunders, Colin; Harvey, Judson

2017-01-01

Disturbances such as fire or flood, in addition to changing the local magnitude of ecological, hydrological, or biogeochemical processes, can also change their functional connectivity—how those processes interact in space. Complex networks offer promise for quantifying functional connectivity in watersheds. The approach resolves connections between nodes in space based on statistical similarities in perturbation signals (derived from solute time series) and is sensitive to a wider range of timescales than traditional mass-balance modeling. We use this approach to test hypotheses about how fire and flood impact ecological and biogeochemical dynamics in a wetland (Everglades, FL, USA) that was reconnected to its floodplain. Reintroduction of flow pulses after decades of separation by levees fundamentally reconfigured functional connectivity networks. The most pronounced expansion was that of the calcium network, which reflects periphyton dynamics and may represent an indirect influence of elevated nutrients, despite the comparatively smaller observed expansion of phosphorus networks. With respect to several solutes, periphyton acted as a “biotic filter,” shifting perturbations in water-quality signals to different timescales through slow but persistent transformations of the biotic community. The complex-networks approach also revealed portions of the landscape that operate in fundamentally different regimes with respect to dissolved oxygen, separated by a threshold in flow velocity of 1.2 cm/s, and suggested that complete removal of canals may be needed to restore connectivity with respect to biogeochemical processes. Fire reconfigured functional connectivity networks in a manner that reflected localized burn severity, but had a larger effect on the magnitude of solute concentrations.

Complex networks of functional connectivity in a wetland reconnected to its floodplain

NASA Astrophysics Data System (ADS)

Larsen, Laurel G.; Newman, Susan; Saunders, Colin; Harvey, Judson W.

2017-07-01

Disturbances such as fire or flood, in addition to changing the local magnitude of ecological, hydrological, or biogeochemical processes, can also change their functional connectivity—how those processes interact in space. Complex networks offer promise for quantifying functional connectivity in watersheds. The approach resolves connections between nodes in space based on statistical similarities in perturbation signals (derived from solute time series) and is sensitive to a wider range of timescales than traditional mass-balance modeling. We use this approach to test hypotheses about how fire and flood impact ecological and biogeochemical dynamics in a wetland (Everglades, FL, USA) that was reconnected to its floodplain. Reintroduction of flow pulses after decades of separation by levees fundamentally reconfigured functional connectivity networks. The most pronounced expansion was that of the calcium network, which reflects periphyton dynamics and may represent an indirect influence of elevated nutrients, despite the comparatively smaller observed expansion of phosphorus networks. With respect to several solutes, periphyton acted as a "biotic filter," shifting perturbations in water-quality signals to different timescales through slow but persistent transformations of the biotic community. The complex-networks approach also revealed portions of the landscape that operate in fundamentally different regimes with respect to dissolved oxygen, separated by a threshold in flow velocity of 1.2 cm/s, and suggested that complete removal of canals may be needed to restore connectivity with respect to biogeochemical processes. Fire reconfigured functional connectivity networks in a manner that reflected localized burn severity, but had a larger effect on the magnitude of solute concentrations.

Frontal networks associated with command following after hemorrhagic stroke.

PubMed

Mikell, Charles B; Banks, Garrett P; Frey, Hans-Peter; Youngerman, Brett E; Nelp, Taylor B; Karas, Patrick J; Chan, Andrew K; Voss, Henning U; Connolly, E Sander; Claassen, Jan

2015-01-01

Level of consciousness is frequently assessed by command-following ability in the clinical setting. However, it is unclear what brain circuits are needed to follow commands. We sought to determine what networks differentiate command following from noncommand following patients after hemorrhagic stroke. Structural MRI, resting-state functional MRI, and electroencephalography were performed on 25 awake and unresponsive patients with acute intracerebral and subarachnoid hemorrhage. Structural injury was assessed via volumetric T1-weighted MRI analysis. Functional connectivity differences were analyzed against a template of standard resting-state networks. The default mode network (DMN) and the task-positive network were investigated using seed-based functional connectivity. Networks were interrogated by pairwise coherence of electroencephalograph leads in regions of interest defined by functional MRI. Functional imaging of unresponsive patients identified significant differences in 6 of 16 standard resting-state networks. Significant voxels were found in premotor cortex, dorsal anterior cingulate gyrus, and supplementary motor area. Direct interrogation of the DMN and task-positive network revealed loss of connectivity between the DMN and the orbitofrontal cortex and new connections between the task-positive network and DMN. Coherence between electrodes corresponding to right executive network and visual networks was also decreased in unresponsive patients. Resting-state functional MRI and electroencephalography coherence data support a model in which multiple, chiefly frontal networks are required for command following. Loss of DMN anticorrelation with task-positive network may reflect a loss of inhibitory control of the DMN by motor-executive regions. Frontal networks should thus be a target for future investigations into the mechanism of responsiveness in the intensive care unit environment. © 2014 American Heart Association, Inc.

Functional brain networks in schizophrenia: a review.

PubMed

Calhoun, Vince D; Eichele, Tom; Pearlson, Godfrey

2009-01-01

Functional magnetic resonance imaging (fMRI) has become a major technique for studying cognitive function and its disruption in mental illness, including schizophrenia. The major proportion of imaging studies focused primarily upon identifying regions which hemodynamic response amplitudes covary with particular stimuli and differentiate between patient and control groups. In addition to such amplitude based comparisons, one can estimate temporal correlations and compute maps of functional connectivity between regions which include the variance associated with event-related responses as well as intrinsic fluctuations of hemodynamic activity. Functional connectivity maps can be computed by correlating all voxels with a seed region when a spatial prior is available. An alternative are multivariate decompositions such as independent component analysis (ICA) which extract multiple components, each of which is a spatially distinct map of voxels with a common time course. Recent work has shown that these networks are pervasive in relaxed resting and during task performance and hence provide robust measures of intact and disturbed brain activity. This in turn bears the prospect of yielding biomarkers for schizophrenia, which can be described both in terms of disrupted local processing as well as altered global connectivity between large-scale networks. In this review we will summarize functional connectivity measures with a focus upon work with ICA and discuss the meaning of intrinsic fluctuations. In addition, examples of how brain networks have been used for classification of disease will be shown. We present work with functional network connectivity, an approach that enables the evaluation of the interplay between multiple networks and how they are affected in disease. We conclude by discussing new variants of ICA for extracting maximally group discriminative networks from data. In summary, it is clear that identification of brain networks and their inter-relationships with fMRI has great potential to improve our understanding of schizophrenia.

Connectivity patterns in cognitive control networks predict naturalistic multitasking ability.

PubMed

Wen, Tanya; Liu, De-Cyuan; Hsieh, Shulan

2018-06-01

Multitasking is a fundamental aspect of everyday life activities. To achieve a complex, multi-component goal, the tasks must be subdivided into sub-tasks and component steps, a critical function of prefrontal networks. The prefrontal cortex is considered to be organized in a cascade of executive processes from the sensorimotor to anterior prefrontal cortex, which includes execution of specific goal-directed action, to encoding and maintaining task rules, and finally monitoring distal goals. In the current study, we used a virtual multitasking paradigm to tap into real-world performance and relate it to each individual's resting-state functional connectivity in fMRI. While did not find any correlation between global connectivity of any of the major networks with multitasking ability, global connectivity of the lateral prefrontal cortex (LPFC) was predictive of multitasking ability. Further analysis showed that multivariate connectivity patterns within the sensorimotor network (SMN), and between-network connectivity of the frontoparietal network (FPN) and dorsal attention network (DAN), predicted individual multitasking ability and could be generalized to novel individuals. Together, these results support previous research that prefrontal networks underlie multitasking abilities and show that connectivity patterns in the cascade of prefrontal networks may explain individual differences in performance. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

Violence-related content in video game may lead to functional connectivity changes in brain networks as revealed by fMRI-ICA in young men.

PubMed

Zvyagintsev, M; Klasen, M; Weber, R; Sarkheil, P; Esposito, F; Mathiak, K A; Schwenzer, M; Mathiak, K

2016-04-21

In violent video games, players engage in virtual aggressive behaviors. Exposure to virtual aggressive behavior induces short-term changes in players' behavior. In a previous study, a violence-related version of the racing game "Carmageddon TDR2000" increased aggressive affects, cognitions, and behaviors compared to its non-violence-related version. This study investigates the differences in neural network activity during the playing of both versions of the video game. Functional magnetic resonance imaging (fMRI) recorded ongoing brain activity of 18 young men playing the violence-related and the non-violence-related version of the video game Carmageddon. Image time series were decomposed into functional connectivity (FC) patterns using independent component analysis (ICA) and template-matching yielded a mapping to established functional brain networks. The FC patterns revealed a decrease in connectivity within 6 brain networks during the violence-related compared to the non-violence-related condition: three sensory-motor networks, the reward network, the default mode network (DMN), and the right-lateralized frontoparietal network. Playing violent racing games may change functional brain connectivity, in particular and even after controlling for event frequency, in the reward network and the DMN. These changes may underlie the short-term increase of aggressive affects, cognitions, and behaviors as observed after playing violent video games. Copyright © 2016 IBRO. Published by Elsevier Ltd. All rights reserved.

Dedifferentiation Does Not Account for Hyperconnectivity after Traumatic Brain Injury.

PubMed

Bernier, Rachel Anne; Roy, Arnab; Venkatesan, Umesh Meyyappan; Grossner, Emily C; Brenner, Einat K; Hillary, Frank Gerard

2017-01-01

Changes in functional network connectivity following traumatic brain injury (TBI) have received increasing attention in recent neuroimaging literature. This study sought to understand how disrupted systems adapt to injury during resting and goal-directed brain states. Hyperconnectivity has been a common finding, and dedifferentiation (or loss of segregation of networks) is one possible explanation for this finding. We hypothesized that individuals with TBI would show dedifferentiation of networks (as noted in other clinical populations) and these effects would be associated with cognitive dysfunction. Graph theory was implemented to examine functional connectivity during periods of task and rest in 19 individuals with moderate/severe TBI and 14 healthy controls (HCs). Using a functional brain atlas derived from 83 functional imaging studies, graph theory was used to examine network dynamics and determine whether dedifferentiation accounts for changes in connectivity. Regions of interest were assigned to one of three groups: task-positive, default mode, or other networks. Relationships between these metrics were then compared with performance on neuropsychological tests. Hyperconnectivity in TBI was most commonly observed as increased within-network connectivity. Network strengths within networks that showed differences between TBI and HCs were correlated with performance on five neuropsychological tests typically sensitive to deficits commonly reported in TBI. Hyperconnectivity within the default mode network (DMN) during task was associated with better performance on Digit Span Backward, a measure of working memory [ R 2 (18) = 0.28, p  = 0.02]. In other words, increased differentiation of networks during task was associated with better working memory. Hyperconnectivity within the task-positive network during rest was not associated with behavior. Negative correlation weights were not associated with behavior. The primary hypothesis that hyperconnectivity occurs through increased segregation of networks, rather than dedifferentiation, was not supported. Instead, enhanced connectivity post injury was observed within network. Results suggest that the relationship between increased connectivity and cognitive functioning may be both state (rest or task) and network dependent. High-cost network hubs were identical for both rest and task, and cost was negatively associated with performance on measures of psychomotor speed and set-shifting.

Selective Activation of Resting-State Networks following Focal Stimulation in a Connectome-Based Network Model of the Human Brain

PubMed Central

2016-01-01

Abstract When the brain is stimulated, for example, by sensory inputs or goal-oriented tasks, the brain initially responds with activities in specific areas. The subsequent pattern formation of functional networks is constrained by the structural connectivity (SC) of the brain. The extent to which information is processed over short- or long-range SC is unclear. Whole-brain models based on long-range axonal connections, for example, can partly describe measured functional connectivity dynamics at rest. Here, we study the effect of SC on the network response to stimulation. We use a human whole-brain network model comprising long- and short-range connections. We systematically activate each cortical or thalamic area, and investigate the network response as a function of its short- and long-range SC. We show that when the brain is operating at the edge of criticality, stimulation causes a cascade of network recruitments, collapsing onto a smaller space that is partly constrained by SC. We found both short- and long-range SC essential to reproduce experimental results. In particular, the stimulation of specific areas results in the activation of one or more resting-state networks. We suggest that the stimulus-induced brain activity, which may indicate information and cognitive processing, follows specific routes imposed by structural networks explaining the emergence of functional networks. We provide a lookup table linking stimulation targets and functional network activations, which potentially can be useful in diagnostics and treatments with brain stimulation. PMID:27752540

Developmental Reorganization of the Core and Extended Face Networks Revealed by Global Functional Connectivity.

PubMed

Wang, Xu; Zhu, Qi; Song, Yiying; Liu, Jia

2017-08-28

Prior studies on development of functional specialization in human brain mainly focus on age-related increases in regional activation and connectivity among regions. However, a few recent studies on the face network demonstrate age-related decrease in face-specialized activation in the extended face network (EFN), in addition to increase in activation in the core face network (CFN). Here we used a voxel-based global brain connectivity approach to investigate whether development of the face network exhibited both increase and decrease in network connectivity. We found the voxel-wise resting-state functional connectivity (FC) within the CFN increased with age in bilateral posterior superior temporal sulcus, suggesting the integration of the CFN during development. Interestingly, the FC of the voxels in the EFN to the right fusiform face area and occipital face area decreased with age, suggesting that the CFN segregated from the EFN during development. Moreover, the age-related connectivity in the CFN was related to behavioral performance in face processing. Overall, our study demonstrated developmental reorganization of the face network achieved by both integration within the CFN and segregation of the CFN from the EFN, which may account for the simultaneous increases and decreases in neural activation during the development of the face network. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Changes in Neural Connectivity and Memory Following a Yoga Intervention for Older Adults: A Pilot Study.

PubMed

Eyre, Harris A; Acevedo, Bianca; Yang, Hongyu; Siddarth, Prabha; Van Dyk, Kathleen; Ercoli, Linda; Leaver, Amber M; Cyr, Natalie St; Narr, Katherine; Baune, Bernhard T; Khalsa, Dharma S; Lavretsky, Helen

2016-01-01

No study has explored the effect of yoga on cognitive decline and resting-state functional connectivity. This study explored the relationship between performance on memory tests and resting-state functional connectivity before and after a yoga intervention versus active control for subjects with mild cognitive impairment (MCI). Participants ( ≥ 55 y) with MCI were randomized to receive a yoga intervention or active "gold-standard" control (i.e., memory enhancement training (MET)) for 12 weeks. Resting-state functional magnetic resonance imaging was used to map correlations between brain networks and memory performance changes over time. Default mode networks (DMN), language and superior parietal networks were chosen as networks of interest to analyze the association with changes in verbal and visuospatial memory performance. Fourteen yoga and 11 MET participants completed the study. The yoga group demonstrated a statistically significant improvement in depression and visuospatial memory. We observed improved verbal memory performance correlated with increased connectivity between the DMN and frontal medial cortex, pregenual anterior cingulate cortex, right middle frontal cortex, posterior cingulate cortex, and left lateral occipital cortex. Improved verbal memory performance positively correlated with increased connectivity between the language processing network and the left inferior frontal gyrus. Improved visuospatial memory performance correlated inversely with connectivity between the superior parietal network and the medial parietal cortex. Yoga may be as effective as MET in improving functional connectivity in relation to verbal memory performance. These findings should be confirmed in larger prospective studies.

Functional connectivity dynamics during film viewing reveal common networks for different emotional experiences.

PubMed

Raz, Gal; Touroutoglou, Alexandra; Wilson-Mendenhall, Christine; Gilam, Gadi; Lin, Tamar; Gonen, Tal; Jacob, Yael; Atzil, Shir; Admon, Roee; Bleich-Cohen, Maya; Maron-Katz, Adi; Hendler, Talma; Barrett, Lisa Feldman

2016-08-01

Recent theoretical and empirical work has highlighted the role of domain-general, large-scale brain networks in generating emotional experiences. These networks are hypothesized to process aspects of emotional experiences that are not unique to a specific emotional category (e.g., "sadness," "happiness"), but rather that generalize across categories. In this article, we examined the dynamic interactions (i.e., changing cohesiveness) between specific domain-general networks across time while participants experienced various instances of sadness, fear, and anger. We used a novel method for probing the network connectivity dynamics between two salience networks and three amygdala-based networks. We hypothesized, and found, that the functional connectivity between these networks covaried with the intensity of different emotional experiences. Stronger connectivity between the dorsal salience network and the medial amygdala network was associated with more intense ratings of emotional experience across six different instances of the three emotion categories examined. Also, stronger connectivity between the dorsal salience network and the ventrolateral amygdala network was associated with more intense ratings of emotional experience across five out of the six different instances. Our findings demonstrate that a variety of emotional experiences are associated with dynamic interactions of domain-general neural systems.

A tensorial approach to access cognitive workload related to mental arithmetic from EEG functional connectivity estimates.

PubMed

Dimitriadis, S I; Sun, Yu; Kwok, K; Laskaris, N A; Bezerianos, A

2013-01-01

The association of functional connectivity patterns with particular cognitive tasks has long been a topic of interest in neuroscience, e.g., studies of functional connectivity have demonstrated its potential use for decoding various brain states. However, the high-dimensionality of the pairwise functional connectivity limits its usefulness in some real-time applications. In the present study, the methodology of tensor subspace analysis (TSA) is used to reduce the initial high-dimensionality of the pairwise coupling in the original functional connectivity network to a space of condensed descriptive power, which would significantly decrease the computational cost and facilitate the differentiation of brain states. We assess the feasibility of the proposed method on EEG recordings when the subject was performing mental arithmetic task which differ only in the difficulty level (easy: 1-digit addition v.s. 3-digit additions). Two different cortical connective networks were detected, and by comparing the functional connectivity networks in different work states, it was found that the task-difficulty is best reflected in the connectivity structure of sub-graphs extending over parietooccipital sites. Incorporating this data-driven information within original TSA methodology, we succeeded in predicting the difficulty level from connectivity patterns in an efficient way that can be implemented so as to work in real-time.

Resting-state Network-specific Breakdown of Functional Connectivity during Ketamine Alteration of Consciousness in Volunteers.

PubMed

Bonhomme, Vincent; Vanhaudenhuyse, Audrey; Demertzi, Athena; Bruno, Marie-Aurélie; Jaquet, Oceane; Bahri, Mohamed Ali; Plenevaux, Alain; Boly, Melanie; Boveroux, Pierre; Soddu, Andrea; Brichant, Jean François; Maquet, Pierre; Laureys, Steven

2016-11-01

Consciousness-altering anesthetic agents disturb connectivity between brain regions composing the resting-state consciousness networks (RSNs). The default mode network (DMn), executive control network, salience network (SALn), auditory network, sensorimotor network (SMn), and visual network sustain mentation. Ketamine modifies consciousness differently from other agents, producing psychedelic dreaming and no apparent interaction with the environment. The authors used functional magnetic resonance imaging to explore ketamine-induced changes in RSNs connectivity. Fourteen healthy volunteers received stepwise intravenous infusions of ketamine up to loss of responsiveness. Because of agitation, data from six subjects were excluded from analysis. RSNs connectivity was compared between absence of ketamine (wake state [W1]), light ketamine sedation, and ketamine-induced unresponsiveness (deep sedation [S2]). Increasing the depth of ketamine sedation from W1 to S2 altered DMn and SALn connectivity and suppressed the anticorrelated activity between DMn and other brain regions. During S2, DMn connectivity, particularly between the medial prefrontal cortex and the remaining network (effect size β [95% CI]: W1 = 0.20 [0.18 to 0.22]; S2 = 0.07 [0.04 to 0.09]), and DMn anticorrelated activity (e.g., right sensory cortex: W1 = -0.07 [-0.09 to -0.04]; S2 = 0.04 [0.01 to 0.06]) were broken down. SALn connectivity was nonuniformly suppressed (e.g., left parietal operculum: W1 = 0.08 [0.06 to 0.09]; S2 = 0.05 [0.02 to 0.07]). Executive control networks, auditory network, SMn, and visual network were minimally affected. Ketamine induces specific changes in connectivity within and between RSNs. Breakdown of frontoparietal DMn connectivity and DMn anticorrelation and sensory and SMn connectivity preservation are common to ketamine and propofol-induced alterations of consciousness.

Differences in graph theory functional connectivity in left and right temporal lobe epilepsy.

PubMed

Chiang, Sharon; Stern, John M; Engel, Jerome; Levin, Harvey S; Haneef, Zulfi

2014-12-01

To investigate lateralized differences in limbic system functional connectivity between left and right temporal lobe epilepsy (TLE) using graph theory. Interictal resting state fMRI was performed in 14 left TLE patients, 11 right TLE patients, and 12 controls. Graph theory analysis of 10 bilateral limbic regions of interest was conducted. Changes in edgewise functional connectivity, network topology, and regional topology were quantified, and then left and right TLE were compared. Limbic edgewise functional connectivity was predominantly reduced in both left and right TLE. More regional connections were reduced in right TLE, most prominently involving reduced interhemispheric connectivity between the bilateral insula and bilateral hippocampi. A smaller number of limbic connections were increased in TLE, more so in left than in right TLE. Topologically, the most pronounced change was a reduction in average network betweenness centrality and concurrent increase in left hippocampal betweenness centrality in right TLE. In contrast, left TLE exhibited a weak trend toward increased right hippocampal betweenness centrality, with no change in average network betweenness centrality. Limbic functional connectivity is predominantly reduced in both left and right TLE, with more pronounced reductions in right TLE. In contrast, left TLE exhibits both edgewise and topological changes that suggest a tendency toward reorganization. Network changes in TLE and lateralized differences thereof may have important diagnostic and prognostic implications. Published by Elsevier B.V.

The connectivity structure, giant strong component and centrality of metabolic networks.

PubMed

Ma, Hong-Wu; Zeng, An-Ping

2003-07-22

Structural and functional analysis of genome-based large-scale metabolic networks is important for understanding the design principles and regulation of the metabolism at a system level. The metabolic network is conventionally considered to be highly integrated and very complex. A rational reduction of the metabolic network to its core structure and a deeper understanding of its functional modules are important. In this work, we show that the metabolites in a metabolic network are far from fully connected. A connectivity structure consisting of four major subsets of metabolites and reactions, i.e. a fully connected sub-network, a substrate subset, a product subset and an isolated subset is found to exist in metabolic networks of 65 fully sequenced organisms. The largest fully connected part of a metabolic network, called 'the giant strong component (GSC)', represents the most complicated part and the core of the network and has the feature of scale-free networks. The average path length of the whole network is primarily determined by that of the GSC. For most of the organisms, GSC normally contains less than one-third of the nodes of the network. This connectivity structure is very similar to the 'bow-tie' structure of World Wide Web. Our results indicate that the bow-tie structure may be common for large-scale directed networks. More importantly, the uncovered structure feature makes a structural and functional analysis of large-scale metabolic network more amenable. As shown in this work, comparing the closeness centrality of the nodes in the GSC can identify the most central metabolites of a metabolic network. To quantitatively characterize the overall connection structure of the GSC we introduced the term 'overall closeness centralization index (OCCI)'. OCCI correlates well with the average path length of the GSC and is a useful parameter for a system-level comparison of metabolic networks of different organisms. http://genome.gbf.de/bioinformatics/

Default mode network abnormalities in posttraumatic stress disorder: A novel network-restricted topology approach.

PubMed

Akiki, Teddy J; Averill, Christopher L; Wrocklage, Kristen M; Scott, J Cobb; Averill, Lynnette A; Schweinsburg, Brian; Alexander-Bloch, Aaron; Martini, Brenda; Southwick, Steven M; Krystal, John H; Abdallah, Chadi G

2018-08-01

Disruption in the default mode network (DMN) has been implicated in numerous neuropsychiatric disorders, including posttraumatic stress disorder (PTSD). However, studies have largely been limited to seed-based methods and involved inconsistent definitions of the DMN. Recent advances in neuroimaging and graph theory now permit the systematic exploration of intrinsic brain networks. In this study, we used resting-state functional magnetic resonance imaging (fMRI), diffusion MRI, and graph theoretical analyses to systematically examine the DMN connectivity and its relationship with PTSD symptom severity in a cohort of 65 combat-exposed US Veterans. We employed metrics that index overall connectivity strength, network integration (global efficiency), and network segregation (clustering coefficient). Then, we conducted a modularity and network-based statistical analysis to identify DMN regions of particular importance in PTSD. Finally, structural connectivity analyses were used to probe whether white matter abnormalities are associated with the identified functional DMN changes. We found decreased DMN functional connectivity strength to be associated with increased PTSD symptom severity. Further topological characterization suggests decreased functional integration and increased segregation in subjects with severe PTSD. Modularity analyses suggest a spared connectivity in the posterior DMN community (posterior cingulate, precuneus, angular gyrus) despite overall DMN weakened connections with increasing PTSD severity. Edge-wise network-based statistical analyses revealed a prefrontal dysconnectivity. Analysis of the diffusion networks revealed no alterations in overall strength or prefrontal structural connectivity. DMN abnormalities in patients with severe PTSD symptoms are characterized by decreased overall interconnections. On a finer scale, we found a pattern of prefrontal dysconnectivity, but increased cohesiveness in the posterior DMN community and relative sparing of connectivity in this region. The DMN measures established in this study may serve as a biomarker of disease severity and could have potential utility in developing circuit-based therapeutics. Published by Elsevier Inc.

Mnemonic training reshapes brain networks to support superior memory

PubMed Central

Dresler, Martin; Shirer, William R.; Konrad, Boris N.; Müller, Nils C.J.; Wagner, Isabella C.; Fernández, Guillén; Czisch, Michael; Greicius, Michael D.

2017-01-01

Summary Memory skills strongly differ across the general population, however little is known about the brain characteristics supporting superior memory performance. Here, we assess functional brain network organization of 23 of the world’s most successful memory athletes and matched controls by fMRI during both task-free resting state baseline and active memory encoding. We demonstrate that in a group of naïve controls, functional connectivity changes induced by six weeks of mnemonic training were correlated with the network organization that distinguishes athletes from controls. During rest, this effect was mainly driven by connections between rather than within the visual, medial temporal lobe and default mode networks, whereas during task it was driven by connectivity within these networks. Similarity with memory athlete connectivity patterns predicted memory improvements up to 4 months after training. In conclusion, mnemonic training drives distributed rather than regional changes, reorganizing the brain’s functional network organization to enable superior memory performance. PMID:28279356

Default Mode Network Mechanisms of Transcranial Magnetic Stimulation in Depression

PubMed Central

Liston, Conor; Chen, Ashley C.; Zebley, Benjamin D.; Drysdale, Andrew T.; Gordon, Rebecca; Leuchter, Bruce; Voss, Henning U.; Casey, B.J.; Etkin, Amit; Dubin, Marc J.

2014-01-01

Background Repetitive transcranial magnetic stimulation (TMS) of the dorsolateral prefrontal cortex (DLPFC) is an established treatment for depression, but its underlying mechanism of action remains unknown. Abnormalities in two large-scale neuronal networks—the frontoparietal central executive network (CEN) and the medial prefrontal-medial parietal default mode network (DMN)—are consistent findings in depression and potential therapeutic targets for TMS. Here, we assessed the impact of TMS on activity in these networks and their relation to treatment response. Methods We used resting state functional magnetic resonance imaging (rs-fMRI) to measure functional connectivity within and between the DMN and CEN in 17 depressed patients, before and after a five-week course of TMS. Motivated by prior reports, we focused on connectivity seeded from the DLPFC and the subgenual cingulate, a key region closely aligned with the DMN in depression. Connectivity was also compared to a cohort of 35 healthy controls. Results Prior to treatment, functional connectivity in depressed patients was abnormally elevated within the DMN and diminished within the CEN, and connectivity between these two networks was altered. TMS normalized depression-related subgenual hyperconnectivity in the DMN but did not alter connectivity in the CEN. TMS also induced anticorrelated connectivity between the DLPFC and medial prefrontal DMN nodes. Baseline subgenual connectivity predicted subsequent clinical improvement. Conclusions TMS selectively modulates functional connectivity both within and between the CEN and DMN, and modulation of subgenual cingulate connectivity may play an important mechanistic role in alleviating depression. The results also highlight potential neuroimaging biomarkers for predicting treatment response. PMID:24629537

Disruption to functional networks in neonates with perinatal brain injury predicts motor skills at 8 months.

PubMed

Linke, Annika C; Wild, Conor; Zubiaurre-Elorza, Leire; Herzmann, Charlotte; Duffy, Hester; Han, Victor K; Lee, David S C; Cusack, Rhodri

2018-01-01

Functional connectivity magnetic resonance imaging (fcMRI) of neonates with perinatal brain injury could improve prediction of motor impairment before symptoms manifest, and establish how early brain organization relates to subsequent development. This cohort study is the first to describe and quantitatively assess functional brain networks and their relation to later motor skills in neonates with a diverse range of perinatal brain injuries. Infants ( n  = 65, included in final analyses: n  = 53) were recruited from the neonatal intensive care unit (NICU) and were stratified based on their age at birth (premature vs. term), and on whether neuropathology was diagnosed from structural MRI. Functional brain networks and a measure of disruption to functional connectivity were obtained from 14 min of fcMRI acquired during natural sleep at term-equivalent age. Disruption to connectivity of the somatomotor and frontoparietal executive networks predicted motor impairment at 4 and 8 months. This disruption in functional connectivity was not found to be driven by differences between clinical groups, or by any of the specific measures we captured to describe the clinical course. fcMRI was predictive over and above other clinical measures available at discharge from the NICU, including structural MRI. Motor learning was affected by disruption to somatomotor networks, but also frontoparietal executive networks, which supports the functional importance of these networks in early development. Disruption to these two networks might be best addressed by distinct intervention strategies.

Development of the brain's functional network architecture.

PubMed

Vogel, Alecia C; Power, Jonathan D; Petersen, Steven E; Schlaggar, Bradley L

2010-12-01

A full understanding of the development of the brain's functional network architecture requires not only an understanding of developmental changes in neural processing in individual brain regions but also an understanding of changes in inter-regional interactions. Resting state functional connectivity MRI (rs-fcMRI) is increasingly being used to study functional interactions between brain regions in both adults and children. We briefly review methods used to study functional interactions and networks with rs-fcMRI and how these methods have been used to define developmental changes in network functional connectivity. The developmental rs-fcMRI studies to date have found two general properties. First, regional interactions change from being predominately anatomically local in children to interactions spanning longer cortical distances in young adults. Second, this developmental change in functional connectivity occurs, in general, via mechanisms of segregation of local regions and integration of distant regions into disparate subnetworks.

Development of the Brain's Functional Network Architecture

PubMed Central

Power, Jonathan D.; Petersen, Steven E.; Schlaggar, Bradley L.

2013-01-01

A full understanding of the development of the brain's functional network architecture requires not only an understanding of developmental changes in neural processing in individual brain regions but also an understanding of changes in inter-regional interactions. Resting state functional connectivity MRI (rs-fcMRI) is increasingly being used to study functional interactions between brain regions in both adults and children. We briefly review methods used to study functional interactions and networks with rs-fcMRI and how these methods have been used to define developmental changes in network functional connectivity. The developmental rs-fcMRI studies to date have found two general properties. First, regional interactions change from being predominately anatomically local in children to interactions spanning longer cortical distances in young adults. Second, this developmental change in functional connectivity occurs, in general, via mechanisms of segregation of local regions and integration of distant regions into disparate subnetworks. PMID:20976563

Investigating changes in brain network properties in HIV-associated neurocognitive disease (HAND) using mutual connectivity analysis (MCA)

NASA Astrophysics Data System (ADS)

Abidin, Anas Zainul; D'Souza, Adora M.; Nagarajan, Mahesh B.; Wismüller, Axel

2016-03-01

About 50% of subjects infected with HIV present deficits in cognitive domains, which are known collectively as HIV associated neurocognitive disorder (HAND). The underlying synaptodendritic damage can be captured using resting state functional MRI, as has been demonstrated by a few earlier studies. Such damage may induce topological changes of brain connectivity networks. We test this hypothesis by capturing the functional interdependence of 90 brain network nodes using a Mutual Connectivity Analysis (MCA) framework with non-linear time series modeling based on Generalized Radial Basis function (GRBF) neural networks. The network nodes are selected based on the regions defined in the Automated Anatomic Labeling (AAL) atlas. Each node is represented by the average time series of the voxels of that region. The resulting networks are then characterized using graph-theoretic measures that quantify various network topology properties at a global as well as at a local level. We tested for differences in these properties in network graphs obtained for 10 subjects (6 male and 4 female, 5 HIV+ and 5 HIV-). Global network properties captured some differences between these subject cohorts, though significant differences were seen only with the clustering coefficient measure. Local network properties, such as local efficiency and the degree of connections, captured significant differences in regions of the frontal lobe, precentral and cingulate cortex amongst a few others. These results suggest that our method can be used to effectively capture differences occurring in brain network connectivity properties revealed by resting-state functional MRI in neurological disease states, such as HAND.

Motor imagery learning modulates functional connectivity of multiple brain systems in resting state.

PubMed

Zhang, Hang; Long, Zhiying; Ge, Ruiyang; Xu, Lele; Jin, Zhen; Yao, Li; Liu, Yijun

2014-01-01

Learning motor skills involves subsequent modulation of resting-state functional connectivity in the sensory-motor system. This idea was mostly derived from the investigations on motor execution learning which mainly recruits the processing of sensory-motor information. Behavioral evidences demonstrated that motor skills in our daily lives could be learned through imagery procedures. However, it remains unclear whether the modulation of resting-state functional connectivity also exists in the sensory-motor system after motor imagery learning. We performed a fMRI investigation on motor imagery learning from resting state. Based on previous studies, we identified eight sensory and cognitive resting-state networks (RSNs) corresponding to the brain systems and further explored the functional connectivity of these RSNs through the assessments, connectivity and network strengths before and after the two-week consecutive learning. Two intriguing results were revealed: (1) The sensory RSNs, specifically sensory-motor and lateral visual networks exhibited greater connectivity strengths in precuneus and fusiform gyrus after learning; (2) Decreased network strength induced by learning was proved in the default mode network, a cognitive RSN. These results indicated that resting-state functional connectivity could be modulated by motor imagery learning in multiple brain systems, and such modulation displayed in the sensory-motor, visual and default brain systems may be associated with the establishment of motor schema and the regulation of introspective thought. These findings further revealed the neural substrates underlying motor skill learning and potentially provided new insights into the therapeutic benefits of motor imagery learning.

Default-Mode Network Functional Connectivity in Aphasia: Therapy-Induced Neuroplasticity

ERIC Educational Resources Information Center

Marcotte, Karine; Perlbarg, Vincent; Marrelec, Guillaume; Benali, Habib; Ansaldo, Ana Ines

2013-01-01

Previous research on participants with aphasia has mainly been based on standard functional neuroimaging analysis. Recent studies have shown that functional connectivity analysis can detect compensatory activity, not revealed by standard analysis. Little is known, however, about the default-mode network in aphasia. In the current study, we studied…

Differences in Resting State Functional Connectivity between Young Adult Endurance Athletes and Healthy Controls

PubMed Central

Raichlen, David A.; Bharadwaj, Pradyumna K.; Fitzhugh, Megan C.; Haws, Kari A.; Torre, Gabrielle-Ann; Trouard, Theodore P.; Alexander, Gene E.

2016-01-01

Expertise and training in fine motor skills has been associated with changes in brain structure, function, and connectivity. Fewer studies have explored the neural effects of athletic activities that do not seem to rely on precise fine motor control (e.g., distance running). Here, we compared resting-state functional connectivity in a sample of adult male collegiate distance runners (n = 11; age = 21.3 ± 2.5) and a group of healthy age-matched non-athlete male controls (n = 11; age = 20.6 ± 1.1), to test the hypothesis that expertise in sustained aerobic motor behaviors affects resting state functional connectivity in young adults. Although generally considered an automated repetitive task, locomotion, especially at an elite level, likely engages multiple cognitive actions including planning, inhibition, monitoring, attentional switching and multi-tasking, and motor control. Here, we examined connectivity in three resting-state networks that link such executive functions with motor control: the default mode network (DMN), the frontoparietal network (FPN), and the motor network (MN). We found two key patterns of significant between-group differences in connectivity that are consistent with the hypothesized cognitive demands of elite endurance running. First, enhanced connectivity between the FPN and brain regions often associated with aspects of working memory and other executive functions (frontal cortex), suggest endurance running may stress executive cognitive functions in ways that increase connectivity in associated networks. Second, we found significant anti-correlations between the DMN and regions associated with motor control (paracentral area), somatosensory functions (post-central region), and visual association abilities (occipital cortex). DMN deactivation with task-positive regions has been shown to be generally beneficial for cognitive performance, suggesting anti-correlated regions observed here are engaged during running. For all between-group differences, there were significant associations between connectivity, self-reported physical activity, and estimates of maximum aerobic capacity, suggesting a dose-response relationship between engagement in endurance running and connectivity strength. Together these results suggest that differences in experience with endurance running are associated with differences in functional brain connectivity. High intensity aerobic activity that requires sustained, repetitive locomotor and navigational skills may stress cognitive domains in ways that lead to altered brain connectivity, which in turn has implications for understanding the beneficial role of exercise for brain and cognitive function over the lifespan. PMID:28018192

Functional brain imaging across development.

PubMed

Rubia, Katya

2013-12-01

The developmental cognitive neuroscience literature has grown exponentially over the last decade. This paper reviews the functional magnetic resonance imaging (fMRI) literature on brain function development of typically late developing functions of cognitive and motivation control, timing and attention as well as of resting state neural networks. Evidence shows that between childhood and adulthood, concomitant with cognitive maturation, there is progressively increased functional activation in task-relevant lateral and medial frontal, striatal and parieto-temporal brain regions that mediate these higher level control functions. This is accompanied by progressively stronger functional inter-regional connectivity within task-relevant fronto-striatal and fronto-parieto-temporal networks. Negative age associations are observed in earlier developing posterior and limbic regions, suggesting a shift with age from the recruitment of "bottom-up" processing regions towards "top-down" fronto-cortical and fronto-subcortical connections, leading to a more mature, supervised cognition. The resting state fMRI literature further complements this evidence by showing progressively stronger deactivation with age in anti-correlated task-negative resting state networks, which is associated with better task performance. Furthermore, connectivity analyses during the resting state show that with development increasingly stronger long-range connections are being formed, for example, between fronto-parietal and fronto-cerebellar connections, in both task-positive networks and in task-negative default mode networks, together with progressively lesser short-range connections, suggesting progressive functional integration and segregation with age. Overall, evidence suggests that throughout development between childhood and adulthood, there is progressive refinement and integration of both task-positive fronto-cortical and fronto-subcortical activation and task-negative deactivation, leading to a more mature and controlled cognition.

Impact of real-time fMRI working memory feedback training on the interactions between three core brain networks.

PubMed

Zhang, Qiushi; Zhang, Gaoyan; Yao, Li; Zhao, Xiaojie

2015-01-01

Working memory (WM) refers to the temporary holding and manipulation of information during the performance of a range of cognitive tasks, and WM training is a promising method for improving an individual's cognitive functions. Our previous work demonstrated that WM performance can be improved through self-regulation of dorsal lateral prefrontal cortex (PFC) activation using real-time functional magnetic resonance imaging (rtfMRI), which enables individuals to control local brain activities volitionally according to the neurofeedback. Furthermore, research concerning large-scale brain networks has demonstrated that WM training requires the engagement of several networks, including the central executive network (CEN), the default mode network (DMN) and the salience network (SN), and functional connectivity within the CEN and DMN can be changed by WM training. Although a switching role of the SN between the CEN and DMN has been demonstrated, it remains unclear whether WM training can affect the interactions between the three networks and whether a similar mechanism also exists during the training process. In this study, we investigated the dynamic functional connectivity between the three networks during the rtfMRI feedback training using independent component analysis (ICA) and correlation analysis. The results indicated that functional connectivity within and between the three networks were significantly enhanced by feedback training, and most of the changes were associated with the insula and correlated with behavioral improvements. These findings suggest that the insula plays a critical role in the reorganization of functional connectivity among the three networks induced by rtfMRI training and in WM performance, thus providing new insights into the mechanisms of high-level functions and the clinical treatment of related functional impairments.

Cannabis, cigarettes, and their co-occurring use: disentangling differences in default mode network functional connectivity

PubMed Central

Wetherill, Reagan R.; Fang, Zhuo; Jagannathan, Kanchana; Childress, Anna Rose; Rao, Hengyi; Franklin, Teresa R.

2015-01-01

Background Resting-state functional connectivity is a noninvasive, neuroimaging method for assessing neural network function. Altered functional connectivity among regions of the default-mode network have been associated with both nicotine and cannabis use; however, less is known about co-occurring cannabis and tobacco use. Methods We used posterior cingulate cortex (PCC) seed-based resting-state functional connectivity analyses to examine default mode network (DMN) connectivity strength differences between four groups: 1) individuals diagnosed with cannabis dependence who do not smoke tobacco (n=19; ages 20–50), 2) cannabis-dependent individuals who smoke tobacco (n=23, ages 21–52), 3) cannabis-naïve, nicotine-dependent individuals who smoke tobacco (n=24, ages 21–57), and 4) cannabis- and tobacco-naïve healthy controls (n=21, ages 21–50), controlling for age, sex, and alcohol use. We also explored associations between connectivity strength and measures of cannabis and tobacco use. Results PCC seed-based analyses identified the core nodes of the DMN (i.e., PCC, medial prefrontal cortex, inferior parietal cortex, and temporal cortex). In general, the cannabis-dependent, nicotine-dependent, and co-occurring use groups showed lower DMN connectivity strengths than controls, with unique group differences in connectivity strength between the PCC and the cerebellum, medial prefrontal cortex, parahippocampus, and anterior insula. In cannabis-dependent individuals, PCC-right anterior insula connectivity strength correlated with duration of cannabis use. Conclusions This study extends previous research that independently examined the differences in resting-state functional connectivity among individuals who smoke cannabis and tobacco by including an examination of co-occurring cannabis and tobacco use and provides further evidence that cannabis and tobacco exposure is associated with alterations in DMN connectivity. PMID:26094186

The development of Human Functional Brain Networks

PubMed Central

Power, Jonathan D; Fair, Damien A; Schlaggar, Bradley L

2010-01-01

Recent advances in MRI technology have enabled precise measurements of correlated activity throughout the brain, leading to the first comprehensive descriptions of functional brain networks in humans. This article reviews the growing literature on the development of functional networks, from infancy through adolescence, as measured by resting state functional connectivity MRI. We note several limitations of traditional approaches to describing brain networks, and describe a powerful framework for analyzing networks, called graph theory. We argue that characterization of the development of brain systems (e.g. the default mode network) should be comprehensive, considering not only relationships within a given system, but also how these relationships are situated within wider network contexts. We note that, despite substantial reorganization of functional connectivity, several large-scale network properties appear to be preserved across development, suggesting that functional brain networks, even in children, are organized in manners similar to other complex systems. PMID:20826306

Connectomics and neuroticism: an altered functional network organization.

PubMed

Servaas, Michelle N; Geerligs, Linda; Renken, Remco J; Marsman, Jan-Bernard C; Ormel, Johan; Riese, Harriëtte; Aleman, André

2015-01-01

The personality trait neuroticism is a potent risk marker for psychopathology. Although the neurobiological basis remains unclear, studies have suggested that alterations in connectivity may underlie it. Therefore, the aim of the current study was to shed more light on the functional network organization in neuroticism. To this end, we applied graph theory on resting-state functional magnetic resonance imaging (fMRI) data in 120 women selected based on their neuroticism score. Binary and weighted brain-wide graphs were constructed to examine changes in the functional network structure and functional connectivity strength. Furthermore, graphs were partitioned into modules to specifically investigate connectivity within and between functional subnetworks related to emotion processing and cognitive control. Subsequently, complex network measures (ie, efficiency and modularity) were calculated on the brain-wide graphs and modules, and correlated with neuroticism scores. Compared with low neurotic individuals, high neurotic individuals exhibited a whole-brain network structure resembling more that of a random network and had overall weaker functional connections. Furthermore, in these high neurotic individuals, functional subnetworks could be delineated less clearly and the majority of these subnetworks showed lower efficiency, while the affective subnetwork showed higher efficiency. In addition, the cingulo-operculum subnetwork demonstrated more ties with other functional subnetworks in association with neuroticism. In conclusion, the 'neurotic brain' has a less than optimal functional network organization and shows signs of functional disconnectivity. Moreover, in high compared with low neurotic individuals, emotion and salience subnetworks have a more prominent role in the information exchange, while sensory(-motor) and cognitive control subnetworks have a less prominent role.

Default Mode Network Subsystems are Differentially Disrupted in Posttraumatic Stress Disorder

PubMed Central

Miller, Danielle R.; Hayes, Scott M.; Hayes, Jasmeet P.; Spielberg, Jeffrey M.; Lafleche, Ginette; Verfaellie, Mieke

2017-01-01

Background Posttraumatic stress disorder (PTSD) is a psychiatric disorder characterized by debilitating re-experiencing, avoidance, and hyperarousal symptoms following trauma exposure. Recent evidence suggests that individuals with PTSD show disrupted functional connectivity in the default mode network, an intrinsic network that consists of a midline core, a medial temporal lobe (MTL) subsystem, and a dorsomedial prefrontal cortex (dMPFC) subsystem. The present study examined whether functional connectivity in these subsystems is differentially disrupted in PTSD. Methods Sixty-nine returning war Veterans with PTSD and 44 trauma-exposed Veterans without PTSD underwent resting state functional MRI (rs-fMRI). To examine functional connectivity, seeds were placed in the core hubs of the default mode network, namely the posterior cingulate cortex (PCC) and anterior medial PFC (aMPFC), and in each subsystem. Results Compared to controls, individuals with PTSD had reduced functional connectivity between the PCC and the hippocampus, a region of the MTL subsystem. Groups did not differ in connectivity between the PCC and dMPFC subsystem or between the aMPFC and any region within either subsystem. In the PTSD group, connectivity between the PCC and hippocampus was negatively associated with avoidance/numbing symptoms. Examination of the MTL and dMPFC subsystems revealed reduced anticorrelation between the ventromedial PFC (vMPFC) seed of the MTL subsystem and the dorsal anterior cingulate cortex in the PTSD group. Conclusions Our results suggest that selective alterations in functional connectivity in the MTL subsystem of the default mode network in PTSD may be an important factor in PTSD pathology and symptomatology. PMID:28435932

Default Mode Network Subsystems are Differentially Disrupted in Posttraumatic Stress Disorder.

PubMed

Miller, Danielle R; Hayes, Scott M; Hayes, Jasmeet P; Spielberg, Jeffrey M; Lafleche, Ginette; Verfaellie, Mieke

2017-05-01

Posttraumatic stress disorder (PTSD) is a psychiatric disorder characterized by debilitating re-experiencing, avoidance, and hyperarousal symptoms following trauma exposure. Recent evidence suggests that individuals with PTSD show disrupted functional connectivity in the default mode network, an intrinsic network that consists of a midline core, a medial temporal lobe (MTL) subsystem, and a dorsomedial prefrontal cortex (dMPFC) subsystem. The present study examined whether functional connectivity in these subsystems is differentially disrupted in PTSD. Sixty-nine returning war Veterans with PTSD and 44 trauma-exposed Veterans without PTSD underwent resting state functional MRI (rs-fMRI). To examine functional connectivity, seeds were placed in the core hubs of the default mode network, namely the posterior cingulate cortex (PCC) and anterior medial PFC (aMPFC), and in each subsystem. Compared to controls, individuals with PTSD had reduced functional connectivity between the PCC and the hippocampus, a region of the MTL subsystem. Groups did not differ in connectivity between the PCC and dMPFC subsystem or between the aMPFC and any region within either subsystem. In the PTSD group, connectivity between the PCC and hippocampus was negatively associated with avoidance/numbing symptoms. Examination of the MTL and dMPFC subsystems revealed reduced anticorrelation between the ventromedial PFC (vMPFC) seed of the MTL subsystem and the dorsal anterior cingulate cortex in the PTSD group. Our results suggest that selective alterations in functional connectivity in the MTL subsystem of the default mode network in PTSD may be an important factor in PTSD pathology and symptomatology.

Is Rest Really Rest? Resting State Functional Connectivity during Rest and Motor Task Paradigms.

PubMed

Jurkiewicz, Michael T; Crawley, Adrian P; Mikulis, David J

2018-04-18

Numerous studies have identified the default mode network (DMN) within the brain of healthy individuals, which has been attributed to the ongoing mental activity of the brain during the wakeful resting-state. While engaged during specific resting-state fMRI paradigms, it remains unclear as to whether traditional block-design simple movement fMRI experiments significantly influence the default mode network or other areas. Using blood-oxygen level dependent (BOLD) fMRI we characterized the pattern of functional connectivity in healthy subjects during a resting-state paradigm and compared this to the same resting-state analysis performed on motor task data residual time courses after regressing out the task paradigm. Using seed-voxel analysis to define the DMN, the executive control network (ECN), and sensorimotor, auditory and visual networks, the resting-state analysis of the residual time courses demonstrated reduced functional connectivity in the motor network and reduced connectivity between the insula and the ECN compared to the standard resting-state datasets. Overall, performance of simple self-directed motor tasks does little to change the resting-state functional connectivity across the brain, especially in non-motor areas. This would suggest that previously acquired fMRI studies incorporating simple block-design motor tasks could be mined retrospectively for assessment of the resting-state connectivity.

Connectivity in MEG resting-state networks increases after resective surgery for low-grade glioma and correlates with improved cognitive performance☆

PubMed Central

van Dellen, E.; de Witt Hamer, P.C.; Douw, L.; Klein, M.; Heimans, J.J.; Stam, C.J.; Reijneveld, J.C.; Hillebrand, A.

2012-01-01

Purpose Low-grade glioma (LGG) patients often have cognitive deficits. Several disease- and treatment related factors affect cognitive processing. Cognitive outcome of resective surgery is unpredictable, both for improvement and deterioration, especially for complex domains such as attention and executive functioning. MEG analysis of resting-state networks (RSNs) is a good candidate for presurgical prediction of cognitive outcome. In this study, we explore the relation between alterations in connectivity of RSNs and changes in cognitive processing after resective surgery, as a stepping stone to ultimately predict postsurgical cognitive outcome. Methods Ten patients with LGG were included, who had no adjuvant therapy. MEG recording and neuropsychological assessment were obtained before and after resective surgery. MEG data were recorded during a no-task eyes-closed condition, and projected to the anatomical space of the AAL atlas. Alterations in functional connectivity, as characterized by the phase lag index (PLI), within the default mode network (DMN), executive control network (ECN), and left- and right-sided frontoparietal networks (FPN) were compared to cognitive changes. Results Lower alpha band DMN connectivity was increased after surgery, and this increase was related to improved verbal memory functioning. Similarly, right FPN connectivity was increased after resection in the upper alpha band, which correlated with improved attention, working memory and executive functioning. Discussion Increased alpha band RSN functional connectivity in MEG recordings correlates with improved cognitive outcome after resective surgery. The mechanisms resulting in functional connectivity alterations after resection remain to be elucidated. Importantly, our findings indicate that connectivity of MEG RSNs may be used for presurgical prediction of cognitive outcome in future studies. PMID:24179752

Immediate and Longitudinal Alterations of Functional Networks after Thalamotomy in Essential Tremor

PubMed Central

Jang, Changwon; Park, Hae-Jeong; Chang, Won Seok; Pae, Chongwon; Chang, Jin Woo

2016-01-01

Thalamotomy at the ventralis intermedius nucleus has been an effective treatment method for essential tremor, but how the brain network changes immediately responding to this deliberate lesion and then reorganizes afterwards are not clear. Taking advantage of a non-cranium-opening MRI-guided focused ultrasound ablation technique, we investigated functional network changes due to a focal lesion. To classify the diverse time courses of those network changes with respect to symptom-related long-lasting treatment effects and symptom-unrelated transient effects, we applied graph-theoretic analyses to longitudinal resting-state functional magnetic resonance imaging data before and 1 day, 7 days, and 3 months after thalamotomy with essential tremor. We found reduced average connections among the motor-related areas, reduced connectivity between substantia nigra and external globus pallidum and reduced total connection in the thalamus after thalamotomy, which are all associated with clinical rating scales. The average connectivity among whole brain regions and inter-hemispheric network asymmetry show symptom-unrelated transient increases, indicating temporary reconfiguration of the whole brain network. In summary, thalamotomy regulates interactions over the motor network via symptom-related connectivity changes but accompanies transient, symptom-unrelated diaschisis in the global brain network. This study suggests the significance of longitudinal network analysis, combined with minimal-invasive treatment techniques, in understanding time-dependent diaschisis in the brain network due to a focal lesion. PMID:27822200

“Guilt by Association” Is the Exception Rather Than the Rule in Gene Networks

PubMed Central

Gillis, Jesse; Pavlidis, Paul

2012-01-01

Gene networks are commonly interpreted as encoding functional information in their connections. An extensively validated principle called guilt by association states that genes which are associated or interacting are more likely to share function. Guilt by association provides the central top-down principle for analyzing gene networks in functional terms or assessing their quality in encoding functional information. In this work, we show that functional information within gene networks is typically concentrated in only a very few interactions whose properties cannot be reliably related to the rest of the network. In effect, the apparent encoding of function within networks has been largely driven by outliers whose behaviour cannot even be generalized to individual genes, let alone to the network at large. While experimentalist-driven analysis of interactions may use prior expert knowledge to focus on the small fraction of critically important data, large-scale computational analyses have typically assumed that high-performance cross-validation in a network is due to a generalizable encoding of function. Because we find that gene function is not systemically encoded in networks, but dependent on specific and critical interactions, we conclude it is necessary to focus on the details of how networks encode function and what information computational analyses use to extract functional meaning. We explore a number of consequences of this and find that network structure itself provides clues as to which connections are critical and that systemic properties, such as scale-free-like behaviour, do not map onto the functional connectivity within networks. PMID:22479173

Atomoxetine Treatment Strengthens an Anti-Correlated Relationship between Functional Brain Networks in Medication-Naïve Adults with Attention-Deficit Hyperactivity Disorder: A Randomized Double-Blind Placebo-Controlled Clinical Trial

PubMed Central

Lin, Hsiang-Yuan

2016-01-01

Background: Although atomoxetine demonstrates efficacy in individuals with attention-deficit hyperactivity disorder, its treatment effects on brain resting-state functional connectivity remain unknown. Therefore, we aimed to investigate major brain functional networks in medication-naïve adults with attention-deficit hyperactivity disorder and the efficacy of atomoxetine treatment on resting-state functional connectivity. Methods: After collecting baseline resting-state functional MRI scans from 24 adults with attention-deficit hyperactivity disorder (aged 18–52 years) and 24 healthy controls (matched in demographic characteristics), the participants with attention-deficit hyperactivity disorder were randomly assigned to atomoxetine (n=12) and placebo (n=12) arms in an 8-week, double-blind, placebo-controlled trial. The primary outcome was functional connectivity assessed by a resting-state functional MRI. Seed-based functional connectivity was calculated and compared for the affective, attention, default, and cognitive control networks. Results: At baseline, we found atypical cross talk between the default, cognitive control, and dorsal attention networks and hypoconnectivity within the dorsal attention and default networks in adults with attention-deficit hyperactivity disorder. Our first-ever placebo-controlled clinical trial incorporating resting-state functional MRI showed that treatment with atomoxetine strengthened an anticorrelated relationship between the default and task-positive networks and modulated all major brain networks. The strengthened anticorrelations were associated with improving clinical symptoms in the atomoxetine-treated adults. Conclusions: Our results support the idea that atypical default mode network task-positive network interaction plays an important role in the pathophysiology of adult attention-deficit hyperactivity disorder. Strengthening this atypical relationship following atomoxetine treatment suggests an important pathway to treat attention-deficit hyperactivity disorder. PMID:26377368

Atomoxetine Treatment Strengthens an Anti-Correlated Relationship between Functional Brain Networks in Medication-Naïve Adults with Attention-Deficit Hyperactivity Disorder: A Randomized Double-Blind Placebo-Controlled Clinical Trial.

PubMed

Lin, Hsiang-Yuan; Gau, Susan Shur-Fen

2015-09-16

Although atomoxetine demonstrates efficacy in individuals with attention-deficit hyperactivity disorder, its treatment effects on brain resting-state functional connectivity remain unknown. Therefore, we aimed to investigate major brain functional networks in medication-naïve adults with attention-deficit hyperactivity disorder and the efficacy of atomoxetine treatment on resting-state functional connectivity. After collecting baseline resting-state functional MRI scans from 24 adults with attention-deficit hyperactivity disorder (aged 18-52 years) and 24 healthy controls (matched in demographic characteristics), the participants with attention-deficit hyperactivity disorder were randomly assigned to atomoxetine (n=12) and placebo (n=12) arms in an 8-week, double-blind, placebo-controlled trial. The primary outcome was functional connectivity assessed by a resting-state functional MRI. Seed-based functional connectivity was calculated and compared for the affective, attention, default, and cognitive control networks. At baseline, we found atypical cross talk between the default, cognitive control, and dorsal attention networks and hypoconnectivity within the dorsal attention and default networks in adults with attention-deficit hyperactivity disorder. Our first-ever placebo-controlled clinical trial incorporating resting-state functional MRI showed that treatment with atomoxetine strengthened an anticorrelated relationship between the default and task-positive networks and modulated all major brain networks. The strengthened anticorrelations were associated with improving clinical symptoms in the atomoxetine-treated adults. Our results support the idea that atypical default mode network task-positive network interaction plays an important role in the pathophysiology of adult attention-deficit hyperactivity disorder. Strengthening this atypical relationship following atomoxetine treatment suggests an important pathway to treat attention-deficit hyperactivity disorder. © The Author 2015. Published by Oxford University Press on behalf of CINP.

Decreased functional connectivity in schizophrenia: The relationship between social functioning, social cognition and graph theoretical network measures.

PubMed

Erdeniz, Burak; Serin, Emin; İbadi, Yelda; Taş, Cumhur

2017-12-30

Schizophrenia is a complex disorder in which abnormalities in brain connectivity and social functioning play a central role. The aim of this study is to explore small-world network properties, and understand their relationship with social functioning and social cognition in the context of schizophrenia, by testing functional connectivity differences in network properties and its relation to clinical behavioral measures. Resting-state fMRI time series data were acquired from 23 patients diagnosed with schizophrenia and 23 healthy volunteers. The results revealed that patients with schizophrenia show significantly decreased connectivity between a range of brain regions, particularly involving connections among the right orbitofrontal cortex, bilateral putamen and left amygdala. Furthermore, topological properties of functional brain networks in patients with schizophrenia were characterized by reduced path length compared to healthy controls; however, no significant difference was found for clustering coefficient, local efficiency or global efficiency. Additionally, we found that nodal efficiency of the amygdala and the putamen were significantly correlated with the independence-performance subscale of social functioning scale (SFC), and Reading the Mind in the Eyes test; however, the correlations do not survive correction for multiple comparison. The current results help to clarify the relationship between social functioning deficits and topological brain measures in schizophrenia. Copyright © 2017 Elsevier B.V. All rights reserved.

Control networks in paediatric Tourette syndrome show immature and anomalous patterns of functional connectivity

PubMed Central

Fair, Damien A.; Dosenbach, Nico U. F.; Cohen, Alexander L.; Miezin, Francis M.; Petersen, Steven E.; Schlaggar, Bradley L.

2009-01-01

Tourette syndrome (TS) is a developmental disorder characterized by unwanted, repetitive behaviours that manifest as stereotyped movements and vocalizations called ‘tics’. Operating under the hypothesis that the brain's control systems may be impaired in TS, we measured resting-state functional connectivity MRI (rs-fcMRI) between 39 previously defined putative control regions in 33 adolescents with TS. We were particularly interested in the effect of TS on two of the brain's task control networks—a fronto-parietal network likely involved in more rapid, adaptive online control, and a cingulo-opercular network apparently important for set-maintenance. To examine the relative maturity of connections in the Tourette subjects, functional connections that changed significantly over typical development were examined. Age curves were created for each functional connection charting correlation coefficients over age for 210 healthy people aged 7–31 years, and the TS group correlation coefficients were compared to these curves. Many of these connections were significantly less ‘mature’ than expected in the TS group. This immaturity was true not only for functional connections that grow stronger with age, but also for those that diminish in strength with age. To explore other differences between Tourette and typically developing subjects further, we performed a second analysis in which the TS group was directly compared to an age-matched, movement-matched group of typically developing, unaffected adolescents. A number of functional connections were found to differ between the two groups. For these identified connections, a large number of connectional differences were found where the TS group value was out of range compared to typical developmental age curves. These anomalous connections were primarily found in the fronto-parietal network, thought to be important for online adaptive control. These results suggest that in adolescents with TS, immature functional connectivity is widespread, with additional, more profound deviation of connectivity in regions related to adaptive online control. PMID:18952678

Altered functional connectivity differs in stroke survivors with impaired touch sensation following left and right hemisphere lesions.

PubMed

Goodin, Peter; Lamp, Gemma; Vidyasagar, Rishma; McArdle, David; Seitz, Rüdiger J; Carey, Leeanne M

2018-01-01

One in two survivors experience impairment in touch sensation after stroke. The nature of this impairment is likely associated with changes associated with the functional somatosensory network of the brain; however few studies have examined this. In particular, the impact of lesioned hemisphere has not been investigated. We examined resting state functional connectivity in 28 stroke survivors, 14 with left hemisphere and 14 with right hemisphere lesion, and 14 healthy controls. Contra-lesional hands showed significantly decreased touch discrimination. Whole brain functional connectivity (FC) data was extracted from four seed regions, i.e. primary (S1) and secondary (S2) somatosensory cortices in both hemispheres. Whole brain FC maps and Laterality Indices (LI) were calculated for subgroups. Inter-hemispheric FC was greater in healthy controls compared to the combined stroke cohort from the left S1 seed and bilateral S2 seeds. The left lesion subgroup showed decreased FC, relative to controls, from left ipsi-lesional S1 to contra-lesional S1 and to distributed temporal, occipital and parietal regions. In comparison, the right lesion group showed decreased connectivity from contra-lesional left S1 and bilateral S2 to ipsi-lesional parietal operculum (S2), and to occipital and temporal regions. The right lesion group also showed increased intra-hemispheric FC from ipsi-lesional right S1 to inferior parietal regions compared to controls. In comparison to the left lesion group, those with right lesion showed greater intra-hemispheric connectivity from left S1 to left parietal and occipital regions and from right S1 to right angular and parietal regions. Laterality Indices were significantly greater for stroke subgroups relative to matched controls for contra-lesional S1 (left lesion group) and contra-lesional S2 (both groups). We provide evidence of altered functional connectivity within the somatosensory network, across both hemispheres, and to other networks in stroke survivors with impaired touch sensation. Hemisphere of lesion was associated with different patterns of altered functional connectivity within the somatosensory network and with related function was associated with different patterns of altered functional connectivity within the somatosensory network and with related functional networks.

Patient-specific connectivity pattern of epileptic network in frontal lobe epilepsy

PubMed Central

Luo, Cheng; An, Dongmei; Yao, Dezhong; Gotman, Jean

2014-01-01

There is evidence that focal epilepsy may involve the dysfunction of a brain network in addition to the focal region. To delineate the characteristics of this epileptic network, we collected EEG/fMRI data from 23 patients with frontal lobe epilepsy. For each patient, EEG/fMRI analysis was first performed to determine the BOLD response to epileptic spikes. The maximum activation cluster in the frontal lobe was then chosen as the seed to identify the epileptic network in fMRI data. Functional connectivity analysis seeded at the same region was also performed in 63 healthy control subjects. Nine features were used to evaluate the differences of epileptic network patterns in three connection levels between patients and controls. Compared with control subjects, patients showed overall more functional connections between the epileptogenic region and the rest of the brain and higher laterality. However, the significantly increased connections were located in the neighborhood of the seed, but the connections between the seed and remote regions actually decreased. Comparing fMRI runs with interictal epileptic discharges (IEDs) and without IEDs, the patient-specific connectivity pattern was not changed significantly. These findings regarding patient-specific connectivity patterns of epileptic networks in FLE reflect local high connectivity and connections with distant regions differing from those of healthy controls. Moreover, the difference between the two groups in most features was observed in the strictest of the three connection levels. The abnormally high connectivity might reflect a predominant attribute of the epileptic network, which may facilitate propagation of epileptic activity among regions in the network. PMID:24936418

Multiple sclerosis lesions affect intrinsic functional connectivity of the spinal cord.

PubMed

Conrad, Benjamin N; Barry, Robert L; Rogers, Baxter P; Maki, Satoshi; Mishra, Arabinda; Thukral, Saakshi; Sriram, Subramaniam; Bhatia, Aashim; Pawate, Siddharama; Gore, John C; Smith, Seth A

2018-06-01

Patients with multiple sclerosis present with focal lesions throughout the spinal cord. There is a clinical need for non-invasive measurements of spinal cord activity and functional organization in multiple sclerosis, given the cord's critical role in the disease. Recent reports of spontaneous blood oxygenation level-dependent fluctuations in the spinal cord using functional MRI suggest that, like the brain, cord activity at rest is organized into distinct, synchronized functional networks among grey matter regions, likely related to motor and sensory systems. Previous studies looking at stimulus-evoked activity in the spinal cord of patients with multiple sclerosis have demonstrated increased levels of activation as well as a more bilateral distribution of activity compared to controls. Functional connectivity studies of brain networks in multiple sclerosis have revealed widespread alterations, which may take on a dynamic trajectory over the course of the disease, with compensatory increases in connectivity followed by decreases associated with structural damage. We build upon this literature by examining functional connectivity in the spinal cord of patients with multiple sclerosis. Using ultra-high field 7 T imaging along with processing strategies for robust spinal cord functional MRI and lesion identification, the present study assessed functional connectivity within cervical cord grey matter of patients with relapsing-remitting multiple sclerosis (n = 22) compared to a large sample of healthy controls (n = 56). Patient anatomical images were rated for lesions by three independent raters, with consensus ratings revealing 19 of 22 patients presented with lesions somewhere in the imaged volume. Linear mixed models were used to assess effects of lesion location on functional connectivity. Analysis in control subjects demonstrated a robust pattern of connectivity among ventral grey matter regions as well as a distinct network among dorsal regions. A gender effect was also observed in controls whereby females demonstrated higher ventral network connectivity. Wilcoxon rank-sum tests detected no differences in average connectivity or power of low frequency fluctuations in patients compared to controls. The presence of lesions was, however, associated with local alterations in connectivity with differential effects depending on columnar location. The patient results suggest that spinal cord functional networks are generally intact in relapsing-remitting multiple sclerosis but that lesions are associated with focal abnormalities in intrinsic connectivity. These findings are discussed in light of the current literature on spinal cord functional MRI and the potential neurological underpinnings.

Increased functional connectivity within memory networks following memory rehabilitation in multiple sclerosis.

PubMed

Leavitt, Victoria M; Wylie, Glenn R; Girgis, Peter A; DeLuca, John; Chiaravalloti, Nancy D

2014-09-01

Identifying effective behavioral treatments to improve memory in persons with learning and memory impairment is a primary goal for neurorehabilitation researchers. Memory deficits are the most common cognitive symptom in multiple sclerosis (MS), and hold negative professional and personal consequences for people who are often in the prime of their lives when diagnosed. A 10-session behavioral treatment, the modified Story Memory Technique (mSMT), was studied in a randomized, placebo-controlled clinical trial. Behavioral improvements and increased fMRI activation were shown after treatment. Here, connectivity within the neural networks underlying memory function was examined with resting-state functional connectivity (RSFC) in a subset of participants from the clinical trial. We hypothesized that the treatment would result in increased integrity of connections within two primary memory networks of the brain, the hippocampal memory network, and the default network (DN). Seeds were placed in left and right hippocampus, and the posterior cingulate cortex. Increased connectivity was found between left hippocampus and cortical regions specifically involved in memory for visual imagery, as well as among critical hubs of the DN. These results represent the first evidence for efficacy of a behavioral intervention to impact the integrity of neural networks subserving memory functions in persons with MS.

Altered resting-state frontoparietal control network in children with attention-deficit/hyperactivity disorder.

PubMed

Lin, Hsiang-Yuan; Tseng, Wen-Yih Isaac; Lai, Meng-Chuan; Matsuo, Kayako; Gau, Susan Shur-Fen

2015-04-01

The frontoparietal control network, anatomically and functionally interposed between the dorsal attention network and default mode network, underpins executive control functions. Individuals with attention-deficit/hyperactivity disorder (ADHD) commonly exhibit deficits in executive functions, which are mainly mediated by the frontoparietal control network. Involvement of the frontoparietal control network based on the anterior prefrontal cortex in neurobiological mechanisms of ADHD has yet to be tested. We used resting-state functional MRI and seed-based correlation analyses to investigate functional connectivity of the frontoparietal control network in a sample of 25 children with ADHD (7-14 years; mean 9.94 ± 1.77 years; 20 males), and 25 age-, sex-, and performance IQ-matched typically developing (TD) children. All participants had limited in-scanner head motion. Spearman's rank correlations were used to test the associations between altered patterns of functional connectivity with clinical symptoms and executive functions, measured by the Conners' Continuous Performance Test and Spatial Span in the Cambridge Neuropsychological Test Automated Battery. Compared with TD children, children with ADHD demonstrated weaker connectivity between the right anterior prefrontal cortex (PFC) and the right ventrolateral PFC, and between the left anterior PFC and the right inferior parietal lobule. Furthermore, this aberrant connectivity of the frontoparietal control network in ADHD was associated with symptoms of impulsivity and opposition-defiance, as well as impaired response inhibition and attentional control. The findings support potential integration of the disconnection model and the executive dysfunction model for ADHD. Atypical frontoparietal control network may play a pivotal role in the pathophysiology of ADHD.

Dynamic functional connectivity shapes individual differences in associative learning.

PubMed

Fatima, Zainab; Kovacevic, Natasha; Misic, Bratislav; McIntosh, Anthony Randal

2016-11-01

Current neuroscientific research has shown that the brain reconfigures its functional interactions at multiple timescales. Here, we sought to link transient changes in functional brain networks to individual differences in behavioral and cognitive performance by using an active learning paradigm. Participants learned associations between pairs of unrelated visual stimuli by using feedback. Interindividual behavioral variability was quantified with a learning rate measure. By using a multivariate statistical framework (partial least squares), we identified patterns of network organization across multiple temporal scales (within a trial, millisecond; across a learning session, minute) and linked these to the rate of change in behavioral performance (fast and slow). Results indicated that posterior network connectivity was present early in the trial for fast, and later in the trial for slow performers. In contrast, connectivity in an associative memory network (frontal, striatal, and medial temporal regions) occurred later in the trial for fast, and earlier for slow performers. Time-dependent changes in the posterior network were correlated with visual/spatial scores obtained from independent neuropsychological assessments, with fast learners performing better on visual/spatial subtests. No relationship was found between functional connectivity dynamics in the memory network and visual/spatial test scores indicative of cognitive skill. By using a comprehensive set of measures (behavioral, cognitive, and neurophysiological), we report that individual variations in learning-related performance change are supported by differences in cognitive ability and time-sensitive connectivity in functional neural networks. Hum Brain Mapp 37:3911-3928, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Unravelling the Intrinsic Functional Organization of the Human Striatum: A Parcellation and Connectivity Study Based on Resting-State fMRI

PubMed Central

Jung, Wi Hoon; Jang, Joon Hwan; Park, Jin Woo; Kim, Euitae; Goo, Eun-Hoe; Im, Oh-Soo; Kwon, Jun Soo

2014-01-01

As the main input hub of the basal ganglia, the striatum receives projections from the cerebral cortex. Many studies have provided evidence for multiple parallel corticostriatal loops based on the structural and functional connectivity profiles of the human striatum. A recent resting-state fMRI study revealed the topography of striatum by assigning each voxel in the striatum to its most strongly correlated cortical network among the cognitive, affective, and motor networks. However, it remains unclear what patterns of striatal parcellation would result from performing the clustering without subsequent assignment to cortical networks. Thus, we applied unsupervised clustering algorithms to parcellate the human striatum based on its functional connectivity patterns to other brain regions without any anatomically or functionally defined cortical targets. Functional connectivity maps of striatal subdivisions, identified through clustering analyses, were also computed. Our findings were consistent with recent accounts of the functional distinctions of the striatum as well as with recent studies about its functional and anatomical connectivity. For example, we found functional connections between dorsal and ventral striatal clusters and the areas involved in cognitive and affective processes, respectively, and between rostral and caudal putamen clusters and the areas involved in cognitive and motor processes, respectively. This study confirms prior findings, showing similar striatal parcellation patterns between the present and prior studies. Given such striking similarity, it is suggested that striatal subregions are functionally linked to cortical networks involving specific functions rather than discrete portions of cortical regions. Our findings also demonstrate that the clustering of functional connectivity patterns is a reliable feature in parcellating the striatum into anatomically and functionally meaningful subdivisions. The striatal subdivisions identified here may have important implications for understanding the relationship between corticostriatal dysfunction and various neurodegenerative and psychiatric disorders. PMID:25203441

Improved Diagnostic Accuracy of Alzheimer's Disease by Combining Regional Cortical Thickness and Default Mode Network Functional Connectivity: Validated in the Alzheimer's Disease Neuroimaging Initiative Set

PubMed Central

Park, Ji Eun; Park, Bumwoo; Kim, Ho Sung; Choi, Choong Gon; Jung, Seung Chai; Oh, Joo Young; Lee, Jae-Hong; Roh, Jee Hoon; Shim, Woo Hyun

2017-01-01

Objective To identify potential imaging biomarkers of Alzheimer's disease by combining brain cortical thickness (CThk) and functional connectivity and to validate this model's diagnostic accuracy in a validation set. Materials and Methods Data from 98 subjects was retrospectively reviewed, including a study set (n = 63) and a validation set from the Alzheimer's Disease Neuroimaging Initiative (n = 35). From each subject, data for CThk and functional connectivity of the default mode network was extracted from structural T1-weighted and resting-state functional magnetic resonance imaging. Cortical regions with significant differences between patients and healthy controls in the correlation of CThk and functional connectivity were identified in the study set. The diagnostic accuracy of functional connectivity measures combined with CThk in the identified regions was evaluated against that in the medial temporal lobes using the validation set and application of a support vector machine. Results Group-wise differences in the correlation of CThk and default mode network functional connectivity were identified in the superior temporal (p < 0.001) and supramarginal gyrus (p = 0.007) of the left cerebral hemisphere. Default mode network functional connectivity combined with the CThk of those two regions were more accurate than that combined with the CThk of both medial temporal lobes (91.7% vs. 75%). Conclusion Combining functional information with CThk of the superior temporal and supramarginal gyri in the left cerebral hemisphere improves diagnostic accuracy, making it a potential imaging biomarker for Alzheimer's disease. PMID:29089831

PreSMA stimulation changes task-free functional connectivity in the fronto-basal-ganglia that correlates with response inhibition efficiency.

PubMed

Xu, Benjamin; Sandrini, Marco; Wang, Wen-Tung; Smith, Jason F; Sarlls, Joelle E; Awosika, Oluwole; Butman, John A; Horwitz, Barry; Cohen, Leonardo G

2016-09-01

Previous work using transcranial magnetic stimulation (TMS) demonstrated that the right presupplementary motor area (preSMA), a node in the fronto-basal-ganglia network, is critical for response inhibition. However, TMS influences interconnected regions, raising the possibility of a link between the preSMA activity and the functional connectivity within the network. To understand this relationship, we applied single-pulse TMS to the right preSMA during functional magnetic resonance imaging when the subjects were at rest to examine changes in neural activity and functional connectivity within the network in relation to the efficiency of response inhibition evaluated with a stop-signal task. The results showed that preSMA-TMS increased activation in the right inferior-frontal cortex (rIFC) and basal ganglia and modulated their task-free functional connectivity. Both the TMS-induced changes in the basal-ganglia activation and the functional connectivity between rIFC and left striatum, and of the overall network correlated with the efficiency of response inhibition and with the white-matter microstructure along the preSMA-rIFC pathway. These results suggest that the task-free functional and structural connectivity between the rIFCop and basal ganglia are critical to the efficiency of response inhibition. Hum Brain Mapp 37:3236-3249, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Disrupted sensorimotor and social–cognitive networks underlie symptoms in childhood-onset schizophrenia

PubMed Central

Gotts, Stephen J.; McAdams, Harrison M.; Greenstein, Dede; Lalonde, Francois; Clasen, Liv; Watsky, Rebecca E.; Shora, Lorie; Ordonez, Anna E.; Raznahan, Armin; Martin, Alex; Gogtay, Nitin; Rapoport, Judith

2016-01-01

Abstract See Lancaster and Hall (doi: 10.1093/awv330 ) for a scientific commentary on this article . Schizophrenia is increasingly recognized as a neurodevelopmental disorder with altered connectivity among brain networks. In the current study we examined large-scale network interactions in childhood-onset schizophrenia, a severe form of the disease with salient genetic and neurobiological abnormalities. Using a data-driven analysis of resting-state functional magnetic resonance imaging fluctuations, we characterized data from 19 patients with schizophrenia and 26 typically developing controls, group matched for age, sex, handedness, and magnitude of head motion during scanning. This approach identified 26 regions with decreased functional correlations in schizophrenia compared to controls. These regions were found to organize into two function-related networks, the first with regions associated with social and higher-level cognitive processing, and the second with regions involved in somatosensory and motor processing. Analyses of across- and within-network regional interactions revealed pronounced across-network decreases in functional connectivity in the schizophrenia group, as well as a set of across-network relationships with overall negative coupling indicating competitive or opponent network dynamics. Critically, across-network decreases in functional connectivity in schizophrenia predicted the severity of positive symptoms in the disorder, such as hallucinations and delusions. By contrast, decreases in functional connectivity within the social-cognitive network of regions predicted the severity of negative symptoms, such as impoverished speech and flattened affect. These results point toward the role that abnormal integration of sensorimotor and social-cognitive processing may play in the pathophysiology and symptomatology of schizophrenia. PMID:26493637

Stomach-brain synchrony reveals a novel, delayed-connectivity resting-state network in humans

PubMed Central

Devauchelle, Anne-Dominique; Béranger, Benoît; Tallon-Baudry, Catherine

2018-01-01

Resting-state networks offer a unique window into the brain’s functional architecture, but their characterization remains limited to instantaneous connectivity thus far. Here, we describe a novel resting-state network based on the delayed connectivity between the brain and the slow electrical rhythm (0.05 Hz) generated in the stomach. The gastric network cuts across classical resting-state networks with partial overlap with autonomic regulation areas. This network is composed of regions with convergent functional properties involved in mapping bodily space through touch, action or vision, as well as mapping external space in bodily coordinates. The network is characterized by a precise temporal sequence of activations within a gastric cycle, beginning with somato-motor cortices and ending with the extrastriate body area and dorsal precuneus. Our results demonstrate that canonical resting-state networks based on instantaneous connectivity represent only one of the possible partitions of the brain into coherent networks based on temporal dynamics. PMID:29561263

Abnormal network connectivity in frontotemporal dementia: evidence for prefrontal isolation.

PubMed

Farb, Norman A S; Grady, Cheryl L; Strother, Stephen; Tang-Wai, David F; Masellis, Mario; Black, Sandra; Freedman, Morris; Pollock, Bruce G; Campbell, Karen L; Hasher, Lynn; Chow, Tiffany W

2013-01-01

Degraded social function, disinhibition, and stereotypy are defining characteristics of frontotemporal dementia (FTD), manifesting in both the behavioral variant of frontotemporal dementia (bvFTD) and semantic dementia (SD) subtypes. Recent neuroimaging research also associates FTD with alterations in the brain's intrinsic connectivity networks. The present study explored the relationship between neural network connectivity and specific behavioral symptoms in FTD. Resting-state functional magnetic resonance imaging was employed to investigate neural network changes in bvFTD and SD. We used independent components analysis (ICA) to examine changes in frontolimbic network connectivity, as well as several metrics of local network strength, such as the fractional amplitude of low-frequency fluctuations, regional homogeneity, and seed-based functional connectivity. For each analysis, we compared each FTD subgroup to healthy controls, characterizing general and subtype-unique network changes. The relationship between abnormal connectivity in FTD and behavior disturbances was explored. Across multiple analytic approaches, both bvFTD and SD were associated with disrupted frontolimbic connectivity and elevated local connectivity within the prefrontal cortex. Even after controlling for structural atrophy, prefrontal hyperconnectivity was robustly associated with apathy scores. Frontolimbic disconnection was associated with lower disinhibition scores, suggesting that abnormal frontolimbic connectivity contributes to positive symptoms in dementia. Unique to bvFTD, stereotypy was associated with elevated default network connectivity in the right angular gyrus. The behavioral variant was also associated with marginally higher apathy scores and a more diffuse pattern of prefrontal hyperconnectivity than SD. The present findings support a theory of FTD as a disorder of frontolimbic disconnection leading to unconstrained prefrontal connectivity. Prefrontal hyperconnectivity may represent a compensatory response to the absence of affective feedback during the planning and execution of behavior. Increased reliance upon prefrontal processes in isolation from subcortical structures appears to be maladaptive and may drive behavioral withdrawal that is commonly observed in later phases of neurodegeneration. Copyright © 2012 Elsevier Ltd. All rights reserved.

Musical training induces functional and structural auditory-motor network plasticity in young adults.

PubMed

Li, Qiongling; Wang, Xuetong; Wang, Shaoyi; Xie, Yongqi; Li, Xinwei; Xie, Yachao; Li, Shuyu

2018-05-01

Playing music requires a strong coupling of perception and action mediated by multimodal integration of brain regions, which can be described as network connections measured by anatomical and functional correlations between regions. However, the structural and functional connectivities within and between the auditory and sensorimotor networks after long-term musical training remain largely uninvestigated. Here, we compared the structural connectivity (SC) and resting-state functional connectivity (rs-FC) within and between the two networks in 29 novice healthy young adults before and after musical training (piano) with those of another 27 novice participants who were evaluated longitudinally but with no intervention. In addition, a correlation analysis was performed between the changes in FC or SC with practice time in the training group. As expected, participants in the training group showed increased FC within the sensorimotor network and increased FC and SC of the auditory-motor network after musical training. Interestingly, we further found that the changes in FC within the sensorimotor network and SC of the auditory-motor network were positively correlated with practice time. Our results indicate that musical training could induce enhanced local interaction and global integration between musical performance-related regions, which provides insights into the mechanism of brain plasticity in young adults. © 2018 Wiley Periodicals, Inc.

Functional connectivity analysis of resting-state fMRI networks in nicotine dependent patients

NASA Astrophysics Data System (ADS)

Smith, Aria; Ehtemami, Anahid; Fratte, Daniel; Meyer-Baese, Anke; Zavala-Romero, Olmo; Goudriaan, Anna E.; Schmaal, Lianne; Schulte, Mieke H. J.

2016-03-01

Brain imaging studies identified brain networks that play a key role in nicotine dependence-related behavior. Functional connectivity of the brain is dynamic; it changes over time due to different causes such as learning, or quitting a habit. Functional connectivity analysis is useful in discovering and comparing patterns between functional magnetic resonance imaging (fMRI) scans of patients' brains. In the resting state, the patient is asked to remain calm and not do any task to minimize the contribution of external stimuli. The study of resting-state fMRI networks have shown functionally connected brain regions that have a high level of activity during this state. In this project, we are interested in the relationship between these functionally connected brain regions to identify nicotine dependent patients, who underwent a smoking cessation treatment. Our approach is on the comparison of the set of connections between the fMRI scans before and after treatment. We applied support vector machines, a machine learning technique, to classify patients based on receiving the treatment or the placebo. Using the functional connectivity (CONN) toolbox, we were able to form a correlation matrix based on the functional connectivity between different regions of the brain. The experimental results show that there is inadequate predictive information to classify nicotine dependent patients using the SVM classifier. We propose other classification methods be explored to better classify the nicotine dependent patients.

Comparison of large-scale human brain functional and anatomical networks in schizophrenia.

PubMed

Nelson, Brent G; Bassett, Danielle S; Camchong, Jazmin; Bullmore, Edward T; Lim, Kelvin O

2017-01-01

Schizophrenia is a disease with disruptions in thought, emotion, and behavior. The dysconnectivity hypothesis suggests these disruptions are due to aberrant brain connectivity. Many studies have identified connectivity differences but few have been able to unify gray and white matter findings into one model. Here we develop an extension of the Network-Based Statistic (NBS) called NBSm (Multimodal Network-based statistic) to compare functional and anatomical networks in schizophrenia. Structural, resting functional, and diffusion magnetic resonance imaging data were collected from 29 chronic patients with schizophrenia and 29 healthy controls. Images were preprocessed, and average time courses were extracted for 90 regions of interest (ROI). Functional connectivity matrices were estimated by pairwise correlations between wavelet coefficients of ROI time series. Following diffusion tractography, anatomical connectivity matrices were estimated by white matter streamline counts between each pair of ROIs. Global and regional strength were calculated for each modality. NBSm was used to find significant overlap between functional and anatomical components that distinguished health from schizophrenia. Global strength was decreased in patients in both functional and anatomical networks. Regional strength was decreased in all regions in functional networks and only one region in anatomical networks. NBSm identified a distinguishing functional component consisting of 46 nodes with 113 links (p < 0.001), a distinguishing anatomical component with 47 nodes and 50 links (p = 0.002), and a distinguishing intermodal component with 26 nodes (p < 0.001). NBSm is a powerful technique for understanding network-based group differences present in both anatomical and functional data. In light of the dysconnectivity hypothesis, these results provide compelling evidence for the presence of significant overlapping anatomical and functional disruption in people with schizophrenia.

Distinct patterns of functional brain connectivity correlate with objective performance and subjective beliefs

PubMed Central

Barttfeld, Pablo; Wicker, Bruno; McAleer, Phil; Belin, Pascal; Cojan, Yann; Graziano, Martín; Leiguarda, Ramón; Sigman, Mariano

2013-01-01

The degree of correspondence between objective performance and subjective beliefs varies widely across individuals. Here we demonstrate that functional brain network connectivity measured before exposure to a perceptual decision task covaries with individual objective (type-I performance) and subjective (type-II performance) accuracy. Increases in connectivity with type-II performance were observed in networks measured while participants directed attention inward (focus on respiration), but not in networks measured during states of neutral (resting state) or exogenous attention. Measures of type-I performance were less sensitive to the subjects’ specific attentional states from which the networks were derived. These results suggest the existence of functional brain networks indexing objective performance and accuracy of subjective beliefs distinctively expressed in a set of stable mental states. PMID:23801762

Localized reductions in resting-state functional connectivity in children with prenatal alcohol exposure.

PubMed

Fan, Jia; Taylor, Paul A; Jacobson, Sandra W; Molteno, Christopher D; Gohel, Suril; Biswal, Bharat B; Jacobson, Joseph L; Meintjes, Ernesta M

2017-10-01

Fetal alcohol spectrum disorders (FASD) are characterized by impairment in cognitive function that may or may not be accompanied by craniofacial anomalies, microcephaly, and/or growth retardation. Resting-state functional MRI (rs-fMRI), which examines the low-frequency component of the blood oxygen level dependent (BOLD) signal in the absence of an explicit task, provides an efficient and powerful mechanism for studying functional brain networks even in low-functioning and young subjects. Studies using independent component analysis (ICA) have identified a set of resting-state networks (RSNs) that have been linked to distinct domains of cognitive and perceptual function, which are believed to reflect the intrinsic functional architecture of the brain. This study is the first to examine resting-state functional connectivity within these RSNs in FASD. Rs-fMRI scans were performed on 38 children with FASD (19 with either full fetal alcohol syndrome (FAS) or partial FAS (PFAS), 19 nonsyndromal heavily exposed (HE)), and 19 controls, mean age 11.3 ± 0.9 years, from the Cape Town Longitudinal Cohort. Nine resting-state networks were generated by ICA. Voxelwise group comparison between a combined FAS/PFAS group and controls revealed localized dose-dependent functional connectivity reductions in five regions in separate networks: anterior default mode, salience, ventral and dorsal attention, and R executive control. The former three also showed lower connectivity in the HE group. Gray matter connectivity deficits in four of the five networks appear to be related to deficits in white matter tracts that provide intra-RSN connections. Hum Brain Mapp 38:5217-5233, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Intrinsic network connectivity and own body perception in gender dysphoria.

PubMed

Feusner, Jamie D; Lidström, Andreas; Moody, Teena D; Dhejne, Cecilia; Bookheimer, Susan Y; Savic, Ivanka

2017-08-01

Gender dysphoria (GD) is characterized by incongruence between one's identity and gender assigned at birth. The biological mechanisms of GD are unclear. We investigated brain network connectivity patterns involved in own body perception in the context of self in GD. Twenty-seven female-to-male (FtM) individuals with GD, 27 male controls, and 27 female controls underwent resting state fMRI. We compared functional connections within intrinsic connectivity networks involved in self-referential processes and own body perception -default mode network (DMN) and salience network - and visual networks, using independent components analyses. Behavioral correlates of network connectivity were also tested using self-perception ratings while viewing own body images morphed to their sex assigned at birth, and to the sex of their gender identity. FtM exhibited decreased connectivity of anterior and posterior cingulate and precuneus within the DMN compared with controls. In FtM, higher "self" ratings for bodies morphed towards the sex of their gender identity were associated with greater connectivity of the anterior cingulate within the DMN, during long viewing times. In controls, higher ratings for bodies morphed towards their gender assigned at birth were associated with right insula connectivity within the salience network, during short viewing times. Within visual networks FtM showed weaker connectivity in occipital and temporal regions. Results suggest disconnectivity within networks involved in own body perception in the context of self in GD. Moreover, perception of bodies in relation to self may be reflective rather than reflexive, as a function of mesial prefrontal processes. These may represent neurobiological correlates to the subjective disconnection between perception of body and self-identification.

Brain resting-state networks in adolescents with high-functioning autism: Analysis of spatial connectivity and temporal neurodynamics.

PubMed

Bernas, Antoine; Barendse, Evelien M; Aldenkamp, Albert P; Backes, Walter H; Hofman, Paul A M; Hendriks, Marc P H; Kessels, Roy P C; Willems, Frans M J; de With, Peter H N; Zinger, Svitlana; Jansen, Jacobus F A

2018-02-01

Autism spectrum disorder (ASD) is mainly characterized by functional and communication impairments as well as restrictive and repetitive behavior. The leading hypothesis for the neural basis of autism postulates globally abnormal brain connectivity, which can be assessed using functional magnetic resonance imaging (fMRI). Even in the absence of a task, the brain exhibits a high degree of functional connectivity, known as intrinsic, or resting-state, connectivity. Global default connectivity in individuals with autism versus controls is not well characterized, especially for a high-functioning young population. The aim of this study is to test whether high-functioning adolescents with ASD (HFA) have an abnormal resting-state functional connectivity. We performed spatial and temporal analyses on resting-state networks (RSNs) in 13 HFA adolescents and 13 IQ- and age-matched controls. For the spatial analysis, we used probabilistic independent component analysis (ICA) and a permutation statistical method to reveal the RSN differences between the groups. For the temporal analysis, we applied Granger causality to find differences in temporal neurodynamics. Controls and HFA display very similar patterns and strengths of resting-state connectivity. We do not find any significant differences between HFA adolescents and controls in the spatial resting-state connectivity. However, in the temporal dynamics of this connectivity, we did find differences in the causal effect properties of RSNs originating in temporal and prefrontal cortices. The results show a difference between HFA and controls in the temporal neurodynamics from the ventral attention network to the salience-executive network: a pathway involving cognitive, executive, and emotion-related cortices. We hypothesized that this weaker dynamic pathway is due to a subtle trigger challenging the cognitive state prior to the resting state.

Identifying aMCI with Functional Connectivity Network Characteristics based on Subtle AAL Atlas.

PubMed

Zhuo, Zhizheng; Mo, Xiao; Ma, Xiangyu; Han, Ying; Li, Haiyun

2018-05-02

To investigate the subtle functional connectivity alterations of aMCI based on AAL atlas with 1024 regions (AAL_1024 atlas). Functional MRI images of 32 aMCI patients (Male/Female:15/17, Ages:66.8±8.36y) and 35 normal controls (Male/Female:13/22, Ages: 62.4±8.14y) were obtained in this study. Firstly, functional connectivity networks were constructed by Pearson's Correlation based on the subtle AAL_1024 atlas. Then, local and global network parameters were calculated from the thresholding functional connectivity matrices. Finally, multiple-comparison analysis was performed on these parameters to find the functional network alterations of aMCI. And furtherly, a couple of classifiers were adopted to identify the aMCI by using the network parameters. More subtle local brain functional alterations were detected by using AAL_1024 atlas. And the predominate nodes including hippocampus, inferior temporal gyrus, inferior parietal gyrus were identified which was not detected by AAL_90 atlas. The identification of aMCI from normal controls were significantly improved with the highest accuracy (98.51%), sensitivity (100%) and specificity (97.14%) compared to those (88.06%, 84.38% and 91.43% for the highest accuracy, sensitivity and specificity respectively) obtained by using AAL_90 atlas. More subtle functional connectivity alterations of aMCI could be found based on AAL_1024 atlas than those based on AAL_90 atlas. Besides, the identification of aMCI could also be improved. Copyright © 2018. Published by Elsevier B.V.

Brain network connectivity in individuals with schizophrenia and their siblings.

PubMed

Repovs, Grega; Csernansky, John G; Barch, Deanna M

2011-05-15

Research on brain activity in schizophrenia has shown that changes in the function of any single region cannot explain the range of cognitive and affective impairments in this illness. Rather, neural circuits that support sensory, cognitive, and emotional processes are now being investigated as substrates for cognitive and affective impairments in schizophrenia, a shift in focus consistent with long-standing hypotheses about schizophrenia as a disconnection syndrome. Our goal was to further examine alterations in functional connectivity within and between the default mode network and three cognitive control networks (frontal-parietal, cingulo-opercular, and cerebellar) as a basis for such impairments. Resting state functional magnetic resonance imaging was collected from 40 individuals with DSM-IV-TR schizophrenia, 31 siblings of individuals with schizophrenia, 15 healthy control subjects, and 18 siblings of healthy control subjects while they rested quietly with their eyes closed. Connectivity metrics were compared between patients and control subjects for both within- and between-network connections and were used to predict clinical symptoms and cognitive function. Individuals with schizophrenia showed reduced distal and somewhat enhanced local connectivity between the cognitive control networks compared with control subjects. Additionally, greater connectivity between the frontal-parietal and cerebellar regions was robustly predictive of better cognitive performance across groups and predictive of fewer disorganization symptoms among patients. These results are consistent with the hypothesis that impairments of executive function and cognitive control result from disruption in the coordination of activity across brain networks and additionally suggest that these might reflect impairments in normal pattern of brain connectivity development. Copyright © 2011 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

Flexible modulation of network connectivity related to cognition in Alzheimer's disease.

PubMed

McLaren, Donald G; Sperling, Reisa A; Atri, Alireza

2014-10-15

Functional neuroimaging tools, such as fMRI methods, may elucidate the neural correlates of clinical, behavioral, and cognitive performance. Most functional imaging studies focus on regional task-related activity or resting state connectivity rather than how changes in functional connectivity across conditions and tasks are related to cognitive and behavioral performance. To investigate the promise of characterizing context-dependent connectivity-behavior relationships, this study applies the method of generalized psychophysiological interactions (gPPI) to assess the patterns of associative-memory-related fMRI hippocampal functional connectivity in Alzheimer's disease (AD) associated with performance on memory and other cognitively demanding neuropsychological tests and clinical measures. Twenty-four subjects with mild AD dementia (ages 54-82, nine females) participated in a face-name paired-associate encoding memory study. Generalized PPI analysis was used to estimate the connectivity between the hippocampus and the whole brain during encoding. The difference in hippocampal-whole brain connectivity between encoding novel and encoding repeated face-name pairs was used in multiple-regression analyses as an independent predictor for 10 behavioral, neuropsychological and clinical tests. The analysis revealed connectivity-behavior relationships that were distributed, dynamically overlapping, and task-specific within and across intrinsic networks; hippocampal-whole brain connectivity-behavior relationships were not isolated to single networks, but spanned multiple brain networks. Importantly, these spatially distributed performance patterns were unique for each measure. In general, out-of-network behavioral associations with encoding novel greater than repeated face-name pairs hippocampal-connectivity were observed in the default-mode network, while correlations with encoding repeated greater than novel face-name pairs hippocampal-connectivity were observed in the executive control network (p<0.05, cluster corrected). Psychophysiological interactions revealed significantly more extensive and robust associations between paired-associate encoding task-dependent hippocampal-whole brain connectivity and performance on memory and behavioral/clinical measures than previously revealed by standard activity-behavior analysis. Compared to resting state and task-activation methods, gPPI analyses may be more sensitive to reveal additional complementary information regarding subtle within- and between-network relations. The patterns of robust correlations between hippocampal-whole brain connectivity and behavioral measures identified here suggest that there are 'coordinated states' in the brain; that the dynamic range of these states is related to behavior and cognition; and that these states can be observed and quantified, even in individuals with mild AD. Copyright © 2014 Elsevier Inc. All rights reserved.

Altered attentional control over the salience network in complex regional pain syndrome.

PubMed

Kim, Jungyoon; Kang, Ilhyang; Chung, Yong-An; Kim, Tae-Suk; Namgung, Eun; Lee, Suji; Oh, Jin Kyoung; Jeong, Hyeonseok S; Cho, Hanbyul; Kim, Myeong Ju; Kim, Tammy D; Choi, Soo Hyun; Lim, Soo Mee; Lyoo, In Kyoon; Yoon, Sujung

2018-05-10

The degree and salience of pain have been known to be constantly monitored and modulated by the brain. In the case of maladaptive neural responses as reported in centralized pain conditions such as complex regional pain syndrome (CRPS), the perception of pain is amplified and remains elevated even without sustained peripheral pain inputs. Given that the attentional state of the brain greatly influences the perception and interpretation of pain, we investigated the role of the attention network and its dynamic interactions with other pain-related networks of the brain in CRPS. We examined alterations in the intra- and inter-network functional connectivities in 21 individuals with CRPS and 49 controls. CRPS-related reduction in intra-network functional connectivity was found in the attention network. Individuals with CRPS had greater inter-network connectivities between the attention and salience networks as compared with healthy controls. Furthermore, individuals within the CRPS group with high levels of pain catastrophizing showed greater inter-network connectivities between the attention and salience networks. Taken together, the current findings suggest that these altered connectivities may be potentially associated with the maladaptive pain coping as found in CRPS patients.

Local functional connectivity suggests functional immaturity in children with attention-deficit/hyperactivity disorder.

PubMed

Marcos-Vidal, Luis; Martínez-García, Magdalena; Pretus, Clara; Garcia-Garcia, David; Martínez, Kenia; Janssen, Joost; Vilarroya, Oscar; Castellanos, Francisco X; Desco, Manuel; Sepulcre, Jorge; Carmona, Susanna

2018-06-01

Previous studies have associated Attention-Deficit/Hyperactivity Disorder (ADHD) with a maturational lag of brain functional networks. Functional connectivity of the human brain changes from primarily local to more distant connectivity patterns during typical development. Under the maturational lag hypothesis, we expect children with ADHD to exhibit increased local connectivity and decreased distant connectivity compared with neurotypically developing (ND) children. We applied a graph-theory method to compute local and distant connectivity levels and cross-sectionally compared them in a sample of 120 children with ADHD and 120 age-matched ND children (age range = 7-17 years). In addition, we measured if potential group differences in local and distant connectivity were stable across the age range considered. Finally, we assessed the clinical relevance of observed group differences by correlating the connectivity levels and ADHD symptoms severity separately for each group. Children with ADHD exhibited more local connectivity than age-matched ND children in multiple brain regions, mainly overlapping with default mode, fronto-parietal and ventral attentional functional networks (p < .05- threshold free-cluster enhancement-family-wise error). We detected an atypical developmental pattern of local connectivity in somatomotor regions, that is, decreases with age in ND children, and increases with age in children with ADHD. Furthermore, local connectivity within somatomotor areas correlated positively with clinical severity of ADHD symptoms, both in ADHD and ND children. Results suggest an immature functional state of multiple brain networks in children with ADHD. Whereas the ADHD diagnosis is associated with the integrity of the system comprising the fronto-parietal, default mode and ventral attentional networks, the severity of clinical symptoms is related to atypical functional connectivity within somatomotor areas. Additionally, our findings are in line with the view of ADHD as a disorder of deviated maturational trajectories, mainly affecting somatomotor areas, rather than delays that normalize with age. © 2018 Wiley Periodicals, Inc.

The Semantic Network at Work and Rest: Differential Connectivity of Anterior Temporal Lobe Subregions.

PubMed

Jackson, Rebecca L; Hoffman, Paul; Pobric, Gorana; Lambon Ralph, Matthew A

2016-02-03

The anterior temporal lobe (ATL) makes a critical contribution to semantic cognition. However, the functional connectivity of the ATL and the functional network underlying semantic cognition has not been elucidated. In addition, subregions of the ATL have distinct functional properties and thus the potential differential connectivity between these subregions requires investigation. We explored these aims using both resting-state and active semantic task data in humans in combination with a dual-echo gradient echo planar imaging (EPI) paradigm designed to ensure signal throughout the ATL. In the resting-state analysis, the ventral ATL (vATL) and anterior middle temporal gyrus (MTG) were shown to connect to areas responsible for multimodal semantic cognition, including bilateral ATL, inferior frontal gyrus, medial prefrontal cortex, angular gyrus, posterior MTG, and medial temporal lobes. In contrast, the anterior superior temporal gyrus (STG)/superior temporal sulcus was connected to a distinct set of auditory and language-related areas, including bilateral STG, precentral and postcentral gyri, supplementary motor area, supramarginal gyrus, posterior temporal cortex, and inferior and middle frontal gyri. Complementary analyses of functional connectivity during an active semantic task were performed using a psychophysiological interaction (PPI) analysis. The PPI analysis highlighted the same semantic regions suggesting a core semantic network active during rest and task states. This supports the necessity for semantic cognition in internal processes occurring during rest. The PPI analysis showed additional connectivity of the vATL to regions of occipital and frontal cortex. These areas strongly overlap with regions found to be sensitive to executively demanding, controlled semantic processing. Previous studies have shown that semantic cognition depends on subregions of the anterior temporal lobe (ATL). However, the network of regions functionally connected to these subregions has not been demarcated. Here, we show that these ventrolateral anterior temporal subregions form part of a network responsible for semantic processing during both rest and an explicit semantic task. This demonstrates the existence of a core functional network responsible for multimodal semantic cognition regardless of state. Distinct connectivity is identified in the superior ATL, which is connected to auditory and language areas. Understanding the functional connectivity of semantic cognition allows greater understanding of how this complex process may be performed and the role of distinct subregions of the anterior temporal cortex. Copyright © 2016 Jackson et al.

The Semantic Network at Work and Rest: Differential Connectivity of Anterior Temporal Lobe Subregions

PubMed Central

Jackson, Rebecca L.; Hoffman, Paul; Pobric, Gorana

2016-01-01

The anterior temporal lobe (ATL) makes a critical contribution to semantic cognition. However, the functional connectivity of the ATL and the functional network underlying semantic cognition has not been elucidated. In addition, subregions of the ATL have distinct functional properties and thus the potential differential connectivity between these subregions requires investigation. We explored these aims using both resting-state and active semantic task data in humans in combination with a dual-echo gradient echo planar imaging (EPI) paradigm designed to ensure signal throughout the ATL. In the resting-state analysis, the ventral ATL (vATL) and anterior middle temporal gyrus (MTG) were shown to connect to areas responsible for multimodal semantic cognition, including bilateral ATL, inferior frontal gyrus, medial prefrontal cortex, angular gyrus, posterior MTG, and medial temporal lobes. In contrast, the anterior superior temporal gyrus (STG)/superior temporal sulcus was connected to a distinct set of auditory and language-related areas, including bilateral STG, precentral and postcentral gyri, supplementary motor area, supramarginal gyrus, posterior temporal cortex, and inferior and middle frontal gyri. Complementary analyses of functional connectivity during an active semantic task were performed using a psychophysiological interaction (PPI) analysis. The PPI analysis highlighted the same semantic regions suggesting a core semantic network active during rest and task states. This supports the necessity for semantic cognition in internal processes occurring during rest. The PPI analysis showed additional connectivity of the vATL to regions of occipital and frontal cortex. These areas strongly overlap with regions found to be sensitive to executively demanding, controlled semantic processing. SIGNIFICANCE STATEMENT Previous studies have shown that semantic cognition depends on subregions of the anterior temporal lobe (ATL). However, the network of regions functionally connected to these subregions has not been demarcated. Here, we show that these ventrolateral anterior temporal subregions form part of a network responsible for semantic processing during both rest and an explicit semantic task. This demonstrates the existence of a core functional network responsible for multimodal semantic cognition regardless of state. Distinct connectivity is identified in the superior ATL, which is connected to auditory and language areas. Understanding the functional connectivity of semantic cognition allows greater understanding of how this complex process may be performed and the role of distinct subregions of the anterior temporal cortex. PMID:26843633

Changes in the interaction of resting-state neural networks from adolescence to adulthood.

PubMed

Stevens, Michael C; Pearlson, Godfrey D; Calhoun, Vince D

2009-08-01

This study examined how the mutual interactions of functionally integrated neural networks during resting-state fMRI differed between adolescence and adulthood. Independent component analysis (ICA) was used to identify functionally connected neural networks in 100 healthy participants aged 12-30 years. Hemodynamic timecourses that represented integrated neural network activity were analyzed with tools that quantified system "causal density" estimates, which indexed the proportion of significant Granger causality relationships among system nodes. Mutual influences among networks decreased with age, likely reflecting stronger within-network connectivity and more efficient between-network influences with greater development. Supplemental tests showed that this normative age-related reduction in causal density was accompanied by fewer significant connections to and from each network, regional increases in the strength of functional integration within networks, and age-related reductions in the strength of numerous specific system interactions. The latter included paths between lateral prefrontal-parietal circuits and "default mode" networks. These results contribute to an emerging understanding that activity in widely distributed networks thought to underlie complex cognition influences activity in other networks. (c) 2009 Wiley-Liss, Inc.

Dissociable Temporo-Parietal Memory Networks Revealed by Functional Connectivity during Episodic Retrieval

PubMed Central

Hirose, Satoshi; Kimura, Hiroko M.; Jimura, Koji; Kunimatsu, Akira; Abe, Osamu; Ohtomo, Kuni; Miyashita, Yasushi; Konishi, Seiki

2013-01-01

Episodic memory retrieval most often recruits multiple separate processes that are thought to involve different temporal regions. Previous studies suggest dissociable regions in the left lateral parietal cortex that are associated with the retrieval processes. Moreover, studies using resting-state functional connectivity (RSFC) have provided evidence for the temporo-parietal memory networks that may support the retrieval processes. In this functional MRI study, we tested functional significance of the memory networks by examining functional connectivity of brain activity during episodic retrieval in the temporal and parietal regions of the memory networks. Recency judgments, judgments of the temporal order of past events, can be achieved by at least two retrieval processes, relational and item-based. Neuroimaging results revealed several temporal and parietal activations associated with relational/item-based recency judgments. Significant RSFC was observed between one parahippocampal region and one left lateral parietal region associated with relational recency judgments, and between four lateral temporal regions and another left lateral parietal region associated with item-based recency judgments. Functional connectivity during task was found to be significant between the parahippocampal region and the parietal region in the RSFC network associated with relational recency judgments. However, out of the four tempo-parietal RSFC networks associated with item-based recency judgments, only one of them (between the left posterior lateral temporal region and the left lateral parietal region) showed significant functional connectivity during task. These results highlight the contrasting roles of the parahippocampal and the lateral temporal regions in recency judgments, and suggest that only a part of the tempo-parietal RSFC networks are recruited to support particular retrieval processes. PMID:24009657

Lifespan anxiety is reflected in human amygdala cortical connectivity

PubMed Central

He, Ye; Xu, Ting; Zhang, Wei

2016-01-01

Abstract The amygdala plays a pivotal role in processing anxiety and connects to large‐scale brain networks. However, intrinsic functional connectivity (iFC) between amygdala and these networks has rarely been examined in relation to anxiety, especially across the lifespan. We employed resting‐state functional MRI data from 280 healthy adults (18–83.5 yrs) to elucidate the relationship between anxiety and amygdala iFC with common cortical networks including the visual network, somatomotor network, dorsal attention network, ventral attention network, limbic network, frontoparietal network, and default network. Global and network‐specific iFC were separately computed as mean iFC of amygdala with the entire cerebral cortex and each cortical network. We detected negative correlation between global positive amygdala iFC and trait anxiety. Network‐specific associations between amygdala iFC and anxiety were also detectable. Specifically, the higher iFC strength between the left amygdala and the limbic network predicted lower state anxiety. For the trait anxiety, left amygdala anxiety–connectivity correlation was observed in both somatomotor and dorsal attention networks, whereas the right amygdala anxiety–connectivity correlation was primarily distributed in the frontoparietal and ventral attention networks. Ventral attention network exhibited significant anxiety–gender interactions on its iFC with amygdala. Together with findings from additional vertex‐wise analysis, these data clearly indicated that both low‐level sensory networks and high‐level associative networks could contribute to detectable predictions of anxiety behaviors by their iFC profiles with the amygdala. This set of systems neuroscience findings could lead to novel functional network models on neural correlates of human anxiety and provide targets for novel treatment strategies on anxiety disorders. Hum Brain Mapp 37:1178–1193, 2016. © 2015 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc. PMID:26859312

The development of hub architecture in the human functional brain network.

PubMed

Hwang, Kai; Hallquist, Michael N; Luna, Beatriz

2013-10-01

Functional hubs are brain regions that play a crucial role in facilitating communication among parallel, distributed brain networks. The developmental emergence and stability of hubs, however, is not well understood. The current study used measures of network topology drawn from graph theory to investigate the development of functional hubs in 99 participants, 10-20 years of age. We found that hub architecture was evident in late childhood and was stable from adolescence to early adulthood. Connectivity between hub and non-hub ("spoke") regions, however, changed with development. From childhood to adolescence, the strength of connections between frontal hubs and cortical and subcortical spoke regions increased. From adolescence to adulthood, hub-spoke connections with frontal hubs were stable, whereas connectivity between cerebellar hubs and cortical spoke regions increased. Our findings suggest that a developmentally stable functional hub architecture provides the foundation of information flow in the brain, whereas connections between hubs and spokes continue to develop, possibly supporting mature cognitive function.

The relative efficiency of modular and non-modular networks of different size

PubMed Central

Tosh, Colin R.; McNally, Luke

2015-01-01

Most biological networks are modular but previous work with small model networks has indicated that modularity does not necessarily lead to increased functional efficiency. Most biological networks are large, however, and here we examine the relative functional efficiency of modular and non-modular neural networks at a range of sizes. We conduct a detailed analysis of efficiency in networks of two size classes: ‘small’ and ‘large’, and a less detailed analysis across a range of network sizes. The former analysis reveals that while the modular network is less efficient than one of the two non-modular networks considered when networks are small, it is usually equally or more efficient than both non-modular networks when networks are large. The latter analysis shows that in networks of small to intermediate size, modular networks are much more efficient that non-modular networks of the same (low) connective density. If connective density must be kept low to reduce energy needs for example, this could promote modularity. We have shown how relative functionality/performance scales with network size, but the precise nature of evolutionary relationship between network size and prevalence of modularity will depend on the costs of connectivity. PMID:25631996

Structural network efficiency is associated with cognitive impairment in small-vessel disease.

PubMed

Lawrence, Andrew J; Chung, Ai Wern; Morris, Robin G; Markus, Hugh S; Barrick, Thomas R

2014-07-22

To characterize brain network connectivity impairment in cerebral small-vessel disease (SVD) and its relationship with MRI disease markers and cognitive impairment. A cross-sectional design applied graph-based efficiency analysis to deterministic diffusion tensor tractography data from 115 patients with lacunar infarction and leukoaraiosis and 50 healthy individuals. Structural connectivity was estimated between 90 cortical and subcortical brain regions and efficiency measures of resulting graphs were analyzed. Networks were compared between SVD and control groups, and associations between efficiency measures, conventional MRI disease markers, and cognitive function were tested. Brain diffusion tensor tractography network connectivity was significantly reduced in SVD: networks were less dense, connection weights were lower, and measures of network efficiency were significantly disrupted. The degree of brain network disruption was associated with MRI measures of disease severity and cognitive function. In multiple regression models controlling for confounding variables, associations with cognition were stronger for network measures than other MRI measures including conventional diffusion tensor imaging measures. A total mediation effect was observed for the association between fractional anisotropy and mean diffusivity measures and executive function and processing speed. Brain network connectivity in SVD is disturbed, this disturbance is related to disease severity, and within a mediation framework fully or partly explains previously observed associations between MRI measures and SVD-related cognitive dysfunction. These cross-sectional results highlight the importance of network disruption in SVD and provide support for network measures as a disease marker in treatment studies. © 2014 American Academy of Neurology.

Structural network efficiency is associated with cognitive impairment in small-vessel disease

PubMed Central

Chung, Ai Wern; Morris, Robin G.; Markus, Hugh S.; Barrick, Thomas R.

2014-01-01

Objective: To characterize brain network connectivity impairment in cerebral small-vessel disease (SVD) and its relationship with MRI disease markers and cognitive impairment. Methods: A cross-sectional design applied graph-based efficiency analysis to deterministic diffusion tensor tractography data from 115 patients with lacunar infarction and leukoaraiosis and 50 healthy individuals. Structural connectivity was estimated between 90 cortical and subcortical brain regions and efficiency measures of resulting graphs were analyzed. Networks were compared between SVD and control groups, and associations between efficiency measures, conventional MRI disease markers, and cognitive function were tested. Results: Brain diffusion tensor tractography network connectivity was significantly reduced in SVD: networks were less dense, connection weights were lower, and measures of network efficiency were significantly disrupted. The degree of brain network disruption was associated with MRI measures of disease severity and cognitive function. In multiple regression models controlling for confounding variables, associations with cognition were stronger for network measures than other MRI measures including conventional diffusion tensor imaging measures. A total mediation effect was observed for the association between fractional anisotropy and mean diffusivity measures and executive function and processing speed. Conclusions: Brain network connectivity in SVD is disturbed, this disturbance is related to disease severity, and within a mediation framework fully or partly explains previously observed associations between MRI measures and SVD-related cognitive dysfunction. These cross-sectional results highlight the importance of network disruption in SVD and provide support for network measures as a disease marker in treatment studies. PMID:24951477

Disrupted functional connectome in antisocial personality disorder.

PubMed

Jiang, Weixiong; Shi, Feng; Liao, Jian; Liu, Huasheng; Wang, Tao; Shen, Celina; Shen, Hui; Hu, Dewen; Wang, Wei; Shen, Dinggang

2017-08-01

Studies on antisocial personality disorder (ASPD) subjects focus on brain functional alterations in relation to antisocial behaviors. Neuroimaging research has identified a number of focal brain regions with abnormal structures or functions in ASPD. However, little is known about the connections among brain regions in terms of inter-regional whole-brain networks in ASPD patients, as well as possible alterations of brain functional topological organization. In this study, we employ resting-state functional magnetic resonance imaging (R-fMRI) to examine functional connectome of 32 ASPD patients and 35 normal controls by using a variety of network properties, including small-worldness, modularity, and connectivity. The small-world analysis reveals that ASPD patients have increased path length and decreased network efficiency, which implies a reduced ability of global integration of whole-brain functions. Modularity analysis suggests ASPD patients have decreased overall modularity, merged network modules, and reduced intra- and inter-module connectivities related to frontal regions. Also, network-based statistics show that an internal sub-network, composed of 16 nodes and 16 edges, is significantly affected in ASPD patients, where brain regions are mostly located in the fronto-parietal control network. These results suggest that ASPD is associated with both reduced brain integration and segregation in topological organization of functional brain networks, particularly in the fronto-parietal control network. These disruptions may contribute to disturbances in behavior and cognition in patients with ASPD. Our findings may provide insights into a deeper understanding of functional brain networks of ASPD.

Disrupted functional connectome in antisocial personality disorder

PubMed Central

Jiang, Weixiong; Shi, Feng; Liao, Jian; Liu, Huasheng; Wang, Tao; Shen, Celina; Shen, Hui; Hu, Dewen

2017-01-01

Studies on antisocial personality disorder (ASPD) subjects focus on brain functional alterations in relation to antisocial behaviors. Neuroimaging research has identified a number of focal brain regions with abnormal structures or functions in ASPD. However, little is known about the connections among brain regions in terms of inter-regional whole-brain networks in ASPD patients, as well as possible alterations of brain functional topological organization. In this study, we employ resting-state functional magnetic resonance imaging (R-fMRI) to examine functional connectome of 32 ASPD patients and 35 normal controls by using a variety of network properties, including small-worldness, modularity, and connectivity. The small-world analysis reveals that ASPD patients have increased path length and decreased network efficiency, which implies a reduced ability of global integration of whole-brain functions. Modularity analysis suggests ASPD patients have decreased overall modularity, merged network modules, and reduced intra- and inter-module connectivities related to frontal regions. Also, network-based statistics show that an internal sub-network, composed of 16 nodes and 16 edges, is significantly affected in ASPD patients, where brain regions are mostly located in the fronto-parietal control network. These results suggest that ASPD is associated with both reduced brain integration and segregation in topological organization of functional brain networks, particularly in the fronto-parietal control network. These disruptions may contribute to disturbances in behavior and cognition in patients with ASPD. Our findings may provide insights into a deeper understanding of functional brain networks of ASPD. PMID:27541949

Neural Connectivity Evidence for a Categorical-Dimensional Hybrid Model of Autism Spectrum Disorder.

PubMed

Elton, Amanda; Di Martino, Adriana; Hazlett, Heather Cody; Gao, Wei

2016-07-15

Autism spectrum disorder (ASD) encompasses a complex manifestation of symptoms that include deficits in social interaction and repetitive or stereotyped interests and behaviors. In keeping with the increasing recognition of the dimensional characteristics of ASD symptoms and the categorical nature of a diagnosis, we sought to delineate the neural mechanisms of ASD symptoms based on the functional connectivity of four known neural networks (i.e., default mode network, dorsal attention network, salience network, and executive control network). We leveraged an open data resource (Autism Brain Imaging Data Exchange) providing resting-state functional magnetic resonance imaging data sets from 90 boys with ASD and 95 typically developing boys. This data set also included the Social Responsiveness Scale as a dimensional measure of ASD traits. Seed-based functional connectivity was paired with linear regression to identify functional connectivity abnormalities associated with categorical effects of ASD diagnosis, dimensional effects of ASD-like behaviors, and their interaction. Our results revealed the existence of dimensional mechanisms of ASD uniquely affecting each network based on the presence of connectivity-behavioral relationships; these were independent of diagnostic category. However, we also found evidence of categorical differences (i.e., diagnostic group differences) in connectivity strength for each network as well as categorical differences in connectivity-behavioral relationships (i.e., diagnosis-by-behavior interactions), supporting the coexistence of categorical mechanisms of ASD. Our findings support a hybrid model for ASD characterization that includes a combination of categorical and dimensional brain mechanisms and provide a novel understanding of the neural underpinnings of ASD. Copyright © 2016 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

Functional connectivity and information flow of the respiratory neural network in chronic obstructive pulmonary disease.

PubMed

Yu, Lianchun; De Mazancourt, Marine; Hess, Agathe; Ashadi, Fakhrul R; Klein, Isabelle; Mal, Hervé; Courbage, Maurice; Mangin, Laurence

2016-08-01

Breathing involves a complex interplay between the brainstem automatic network and cortical voluntary command. How these brain regions communicate at rest or during inspiratory loading is unknown. This issue is crucial for several reasons: (i) increased respiratory loading is a major feature of several respiratory diseases, (ii) failure of the voluntary motor and cortical sensory processing drives is among the mechanisms that precede acute respiratory failure, (iii) several cerebral structures involved in responding to inspiratory loading participate in the perception of dyspnea, a distressing symptom in many disease. We studied functional connectivity and Granger causality of the respiratory network in controls and patients with chronic obstructive pulmonary disease (COPD), at rest and during inspiratory loading. Compared with those of controls, the motor cortex area of patients exhibited decreased connectivity with their contralateral counterparts and no connectivity with the brainstem. In the patients, the information flow was reversed at rest with the source of the network shifted from the medulla towards the motor cortex. During inspiratory loading, the system was overwhelmed and the motor cortex became the sink of the network. This major finding may help to understand why some patients with COPD are prone to acute respiratory failure. Network connectivity and causality were related to lung function and illness severity. We validated our connectivity and causality results with a mathematical model of neural network. Our findings suggest a new therapeutic strategy involving the modulation of brain activity to increase motor cortex functional connectivity and improve respiratory muscles performance in patients. Hum Brain Mapp 37:2736-2754, 2016. © 2016 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc. © 2016 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

Differential Motor and Prefrontal Cerebello-Cortical Network Development: Evidence from Multimodal Neuroimaging

PubMed Central

Bernard, Jessica A.; Orr, Joseph M.; Mittal, Vijay A.

2015-01-01

While our understanding of cerebellar structural development through adolescence and young adulthood has expanded, we still lack knowledge of the developmental patterns of cerebellar networks during this critical portion of the lifespan. Volume in lateral posterior cerebellar regions associated with cognition and the prefrontal cortex develops more slowly, reaching their peak volume in adulthood, particularly as compared to motor Lobule V. We predicted that resting state functional connectivity of the lateral posterior regions would show a similar pattern of development during adolescence and young adulthood. That is, we expected to see changes over time in Crus I and Crus II connectivity with the cortex, but no changes in Lobule V connectivity. Additionally, we were interested in how structural connectivity changes in cerebello-thalamo-cortical white matter are related to changes in functional connectivity. A sample of 23 individuals between 12 and 21 years old underwent neuroimaging scans at baseline and 12-months later. Functional networks of Crus I and Crus II showed significant connectivity decreases over 12-months, though there were no differences in Lobule V. Furthermore, these functional connectivity changes were correlated with increases in white matter structural integrity in the corresponding cerebello-thalamo-cortical white matter tract. We suggest that these functional network changes are due to both later pruning in the prefrontal cortex as well as further development of the white matter tracts linking these brain regions. PMID:26391125

Multimodal Investigation of Network Level Effects Using Intrinsic Functional Connectivity, Anatomical Covariance, and Structure-to-Function Correlations in Unmedicated Major Depressive Disorder

PubMed Central

Scheinost, Dustin; Holmes, Sophie E; DellaGioia, Nicole; Schleifer, Charlie; Matuskey, David; Abdallah, Chadi G; Hampson, Michelle; Krystal, John H; Anticevic, Alan; Esterlis, Irina

2018-01-01

Converging evidence suggests that major depressive disorder (MDD) affects multiple large-scale brain networks. Analyses of the correlation or covariance of regional brain structure and function applied to structural and functional MRI data may provide insights into systems-level organization and structure-to-function correlations in the brain in MDD. This study applied tensor-based morphometry and intrinsic connectivity distribution to identify regions of altered volume and intrinsic functional connectivity in data from unmedicated individuals with MDD (n=17) and healthy comparison participants (HC, n=20). These regions were then used as seeds for exploratory anatomical covariance and connectivity analyses. Reduction in volume in the anterior cingulate cortex (ACC) and lower structural covariance between the ACC and the cerebellum were observed in the MDD group. Additionally, individuals with MDD had significantly lower whole-brain intrinsic functional connectivity in the medial prefrontal cortex (mPFC). This mPFC region showed altered connectivity to the ventral lateral PFC (vlPFC) and local circuitry in MDD. Global connectivity in the ACC was negatively correlated with reported depressive symptomatology. The mPFC–vlPFC connectivity was positively correlated with depressive symptoms. Finally, we observed increased structure-to-function correlation in the PFC/ACC in the MDD group. Although across all analysis methods and modalities alterations in the PFC/ACC were a common finding, each modality and method detected alterations in subregions belonging to distinct large-scale brain networks. These exploratory results support the hypothesis that MDD is a systems level disorder affecting multiple brain networks located in the PFC and provide new insights into the pathophysiology of this disorder. PMID:28944772

Multimodal Investigation of Network Level Effects Using Intrinsic Functional Connectivity, Anatomical Covariance, and Structure-to-Function Correlations in Unmedicated Major Depressive Disorder.

PubMed

Scheinost, Dustin; Holmes, Sophie E; DellaGioia, Nicole; Schleifer, Charlie; Matuskey, David; Abdallah, Chadi G; Hampson, Michelle; Krystal, John H; Anticevic, Alan; Esterlis, Irina

2018-04-01

Converging evidence suggests that major depressive disorder (MDD) affects multiple large-scale brain networks. Analyses of the correlation or covariance of regional brain structure and function applied to structural and functional MRI data may provide insights into systems-level organization and structure-to-function correlations in the brain in MDD. This study applied tensor-based morphometry and intrinsic connectivity distribution to identify regions of altered volume and intrinsic functional connectivity in data from unmedicated individuals with MDD (n=17) and healthy comparison participants (HC, n=20). These regions were then used as seeds for exploratory anatomical covariance and connectivity analyses. Reduction in volume in the anterior cingulate cortex (ACC) and lower structural covariance between the ACC and the cerebellum were observed in the MDD group. Additionally, individuals with MDD had significantly lower whole-brain intrinsic functional connectivity in the medial prefrontal cortex (mPFC). This mPFC region showed altered connectivity to the ventral lateral PFC (vlPFC) and local circuitry in MDD. Global connectivity in the ACC was negatively correlated with reported depressive symptomatology. The mPFC-vlPFC connectivity was positively correlated with depressive symptoms. Finally, we observed increased structure-to-function correlation in the PFC/ACC in the MDD group. Although across all analysis methods and modalities alterations in the PFC/ACC were a common finding, each modality and method detected alterations in subregions belonging to distinct large-scale brain networks. These exploratory results support the hypothesis that MDD is a systems level disorder affecting multiple brain networks located in the PFC and provide new insights into the pathophysiology of this disorder.

Perturbed connectivity of the amygdala and its subregions with the central executive and default mode networks in chronic pain.

PubMed

Jiang, Ying; Oathes, Desmond; Hush, Julia; Darnall, Beth; Charvat, Mylea; Mackey, Sean; Etkin, Amit

2016-09-01

Maladaptive responses to pain-related distress, such as pain catastrophizing, amplify the impairments associated with chronic pain. Many of these aspects of chronic pain are similar to affective distress in clinical anxiety disorders. In light of the role of the amygdala in pain and affective distress, disruption of amygdalar functional connectivity in anxiety states, and its implication in the response to noxious stimuli, we investigated amygdala functional connectivity in 17 patients with chronic low back pain and 17 healthy comparison subjects, with respect to normal targets of amygdala subregions (basolateral vs centromedial nuclei), and connectivity to large-scale cognitive-emotional networks, including the default mode network, central executive network, and salience network. We found that patients with chronic pain had exaggerated and abnormal amygdala connectivity with central executive network, which was most exaggerated in patients with the greatest pain catastrophizing. We also found that the normally basolateral-predominant amygdala connectivity to the default mode network was blunted in patients with chronic pain. Our results therefore highlight the importance of the amygdala and its network-level interaction with large-scale cognitive/affective cortical networks in chronic pain, and help link the neurobiological mechanisms of cognitive theories for pain with other clinical states of affective distress.

Convergent and divergent intranetwork and internetwork connectivity patterns in patients with remitted late-life depression and amnestic mild cognitive impairment.

PubMed

Chen, Jiu; Shu, Hao; Wang, Zan; Zhan, Yafeng; Liu, Duan; Liao, Wenxiang; Xu, Lin; Liu, Yong; Zhang, Zhijun

2016-10-01

Both remitted late-life depression (rLLD) and amnesiac mild cognitive impairment (aMCI) alter brain functions in specific regions of the brain. They are also disconnection syndromes that are associated with a high risk of developing Alzheimer's disease (AD). Resting-state functional connectivity magnetic resonance imaging (rs-fcMRI) was performed to define the shared and distinct aberrant patterns in intranetwork and internetwork connectivity between rLLD and aMCI and to determine how knowledge of these differences might contribute to our essential understanding of the altered sequences involved in functional systems both inside and outside of resting-state networks. We used rs-fcMRI to investigate in five functionally well-defined brain networks in two large cohorts of subjects at high risk for AD (55 rLLD and 87 aMCI) and 114 healthy controls (HC). A reduced degree of functional connectivity was observed in the bilateral inferior temporal cortex and supplemental motor area, and reduced correlations were observed within the sensory-motor network (SMN) and in the default mode network (DMN)-control network (CON) pair in the rLLD group than the HC group. The aMCI group showed only focal functional changes in regions of interest pairs, a trend toward increased correlations within the salience network and SMN, and a trend toward a reduced correlation in the DMN-CON pair. Furthermore, the rLLD group exhibited more severely altered functional connectivity than the aMCI group. Interestingly, these altered connectivities were associated with specific multi-domain cognitive and behavioral functions in both rLLD and aMCI. The degree of functional connectivity in the right primary auditory areas was negatively correlated with Hamilton Depression Scale scores in rLLD. Notably, altered connectivity between the right middle temporal cortex and the posterior cerebellum was negatively correlated with Mattis Dementia Rating Scale scores in both rLLD and aMCI. These results demonstrate that rLLD and aMCI may share convergent and divergent aberrant intranetwork and internetwork connectivity patterns as a potential continuous spectrum of the same disease. They further suggest that dysfunctions in the right specific temporal-cerebellum neural circuit may contribute to the similarities observed in rLLD and aMCI conversion to AD. Copyright © 2016 Elsevier Ltd. All rights reserved.

Changes in Neural Connectivity and Memory Following a Yoga Intervention for Older Adults: A Pilot Study

PubMed Central

Eyre, Harris A.; Acevedo, Bianca; Yang, Hongyu; Siddarth, Prabha; Van Dyk, Kathleen; Ercoli, Linda; Leaver, Amber M.; Cyr, Natalie St.; Narr, Katherine; Baune, Bernhard T.; Khalsa, Dharma S.; Lavretsky, Helen

2016-01-01

Background: No study has explored the effect of yoga on cognitive decline and resting-state functional connectivity. Objectives: This study explored the relationship between performance on memory tests and resting-state functional connectivity before and after a yoga intervention versus active control for subjects with mild cognitive impairment (MCI). Methods: Participants ( ≥ 55 y) with MCI were randomized to receive a yoga intervention or active “gold-standard” control (i.e., memory enhancement training (MET)) for 12 weeks. Resting-state functional magnetic resonance imaging was used to map correlations between brain networks and memory performance changes over time. Default mode networks (DMN), language and superior parietal networks were chosen as networks of interest to analyze the association with changes in verbal and visuospatial memory performance. Results: Fourteen yoga and 11 MET participants completed the study. The yoga group demonstrated a statistically significant improvement in depression and visuospatial memory. We observed improved verbal memory performance correlated with increased connectivity between the DMN and frontal medial cortex, pregenual anterior cingulate cortex, right middle frontal cortex, posterior cingulate cortex, and left lateral occipital cortex. Improved verbal memory performance positively correlated with increased connectivity between the language processing network and the left inferior frontal gyrus. Improved visuospatial memory performance correlated inversely with connectivity between the superior parietal network and the medial parietal cortex. Conclusion:Yoga may be as effective as MET in improving functional connectivity in relation to verbal memory performance. These findings should be confirmed in larger prospective studies. PMID:27060939

Single-Neuron NMDA Receptor Phenotype Influences Neuronal Rewiring and Reintegration following Traumatic Injury

PubMed Central

Patel, Tapan P.; Ventre, Scott C.; Geddes-Klein, Donna; Singh, Pallab K.

2014-01-01

Alterations in the activity of neural circuits are a common consequence of traumatic brain injury (TBI), but the relationship between single-neuron properties and the aggregate network behavior is not well understood. We recently reported that the GluN2B-containing NMDA receptors (NMDARs) are key in mediating mechanical forces during TBI, and that TBI produces a complex change in the functional connectivity of neuronal networks. Here, we evaluated whether cell-to-cell heterogeneity in the connectivity and aggregate contribution of GluN2B receptors to [Ca2+]i before injury influenced the functional rewiring, spontaneous activity, and network plasticity following injury using primary rat cortical dissociated neurons. We found that the functional connectivity of a neuron to its neighbors, combined with the relative influx of calcium through distinct NMDAR subtypes, together contributed to the individual neuronal response to trauma. Specifically, individual neurons whose [Ca2+]i oscillations were largely due to GluN2B NMDAR activation lost many of their functional targets 1 h following injury. In comparison, neurons with large GluN2A contribution or neurons with high functional connectivity both independently protected against injury-induced loss in connectivity. Mechanistically, we found that traumatic injury resulted in increased uncorrelated network activity, an effect linked to reduction of the voltage-sensitive Mg2+ block of GluN2B-containing NMDARs. This uncorrelated activation of GluN2B subtypes after injury significantly limited the potential for network remodeling in response to a plasticity stimulus. Together, our data suggest that two single-cell characteristics, the aggregate contribution of NMDAR subtypes and the number of functional connections, influence network structure following traumatic injury. PMID:24647941

Entropy of spatial network ensembles

NASA Astrophysics Data System (ADS)

Coon, Justin P.; Dettmann, Carl P.; Georgiou, Orestis

2018-04-01

We analyze complexity in spatial network ensembles through the lens of graph entropy. Mathematically, we model a spatial network as a soft random geometric graph, i.e., a graph with two sources of randomness, namely nodes located randomly in space and links formed independently between pairs of nodes with probability given by a specified function (the "pair connection function") of their mutual distance. We consider the general case where randomness arises in node positions as well as pairwise connections (i.e., for a given pair distance, the corresponding edge state is a random variable). Classical random geometric graph and exponential graph models can be recovered in certain limits. We derive a simple bound for the entropy of a spatial network ensemble and calculate the conditional entropy of an ensemble given the node location distribution for hard and soft (probabilistic) pair connection functions. Under this formalism, we derive the connection function that yields maximum entropy under general constraints. Finally, we apply our analytical framework to study two practical examples: ad hoc wireless networks and the US flight network. Through the study of these examples, we illustrate that both exhibit properties that are indicative of nearly maximally entropic ensembles.

The Time Course of Task-Specific Memory Consolidation Effects in Resting State Networks

PubMed Central

Sami, Saber; Robertson, Edwin M.

2014-01-01

Previous studies have reported functionally localized changes in resting-state brain activity following a short period of motor learning, but their relationship with memory consolidation and their dependence on the form of learning is unclear. We investigate these questions with implicit or explicit variants of the serial reaction time task (SRTT). fMRI resting-state functional connectivity was measured in human subjects before the tasks, and 0.1, 0.5, and 6 h after learning. There was significant improvement in procedural skill in both groups, with the group learning under explicit conditions showing stronger initial acquisition, and greater improvement at the 6 h retest. Immediately following acquisition, this group showed enhanced functional connectivity in networks including frontal and cerebellar areas and in the visual cortex. Thirty minutes later, enhanced connectivity was observed between cerebellar nuclei, thalamus, and basal ganglia, whereas at 6 h there was enhanced connectivity in a sensory-motor cortical network. In contrast, immediately after acquisition under implicit conditions, there was increased connectivity in a network including precentral and sensory-motor areas, whereas after 30 min a similar cerebello-thalamo-basal ganglionic network was seen as in explicit learning. Finally, 6 h after implicit learning, we found increased connectivity in medial temporal cortex, but reduction in precentral and sensory-motor areas. Our findings are consistent with predictions that two variants of the SRTT task engage dissociable functional networks, although there are also networks in common. We also show a converging and diverging pattern of flux between prefrontal, sensory-motor, and parietal areas, and subcortical circuits across a 6 h consolidation period. PMID:24623776

Connectome analysis for pre-operative brain mapping in neurosurgery

PubMed Central

Hart, Michael G.; Price, Stephen J.; Suckling, John

2016-01-01

Abstract Object: Brain mapping has entered a new era focusing on complex network connectivity. Central to this is the search for the connectome or the brains ‘wiring diagram’. Graph theory analysis of the connectome allows understanding of the importance of regions to network function, and the consequences of their impairment or excision. Our goal was to apply connectome analysis in patients with brain tumours to characterise overall network topology and individual patterns of connectivity alterations. Methods: Resting-state functional MRI data were acquired using multi-echo, echo planar imaging pre-operatively from five participants each with a right temporal–parietal–occipital glioblastoma. Complex networks analysis was initiated by parcellating the brain into anatomically regions amongst which connections were identified by retaining the most significant correlations between the respective wavelet decomposed time-series. Results: Key characteristics of complex networks described in healthy controls were preserved in these patients, including ubiquitous small world organization. An exponentially truncated power law fit to the degree distribution predicted findings of general network robustness to injury but with a core of hubs exhibiting disproportionate vulnerability. Tumours produced a consistent reduction in local and long-range connectivity with distinct patterns of connection loss depending on lesion location. Conclusions: Connectome analysis is a feasible and novel approach to brain mapping in individual patients with brain tumours. Applications to pre-surgical planning include identifying regions critical to network function that should be preserved and visualising connections at risk from tumour resection. In the future one could use such data to model functional plasticity and recovery of cognitive deficits. PMID:27447756

Magnetoencephalography Reveals a Widespread Increase in Network Connectivity in Idiopathic/Genetic Generalized Epilepsy

PubMed Central

Elshahabi, Adham; Klamer, Silke; Sahib, Ashish Kaul; Lerche, Holger; Braun, Christoph; Focke, Niels K.

2015-01-01

Idiopathic/genetic generalized epilepsy (IGE/GGE) is characterized by seizures, which start and rapidly engage widely distributed networks, and result in symptoms such as absences, generalized myoclonic and primary generalized tonic-clonic seizures. Although routine magnetic resonance imaging is apparently normal, many studies have reported structural alterations in IGE/GGE patients using diffusion tensor imaging and voxel-based morphometry. Changes have also been reported in functional networks during generalized spike wave discharges. However, network function in the resting-state without epileptiforme discharges has been less well studied. We hypothesize that resting-state networks are more representative of the underlying pathophysiology and abnormal network synchrony. We studied functional network connectivity derived from whole-brain magnetoencephalography recordings in thirteen IGE/GGE and nineteen healthy controls. Using graph theoretical network analysis, we found a widespread increase in connectivity in patients compared to controls. These changes were most pronounced in the motor network, the mesio-frontal and temporal cortex. We did not, however, find any significant difference between the normalized clustering coefficients, indicating preserved gross network architecture. Our findings suggest that increased resting state connectivity could be an important factor for seizure spread and/or generation in IGE/GGE, and could serve as a biomarker for the disease. PMID:26368933

Auditory Resting-State Network Connectivity in Tinnitus: A Functional MRI Study

PubMed Central

Maudoux, Audrey; Lefebvre, Philippe; Cabay, Jean-Evrard; Demertzi, Athena; Vanhaudenhuyse, Audrey; Laureys, Steven; Soddu, Andrea

2012-01-01

The underlying functional neuroanatomy of tinnitus remains poorly understood. Few studies have focused on functional cerebral connectivity changes in tinnitus patients. The aim of this study was to test if functional MRI “resting-state” connectivity patterns in auditory network differ between tinnitus patients and normal controls. Thirteen chronic tinnitus subjects and fifteen age-matched healthy controls were studied on a 3 tesla MRI. Connectivity was investigated using independent component analysis and an automated component selection approach taking into account the spatial and temporal properties of each component. Connectivity in extra-auditory regions such as brainstem, basal ganglia/NAc, cerebellum, parahippocampal, right prefrontal, parietal, and sensorimotor areas was found to be increased in tinnitus subjects. The right primary auditory cortex, left prefrontal, left fusiform gyrus, and bilateral occipital regions showed a decreased connectivity in tinnitus. These results show that there is a modification of cortical and subcortical functional connectivity in tinnitus encompassing attentional, mnemonic, and emotional networks. Our data corroborate the hypothesized implication of non-auditory regions in tinnitus physiopathology and suggest that various regions of the brain seem involved in the persistent awareness of the phenomenon as well as in the development of the associated distress leading to disabling chronic tinnitus. PMID:22574141

Motor Imagery Learning Modulates Functional Connectivity of Multiple Brain Systems in Resting State

PubMed Central

Zhang, Hang; Long, Zhiying; Ge, Ruiyang; Xu, Lele; Jin, Zhen; Yao, Li; Liu, Yijun

2014-01-01

Background Learning motor skills involves subsequent modulation of resting-state functional connectivity in the sensory-motor system. This idea was mostly derived from the investigations on motor execution learning which mainly recruits the processing of sensory-motor information. Behavioral evidences demonstrated that motor skills in our daily lives could be learned through imagery procedures. However, it remains unclear whether the modulation of resting-state functional connectivity also exists in the sensory-motor system after motor imagery learning. Methodology/Principal Findings We performed a fMRI investigation on motor imagery learning from resting state. Based on previous studies, we identified eight sensory and cognitive resting-state networks (RSNs) corresponding to the brain systems and further explored the functional connectivity of these RSNs through the assessments, connectivity and network strengths before and after the two-week consecutive learning. Two intriguing results were revealed: (1) The sensory RSNs, specifically sensory-motor and lateral visual networks exhibited greater connectivity strengths in precuneus and fusiform gyrus after learning; (2) Decreased network strength induced by learning was proved in the default mode network, a cognitive RSN. Conclusions/Significance These results indicated that resting-state functional connectivity could be modulated by motor imagery learning in multiple brain systems, and such modulation displayed in the sensory-motor, visual and default brain systems may be associated with the establishment of motor schema and the regulation of introspective thought. These findings further revealed the neural substrates underlying motor skill learning and potentially provided new insights into the therapeutic benefits of motor imagery learning. PMID:24465577

Uniting functional network topology and oscillations in the fronto-parietal single unit network of behaving primates.

PubMed

Dann, Benjamin; Michaels, Jonathan A; Schaffelhofer, Stefan; Scherberger, Hansjörg

2016-08-15

The functional communication of neurons in cortical networks underlies higher cognitive processes. Yet, little is known about the organization of the single neuron network or its relationship to the synchronization processes that are essential for its formation. Here, we show that the functional single neuron network of three fronto-parietal areas during active behavior of macaque monkeys is highly complex. The network was closely connected (small-world) and consisted of functional modules spanning these areas. Surprisingly, the importance of different neurons to the network was highly heterogeneous with a small number of neurons contributing strongly to the network function (hubs), which were in turn strongly inter-connected (rich-club). Examination of the network synchronization revealed that the identified rich-club consisted of neurons that were synchronized in the beta or low frequency range, whereas other neurons were mostly non-oscillatory synchronized. Therefore, oscillatory synchrony may be a central communication mechanism for highly organized functional spiking networks.

Dynamic functional connectivity using state-based dynamic community structure: method and application to opioid analgesia.

PubMed

Robinson, Lucy F; Atlas, Lauren Y; Wager, Tor D

2015-03-01

We present a new method, State-based Dynamic Community Structure, that detects time-dependent community structure in networks of brain regions. Most analyses of functional connectivity assume that network behavior is static in time, or differs between task conditions with known timing. Our goal is to determine whether brain network topology remains stationary over time, or if changes in network organization occur at unknown time points. Changes in network organization may be related to shifts in neurological state, such as those associated with learning, drug uptake or experimental conditions. Using a hidden Markov stochastic blockmodel, we define a time-dependent community structure. We apply this approach to data from a functional magnetic resonance imaging experiment examining how contextual factors influence drug-induced analgesia. Results reveal that networks involved in pain, working memory, and emotion show distinct profiles of time-varying connectivity. Copyright © 2014 Elsevier Inc. All rights reserved.

A Novel Re-keying Function Protocol (NRFP) For Wireless Sensor Network Security.

PubMed

Abdullah, Maan Younis; Hua, Gui Wei; Alsharabi, Naif

2008-12-04

This paper describes a novel re-keying function protocol (NRFP) for wireless sensor network security. A re-keying process management system for sensor networks is designed to support in-network processing. The design of the protocol is motivated by decentralization key management for wireless sensor networks (WSNs), covering key deployment, key refreshment, and key establishment. NRFP supports the establishment of novel administrative functions for sensor nodes that derive/re-derive a session key for each communication session. The protocol proposes direct connection, in-direct connection and hybrid connection. NRFP also includes an efficient protocol for local broadcast authentication based on the use of one-way key chains. A salient feature of the authentication protocol is that it supports source authentication without precluding in-network processing. Security and performance analysis shows that it is very efficient in computation, communication and storage and, that NRFP is also effective in defending against many sophisticated attacks.

Disruption of thalamic functional connectivity is a neural correlate of dexmedetomidine-induced unconsciousness

PubMed Central

Akeju, Oluwaseun; Loggia, Marco L; Catana, Ciprian; Pavone, Kara J; Vazquez, Rafael; Rhee, James; Contreras Ramirez, Violeta; Chonde, Daniel B; Izquierdo-Garcia, David; Arabasz, Grae; Hsu, Shirley; Habeeb, Kathleen; Hooker, Jacob M; Napadow, Vitaly; Brown, Emery N; Purdon, Patrick L

2014-01-01

Understanding the neural basis of consciousness is fundamental to neuroscience research. Disruptions in cortico-cortical connectivity have been suggested as a primary mechanism of unconsciousness. By using a novel combination of positron emission tomography and functional magnetic resonance imaging, we studied anesthesia-induced unconsciousness and recovery using the α2-agonist dexmedetomidine. During unconsciousness, cerebral metabolic rate of glucose and cerebral blood flow were preferentially decreased in the thalamus, the Default Mode Network (DMN), and the bilateral Frontoparietal Networks (FPNs). Cortico-cortical functional connectivity within the DMN and FPNs was preserved. However, DMN thalamo-cortical functional connectivity was disrupted. Recovery from this state was associated with sustained reduction in cerebral blood flow and restored DMN thalamo-cortical functional connectivity. We report that loss of thalamo-cortical functional connectivity is sufficient to produce unconsciousness. DOI: http://dx.doi.org/10.7554/eLife.04499.001 PMID:25432022

Resting-State fMRI Functional Connectivity Is Associated with Sleepiness, Imagery, and Discontinuity of Mind

PubMed Central

Chen, Gang; den Braber, Anouk; van ‘t Ent, Dennis; Boomsma, Dorret I.; Mansvelder, Huibert D.; de Geus, Eco; Van Someren, Eus J. W.; Linkenkaer-Hansen, Klaus

2015-01-01

Resting-state functional magnetic resonance imaging (rs-fMRI) is widely used to investigate the functional architecture of the healthy human brain and how it is affected by learning, lifelong development, brain disorders or pharmacological intervention. Non-sensory experiences are prevalent during rest and must arise from ongoing brain activity, yet little is known about this relationship. Here, we used two runs of rs-fMRI both immediately followed by the Amsterdam Resting-State Questionnaire (ARSQ) to investigate the relationship between functional connectivity within ten large-scale functional brain networks and ten dimensions of thoughts and feelings experienced during the scan in 106 healthy participants. We identified 11 positive associations between brain-network functional connectivity and ARSQ dimensions. ‘Sleepiness’ exhibited significant associations with functional connectivity within Visual, Sensorimotor and Default Mode networks. Similar associations were observed for ‘Visual Thought’ and ‘Discontinuity of Mind’, which may relate to variation in imagery and thought control mediated by arousal fluctuations. Our findings show that self-reports of thoughts and feelings experienced during a rs-fMRI scan help understand the functional significance of variations in functional connectivity, which should be of special relevance to clinical studies. PMID:26540239

Loneliness in late-life depression: structural and functional connectivity during affective processing.

PubMed

Wong, N M L; Liu, H-L; Lin, C; Huang, C-M; Wai, Y-Y; Lee, S-H; Lee, T M C

2016-09-01

Late-life depression (LLD) in the elderly was reported to present with emotion dysregulation accompanied by high perceived loneliness. Previous research has suggested that LLD is a disorder of connectivity and is associated with aberrant network properties. On the other hand, perceived loneliness is found to adversely affect the brain, but little is known about its neurobiological basis in LLD. The current study investigated the relationships between the structural connectivity, functional connectivity during affective processing, and perceived loneliness in LLD. The current study included 54 participants aged >60 years of whom 31 were diagnosed with LLD. Diffusion tensor imaging (DTI) data and task-based functional magnetic resonance imaging (fMRI) data of an affective processing task were collected. Network-based statistics and graph theory techniques were applied, and the participants' perceived loneliness and depression level were measured. The affective processing task included viewing affective stimuli. Structurally, a loneliness-related sub-network was identified across all subjects. Functionally, perceived loneliness was related to connectivity differently in LLD than that in controls when they were processing negative stimuli, with aberrant networking in subcortical area. Perceived loneliness was identified to have a unique role in relation to the negative affective processing in LLD at the functional brain connectional and network levels. The findings increas our understanding of LLD and provide initial evidence of the neurobiological mechanisms of loneliness in LLD. Loneliness might be a potential intervention target in depressive patients.

Differences in interregional brain connectivity in children with unilateral hearing loss.

PubMed

Jung, Matthew E; Colletta, Miranda; Coalson, Rebecca; Schlaggar, Bradley L; Lieu, Judith E C

2017-11-01

To identify functional network architecture differences in the brains of children with unilateral hearing loss (UHL) using resting-state functional-connectivity magnetic resonance imaging (rs-fcMRI). Prospective observational study. Children (7 to 17 years of age) with severe to profound hearing loss in one ear, along with their normal hearing (NH) siblings, were recruited and imaged using rs-fcMRI. Eleven children had right UHL; nine had left UHL; and 13 had normal hearing. Forty-one brain regions of interest culled from established brain networks such as the default mode (DMN); cingulo-opercular (CON); and frontoparietal networks (FPN); as well as regions for language, phonological, and visual processing, were analyzed using regionwise correlations and conjunction analysis to determine differences in functional connectivity between the UHL and normal hearing children. When compared to the NH group, children with UHL showed increased connectivity patterns between multiple networks, such as between the CON and visual processing centers. However, there were decreased, as well as aberrant connectivity patterns with the coactivation of the DMN and FPN, a relationship that usually is negatively correlated. Children with UHL demonstrate multiple functional connectivity differences between brain networks involved with executive function, cognition, and language comprehension that may represent adaptive as well as maladaptive changes. These findings suggest that possible interventions or habilitation, beyond amplification, might be able to affect some children's requirement for additional help at school. 3b. Laryngoscope, 127:2636-2645, 2017. © 2017 The American Laryngological, Rhinological and Otological Society, Inc.

Large-scale changes in network interactions as a physiological signature of spatial neglect

PubMed Central

Baldassarre, Antonello; Ramsey, Lenny; Hacker, Carl L.; Callejas, Alicia; Astafiev, Serguei V.; Metcalf, Nicholas V.; Zinn, Kristi; Rengachary, Jennifer; Snyder, Abraham Z.; Carter, Alex R.; Shulman, Gordon L.

2014-01-01

The relationship between spontaneous brain activity and behaviour following focal injury is not well understood. Here, we report a large-scale study of resting state functional connectivity MRI and spatial neglect following stroke in a large (n = 84) heterogeneous sample of first-ever stroke patients (within 1–2 weeks). Spatial neglect, which is typically more severe after right than left hemisphere injury, includes deficits of spatial attention and motor actions contralateral to the lesion, and low general attention due to impaired vigilance/arousal. Patients underwent structural and resting state functional MRI scans, and spatial neglect was measured using the Posner spatial cueing task, and Mesulam and Behavioural Inattention Test cancellation tests. A principal component analysis of the behavioural tests revealed a main factor accounting for 34% of variance that captured three correlated behavioural deficits: visual neglect of the contralesional visual field, visuomotor neglect of the contralesional field, and low overall performance. In an independent sample (21 healthy subjects), we defined 10 resting state networks consisting of 169 brain regions: visual-fovea and visual-periphery, sensory-motor, auditory, dorsal attention, ventral attention, language, fronto-parietal control, cingulo-opercular control, and default mode. We correlated the neglect factor score with the strength of resting state functional connectivity within and across the 10 resting state networks. All damaged brain voxels were removed from the functional connectivity:behaviour correlational analysis. We found that the correlated behavioural deficits summarized by the factor score were associated with correlated multi-network patterns of abnormal functional connectivity involving large swaths of cortex. Specifically, dorsal attention and sensory-motor networks showed: (i) reduced interhemispheric functional connectivity; (ii) reduced anti-correlation with fronto-parietal and default mode networks in the right hemisphere; and (iii) increased intrahemispheric connectivity with the basal ganglia. These patterns of functional connectivity:behaviour correlations were stronger in patients with right- as compared to left-hemisphere damage and were independent of lesion volume. Our findings identify large-scale changes in resting state network interactions that are a physiological signature of spatial neglect and may relate to its right hemisphere lateralization. PMID:25367028

Abnormal regional activity and functional connectivity in resting-state brain networks associated with etiology confirmed unilateral pulsatile tinnitus in the early stage of disease.

PubMed

Lv, Han; Zhao, Pengfei; Liu, Zhaohui; Li, Rui; Zhang, Ling; Wang, Peng; Yan, Fei; Liu, Liheng; Wang, Guopeng; Zeng, Rong; Li, Ting; Dong, Cheng; Gong, Shusheng; Wang, Zhenchang

2017-03-01

Abnormal neural activities can be revealed by resting-state functional magnetic resonance imaging (rs-fMRI) using analyses of the regional activity and functional connectivity (FC) of the networks in the brain. This study was designed to demonstrate the functional network alterations in the patients with pulsatile tinnitus (PT). In this study, we recruited 45 patients with unilateral PT in the early stage of disease (less than 48 months of disease duration) and 45 normal controls. We used regional homogeneity (ReHo) and seed-based FC computational methods to reveal resting-state brain activity features associated with pulsatile tinnitus. Compared with healthy controls, PT patients showed regional abnormalities mainly in the left middle occipital gyrus (MOG), posterior cingulate gyrus (PCC), precuneus and right anterior insula (AI). When these regions were defined as seeds, we demonstrated widespread modification of interaction between the auditory and non-auditory networks. The auditory network was positively connected with the cognitive control network (CCN), which may associate with tinnitus related distress. Both altered regional activity and changed FC were found in the visual network. The modification of interactions of higher order networks were mainly found in the DMN, CCN and limbic networks. Functional connectivity between the left MOG and left parahippocampal gyrus could also be an index to reflect the disease duration. This study helped us gain a better understanding of the characteristics of neural network modifications in patients with pulsatile tinnitus. Copyright © 2017 Elsevier B.V. All rights reserved.

Functional ultrasound imaging of intrinsic connectivity in the living rat brain with high spatiotemporal resolution

PubMed Central

Osmanski, Bruno-Félix; Pezet, Sophie; Ricobaraza, Ana; Lenkei, Zsolt; Tanter, Mickael

2014-01-01

Long-range coherences in spontaneous brain activity reflect functional connectivity. Here we propose a novel, highly resolved connectivity mapping approach, using ultrafast functional ultrasound (fUS), which enables imaging of cerebral microvascular haemodynamics deep in the anaesthetized rodent brain, through a large thinned-skull cranial window, with pixel dimensions of 100 μm × 100 μm in-plane. The millisecond-range temporal resolution allows unambiguous cancellation of low-frequency cardio-respiratory noise. Both seed-based and singular value decomposition analysis of spatial coherences in the low-frequency (<0.1 Hz) spontaneous fUS signal fluctuations reproducibly report, at different coronal planes, overlapping high-contrast, intrinsic functional connectivity patterns. These patterns are similar to major functional networks described in humans by resting-state fMRI, such as the lateral task-dependent network putatively anticorrelated with the midline default-mode network. These results introduce fUS as a powerful novel neuroimaging method, which could be extended to portable systems for three-dimensional functional connectivity imaging in awake and freely moving rodents. PMID:25277668

Dysregulated left inferior parietal activity in schizophrenia and depression: functional connectivity and characterization

PubMed Central

Müller, Veronika I.; Cieslik, Edna C.; Laird, Angela R.; Fox, Peter T.; Eickhoff, Simon B.

2013-01-01

The inferior parietal cortex (IPC) is a heterogeneous region that is known to be involved in a multitude of diverse different tasks and processes, though its contribution to these often-complex functions is yet poorly understood. In a previous study we demonstrated that patients with depression failed to deactivate the left IPC during processing of congruent audiovisual information. We now found the same dysregulation (same region and condition) in schizophrenia. By using task-independent (resting state) and task-dependent meta-analytic connectivity modeling (MACM) analyses we aimed at characterizing this particular region with regard to its connectivity and function. Across both approaches, results revealed functional connectivity of the left inferior parietal seed region with bilateral IPC, precuneus and posterior cingulate cortex (PrC/PCC), medial orbitofrontal cortex (mOFC), left middle frontal (MFG) as well as inferior frontal (IFG) gyrus. Network-level functional characterization further revealed that on the one hand, all interconnected regions are part of a network involved in memory processes. On the other hand, sub-networks are formed when emotion, language, social cognition and reasoning processes are required. Thus, the IPC-region that is dysregulated in both depression and schizophrenia is functionally connected to a network of regions which, depending on task demands may form sub-networks. These results therefore indicate that dysregulation of left IPC in depression and schizophrenia might not only be connected to deficits in audiovisual integration, but is possibly also associated to impaired memory and deficits in emotion processing in these patient groups. PMID:23781190

Intrinsic Functional Connectivity in the Adult Brain and Success in Second-Language Learning.

PubMed

Chai, Xiaoqian J; Berken, Jonathan A; Barbeau, Elise B; Soles, Jennika; Callahan, Megan; Chen, Jen-Kai; Klein, Denise

2016-01-20

There is considerable variability in an individual's ability to acquire a second language (L2) during adulthood. Using resting-state fMRI data acquired before training in English speakers who underwent a 12 week intensive French immersion training course, we investigated whether individual differences in intrinsic resting-state functional connectivity relate to a person's ability to acquire an L2. We focused on two key aspects of language processing--lexical retrieval in spontaneous speech and reading speed--and computed whole-brain functional connectivity from two regions of interest in the language network, namely the left anterior insula/frontal operculum (AI/FO) and the visual word form area (VWFA). Connectivity between the left AI/FO and left posterior superior temporal gyrus (STG) and between the left AI/FO and dorsal anterior cingulate cortex correlated positively with improvement in L2 lexical retrieval in spontaneous speech. Connectivity between the VWFA and left mid-STG correlated positively with improvement in L2 reading speed. These findings are consistent with the different language functions subserved by subcomponents of the language network and suggest that the human capacity to learn an L2 can be predicted by an individual's intrinsic functional connectivity within the language network. Significance statement: There is considerable variability in second-language learning abilities during adulthood. We investigated whether individual differences in intrinsic functional connectivity in the adult brain relate to success in second-language learning, using resting-state functional magnetic resonance imaging in English speakers who underwent a 12 week intensive French immersion training course. We found that pretraining functional connectivity within two different language subnetworks correlated strongly with learning outcome in two different language skills: lexical retrieval in spontaneous speech and reading speed. Our results suggest that the human capacity to learn a second language can be predicted by an individual's intrinsic functional connectivity within the language network. Copyright © 2016 the authors 0270-6474/16/360755-07$15.00/0.

Frequency-specific alterations in functional connectivity in treatment-resistant and -sensitive major depressive disorder.

PubMed

He, Zongling; Cui, Qian; Zheng, Junjie; Duan, Xujun; Pang, Yajing; Gao, Qing; Han, Shaoqiang; Long, Zhiliang; Wang, Yifeng; Li, Jiao; Wang, Xiao; Zhao, Jingping; Chen, Huafu

2016-11-01

Major depressive disorder (MDD) may involve alterations in brain functional connectivity in multiple neural circuits and present large-scale network dysfunction. Patients with treatment-resistant depression (TRD) and treatment-sensitive depression (TSD) show different responses to antidepressants and aberrant brain functions. This study aims to investigate functional connectivity patterns of TRD and TSD at the whole brain resting state. Seventeen patients with TRD, 17 patients with TSD, and 17 healthy controls matched with age, gender, and years of education were recruited in this study. The brain was divided using an automated anatomical labeling atlas into 90 regions of interest, which were used to construct the entire brain functional networks. An analysis method called network-based statistic was used to explore the dysconnected subnetworks of TRD and TSD at different frequency bands. At resting state, TSD and TRD present characteristic patterns of network dysfunction at special frequency bands. The dysconnected subnetwork of TSD mainly lies in the fronto-parietal top-down control network. Moreover, the abnormal neural circuits of TRD are extensive and complex. These circuits not only depend on the abnormal affective network but also involve other networks, including salience network, auditory network, visual network, and language processing cortex. Our findings reflect that the pathological mechanism of TSD may refer to impairment in cognitive control, whereas TRD mainly triggers the dysfunction of emotion processing and affective cognition. This study reveals that differences in brain functional connectivity at resting state reflect distinct pathophysiological mechanisms in TSD and TRD. These findings may be helpful in differentiating two types of MDD and predicting treatment responses. Copyright © 2016 Elsevier Ltd. All rights reserved.

Functional Connectivity in Islets of Langerhans from Mouse Pancreas Tissue Slices

PubMed Central

Stožer, Andraž; Gosak, Marko; Dolenšek, Jurij; Perc, Matjaž; Marhl, Marko; Rupnik, Marjan Slak; Korošak, Dean

2013-01-01

We propose a network representation of electrically coupled beta cells in islets of Langerhans. Beta cells are functionally connected on the basis of correlations between calcium dynamics of individual cells, obtained by means of confocal laser-scanning calcium imaging in islets from acute mouse pancreas tissue slices. Obtained functional networks are analyzed in the light of known structural and physiological properties of islets. Focusing on the temporal evolution of the network under stimulation with glucose, we show that the dynamics are more correlated under stimulation than under non-stimulated conditions and that the highest overall correlation, largely independent of Euclidean distances between cells, is observed in the activation and deactivation phases when cells are driven by the external stimulus. Moreover, we find that the range of interactions in networks during activity shows a clear dependence on the Euclidean distance, lending support to previous observations that beta cells are synchronized via calcium waves spreading throughout islets. Most interestingly, the functional connectivity patterns between beta cells exhibit small-world properties, suggesting that beta cells do not form a homogeneous geometric network but are connected in a functionally more efficient way. Presented results provide support for the existing knowledge of beta cell physiology from a network perspective and shed important new light on the functional organization of beta cell syncitia whose structural topology is probably not as trivial as believed so far. PMID:23468610

On characterizing population commonalities and subject variations in brain networks.

PubMed

Ghanbari, Yasser; Bloy, Luke; Tunc, Birkan; Shankar, Varsha; Roberts, Timothy P L; Edgar, J Christopher; Schultz, Robert T; Verma, Ragini

2017-05-01

Brain networks based on resting state connectivity as well as inter-regional anatomical pathways obtained using diffusion imaging have provided insight into pathology and development. Such work has underscored the need for methods that can extract sub-networks that can accurately capture the connectivity patterns of the underlying population while simultaneously describing the variation of sub-networks at the subject level. We have designed a multi-layer graph clustering method that extracts clusters of nodes, called 'network hubs', which display higher levels of connectivity within the cluster than to the rest of the brain. The method determines an atlas of network hubs that describes the population, as well as weights that characterize subject-wise variation in terms of within- and between-hub connectivity. This lowers the dimensionality of brain networks, thereby providing a representation amenable to statistical analyses. The applicability of the proposed technique is demonstrated by extracting an atlas of network hubs for a population of typically developing controls (TDCs) as well as children with autism spectrum disorder (ASD), and using the structural and functional networks of a population to determine the subject-level variation of these hubs and their inter-connectivity. These hubs are then used to compare ASD and TDCs. Our method is generalizable to any population whose connectivity (structural or functional) can be captured via non-negative network graphs. Copyright © 2015 Elsevier B.V. All rights reserved.

Sparse Multivariate Autoregressive Modeling for Mild Cognitive Impairment Classification

PubMed Central

Li, Yang; Wee, Chong-Yaw; Jie, Biao; Peng, Ziwen

2014-01-01

Brain connectivity network derived from functional magnetic resonance imaging (fMRI) is becoming increasingly prevalent in the researches related to cognitive and perceptual processes. The capability to detect causal or effective connectivity is highly desirable for understanding the cooperative nature of brain network, particularly when the ultimate goal is to obtain good performance of control-patient classification with biological meaningful interpretations. Understanding directed functional interactions between brain regions via brain connectivity network is a challenging task. Since many genetic and biomedical networks are intrinsically sparse, incorporating sparsity property into connectivity modeling can make the derived models more biologically plausible. Accordingly, we propose an effective connectivity modeling of resting-state fMRI data based on the multivariate autoregressive (MAR) modeling technique, which is widely used to characterize temporal information of dynamic systems. This MAR modeling technique allows for the identification of effective connectivity using the Granger causality concept and reducing the spurious causality connectivity in assessment of directed functional interaction from fMRI data. A forward orthogonal least squares (OLS) regression algorithm is further used to construct a sparse MAR model. By applying the proposed modeling to mild cognitive impairment (MCI) classification, we identify several most discriminative regions, including middle cingulate gyrus, posterior cingulate gyrus, lingual gyrus and caudate regions, in line with results reported in previous findings. A relatively high classification accuracy of 91.89 % is also achieved, with an increment of 5.4 % compared to the fully-connected, non-directional Pearson-correlation-based functional connectivity approach. PMID:24595922

Functional connectivity in task-negative network of the Deaf: effects of sign language experience

PubMed Central

Talavage, Thomas M.; Wilbur, Ronnie B.

2014-01-01

Prior studies investigating cortical processing in Deaf signers suggest that life-long experience with sign language and/or auditory deprivation may alter the brain’s anatomical structure and the function of brain regions typically recruited for auditory processing (Emmorey et al., 2010; Pénicaud et al., 2013 inter alia). We report the first investigation of the task-negative network in Deaf signers and its functional connectivity—the temporal correlations among spatially remote neurophysiological events. We show that Deaf signers manifest increased functional connectivity between posterior cingulate/precuneus and left medial temporal gyrus (MTG), but also inferior parietal lobe and medial temporal gyrus in the right hemisphere- areas that have been found to show functional recruitment specifically during sign language processing. These findings suggest that the organization of the brain at the level of inter-network connectivity is likely affected by experience with processing visual language, although sensory deprivation could be another source of the difference. We hypothesize that connectivity alterations in the task negative network reflect predictive/automatized processing of the visual signal. PMID:25024915

Nonequilibrium landscape theory of neural networks.

PubMed

Yan, Han; Zhao, Lei; Hu, Liang; Wang, Xidi; Wang, Erkang; Wang, Jin

2013-11-05

The brain map project aims to map out the neuron connections of the human brain. Even with all of the wirings mapped out, the global and physical understandings of the function and behavior are still challenging. Hopfield quantified the learning and memory process of symmetrically connected neural networks globally through equilibrium energy. The energy basins of attractions represent memories, and the memory retrieval dynamics is determined by the energy gradient. However, the realistic neural networks are asymmetrically connected, and oscillations cannot emerge from symmetric neural networks. Here, we developed a nonequilibrium landscape-flux theory for realistic asymmetrically connected neural networks. We uncovered the underlying potential landscape and the associated Lyapunov function for quantifying the global stability and function. We found the dynamics and oscillations in human brains responsible for cognitive processes and physiological rhythm regulations are determined not only by the landscape gradient but also by the flux. We found that the flux is closely related to the degrees of the asymmetric connections in neural networks and is the origin of the neural oscillations. The neural oscillation landscape shows a closed-ring attractor topology. The landscape gradient attracts the network down to the ring. The flux is responsible for coherent oscillations on the ring. We suggest the flux may provide the driving force for associations among memories. We applied our theory to rapid-eye movement sleep cycle. We identified the key regulation factors for function through global sensitivity analysis of landscape topography against wirings, which are in good agreements with experiments.

Nonequilibrium landscape theory of neural networks

PubMed Central

Yan, Han; Zhao, Lei; Hu, Liang; Wang, Xidi; Wang, Erkang; Wang, Jin

2013-01-01

The brain map project aims to map out the neuron connections of the human brain. Even with all of the wirings mapped out, the global and physical understandings of the function and behavior are still challenging. Hopfield quantified the learning and memory process of symmetrically connected neural networks globally through equilibrium energy. The energy basins of attractions represent memories, and the memory retrieval dynamics is determined by the energy gradient. However, the realistic neural networks are asymmetrically connected, and oscillations cannot emerge from symmetric neural networks. Here, we developed a nonequilibrium landscape–flux theory for realistic asymmetrically connected neural networks. We uncovered the underlying potential landscape and the associated Lyapunov function for quantifying the global stability and function. We found the dynamics and oscillations in human brains responsible for cognitive processes and physiological rhythm regulations are determined not only by the landscape gradient but also by the flux. We found that the flux is closely related to the degrees of the asymmetric connections in neural networks and is the origin of the neural oscillations. The neural oscillation landscape shows a closed-ring attractor topology. The landscape gradient attracts the network down to the ring. The flux is responsible for coherent oscillations on the ring. We suggest the flux may provide the driving force for associations among memories. We applied our theory to rapid-eye movement sleep cycle. We identified the key regulation factors for function through global sensitivity analysis of landscape topography against wirings, which are in good agreements with experiments. PMID:24145451

Social interactions elicit rapid shifts in functional connectivity in the social decision-making network of zebrafish

PubMed Central

Teles, Magda C.; Almeida, Olinda; Lopes, João S.; Oliveira, Rui F.

2015-01-01

According to the social decision-making (SDM) network hypothesis, SDM is encoded in a network of forebrain and midbrain structures in a distributed and dynamic fashion, such that the expression of a given social behaviour is better reflected by the overall profile of activation across the different loci rather than by the activity of a single node. This proposal has the implicit assumption that SDM relies on integration across brain regions, rather than on regional specialization. Here we tested the occurrence of functional localization and of functional connectivity in the SDM network. For this purpose we used zebrafish to map different social behaviour states into patterns of neuronal activity, as indicated by the expression of the immediate early genes c-fos and egr-1, across the SDM network. The results did not support functional localization, as some loci had similar patterns of activity associated with different social behaviour states, and showed socially driven changes in functional connectivity. Thus, this study provides functional support to the SDM network hypothesis and suggests that the neural context in which a given node of the network is operating (i.e. the state of its interconnected areas) is central to its functional relevance. PMID:26423839

Social interactions elicit rapid shifts in functional connectivity in the social decision-making network of zebrafish.

PubMed

Teles, Magda C; Almeida, Olinda; Lopes, João S; Oliveira, Rui F

2015-10-07

According to the social decision-making (SDM) network hypothesis, SDM is encoded in a network of forebrain and midbrain structures in a distributed and dynamic fashion, such that the expression of a given social behaviour is better reflected by the overall profile of activation across the different loci rather than by the activity of a single node. This proposal has the implicit assumption that SDM relies on integration across brain regions, rather than on regional specialization. Here we tested the occurrence of functional localization and of functional connectivity in the SDM network. For this purpose we used zebrafish to map different social behaviour states into patterns of neuronal activity, as indicated by the expression of the immediate early genes c-fos and egr-1, across the SDM network. The results did not support functional localization, as some loci had similar patterns of activity associated with different social behaviour states, and showed socially driven changes in functional connectivity. Thus, this study provides functional support to the SDM network hypothesis and suggests that the neural context in which a given node of the network is operating (i.e. the state of its interconnected areas) is central to its functional relevance. © 2015 The Author(s).

Joint Attention and Brain Functional Connectivity in Infants and Toddlers.

PubMed

Eggebrecht, Adam T; Elison, Jed T; Feczko, Eric; Todorov, Alexandre; Wolff, Jason J; Kandala, Sridhar; Adams, Chloe M; Snyder, Abraham Z; Lewis, John D; Estes, Annette M; Zwaigenbaum, Lonnie; Botteron, Kelly N; McKinstry, Robert C; Constantino, John N; Evans, Alan; Hazlett, Heather C; Dager, Stephen; Paterson, Sarah J; Schultz, Robert T; Styner, Martin A; Gerig, Guido; Das, Samir; Kostopoulos, Penelope; Schlaggar, Bradley L; Petersen, Steven E; Piven, Joseph; Pruett, John R

2017-03-01

Initiating joint attention (IJA), the behavioral instigation of coordinated focus of 2 people on an object, emerges over the first 2 years of life and supports social-communicative functioning related to the healthy development of aspects of language, empathy, and theory of mind. Deficits in IJA provide strong early indicators for autism spectrum disorder, and therapies targeting joint attention have shown tremendous promise. However, the brain systems underlying IJA in early childhood are poorly understood, due in part to significant methodological challenges in imaging localized brain function that supports social behaviors during the first 2 years of life. Herein, we show that the functional organization of the brain is intimately related to the emergence of IJA using functional connectivity magnetic resonance imaging and dimensional behavioral assessments in a large semilongitudinal cohort of infants and toddlers. In particular, though functional connections spanning the brain are involved in IJA, the strongest brain-behavior associations cluster within connections between a small subset of functional brain networks; namely between the visual network and dorsal attention network and between the visual network and posterior cingulate aspects of the default mode network. These observations mark the earliest known description of how functional brain systems underlie a burgeoning fundamental social behavior, may help improve the design of targeted therapies for neurodevelopmental disorders, and, more generally, elucidate physiological mechanisms essential to healthy social behavior development. © The Author 2017. Published by Oxford University Press.

Joint Attention and Brain Functional Connectivity in Infants and Toddlers

PubMed Central

Eggebrecht, Adam T.; Elison, Jed T.; Feczko, Eric; Todorov, Alexandre; Wolff, Jason J.; Kandala, Sridhar; Adams, Chloe M.; Snyder, Abraham Z.; Lewis, John D.; Estes, Annette M.; Zwaigenbaum, Lonnie; Botteron, Kelly N.; McKinstry, Robert C.; Constantino, John N.; Evans, Alan; Hazlett, Heather C.; Dager, Stephen; Paterson, Sarah J.; Schultz, Robert T.; Styner, Martin A.; Gerig, Guido; Das, Samir; Kostopoulos, Penelope; Schlaggar, Bradley L.; Petersen, Steven E.; Piven, Joseph; Pruett, John R.

2017-01-01

Abstract Initiating joint attention (IJA), the behavioral instigation of coordinated focus of 2 people on an object, emerges over the first 2 years of life and supports social-communicative functioning related to the healthy development of aspects of language, empathy, and theory of mind. Deficits in IJA provide strong early indicators for autism spectrum disorder, and therapies targeting joint attention have shown tremendous promise. However, the brain systems underlying IJA in early childhood are poorly understood, due in part to significant methodological challenges in imaging localized brain function that supports social behaviors during the first 2 years of life. Herein, we show that the functional organization of the brain is intimately related to the emergence of IJA using functional connectivity magnetic resonance imaging and dimensional behavioral assessments in a large semilongitudinal cohort of infants and toddlers. In particular, though functional connections spanning the brain are involved in IJA, the strongest brain-behavior associations cluster within connections between a small subset of functional brain networks; namely between the visual network and dorsal attention network and between the visual network and posterior cingulate aspects of the default mode network. These observations mark the earliest known description of how functional brain systems underlie a burgeoning fundamental social behavior, may help improve the design of targeted therapies for neurodevelopmental disorders, and, more generally, elucidate physiological mechanisms essential to healthy social behavior development. PMID:28062515

Functional Connectivity with Distinct Neural Networks Tracks Fluctuations in Gain/Loss Framing Susceptibility

PubMed Central

Smith, David V.; Sip, Kamila E.; Delgado, Mauricio R.

2016-01-01

Multiple large-scale neural networks orchestrate a wide range of cognitive processes. For example, interoceptive processes related to self-referential thinking have been linked to the default-mode network (DMN); whereas exteroceptive processes related to cognitive control have been linked to the executive-control network (ECN). Although the DMN and ECN have been postulated to exert opposing effects on cognition, it remains unclear how connectivity with these spatially overlapping networks contribute to fluctuations in behavior. While previous work has suggested the medial prefrontal cortex (MPFC) is involved in behavioral change following feedback, these observations could be linked to interoceptive processes tied to DMN or exteroceptive processes tied to ECN because MPFC is positioned in both networks. To address this problem, we employed independent component analysis combined with dual-regression functional connectivity analysis. Participants made a series of financial decisions framed as monetary gains or losses. In some sessions, participants received feedback from a peer observing their choices; in other sessions, feedback was not provided. Following feedback, framing susceptibility—indexed as the increase in gambling behavior in loss frames compared to gain frames—was heightened in some participants and diminished in others. We examined whether these individual differences were linked to differences in connectivity by contrasting sessions containing feedback against those that did not contain feedback. We found two key results. As framing susceptibility increased, the MPFC increased connectivity with DMN; in contrast, temporal-parietal junction decreased connectivity with the ECN. Our results highlight how functional connectivity patterns with distinct neural networks contribute to idiosyncratic behavioral changes. PMID:25858445

Functional connectivity with distinct neural networks tracks fluctuations in gain/loss framing susceptibility.

PubMed

Smith, David V; Sip, Kamila E; Delgado, Mauricio R

2015-07-01

Multiple large-scale neural networks orchestrate a wide range of cognitive processes. For example, interoceptive processes related to self-referential thinking have been linked to the default-mode network (DMN); whereas exteroceptive processes related to cognitive control have been linked to the executive-control network (ECN). Although the DMN and ECN have been postulated to exert opposing effects on cognition, it remains unclear how connectivity with these spatially overlapping networks contribute to fluctuations in behavior. While previous work has suggested the medial-prefrontal cortex (MPFC) is involved in behavioral change following feedback, these observations could be linked to interoceptive processes tied to DMN or exteroceptive processes tied to ECN because MPFC is positioned in both networks. To address this problem, we employed independent component analysis combined with dual-regression functional connectivity analysis. Participants made a series of financial decisions framed as monetary gains or losses. In some sessions, participants received feedback from a peer observing their choices; in other sessions, feedback was not provided. Following feedback, framing susceptibility-indexed as the increase in gambling behavior in loss frames compared to gain frames-was heightened in some participants and diminished in others. We examined whether these individual differences were linked to differences in connectivity by contrasting sessions containing feedback against those that did not contain feedback. We found two key results. As framing susceptibility increased, the MPFC increased connectivity with DMN; in contrast, temporal-parietal junction decreased connectivity with the ECN. Our results highlight how functional connectivity patterns with distinct neural networks contribute to idiosyncratic behavioral changes. © 2015 Wiley Periodicals, Inc.

Dynamic Network Drivers of Seizure Generation, Propagation and Termination in Human Neocortical Epilepsy

PubMed Central

Khambhati, Ankit N.; Davis, Kathryn A.; Oommen, Brian S.; Chen, Stephanie H.; Lucas, Timothy H.; Litt, Brian; Bassett, Danielle S.

2015-01-01

The epileptic network is characterized by pathologic, seizure-generating ‘foci’ embedded in a web of structural and functional connections. Clinically, seizure foci are considered optimal targets for surgery. However, poor surgical outcome suggests a complex relationship between foci and the surrounding network that drives seizure dynamics. We developed a novel technique to objectively track seizure states from dynamic functional networks constructed from intracranial recordings. Each dynamical state captures unique patterns of network connections that indicate synchronized and desynchronized hubs of neural populations. Our approach suggests that seizures are generated when synchronous relationships near foci work in tandem with rapidly changing desynchronous relationships from the surrounding epileptic network. As seizures progress, topographical and geometrical changes in network connectivity strengthen and tighten synchronous connectivity near foci—a mechanism that may aid seizure termination. Collectively, our observations implicate distributed cortical structures in seizure generation, propagation and termination, and may have practical significance in determining which circuits to modulate with implantable devices. PMID:26680762

Disruption to control network function correlates with altered dynamic connectivity in the wider autism spectrum.

PubMed

de Lacy, N; Doherty, D; King, B H; Rachakonda, S; Calhoun, V D

2017-01-01

Autism is a common developmental condition with a wide, variable range of co-occurring neuropsychiatric symptoms. Contrasting with most extant studies, we explored whole-brain functional organization at multiple levels simultaneously in a large subject group reflecting autism's clinical diversity, and present the first network-based analysis of transient brain states, or dynamic connectivity , in autism. Disruption to inter-network and inter-system connectivity, rather than within individual networks, predominated. We identified coupling disruption in the anterior-posterior default mode axis, and among specific control networks specialized for task start cues and the maintenance of domain-independent task positive status, specifically between the right fronto-parietal and cingulo-opercular networks and default mode network subsystems. These appear to propagate downstream in autism, with significantly dampened subject oscillations between brain states, and dynamic connectivity configuration differences. Our account proposes specific motifs that may provide candidates for neuroimaging biomarkers within heterogeneous clinical populations in this diverse condition.

Mindfulness Meditation Training and Executive Control Network Resting State Functional Connectivity: A Randomized Controlled Trial.

PubMed

Taren, Adrienne A; Gianaros, Peter J; Greco, Carol M; Lindsay, Emily K; Fairgrieve, April; Brown, Kirk Warren; Rosen, Rhonda K; Ferris, Jennifer L; Julson, Erica; Marsland, Anna L; Creswell, J David

Mindfulness meditation training has been previously shown to enhance behavioral measures of executive control (e.g., attention, working memory, cognitive control), but the neural mechanisms underlying these improvements are largely unknown. Here, we test whether mindfulness training interventions foster executive control by strengthening functional connections between dorsolateral prefrontal cortex (dlPFC)-a hub of the executive control network-and frontoparietal regions that coordinate executive function. Thirty-five adults with elevated levels of psychological distress participated in a 3-day randomized controlled trial of intensive mindfulness meditation or relaxation training. Participants completed a resting state functional magnetic resonance imaging scan before and after the intervention. We tested whether mindfulness meditation training increased resting state functional connectivity (rsFC) between dlPFC and frontoparietal control network regions. Left dlPFC showed increased connectivity to the right inferior frontal gyrus (T = 3.74), right middle frontal gyrus (MFG) (T = 3.98), right supplementary eye field (T = 4.29), right parietal cortex (T = 4.44), and left middle temporal gyrus (T = 3.97, all p < .05) after mindfulness training relative to the relaxation control. Right dlPFC showed increased connectivity to right MFG (T = 4.97, p < .05). We report that mindfulness training increases rsFC between dlPFC and dorsal network (superior parietal lobule, supplementary eye field, MFG) and ventral network (right IFG, middle temporal/angular gyrus) regions. These findings extend previous work showing increased functional connectivity among brain regions associated with executive function during active meditation by identifying specific neural circuits in which rsFC is enhanced by a mindfulness intervention in individuals with high levels of psychological distress. Clinicaltrials.gov,NCT01628809.

Altered Structural and Functional Connectivity in Late Preterm Preadolescence: An Anatomic Seed-Based Study of Resting State Networks Related to the Posteromedial and Lateral Parietal Cortex.

PubMed

Degnan, Andrew J; Wisnowski, Jessica L; Choi, SoYoung; Ceschin, Rafael; Bhushan, Chitresh; Leahy, Richard M; Corby, Patricia; Schmithorst, Vincent J; Panigrahy, Ashok

2015-01-01

Late preterm birth confers increased risk of developmental delay, academic difficulties and social deficits. The late third trimester may represent a critical period of development of neural networks including the default mode network (DMN), which is essential to normal cognition. Our objective is to identify functional and structural connectivity differences in the posteromedial cortex related to late preterm birth. Thirty-eight preadolescents (ages 9-13; 19 born in the late preterm period (≥32 weeks gestational age) and 19 at term) without access to advanced neonatal care were recruited from a low socioeconomic status community in Brazil. Participants underwent neurocognitive testing, 3-dimensional T1-weighted imaging, diffusion-weighted imaging and resting state functional MRI (RS-fMRI). Seed-based probabilistic diffusion tractography and RS-fMRI analyses were performed using unilateral seeds within the posterior DMN (posterior cingulate cortex, precuneus) and lateral parietal DMN (superior marginal and angular gyri). Late preterm children demonstrated increased functional connectivity within the posterior default mode networks and increased anti-correlation with the central-executive network when seeded from the posteromedial cortex (PMC). Key differences were demonstrated between PMC components with increased anti-correlation with the salience network seen only with posterior cingulate cortex seeding but not with precuneus seeding. Probabilistic tractography showed increased streamlines within the right inferior longitudinal fasciculus and inferior fronto-occipital fasciculus within late preterm children while decreased intrahemispheric streamlines were also observed. No significant differences in neurocognitive testing were demonstrated between groups. Late preterm preadolescence is associated with altered functional connectivity from the PMC and lateral parietal cortex to known distributed functional cortical networks despite no significant executive neurocognitive differences. Selective increased structural connectivity was observed in the setting of decreased posterior interhemispheric connections. Future work is needed to determine if these findings represent a compensatory adaptation employing alternate neural circuitry or could reflect subtle pathology resulting in emotional processing deficits not seen with neurocognitive testing.

Oscillations during observations: Dynamic oscillatory networks serving visuospatial attention.

PubMed

Wiesman, Alex I; Heinrichs-Graham, Elizabeth; Proskovec, Amy L; McDermott, Timothy J; Wilson, Tony W

2017-10-01

The dynamic allocation of neural resources to discrete features within a visual scene enables us to react quickly and accurately to salient environmental circumstances. A network of bilateral cortical regions is known to subserve such visuospatial attention functions; however the oscillatory and functional connectivity dynamics of information coding within this network are not fully understood. Particularly, the coding of information within prototypical attention-network hubs and the subsecond functional connections formed between these hubs have not been adequately characterized. Herein, we use the precise temporal resolution of magnetoencephalography (MEG) to define spectrally specific functional nodes and connections that underlie the deployment of attention in visual space. Twenty-three healthy young adults completed a visuospatial discrimination task designed to elicit multispectral activity in visual cortex during MEG, and the resulting data were preprocessed and reconstructed in the time-frequency domain. Oscillatory responses were projected to the cortical surface using a beamformer, and time series were extracted from peak voxels to examine their temporal evolution. Dynamic functional connectivity was then computed between nodes within each frequency band of interest. We find that visual attention network nodes are defined functionally by oscillatory frequency, that the allocation of attention to the visual space dynamically modulates functional connectivity between these regions on a millisecond timescale, and that these modulations significantly correlate with performance on a spatial discrimination task. We conclude that functional hubs underlying visuospatial attention are segregated not only anatomically but also by oscillatory frequency, and importantly that these oscillatory signatures promote dynamic communication between these hubs. Hum Brain Mapp 38:5128-5140, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Changed Hub and Corresponding Functional Connectivity of Subgenual Anterior Cingulate Cortex in Major Depressive Disorder

PubMed Central

Wu, Huawang; Sun, Hui; Xu, Jinping; Wu, Yan; Wang, Chao; Xiao, Jing; She, Shenglin; Huang, Jianwei; Zou, Wenjin; Peng, Hongjun; Lu, Xiaobing; Huang, Guimao; Jiang, Tianzi; Ning, Yuping; Wang, Jiaojian

2016-01-01

Major depressive disorder (MDD) is one of the most prevalent mental disorders. In the brain, the hubs of the brain network play a key role in integrating and transferring information between different functional modules. However, whether the changed pattern in functional network hubs contributes to the onset of MDD remains unclear. Using resting-state functional magnetic resonance imaging (rs-fMRI) and graph theory methods, we investigated whether alterations of hubs can be detected in MDD. First, we constructed the whole-brain voxel-wise functional networks and calculated a functional connectivity strength (FCS) map in each subject in 34 MDD patients and 34 gender-, age- and education level-matched healthy controls (HCs). Next, the two-sample t-test was applied to compare the FCS maps between HC and MDD patients and identified significant decrease of FCS in subgenual anterior cingulate cortex (sgACC) in MDD patients. Subsequent functional connectivity analyses of sgACC showed disruptions in functional connectivity with posterior insula, middle and inferior temporal gyrus, lingual gyrus and cerebellum in MDD patients. Furthermore, the changed FCS of sgACC and functional connections to sgACC were significantly correlated with the Hamilton Depression Rating Scale (HDRS) scores in MDD patients. The results of the present study revealed the abnormal hub of sgACC and its corresponding disrupted frontal-limbic-visual cognitive-cerebellum functional networks in MDD. These findings may provide a new insight for the diagnosis and treatment of MDD. PMID:28018183

Large-Scale Network Dysfunction in Major Depressive Disorder: A Meta-analysis of Resting-State Functional Connectivity.

PubMed

Kaiser, Roselinde H; Andrews-Hanna, Jessica R; Wager, Tor D; Pizzagalli, Diego A

2015-06-01

Major depressive disorder (MDD) has been linked to imbalanced communication among large-scale brain networks, as reflected by abnormal resting-state functional connectivity (rsFC). However, given variable methods and results across studies, identifying consistent patterns of network dysfunction in MDD has been elusive. To investigate network dysfunction in MDD through a meta-analysis of rsFC studies. Seed-based voxelwise rsFC studies comparing individuals with MDD with healthy controls (published before June 30, 2014) were retrieved from electronic databases (PubMed, Web of Science, and EMBASE) and authors contacted for additional data. Twenty-seven seed-based voxel-wise rsFC data sets from 25 publications (556 individuals with MDD and 518 healthy controls) were included in the meta-analysis. Coordinates of seed regions of interest and between-group effects were extracted. Seeds were categorized into seed-networks by their location within a priori functional networks. Multilevel kernel density analysis of between-group effects identified brain systems in which MDD was associated with hyperconnectivity (increased positive or reduced negative connectivity) or hypoconnectivity (increased negative or reduced positive connectivity) with each seed-network. Major depressive disorder was characterized by hypoconnectivity within the frontoparietal network, a set of regions involved in cognitive control of attention and emotion regulation, and hypoconnectivity between frontoparietal systems and parietal regions of the dorsal attention network involved in attending to the external environment. Major depressive disorder was also associated with hyperconnectivity within the default network, a network believed to support internally oriented and self-referential thought, and hyperconnectivity between frontoparietal control systems and regions of the default network. Finally, the MDD groups exhibited hypoconnectivity between neural systems involved in processing emotion or salience and midline cortical regions that may mediate top-down regulation of such functions. Reduced connectivity within frontoparietal control systems and imbalanced connectivity between control systems and networks involved in internal or external attention may reflect depressive biases toward internal thoughts at the cost of engaging with the external world. Meanwhile, altered connectivity between neural systems involved in cognitive control and those that support salience or emotion processing may relate to deficits regulating mood. These findings provide an empirical foundation for a neurocognitive model in which network dysfunction underlies core cognitive and affective abnormalities in depression.

Anti-correlated cortical networks of intrinsic connectivity in the rat brain.

PubMed

Schwarz, Adam J; Gass, Natalia; Sartorius, Alexander; Risterucci, Celine; Spedding, Michael; Schenker, Esther; Meyer-Lindenberg, Andreas; Weber-Fahr, Wolfgang

2013-01-01

In humans, resting-state blood oxygen level-dependent (BOLD) signals in the default mode network (DMN) are temporally anti-correlated with those from a lateral cortical network involving the frontal eye fields, secondary somatosensory and posterior insular cortices. Here, we demonstrate the existence of an analogous lateral cortical network in the rat brain, extending laterally from anterior secondary sensorimotor regions to the insular cortex and exhibiting low-frequency BOLD fluctuations that are temporally anti-correlated with a midline "DMN-like" network comprising posterior/anterior cingulate and prefrontal cortices. The primary nexus for this anti-correlation relationship was the anterior secondary motor cortex, close to regions that have been identified with frontal eye fields in the rat brain. The anti-correlation relationship was corroborated after global signal removal, underscoring this finding as a robust property of the functional connectivity signature in the rat brain. These anti-correlated networks demonstrate strong anatomical homology to networks identified in human and monkey connectivity studies, extend the known preserved functional connectivity relationships between rodent and primates, and support the use of resting-state functional magnetic resonance imaging as a translational imaging method between rat models and humans.

Anti-Correlated Cortical Networks of Intrinsic Connectivity in the Rat Brain

PubMed Central

Gass, Natalia; Sartorius, Alexander; Risterucci, Celine; Spedding, Michael; Schenker, Esther; Meyer-Lindenberg, Andreas; Weber-Fahr, Wolfgang

2013-01-01

Abstract In humans, resting-state blood oxygen level-dependent (BOLD) signals in the default mode network (DMN) are temporally anti-correlated with those from a lateral cortical network involving the frontal eye fields, secondary somatosensory and posterior insular cortices. Here, we demonstrate the existence of an analogous lateral cortical network in the rat brain, extending laterally from anterior secondary sensorimotor regions to the insular cortex and exhibiting low-frequency BOLD fluctuations that are temporally anti-correlated with a midline “DMN-like” network comprising posterior/anterior cingulate and prefrontal cortices. The primary nexus for this anti-correlation relationship was the anterior secondary motor cortex, close to regions that have been identified with frontal eye fields in the rat brain. The anti-correlation relationship was corroborated after global signal removal, underscoring this finding as a robust property of the functional connectivity signature in the rat brain. These anti-correlated networks demonstrate strong anatomical homology to networks identified in human and monkey connectivity studies, extend the known preserved functional connectivity relationships between rodent and primates, and support the use of resting-state functional magnetic resonance imaging as a translational imaging method between rat models and humans. PMID:23919836

Dexmedetomidine Disrupts the Local and Global Efficiencies of Large-scale Brain Networks.

PubMed

Hashmi, Javeria A; Loggia, Marco L; Khan, Sheraz; Gao, Lei; Kim, Jieun; Napadow, Vitaly; Brown, Emery N; Akeju, Oluwaseun

2017-03-01

A clear understanding of the neural basis of consciousness is fundamental to research in clinical and basic neuroscience disciplines and anesthesia. Recently, decreased efficiency of information integration was suggested as a core network feature of propofol-induced unconsciousness. However, it is unclear whether this finding can be generalized to dexmedetomidine, which has a different molecular target. Dexmedetomidine was administered as a 1-μg/kg bolus over 10 min, followed by a 0.7-μg · kg · h infusion to healthy human volunteers (age range, 18 to 36 yr; n = 15). Resting-state functional magnetic resonance imaging data were acquired during baseline, dexmedetomidine-induced altered arousal, and recovery states. Zero-lag correlations between resting-state functional magnetic resonance imaging signals extracted from 131 brain parcellations were used to construct weighted brain networks. Network efficiency, degree distribution, and node strength were computed using graph analysis. Parcellated brain regions were also mapped to known resting-state networks to study functional connectivity changes. Dexmedetomidine significantly reduced the local and global efficiencies of graph theory-derived networks. Dexmedetomidine also reduced the average brain connectivity strength without impairing the degree distribution. Functional connectivity within and between all resting-state networks was modulated by dexmedetomidine. Dexmedetomidine is associated with a significant drop in the capacity for efficient information transmission at both the local and global levels. These changes result from reductions in the strength of connectivity and also manifest as reduced within and between resting-state network connectivity. These findings strengthen the hypothesis that conscious processing relies on an efficient system of information transfer in the brain.

Physical Activity After Stroke Is Associated With Increased Interhemispheric Connectivity of the Dorsal Attention Network.

PubMed

Veldsman, Michele; Churilov, Leonid; Werden, Emilio; Li, Qi; Cumming, Toby; Brodtmann, Amy

2017-02-01

Attention is frequently impaired after stroke, and its impairment is associated with poor quality of life. Physical activity benefits attention in healthy populations and has also been associated with recovery after brain injury. We investigated the relationship between objectively measured daily physical activity, attention network connectivity, and attention task performance after stroke. We hypothesized that increased daily physical activity would be associated with improved attention network function. Stroke patients (n = 62; mean age = 67 years, SD = 12.6 years) and healthy controls (n = 27; mean age = 68 years, SD = 6 years) underwent cognitive testing and 7 minutes of functional magnetic resonance imaging in the resting-state. Patients were tested 3 months after ischemic stroke. Physical activity was monitored with an electronic armband worn for 7 days. Dorsal and ventral attention network function was examined using seed-based connectivity analyses. Greater daily physical activity was associated with increased interhemispheric connectivity of the superior parietal lobule in the dorsal attention network (DAN; P < .05, false discovery rate corrected). This relationship was not explained by stroke lesion volume. Importantly, stronger connectivity in this region was related to faster reaction time in 3 attention tasks, as revealed by robust linear regression. The relationship remained after adjusting for age, gray matter volume, and white matter hyperintensity load. Daily physical activity was associated with increased resting interhemispheric connectivity of the DAN. Increased connectivity was associated with faster attention performance, suggesting a cognitive correlate to increased network connectivity. Attentional modulation by physical activity represents a key focus for intervention studies.

An Adaptive Complex Network Model for Brain Functional Networks

PubMed Central

Gomez Portillo, Ignacio J.; Gleiser, Pablo M.

2009-01-01

Brain functional networks are graph representations of activity in the brain, where the vertices represent anatomical regions and the edges their functional connectivity. These networks present a robust small world topological structure, characterized by highly integrated modules connected sparsely by long range links. Recent studies showed that other topological properties such as the degree distribution and the presence (or absence) of a hierarchical structure are not robust, and show different intriguing behaviors. In order to understand the basic ingredients necessary for the emergence of these complex network structures we present an adaptive complex network model for human brain functional networks. The microscopic units of the model are dynamical nodes that represent active regions of the brain, whose interaction gives rise to complex network structures. The links between the nodes are chosen following an adaptive algorithm that establishes connections between dynamical elements with similar internal states. We show that the model is able to describe topological characteristics of human brain networks obtained from functional magnetic resonance imaging studies. In particular, when the dynamical rules of the model allow for integrated processing over the entire network scale-free non-hierarchical networks with well defined communities emerge. On the other hand, when the dynamical rules restrict the information to a local neighborhood, communities cluster together into larger ones, giving rise to a hierarchical structure, with a truncated power law degree distribution. PMID:19738902

Functional Disconnectivity during Inter-Task Resting State in Dementia with Lewy Bodies.

PubMed

Chabran, Eléna; Roquet, Daniel; Gounot, Daniel; Sourty, Marion; Armspach, Jean-Paul; Blanc, Frédéric

2018-01-01

Limited research has been done on the functional connectivity in visuoperceptual regions in dementia with Lewy bodies (DLB) patients. This study aimed to investigate the functional connectivity differences between a task condition and an inter-task resting state condition within a visuoperceptual paradigm, in DLB patients compared with Alzheimer disease (AD) patients and healthy elderly control subjects. Twenty-six DLB, 29 AD, and 22 healthy subjects underwent a detailed clinical and neuropsychological examination along with a functional MRI during the different conditions of a visuoperceptual paradigm. Functional images were analyzed using group-level spatial independent component analysis and seed-based connectivity analyses. While the DLB patients scored well and did not differ from the control and AD groups in terms of functional activity and connectivity during the task conditions, they showed decreased functional connectivity in visuoperceptual regions during the resting state condition, along with a temporal impairment of the default-mode network activity. Functional connectivity disturbances were also found within two attentional-executive networks and between these networks and visuoperceptual regions. We found a specific functional profile in the switching between task and resting state conditions in DLB patients. This result could help better characterize functional impairments in DLB and their contribution to several core symptoms of this pathology such as visual hallucinations and cognitive fluctuations. © 2018 S. Karger AG, Basel.

Distinctive Resting State Network Disruptions Among Alzheimer's Disease, Subcortical Vascular Dementia, and Mixed Dementia Patients.

PubMed

Kim, Hee Jin; Cha, Jungho; Lee, Jong-Min; Shin, Ji Soo; Jung, Na-Yeon; Kim, Yeo Jin; Choe, Yearn Seong; Lee, Kyung Han; Kim, Sung Tae; Kim, Jae Seung; Lee, Jae Hong; Na, Duk L; Seo, Sang Won

2016-01-01

Recent advances in resting-state functional MRI have revealed altered functional networks in Alzheimer's disease (AD), especially those of the default mode network (DMN) and central executive network (CEN). However, few studies have evaluated whether small vessel disease (SVD) or combined amyloid and SVD burdens affect the DMN or CEN. The aim of this study was to evaluate whether SVD or combined amyloid and SVD burdens affect the DMN or CEN. In this cross-sectional study, we investigated the resting-state functional connectivity within DMN and CEN in 37 Pittsburgh compound-B (PiB)(+) AD, 37 PiB(-) subcortical vascular dementia (SVaD), 13 mixed dementia patients, and 65 normal controls. When the resting-state DMN of PiB(+) AD and PiB(-) SVaD patients were compared, the PiB(+) AD patients displayed lower functional connectivity in the inferior parietal lobule while the PiB(-) SVaD patients displayed lower functional connectivity in the medial frontal and superior frontal gyri. Compared to the PiB(-) SVaD or PiB(+) AD, the mixed dementia patients displayed lower functional connectivity within the DMN in the posterior cingulate gyrus. When the resting-state CEN connectivity of PiB(+) AD and PiB(-) SVaD patients were compared, the PiB(-) SVaD patients displayed lower functional connectivity in the anterior insular region. Compared to the PiB(-) SVaD or PiB(+) AD, the mixed dementia patients displayed lower functional connectivity within the CEN in the inferior frontal gyrus. Our findings suggest that in PiB(+) AD and PiB(-) SVaD, there is divergent disruptions in resting-state DMN and CEN. Furthermore, patients with combined amyloid and SVD burdens exhibited more disrupted resting-state DMN and CEN than patients with only amyloid or SVD burden.

Ventral Striatum Functional Connectivity as a Predictor of Adolescent Depressive Disorder in a Longitudinal Community-Based Sample.

PubMed

Pan, Pedro Mario; Sato, João R; Salum, Giovanni A; Rohde, Luis A; Gadelha, Ary; Zugman, Andre; Mari, Jair; Jackowski, Andrea; Picon, Felipe; Miguel, Eurípedes C; Pine, Daniel S; Leibenluft, Ellen; Bressan, Rodrigo A; Stringaris, Argyris

2017-11-01

Previous studies have implicated aberrant reward processing in the pathogenesis of adolescent depression. However, no study has used functional connectivity within a distributed reward network, assessed using resting-state functional MRI (fMRI), to predict the onset of depression in adolescents. This study used reward network-based functional connectivity at baseline to predict depressive disorder at follow-up in a community sample of adolescents. A total of 637 children 6-12 years old underwent resting-state fMRI. Discovery and replication analyses tested intrinsic functional connectivity (iFC) among nodes of a putative reward network. Logistic regression tested whether striatal node strength, a measure of reward-related iFC, predicted onset of a depressive disorder at 3-year follow-up. Further analyses investigated the specificity of this prediction. Increased left ventral striatum node strength predicted increased risk for future depressive disorder (odds ratio=1.54, 95% CI=1.09-2.18), even after excluding participants who had depressive disorders at baseline (odds ratio=1.52, 95% CI=1.05-2.20). Among 11 reward-network nodes, only the left ventral striatum significantly predicted depression. Striatal node strength did not predict other common adolescent psychopathology, such as anxiety, attention deficit hyperactivity disorder, and substance use. Aberrant ventral striatum functional connectivity specifically predicts future risk for depressive disorder. This finding further emphasizes the need to understand how brain reward networks contribute to youth depression.

[Seeking the aetiology of autistic spectrum disorder. Part 2: Functional neuroimaging].

PubMed

Bryńska, Anita

2012-01-01

Multiple functional imaging techniques help to a better understanding of the neurobiological basis of autism-spectrum disorders (ASD). The early functional imaging studies on ASD focused on task-specific methods related to core symptom domains and explored patterns of activation in response to face processing, theory of mind tasks, language processing and executive function tasks. On the other hand, fMRI research in ASD focused on the development of functional connectivity methods and has provided evidence of alterations in cortical connectivity in ASD and establish autism as a disorder of under-connectivity among the brain regions participating in cortical networks. This atypical functional connectivity in ASD results in inefficiency and poor integration of processing in network connections to achieve task performance. The goal of this review is to summarise the actual neuroimaging functional data and examine their implication for understanding of the neurobiology of ASD.

Double-dissociation between the mechanism leading to impulsivity and inattention in Attention Deficit Hyperactivity Disorder: A resting-state functional connectivity study.

PubMed

Sanefuji, Masafumi; Craig, Michael; Parlatini, Valeria; Mehta, Mitul A; Murphy, Declan G; Catani, Marco; Cerliani, Leonardo; Thiebaut de Schotten, Michel

2017-01-01

Two core symptoms characterize Attention Deficit Hyperactivity Disorder (ADHD) subtypes: inattentiveness and hyperactivity-impulsivity. While previous brain imaging research investigated ADHD as if it was a homogenous condition, its two core symptoms may originate from different brain mechanisms. We, therefore, hypothesized that the functional connectivity of cortico-striatal and attentional networks would be different between ADHD subtypes. We studied 165 children (mean age 10.93 years; age range, 7-17 year old) diagnosed as having ADHD based on their revised Conner's rating scale score and 170 typical developing individuals (mean age 11.46 years; age range, 7-17 year old) using resting state functional fMRI. Groups were matched for age, IQ and head motion during the MRI acquisition. We fractionated the ADHD group into predominantly inattentive, hyperactive-impulsive and combined subtypes based on their revised Conner's rating scale score. We then analyzed differences in resting state functional connectivity of the cortico-striatal and attentional networks between these subtypes. We found a double dissociation of functional connectivity in the cortico-striatal and ventral attentional networks, reflecting the subtypes of the ADHD participants. Particularly, the hyperactive-impulsive subtype was associated with increased connectivity in cortico-striatal network, whereas the inattentive subtype was associated with increased connectivity in the right ventral attention network. Our study demonstrated for the first time a right lateralized, double dissociation between specific networks associated with hyperactivity-impulsivity and inattentiveness in ADHD children, providing a biological basis for exploring symptom dimensions and revealing potential targets for more personalized treatments. Copyright © 2016 Elsevier Ltd. All rights reserved.

Hemispheric asymmetry of electroencephalography-based functional brain networks.

PubMed

Jalili, Mahdi

2014-11-12

Electroencephalography (EEG)-based functional brain networks have been investigated frequently in health and disease. It has been shown that a number of graph theory metrics are disrupted in brain disorders. EEG-based brain networks are often studied in the whole-brain framework, where all the nodes are grouped into a single network. In this study, we studied the brain networks in two hemispheres and assessed whether there are any hemispheric-specific patterns in the properties of the networks. To this end, resting state closed-eyes EEGs from 44 healthy individuals were processed and the network structures were extracted separately for each hemisphere. We examined neurophysiologically meaningful graph theory metrics: global and local efficiency measures. The global efficiency did not show any hemispheric asymmetry, whereas the local connectivity showed rightward asymmetry for a range of intermediate density values for the constructed networks. Furthermore, the age of the participants showed significant direct correlations with the global efficiency of the left hemisphere, but only in the right hemisphere, with local connectivity. These results suggest that only local connectivity of EEG-based functional networks is associated with brain hemispheres.

Weak network efficiency in young children with Autism Spectrum Disorder: Evidence from a functional near-infrared spectroscopy study.

PubMed

Li, Yanwei; Yu, Dongchuan

2016-10-01

Functional near infrared spectroscopy (fNIRS) is particularly suited for the young population and ecological measurement. However, thus far, not enough effort has been given to the clinical diagnosis of young children with Autism Spectrum Disorder (ASD) by using fNIRS. The current study provided some insights into the quantitative analysis of functional networks in young children (ages 4.8-8.0years old) with and without ASD and, in particular, investigated the network efficiency and lobe-level connectivity of their functional networks while watching a cartoon. The main results included that: (i) Weak network efficiency was observed in young children with ASD, even for a wide range of threshold for the binarization of functional networks; (ii) A maximum classification accuracy rate of 83.3% was obtained for all participants by using the k-means clustering method with network efficiencies as the feature parameters; and (iii) Weak lobe-level inter-region connections were uncovered in the right prefrontal cortex, including its linkages with the left prefrontal cortex and the bilateral temporal cortex. Such results indicate that the right prefrontal cortex might make a major contribution to the psychopathology of young children with ASD at the functional network architecture level, and at the functional lobe-connectivity level, respectively. Copyright © 2016 Elsevier Inc. All rights reserved.

Functional connectome fingerprinting: identifying individuals using patterns of brain connectivity.

PubMed

Finn, Emily S; Shen, Xilin; Scheinost, Dustin; Rosenberg, Monica D; Huang, Jessica; Chun, Marvin M; Papademetris, Xenophon; Constable, R Todd

2015-11-01

Functional magnetic resonance imaging (fMRI) studies typically collapse data from many subjects, but brain functional organization varies between individuals. Here we establish that this individual variability is both robust and reliable, using data from the Human Connectome Project to demonstrate that functional connectivity profiles act as a 'fingerprint' that can accurately identify subjects from a large group. Identification was successful across scan sessions and even between task and rest conditions, indicating that an individual's connectivity profile is intrinsic, and can be used to distinguish that individual regardless of how the brain is engaged during imaging. Characteristic connectivity patterns were distributed throughout the brain, but the frontoparietal network emerged as most distinctive. Furthermore, we show that connectivity profiles predict levels of fluid intelligence: the same networks that were most discriminating of individuals were also most predictive of cognitive behavior. Results indicate the potential to draw inferences about single subjects on the basis of functional connectivity fMRI.

Brain Connectivity and Functional Recovery in Patients With Ischemic Stroke.

PubMed

Almeida, Sara Regina Meira; Vicentini, Jessica; Bonilha, Leonardo; De Campos, Brunno M; Casseb, Raphael F; Min, Li Li

2017-01-01

Brain mapping studies have demonstrated that functional poststroke brain reorganization is associated with recovery of motor function. Nonetheless, the specific mechanisms associated with functional reorganization leading to motor recovery are still partly unknown. In this study, we performed a cross-sectional evaluation of poststroke subjects with the following goals: (1) To assess intra- and interhemispheric functional brain activation patterns associated with motor function in poststroke patients with variable degrees of recovery; (2) to investigate the involvement of other nonmotor functional networks in relationship with recovery. We studied 59 individuals: 13 patients with function Rankin > 1 and Barthel < 100; 19 patients with preserved function with Rankin 0-1 and Barthel = 100; and 27 healthy controls. All subjects underwent structural and functional magnetic resonance imaging (3T Philips Achieva, Holland) using the same protocol (TR = 2 seconds, TE = 30 ms, FOV = 240 × 240 × 117, slice = 39). Resting state functional connectivity was used by in-house software, based on SPM12. Among patients with and without preserved function, the functional connectivity between the primary motor region (M1) and the contralateral hemisphere was increased compared with controls. Nonetheless, only patients with decreased function exhibited decreased functional connectivity between executive control, sensorimotor and visuospatial networks. Functional recovery after stroke is associated with preserved functional connectivity of motor to nonmotor networks. Copyright © 2016 by the American Society of Neuroimaging.

Intranetwork and internetwork connectivity in patients with Alzheimer disease and the association with cerebrospinal fluid biomarker levels.

PubMed

Weiler, Marina; de Campos, Brunno Machado; Teixeira, Camila Vieira de Ligo; Casseb, Raphael Fernandes; Carletti-Cassani, Ana Flávia Mac Knight; Vicentini, Jéssica Elias; Magalhães, Thamires Naela Cardoso; Talib, Leda Leme; Forlenza, Orestes Vicente; Balthazar, Marcio Luiz Figueredo

2017-11-01

In the last decade, many studies have reported abnormal connectivity within the default mode network (DMN) in patients with Alzheimer disease. Few studies, however, have investigated other networks and their association with pathophysiological proteins obtained from cerebrospinal fluid (CSF). We performed 3 T imaging in patients with mild Alzheimer disease, patients with amnestic mild cognitive impairment (aMCI) and healthy controls, and we collected CSF samples from the patients with aMCI and mild Alzheimer disease. We analyzed 57 regions from 8 networks. Additionally, we performed correlation tests to investigate possible associations between the networks' functional connectivity and the protein levels obtained from the CSF of patients with aMCI and Alzheimer disease. Our sample included 41 patients with Alzheimer disease, 35 with aMCI and 48 controls. We found that the main connectivity abnormalities in those with Alzheimer disease occurred between the DMN and task-positive networks: these patients presented not only a decreased anticorrelation between some regions, but also an inversion of the correlation signal (positive correlation instead of anticorrelation). Those with aMCI did not present statistically different connectivity from patients with Alzheimer disease or controls. Abnormal levels of CSF proteins were associated with functional disconnectivity between several regions in both the aMCI and mild Alzheimer disease groups, extending well beyond the DMN or temporal areas. The presented data are cross-sectional in nature, and our findings are dependent on the choice of seed regions used. We found that the main functional connectivity abnormalities occur between the DMN and task-positive networks and that the pathological levels of CSF biomarkers correlate with functional connectivity disruption in patients with Alzheimer disease.

Brain intrinsic network connectivity in individuals with frequent tanning behavior.

PubMed

Ketcherside, Ariel; Filbey, Francesca M; Aubert, Pamela M; Seibyl, John P; Price, Julianne L; Adinoff, Bryon

2018-05-01

Emergent studies suggest a bidirectional relationship between brain functioning and the skin. This neurocutaneous connection may be responsible for the reward response to tanning and, thus, may contribute to excessive tanning behavior. To date, however, this association has not yet been examined. To explore whether intrinsic brain functional connectivity within the default mode network (DMN) is related to indoor tanning behavior. Resting state functional connectivity (rsFC) was obtained in twenty adults (16 females) with a history of indoor tanning. Using a seed-based [(posterior cingulate cortex (PCC)] approach, the relationship between tanning severity and FC strength was assessed. Tanning severity was measured with symptom count from the Structured Clinical Interview for Tanning Abuse and Dependence (SITAD) and tanning intensity (lifetime indoor tanning episodes/years tanning). rsFC strength between the PCC and other DMN regions (left globus pallidus, left medial frontal gyrus, left superior frontal gyrus) is positively correlated with tanning symptom count. rsFC strength between the PCC and salience network regions (right anterior cingulate cortex, left inferior parietal lobe, left inferior temporal gyrus) is correlated with tanning intensity. Greater connectivity between tanning severity and DMN and salience network connectivity suggests that heightened self-awareness of salient stimuli may be a mechanism that underlies frequent tanning behavior. These findings add to the growing evidence of brain-skin connection and reflect dysregulation in the reward processing networks in those with frequent tanning.

Intrinsic Connectivity Networks in post-traumatic stress disorder during sub- and supraliminal processing of threat-related stimuli.

PubMed

Rabellino, D; Tursich, M; Frewen, P A; Daniels, J K; Densmore, M; Théberge, J; Lanius, R A

2015-11-01

To investigate the functional connectivity of large-scale intrinsic connectivity networks (ICNs) in post-traumatic stress disorder (PTSD) during subliminal and supraliminal presentation of threat-related stimuli. Group independent component analysis was utilized to study functional connectivity within the ICNs most correlated with the Default-mode Network (DMN), Salience Network (SN), and Central Executive Network (CEN) in PTSD participants (n = 26) as compared to healthy controls (n = 20) during sub- and supraliminal processing of threat-related stimuli. Comparing patients with PTSD with healthy participants, prefrontal and anterior cingulate cortex involved in top-down regulation showed increased integration during subliminal threat processing within the CEN and SN and during supraliminal threat processing within the DMN. The right amygdala showed increased connectivity with the DMN during subliminal processing in PTSD as compared to controls. Brain regions associated with self-awareness and consciousness exhibited decreased connectivity during subliminal threat processing in PTSD as compared to controls: the claustrum within the SN and the precuneus within the DMN. Key nodes of the ICNs showed altered functional connectivity in PTSD as compared to controls, and differential results characterized sub- and supraliminal processing of threat-related stimuli. These findings enhance our understanding of ICNs underlying PTSD at different levels of conscious threat perception. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Large-scale coupling dynamics of instructed reversal learning.

PubMed

Mohr, Holger; Wolfensteller, Uta; Ruge, Hannes

2018-02-15

The ability to rapidly learn from others by instruction is an important characteristic of human cognition. A recent study found that the rapid transfer from initial instructions to fluid behavior is supported by changes of functional connectivity between and within several large-scale brain networks, and particularly by the coupling of the dorsal attention network (DAN) with the cingulo-opercular network (CON). In the present study, we extended this approach to investigate how these brain networks interact when stimulus-response mappings are altered by novel instructions. We hypothesized that residual stimulus-response associations from initial practice might negatively impact the ability to implement novel instructions. Using functional imaging and large-scale connectivity analysis, we found that functional coupling between the CON and DAN was generally at a higher level during initial than reversal learning. Examining the learning-related connectivity dynamics between the CON and DAN in more detail by means of multivariate patterns analyses, we identified a specific subset of connections which showed a particularly high increase in connectivity during initial learning compared to reversal learning. This finding suggests that the CON-DAN connections can be separated into two functionally dissociable yet spatially intertwined subsystems supporting different aspects of short-term task automatization. Copyright © 2017 Elsevier Inc. All rights reserved.

Schizophrenic patients and their unaffected siblings share increased resting-state connectivity in the task-negative network but not its anticorrelated task-positive network.

PubMed

Liu, Haihong; Kaneko, Yoshio; Ouyang, Xuan; Li, Li; Hao, Yihui; Chen, Eric Y H; Jiang, Tianzi; Zhou, Yuan; Liu, Zhening

2012-03-01

Abnormal connectivity of the anticorrelated intrinsic networks, the task-negative network (TNN), and the task-positive network (TPN) is implicated in schizophrenia. Comparisons between schizophrenic patients and their unaffected siblings enable further understanding of illness susceptibility and pathophysiology. We examined the resting-state connectivity differences in the intrinsic networks between schizophrenic patients, their unaffected siblings, and healthy controls. Resting-state functional magnetic resonance images were obtained from 25 individuals in each subject group. The posterior cingulate cortex/precuneus and right dorsolateral prefrontal cortex were used as seed regions to identify the TNN and TPN through functional connectivity analysis. Interregional connectivity strengths were analyzed using overlapped intrinsic networks composed of regions common to all subject groups. Schizophrenic patients and their unaffected siblings showed increased connectivity in the TNN between the bilateral inferior temporal gyri. By contrast, schizophrenic patients alone demonstrated increased connectivity between the posterior cingulate cortex/precuneus and left inferior temporal gyrus and between the ventral medial prefrontal cortex and right lateral parietal cortex in the TNN. Schizophrenic patients exhibited increased connectivity between the left dorsolateral prefrontal cortex and right inferior frontal gyrus in the TPN relative to their unaffected siblings, though this trend only approached statistical significance in comparison to healthy controls. Resting-state hyperconnectivity of the intrinsic networks may disrupt network coordination and thereby contribute to the pathophysiology of schizophrenia. Similar, though milder, hyperconnectivity of the TNN in unaffected siblings of schizophrenic patients may contribute to the identification of schizophrenia endophenotypes and ultimately to the determination of schizophrenia risk genes.

Intranasal oxytocin modulates neural functional connectivity during human social interaction.

PubMed

Rilling, James K; Chen, Xiangchuan; Chen, Xu; Haroon, Ebrahim

2018-02-10

Oxytocin (OT) modulates social behavior in primates and many other vertebrate species. Studies in non-primate animals have demonstrated that, in addition to influencing activity within individual brain areas, OT influences functional connectivity across networks of areas involved in social behavior. Previously, we used fMRI to image brain function in human subjects during a dyadic social interaction task following administration of either intranasal oxytocin (INOT) or placebo, and analyzed the data with a standard general linear model. Here, we conduct an extensive re-analysis of these data to explore how OT modulates functional connectivity across a neural network that animal studies implicate in social behavior. OT induced widespread increases in functional connectivity in response to positive social interactions among men and widespread decreases in functional connectivity in response to negative social interactions among women. Nucleus basalis of Meynert, an important regulator of selective attention and motivation with a particularly high density of OT receptors, had the largest number of OT-modulated connections. Regions known to receive mesolimbic dopamine projections such as the nucleus accumbens and lateral septum were also hubs for OT effects on functional connectivity. Our results suggest that the neural mechanism by which OT influences primate social cognition may include changes in patterns of activity across neural networks that regulate social behavior in other animals. © 2018 Wiley Periodicals, Inc.

Programmability of nanowire networks

NASA Astrophysics Data System (ADS)

Bellew, A. T.; Bell, A. P.; McCarthy, E. K.; Fairfield, J. A.; Boland, J. J.

2014-07-01

Electrical connectivity in networks of nanoscale junctions must be better understood if nanowire devices are to be scaled up from single wires to functional material systems. We show that the natural connectivity behaviour found in random nanowire networks presents a new paradigm for creating multi-functional, programmable materials. In devices made from networks of Ni/NiO core-shell nanowires at different length scales, we discover the emergence of distinct behavioural regimes when networks are electrically stressed. We show that a small network, with few nanowire-nanowire junctions, acts as a unipolar resistive switch, demonstrating very high ON/OFF current ratios (>105). However, large networks of nanowires distribute an applied bias across a large number of junctions, and thus respond not by switching but instead by evolving connectivity. We demonstrate that these emergent properties lead to fault-tolerant materials whose resistance may be tuned, and which are capable of adaptively reconfiguring under stress. By combining these two behavioural regimes, we demonstrate that the same nanowire network may be programmed to act both as a metallic interconnect, and a resistive switch device with high ON/OFF ratio. These results enable the fabrication of programmable, multi-functional materials from random nanowire networks.Electrical connectivity in networks of nanoscale junctions must be better understood if nanowire devices are to be scaled up from single wires to functional material systems. We show that the natural connectivity behaviour found in random nanowire networks presents a new paradigm for creating multi-functional, programmable materials. In devices made from networks of Ni/NiO core-shell nanowires at different length scales, we discover the emergence of distinct behavioural regimes when networks are electrically stressed. We show that a small network, with few nanowire-nanowire junctions, acts as a unipolar resistive switch, demonstrating very high ON/OFF current ratios (>105). However, large networks of nanowires distribute an applied bias across a large number of junctions, and thus respond not by switching but instead by evolving connectivity. We demonstrate that these emergent properties lead to fault-tolerant materials whose resistance may be tuned, and which are capable of adaptively reconfiguring under stress. By combining these two behavioural regimes, we demonstrate that the same nanowire network may be programmed to act both as a metallic interconnect, and a resistive switch device with high ON/OFF ratio. These results enable the fabrication of programmable, multi-functional materials from random nanowire networks. Electronic supplementary information (ESI) available: Nanowire statistics (length, diameter statistics, and oxide thickness) are provided. Forming curves for single junctions and networks. Passive voltage contrast image demonstrating selectivity of conductive pathways in 100 μm network. See DOI: 10.1039/c4nr02338b

Abnormal small-world architecture of top–down control networks in obsessive–compulsive disorder

PubMed Central

Zhang, Tijiang; Wang, Jinhui; Yang, Yanchun; Wu, Qizhu; Li, Bin; Chen, Long; Yue, Qiang; Tang, Hehan; Yan, Chaogan; Lui, Su; Huang, Xiaoqi; Chan, Raymond C.K.; Zang, Yufeng; He, Yong; Gong, Qiyong

2011-01-01

Background Obsessive–compulsive disorder (OCD) is a common neuropsychiatric disorder that is characterized by recurrent intrusive thoughts, ideas or images and repetitive ritualistic behaviours. Although focal structural and functional abnormalities in specific brain regions have been widely studied in populations with OCD, changes in the functional relations among them remain poorly understood. This study examined OCD–related alterations in functional connectivity patterns in the brain’s top–down control network. Methods We applied resting-state functional magnetic resonance imaging to investigate the correlation patterns of intrinsic or spontaneous blood oxygen level–dependent signal fluctuations in 18 patients with OCD and 16 healthy controls. The brain control networks were first constructed by thresholding temporal correlation matrices of 39 brain regions associated with top–down control and then analyzed using graph theory-based approaches. Results Compared with healthy controls, the patients with OCD showed decreased functional connectivity in the posterior temporal regions and increased connectivity in various control regions such as the cingulate, precuneus, thalamus and cerebellum. Furthermore, the brain’s control networks in the healthy controls showed small-world architecture (high clustering coefficients and short path lengths), suggesting an optimal balance between modularized and distributed information processing. In contrast, the patients with OCD showed significantly higher local clustering, implying abnormal functional organization in the control network. Further analysis revealed that the changes in network properties occurred in regions of increased functional connectivity strength in patients with OCD. Limitations The patient group in the present study was heterogeneous in terms of symptom clusters, and most of the patients with OCD were medicated. Conclusion Our preliminary results suggest that the organizational patterns of intrinsic brain activity in the control networks are altered in patients with OCD and thus provide empirical evidence for aberrant functional connectivity in the large-scale brain systems in people with this disorder. PMID:20964957

Comparison of functional network connectivity for passive-listening and active-response narrative comprehension in adolescents.

PubMed

Wang, Yingying; Holland, Scott K

2014-05-01

Comprehension of narrative stories plays an important role in the development of language skills. In this study, we compared brain activity elicited by a passive-listening version and an active-response (AR) version of a narrative comprehension task by using independent component (IC) analysis on functional magnetic resonance imaging data from 21 adolescents (ages 14-18 years). Furthermore, we explored differences in functional network connectivity engaged by two versions of the task and investigated the relationship between the online response time and the strength of connectivity between each pair of ICs. Despite similar brain region involvements in auditory, temporoparietal, and frontoparietal language networks for both versions, the AR version engages some additional network elements including the left dorsolateral prefrontal, anterior cingulate, and sensorimotor networks. These additional involvements are likely associated with working memory and maintenance of attention, which can be attributed to the differences in cognitive strategic aspects of the two versions. We found significant positive correlation between the online response time and the strength of connectivity between an IC in left inferior frontal region and an IC in sensorimotor region. An explanation for this finding is that longer reaction time indicates stronger connection between the frontal and sensorimotor networks caused by increased activation in adolescents who require more effort to complete the task.

Network analysis reveals disrupted functional brain circuitry in drug-naive social anxiety disorder.

PubMed

Yang, Xun; Liu, Jin; Meng, Yajing; Xia, Mingrui; Cui, Zaixu; Wu, Xi; Hu, Xinyu; Zhang, Wei; Gong, Gaolang; Gong, Qiyong; Sweeney, John A; He, Yong

2017-12-07

Social anxiety disorder (SAD) is a common and disabling condition characterized by excessive fear and avoidance of public scrutiny. Psychoradiology studies have suggested that the emotional and behavior deficits in SAD are associated with abnormalities in regional brain function and functional connectivity. However, little is known about whether intrinsic functional brain networks in patients with SAD are topologically disrupted. Here, we collected resting-state fMRI data from 33 drug-naive patients with SAD and 32 healthy controls (HC), constructed functional networks with 34 predefined regions based on previous meta-analytic research with task-based fMRI in SAD, and performed network-based statistic and graph-theory analyses. The network-based statistic analysis revealed a single connected abnormal circuitry including the frontolimbic circuit (termed the "fear circuit", including the dorsolateral prefrontal cortex, ventral medial prefrontal cortex and insula) and posterior cingulate/occipital areas supporting perceptual processing. In this single altered network, patients with SAD had higher functional connectivity than HC. At the global level, graph-theory analysis revealed that the patients exhibited a lower normalized characteristic path length than HC, which suggests a disorder-related shift of network topology toward randomized configurations. SAD-related deficits in nodal degree, efficiency and participation coefficient were detected in the parahippocampal gyrus, posterior cingulate cortex, dorsolateral prefrontal cortex, insula and the calcarine sulcus. Aspects of abnormal connectivity were associated with anxiety symptoms. These findings highlight the aberrant topological organization of functional brain network organization in SAD, which provides insights into the neural mechanisms underlying excessive fear and avoidance of social interactions in patients with debilitating social anxiety. Copyright © 2017. Published by Elsevier Inc.

Altered affective, executive and sensorimotor resting state networks in patients with pediatric mania

PubMed Central

Wu, Minjie; Lu, Lisa H.; Passarotti, Alessandra M.; Wegbreit, Ezra; Fitzgerald, Jacklynn; Pavuluri, Mani N.

2013-01-01

Background The aim of the present study was to map the pathophysiology of resting state functional connectivity accompanying structural and functional abnormalities in children with bipolar disorder. Methods Children with bipolar disorder and demographically matched healthy controls underwent resting-state functional magnetic resonance imaging. A model-free independent component analysis was performed to identify intrinsically interconnected networks. Results We included 34 children with bipolar disorder and 40 controls in our analysis. Three distinct resting state networks corresponding to affective, executive and sensorimotor functions emerged as being significantly different between the pediatric bipolar disorder (PBD) and control groups. All 3 networks showed hyperconnectivity in the PBD relative to the control group. Specifically, the connectivity of the dorsal anterior cingulate cortex (ACC) differentiated the PBD from the control group in both the affective and the executive networks. Exploratory analysis suggests that greater connectivity of the right amygdala within the affective network is associated with better executive function in children with bipolar disorder, but not in controls. Limitations Unique clinical characteristics of the study sample allowed us to evaluate the pathophysiology of resting state connectivity at an early state of PBD, which led to the lack of generalizability in terms of comorbid disorders existing in a typical PBD population. Conclusion Abnormally engaged resting state affective, executive and sensorimotor networks observed in children with bipolar disorder may reflect a biological context in which abnormal task-based brain activity can occur. Dual engagement of the dorsal ACC in affective and executive networks supports the neuroanatomical interface of these networks, and the amygdala’s engagement in moderating executive function illustrates the intricate interplay of these neural operations at rest. PMID:23735583

Cortical brain connectivity evaluated by graph theory in dementia: a correlation study between functional and structural data.

PubMed

Vecchio, Fabrizio; Miraglia, Francesca; Curcio, Giuseppe; Altavilla, Riccardo; Scrascia, Federica; Giambattistelli, Federica; Quattrocchi, Carlo Cosimo; Bramanti, Placido; Vernieri, Fabrizio; Rossini, Paolo Maria

2015-01-01

A relatively new approach to brain function in neuroscience is the "functional connectivity", namely the synchrony in time of activity in anatomically-distinct but functionally-collaborating brain regions. On the other hand, diffusion tensor imaging (DTI) is a recently developed magnetic resonance imaging (MRI)-based technique with the capability to detect brain structural connection with fractional anisotropy (FA) identification. FA decrease has been observed in the corpus callosum of subjects with Alzheimer's disease (AD) and mild cognitive impairment (MCI, an AD prodromal stage). Corpus callosum splenium DTI abnormalities are thought to be associated with functional disconnections among cortical areas. This study aimed to investigate possible correlations between structural damage, measured by MRI-DTI, and functional abnormalities of brain integration, measured by characteristic path length detected in resting state EEG source activity (40 participants: 9 healthy controls, 10 MCI, 10 mild AD, 11 moderate AD). For each subject, undirected and weighted brain network was built to evaluate graph core measures. eLORETA lagged linear connectivity values were used as weight of the edges of the network. Results showed that callosal FA reduction is associated to a loss of brain interhemispheric functional connectivity characterized by increased delta and decreased alpha path length. These findings suggest that "global" (average network shortest path length representing an index of how efficient is the information transfer between two parts of the network) functional measure can reflect the reduction of fiber connecting the two hemispheres as revealed by DTI analysis and also anticipate in time this structural loss.

Towards Optimal Connectivity on Multi-layered Networks.

PubMed

Chen, Chen; He, Jingrui; Bliss, Nadya; Tong, Hanghang

2017-10-01

Networks are prevalent in many high impact domains. Moreover, cross-domain interactions are frequently observed in many applications, which naturally form the dependencies between different networks. Such kind of highly coupled network systems are referred to as multi-layered networks , and have been used to characterize various complex systems, including critical infrastructure networks, cyber-physical systems, collaboration platforms, biological systems and many more. Different from single-layered networks where the functionality of their nodes is mainly affected by within-layer connections, multi-layered networks are more vulnerable to disturbance as the impact can be amplified through cross-layer dependencies, leading to the cascade failure to the entire system. To manipulate the connectivity in multi-layered networks, some recent methods have been proposed based on two-layered networks with specific types of connectivity measures. In this paper, we address the above challenges in multiple dimensions. First, we propose a family of connectivity measures (SUBLINE) that unifies a wide range of classic network connectivity measures. Third, we reveal that the connectivity measures in SUBLINE family enjoy diminishing returns property , which guarantees a near-optimal solution with linear complexity for the connectivity optimization problem. Finally, we evaluate our proposed algorithm on real data sets to demonstrate its effectiveness and efficiency.

Remodeling of Sensorimotor Brain Connectivity in Gpr88-Deficient Mice.

PubMed

Arefin, Tanzil Mahmud; Mechling, Anna E; Meirsman, Aura Carole; Bienert, Thomas; Hübner, Neele Saskia; Lee, Hsu-Lei; Ben Hamida, Sami; Ehrlich, Aliza; Roquet, Dan; Hennig, Jürgen; von Elverfeldt, Dominik; Kieffer, Brigitte Lina; Harsan, Laura-Adela

2017-10-01

Recent studies have demonstrated that orchestrated gene activity and expression support synchronous activity of brain networks. However, there is a paucity of information on the consequences of single gene function on overall brain functional organization and connectivity and how this translates at the behavioral level. In this study, we combined mouse mutagenesis with functional and structural magnetic resonance imaging (MRI) to determine whether targeted inactivation of a single gene would modify whole-brain connectivity in live animals. The targeted gene encodes GPR88 (G protein-coupled receptor 88), an orphan G protein-coupled receptor enriched in the striatum and previously linked to behavioral traits relevant to neuropsychiatric disorders. Connectivity analysis of Gpr88-deficient mice revealed extensive remodeling of intracortical and cortico-subcortical networks. Most prominent modifications were observed at the level of retrosplenial cortex connectivity, central to the default mode network (DMN) whose alteration is considered a hallmark of many psychiatric conditions. Next, somatosensory and motor cortical networks were most affected. These modifications directly relate to sensorimotor gating deficiency reported in mutant animals and also likely underlie their hyperactivity phenotype. Finally, we identified alterations within hippocampal and dorsal striatum functional connectivity, most relevant to a specific learning deficit that we previously reported in Gpr88 -/- animals. In addition, amygdala connectivity with cortex and striatum was weakened, perhaps underlying the risk-taking behavior of these animals. This is the first evidence demonstrating that GPR88 activity shapes the mouse brain functional and structural connectome. The concordance between connectivity alterations and behavior deficits observed in Gpr88-deficient mice suggests a role for GPR88 in brain communication.

219. Changes in Functional Networks Underlying Social Cognition Following Cognitive Training in Individuals at Risk for Psychosis

PubMed Central

Haut, Kristen; Saxena, Abhishek; Yin, Hong; Carol, Emily; Dodell-Feder, David; Lincoln, Sarah Hope; Tully, Laura; Keshavan, Matcheri; Seidman, Larry J.; Nahum, Mor; Hooker, Christine

2017-01-01

Abstract Background: Deficits in social cognition are prominent features of schizophrenia that play a large role in functional impairments and disability. Performance deficits in these domains are associated with altered activity in functional networks, including those that support social cognitive abilities such as emotion recognition. These social cognitive deficits and alterations in neural networks are present prior to the onset of frank psychotic symptoms and thus present a potential target for intervention in early phases of the illness, including in individuals at clinical high risk (CHR) for psychosis. This study assessed changes in social cognitive functional networks following targeted cognitive training (TCT) in CHR individuals. Methods: 14 CHR subjects (7 male, mean age = 21.9) showing attenuated psychotic symptoms as assessed by the SIPS were included in the study. Subjects underwent a clinical evaluation and a functional MRI session prior to and subsequent to completing 40 hours (8 weeks) of targeted cognitive and social cognitive training using Lumosity and SocialVille. 14 matched healthy control (HC) subjects also underwent a single fMRI session as a comparison group for functional activity. Resting state fMRI was acquired as well as fMRI during performance of an emotion recognition task. Group level differences in BOLD activity between HC and CHR group before TCT, and CHR group before and after TCT were computed. Changes in social cognitive network functional connectivity at rest and during task performance was evaluated using seed-based connectivity analyses and psychophysiological interaction (PPI). Results: Prior to training, CHR individuals demonstrated hyperactivity in the amygdala, posterior cingulate, and superior temporal sulcus (STS) during emotion recognition, suggesting inefficient processing. This hyperactivity normalized somewhat after training, with CHR individuals showing less hyperactivity in the amygdala in response to emotional faces. In addition, training was associated with increased connectivity in emotion processing networks, including greater STS-medial prefrontal connectivity and normalization of amygdala connectivity patterns. Conclusion: These results suggest that targeted cognitive training produced improvements in emotion recognition and may be effective in altering functional network connectivity in networks associated with psychosis risk. TCT may be a useful tool for early intervention in individuals at risk for psychotic disorders to address behaviors that impact functional outcome.

Disintegration of Sensorimotor Brain Networks in Schizophrenia.

PubMed

Kaufmann, Tobias; Skåtun, Kristina C; Alnæs, Dag; Doan, Nhat Trung; Duff, Eugene P; Tønnesen, Siren; Roussos, Evangelos; Ueland, Torill; Aminoff, Sofie R; Lagerberg, Trine V; Agartz, Ingrid; Melle, Ingrid S; Smith, Stephen M; Andreassen, Ole A; Westlye, Lars T

2015-11-01

Schizophrenia is a severe mental disorder associated with derogated function across various domains, including perception, language, motor, emotional, and social behavior. Due to its complex symptomatology, schizophrenia is often regarded a disorder of cognitive processes. Yet due to the frequent involvement of sensory and perceptual symptoms, it has been hypothesized that functional disintegration between sensory and cognitive processes mediates the heterogeneous and comprehensive schizophrenia symptomatology. Here, using resting-state functional magnetic resonance imaging in 71 patients and 196 healthy controls, we characterized the standard deviation in BOLD (blood-oxygen-level-dependent) signal amplitude and the functional connectivity across a range of functional brain networks. We investigated connectivity on the edge and node level using network modeling based on independent component analysis and utilized the brain network features in cross-validated classification procedures. Both amplitude and connectivity were significantly altered in patients, largely involving sensory networks. Reduced standard deviation in amplitude was observed in a range of visual, sensorimotor, and auditory nodes in patients. The strongest differences in connectivity implicated within-sensorimotor and sensorimotor-thalamic connections. Furthermore, sensory nodes displayed widespread alterations in the connectivity with higher-order nodes. We demonstrated robustness of effects across subjects by significantly classifying diagnostic group on the individual level based on cross-validated multivariate connectivity features. Taken together, the findings support the hypothesis of disintegrated sensory and cognitive processes in schizophrenia, and the foci of effects emphasize that targeting the sensory and perceptual domains may be key to enhance our understanding of schizophrenia pathophysiology. © The Author 2015. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Functional Connectivity Changes in Systemic Lupus Erythematosus: A Resting-State Study.

PubMed

Nystedt, Jessika; Mannfolk, Peter; Jönsen, Andreas; Bengtsson, Anders; Nilsson, Petra; Sundgren, Pia C; Strandberg, Tor O

2018-05-01

To investigate resting-state functional connectivity of lupus patients and associated subgroups according to the ACR NPSLE case definitions (ACR ad hoc). In addition, we investigated whether or not the observed alterations correlated with disease duration, the systemic lupus erythematosus (SLE)-Disease Activity Index-2000 (SLEDAI-2k), and Systemic Lupus International Collaborating Clinical/ACR organ damage index (SDI)-scores. Anatomical 3T magnetic resonance imaging (MRI) and resting-state functional MRI were performed in 61 female lupus patients (mean age = 37.0 years, range = 18.2-52.0 years) and 20 gender- and age-matched controls (mean age = 36.2 years, range = 23.3-52.2 years) in conjunction with clinical examination and laboratory testing. Whole-brain voxelwise functional connectivity analysis with permutation testing was performed to extract network components that differed in lupus patients relative to healthy controls (HCs). Lupus patients exhibited both inter- and intranetwork hypo- and hyperconnectivity involving several crucial networks. We found reduced connectivity within the default mode network (DMN), the central executive network (CEN), and in-between the DMN and CEN in lupus patients. Increased connectivity was primarily observed within and between the sensory motor network in lupus patients when compared to HCs. Comparing lupus patients with and without neuropsychiatric symptoms, hypoconnectivity was more pronounced in the group with neuropsychiatric complaints. The functional connectivity of SLE patients was both positively and negatively correlated to duration of disease. We conclude that SLE patients in general and neuropsychiatric SLE patients in particular experience altered brain connectivity. These patterns may be due both to direct neuronal damage and compensatory mechanisms through neuronal rewiring and recruitment and may partly explain neuropsychiatric symptoms in SLE patients.

Brain disease, connectivity, plasticity and cognitive therapy: A neurological view of mental disorders.

PubMed

Lubrini, G; Martín-Montes, A; Díez-Ascaso, O; Díez-Tejedor, E

2018-04-01

Our conception of the mind-brain relationship has evolved from the traditional idea of dualism to current evidence that mental functions result from brain activity. This paradigm shift, combined with recent advances in neuroimaging, has led to a novel definition of brain functioning in terms of structural and functional connectivity. The purpose of this literature review is to describe the relationship between connectivity, brain lesions, cerebral plasticity, and functional recovery. Assuming that brain function results from the organisation of the entire brain in networks, brain dysfunction would be a consequence of altered brain network connectivity. According to this approach, cognitive and behavioural impairment following brain damage result from disrupted functional organisation of brain networks. However, the dynamic and versatile nature of these circuits makes recovering brain function possible. Cerebral plasticity allows for functional reorganisation leading to recovery, whether spontaneous or resulting from cognitive therapy, after brain disease. Current knowledge of brain connectivity and cerebral plasticity provides new insights into normal brain functioning, the mechanisms of brain damage, and functional recovery, which in turn serve as the foundations of cognitive therapy. Copyright © 2017 Sociedad Española de Neurología. Publicado por Elsevier España, S.L.U. All rights reserved.

Multi-subject hierarchical inverse covariance modelling improves estimation of functional brain networks.

PubMed

Colclough, Giles L; Woolrich, Mark W; Harrison, Samuel J; Rojas López, Pedro A; Valdes-Sosa, Pedro A; Smith, Stephen M

2018-05-07

A Bayesian model for sparse, hierarchical, inver-covariance estimation is presented, and applied to multi-subject functional connectivity estimation in the human brain. It enables simultaneous inference of the strength of connectivity between brain regions at both subject and population level, and is applicable to fMRI, MEG and EEG data. Two versions of the model can encourage sparse connectivity, either using continuous priors to suppress irrelevant connections, or using an explicit description of the network structure to estimate the connection probability between each pair of regions. A large evaluation of this model, and thirteen methods that represent the state of the art of inverse covariance modelling, is conducted using both simulated and resting-state functional imaging datasets. Our novel Bayesian approach has similar performance to the best extant alternative, Ng et al.'s Sparse Group Gaussian Graphical Model algorithm, which also is based on a hierarchical structure. Using data from the Human Connectome Project, we show that these hierarchical models are able to reduce the measurement error in MEG beta-band functional networks by 10%, producing concomitant increases in estimates of the genetic influence on functional connectivity. Copyright © 2018. Published by Elsevier Inc.

Effect of simulated rill erosion on overland flow connectivity in synthetically generated fields

NASA Astrophysics Data System (ADS)

Penuela Fernandez, Andres; Rocio Rodriguez Pleguezuelo, Carmen; Javaux, Mathieu; Bielders, Charles L.

2014-05-01

Preferential flow paths developed during rill erosion processes connect different parts of the soil surface that may increase the degree of connectivity and hence the hydrological response of the soil surface. However, few studies have tried to quantify the effect of rill networks on overland flow connectivity. For this purpose, simulated rill networks were generated by the RillGrow erosion model (Favis-Mortlock, 1998; Favis-Mortlock et al. 2000) on synthetically generated fields. To characterize the hydrological connectivity a functional connectivity indicator called the relative surface connection function (RSCf) (Antoine et al. 2009) was used. This indicator, which relates the area connected to the outflow boundary to the degree of filling of maximum depression storage (MDS), is fast to compute and was previously shown to be able to efficiently discriminate between contrasted connectivity scenarios. The RSCf function was calculated for different DEM obtained at different times during the development of the simulated rill networks. The evolution of overland flow connectivity was then quantified and compared at these different time steps. The results of this study showed that the changes in microtopography resulting from the simulated rill erosion have a strong impact on the hydrological connectivity as reflected in the RSCf. Furthermore, the results show that the evolution of the RSCf may allow identifying different types of erosion since the shape of the RSCf only starts to change when rill networks are visualized on the surface.

Exploring connectivity with large-scale Granger causality on resting-state functional MRI.

PubMed

DSouza, Adora M; Abidin, Anas Z; Leistritz, Lutz; Wismüller, Axel

2017-08-01

Large-scale Granger causality (lsGC) is a recently developed, resting-state functional MRI (fMRI) connectivity analysis approach that estimates multivariate voxel-resolution connectivity. Unlike most commonly used multivariate approaches, which establish coarse-resolution connectivity by aggregating voxel time-series avoiding an underdetermined problem, lsGC estimates voxel-resolution, fine-grained connectivity by incorporating an embedded dimension reduction. We investigate application of lsGC on realistic fMRI simulations, modeling smoothing of neuronal activity by the hemodynamic response function and repetition time (TR), and empirical resting-state fMRI data. Subsequently, functional subnetworks are extracted from lsGC connectivity measures for both datasets and validated quantitatively. We also provide guidelines to select lsGC free parameters. Results indicate that lsGC reliably recovers underlying network structure with area under receiver operator characteristic curve (AUC) of 0.93 at TR=1.5s for a 10-min session of fMRI simulations. Furthermore, subnetworks of closely interacting modules are recovered from the aforementioned lsGC networks. Results on empirical resting-state fMRI data demonstrate recovery of visual and motor cortex in close agreement with spatial maps obtained from (i) visuo-motor fMRI stimulation task-sequence (Accuracy=0.76) and (ii) independent component analysis (ICA) of resting-state fMRI (Accuracy=0.86). Compared with conventional Granger causality approach (AUC=0.75), lsGC produces better network recovery on fMRI simulations. Furthermore, it cannot recover functional subnetworks from empirical fMRI data, since quantifying voxel-resolution connectivity is not possible as consequence of encountering an underdetermined problem. Functional network recovery from fMRI data suggests that lsGC gives useful insight into connectivity patterns from resting-state fMRI at a multivariate voxel-resolution. Copyright © 2017 Elsevier B.V. All rights reserved.

Increased Functional MEG Connectivity as a Hallmark of MRI-Negative Focal and Generalized Epilepsy.

PubMed

Li Hegner, Yiwen; Marquetand, Justus; Elshahabi, Adham; Klamer, Silke; Lerche, Holger; Braun, Christoph; Focke, Niels K

2018-05-15

Epilepsy is one of the most prevalent neurological diseases with a high morbidity. Accumulating evidence has shown that epilepsy is an archetypical neural network disorder. Here we developed a non-invasive cortical functional connectivity analysis based on magnetoencephalography (MEG) to assess commonalities and differences in the network phenotype in different epilepsy syndromes (non-lesional/cryptogenic focal and idiopathic/genetic generalized epilepsy). Thirty-seven epilepsy patients with normal structural brain anatomy underwent a 30-min resting state MEG measurement with eyes closed. We only analyzed interictal epochs without epileptiform discharges. The imaginary part of coherency was calculated as an indicator of cortical functional connectivity in five classical frequency bands. This connectivity measure was computed between all sources on individually reconstructed cortical surfaces that were surface-aligned to a common template. In comparison to healthy controls, both focal and generalized epilepsy patients showed widespread increased functional connectivity in several frequency bands, demonstrating the potential of elevated functional connectivity as a common pathophysiological hallmark in different epilepsy types. Furthermore, the comparison between focal and generalized epilepsies revealed increased network connectivity in bilateral mesio-frontal and motor regions specifically for the generalized epilepsy patients. Our study indicated that the surface-based normalization of MEG sources of individual brains enables the comparison of imaging findings across subjects and groups on a united platform, which leads to a straightforward and effective disclosure of pathological network characteristics in epilepsy. This approach may allow for the definition of more specific markers of different epilepsy syndromes, and increased MEG-based resting-state functional connectivity seems to be a common feature in MRI-negative epilepsy syndromes.

The hierarchical brain network for face recognition.

PubMed

Zhen, Zonglei; Fang, Huizhen; Liu, Jia

2013-01-01

Numerous functional magnetic resonance imaging (fMRI) studies have identified multiple cortical regions that are involved in face processing in the human brain. However, few studies have characterized the face-processing network as a functioning whole. In this study, we used fMRI to identify face-selective regions in the entire brain and then explore the hierarchical structure of the face-processing network by analyzing functional connectivity among these regions. We identified twenty-five regions mainly in the occipital, temporal and frontal cortex that showed a reliable response selective to faces (versus objects) across participants and across scan sessions. Furthermore, these regions were clustered into three relatively independent sub-networks in a face-recognition task on the basis of the strength of functional connectivity among them. The functionality of the sub-networks likely corresponds to the recognition of individual identity, retrieval of semantic knowledge and representation of emotional information. Interestingly, when the task was switched to object recognition from face recognition, the functional connectivity between the inferior occipital gyrus and the rest of the face-selective regions were significantly reduced, suggesting that this region may serve as an entry node in the face-processing network. In sum, our study provides empirical evidence for cognitive and neural models of face recognition and helps elucidate the neural mechanisms underlying face recognition at the network level.

Structure-function clustering in multiplex brain networks

NASA Astrophysics Data System (ADS)

Crofts, J. J.; Forrester, M.; O'Dea, R. D.

2016-10-01

A key question in neuroscience is to understand how a rich functional repertoire of brain activity arises within relatively static networks of structurally connected neural populations: elucidating the subtle interactions between evoked “functional connectivity” and the underlying “structural connectivity” has the potential to address this. These structural-functional networks (and neural networks more generally) are more naturally described using a multilayer or multiplex network approach, in favour of standard single-layer network analyses that are more typically applied to such systems. In this letter, we address such issues by exploring important structure-function relations in the Macaque cortical network by modelling it as a duplex network that comprises an anatomical layer, describing the known (macro-scale) network topology of the Macaque monkey, and a functional layer derived from simulated neural activity. We investigate and characterize correlations between structural and functional layers, as system parameters controlling simulated neural activity are varied, by employing recently described multiplex network measures. Moreover, we propose a novel measure of multiplex structure-function clustering which allows us to investigate the emergence of functional connections that are distinct from the underlying cortical structure, and to highlight the dependence of multiplex structure on the neural dynamical regime.

A Novel Re-keying Function Protocol (NRFP) For Wireless Sensor Network Security

PubMed Central

Abdullah, Maan Younis; Hua, Gui Wei; Alsharabi, Naif

2008-01-01

This paper describes a novel re-keying function protocol (NRFP) for wireless sensor network security. A re-keying process management system for sensor networks is designed to support in-network processing. The design of the protocol is motivated by decentralization key management for wireless sensor networks (WSNs), covering key deployment, key refreshment, and key establishment. NRFP supports the establishment of novel administrative functions for sensor nodes that derive/re-derive a session key for each communication session. The protocol proposes direct connection, in-direct connection and hybrid connection. NRFP also includes an efficient protocol for local broadcast authentication based on the use of one-way key chains. A salient feature of the authentication protocol is that it supports source authentication without precluding innetwork processing. Security and performance analysis shows that it is very efficient in computation, communication and storage and, that NRFP is also effective in defending against many sophisticated attacks. PMID:27873963

Anxiety Modulates Insula Recruitment in Resting-State Functional Magnetic Resonance Imaging in Youth and Adults

PubMed Central

Gotlib, Ian H.; Thompson, Paul M.; Thomason, Moriah E.

2011-01-01

Abstract Research on resting-state functional connectivity reveals intrinsically connected networks in the brain that are largely consistent across the general population. However, there are individual differences in these networks that have not been elucidated. Here, we measured the influence of naturally occurring mood on functional connectivity. In particular, we examined the association between self-reported levels of anxiety and connectivity in the default mode network (DMN). Healthy youth (n=43; ages 10–18) and adult participants (n=24, ages 19–59) completed a 6-min resting-state functional magnetic resonance imaging scan, then immediately completed questionnaires assessing their mood and thoughts during the scan. Regression analyses conducted separately for the youth and adult samples revealed brain regions in which increases in connectivity differentially corresponded to higher anxiety in each group. In one area, the left insular cortex, both groups showed similar increased connectivity to the DMN (youth: -30, 26, 14; adults: -33, 12, 14) with increased anxiety. State anxiety assessed during scanning was not correlated with trait anxiety, so our results likely reflect state levels of anxiety. To our knowledge, this is the first study to relate naturally occurring mood to resting state connectivity. PMID:22433052

Evolution of Boolean networks under selection for a robust response to external inputs yields an extensive neutral space

NASA Astrophysics Data System (ADS)

Szejka, Agnes; Drossel, Barbara

2010-02-01

We study the evolution of Boolean networks as model systems for gene regulation. Inspired by biological networks, we select simultaneously for robust attractors and for the ability to respond to external inputs by changing the attractor. Mutations change the connections between the nodes and the update functions. In order to investigate the influence of the type of update functions, we perform our simulations with canalizing as well as with threshold functions. We compare the properties of the fitness landscapes that result for different versions of the selection criterion and the update functions. We find that for all studied cases the fitness landscape has a plateau with maximum fitness resulting in the fact that structurally very different networks are able to fulfill the same task and are connected by neutral paths in network (“genotype”) space. We find furthermore a connection between the attractor length and the mutational robustness, and an extremely long memory of the initial evolutionary stage.

Non-parametric model selection for subject-specific topological organization of resting-state functional connectivity.

PubMed

Ferrarini, Luca; Veer, Ilya M; van Lew, Baldur; Oei, Nicole Y L; van Buchem, Mark A; Reiber, Johan H C; Rombouts, Serge A R B; Milles, J

2011-06-01

In recent years, graph theory has been successfully applied to study functional and anatomical connectivity networks in the human brain. Most of these networks have shown small-world topological characteristics: high efficiency in long distance communication between nodes, combined with highly interconnected local clusters of nodes. Moreover, functional studies performed at high resolutions have presented convincing evidence that resting-state functional connectivity networks exhibits (exponentially truncated) scale-free behavior. Such evidence, however, was mostly presented qualitatively, in terms of linear regressions of the degree distributions on log-log plots. Even when quantitative measures were given, these were usually limited to the r(2) correlation coefficient. However, the r(2) statistic is not an optimal estimator of explained variance, when dealing with (truncated) power-law models. Recent developments in statistics have introduced new non-parametric approaches, based on the Kolmogorov-Smirnov test, for the problem of model selection. In this work, we have built on this idea to statistically tackle the issue of model selection for the degree distribution of functional connectivity at rest. The analysis, performed at voxel level and in a subject-specific fashion, confirmed the superiority of a truncated power-law model, showing high consistency across subjects. Moreover, the most highly connected voxels were found to be consistently part of the default mode network. Our results provide statistically sound support to the evidence previously presented in literature for a truncated power-law model of resting-state functional connectivity. Copyright © 2010 Elsevier Inc. All rights reserved.

Brain Activity and Functional Connectivity Associated with Hypnosis.

PubMed

Jiang, Heidi; White, Matthew P; Greicius, Michael D; Waelde, Lynn C; Spiegel, David

2017-08-01

Hypnosis has proven clinical utility, yet changes in brain activity underlying the hypnotic state have not yet been fully identified. Previous research suggests that hypnosis is associated with decreased default mode network (DMN) activity and that high hypnotizability is associated with greater functional connectivity between the executive control network (ECN) and the salience network (SN). We used functional magnetic resonance imaging to investigate activity and functional connectivity among these three networks in hypnosis. We selected 57 of 545 healthy subjects with very high or low hypnotizability using two hypnotizability scales. All subjects underwent four conditions in the scanner: rest, memory retrieval, and two different hypnosis experiences guided by standard pre-recorded instructions in counterbalanced order. Seeds for the ECN, SN, and DMN were left and right dorsolateral prefrontal cortex, dorsal anterior cingulate cortex (dACC), and posterior cingulate cortex (PCC), respectively. During hypnosis there was reduced activity in the dACC, increased functional connectivity between the dorsolateral prefrontal cortex (DLPFC;ECN) and the insula in the SN, and reduced connectivity between the ECN (DLPFC) and the DMN (PCC). These changes in neural activity underlie the focused attention, enhanced somatic and emotional control, and lack of self-consciousness that characterizes hypnosis. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Default-Mode-Like Network Activation in Awake Rodents

PubMed Central

Upadhyay, Jaymin; Baker, Scott J.; Chandran, Prasant; Miller, Loan; Lee, Younglim; Marek, Gerard J.; Sakoglu, Unal; Chin, Chih-Liang; Luo, Feng; Fox, Gerard B.; Day, Mark

2011-01-01

During wakefulness and in absence of performing tasks or sensory processing, the default-mode network (DMN), an intrinsic central nervous system (CNS) network, is in an active state. Non-human primate and human CNS imaging studies have identified the DMN in these two species. Clinical imaging studies have shown that the pattern of activity within the DMN is often modulated in various disease states (e.g., Alzheimer's, schizophrenia or chronic pain). However, whether the DMN exists in awake rodents has not been characterized. The current data provides evidence that awake rodents also possess ‘DMN-like’ functional connectivity, but only subsequent to habituation to what is initially a novel magnetic resonance imaging (MRI) environment as well as physical restraint. Specifically, the habituation process spanned across four separate scanning sessions (Day 2, 4, 6 and 8). At Day 8, significant (p<0.05) functional connectivity was observed amongst structures such as the anterior cingulate (seed region), retrosplenial, parietal, and hippocampal cortices. Prior to habituation (Day 2), functional connectivity was only detected (p<0.05) amongst CNS structures known to mediate anxiety (i.e., anterior cingulate (seed region), posterior hypothalamic area, amygdala and parabracial nucleus). In relating functional connectivity between cingulate-default-mode and cingulate-anxiety structures across Days 2-8, a significant inverse relationship (r = −0.65, p = 0.0004) was observed between these two functional interactions such that increased cingulate-DMN connectivity corresponded to decreased cingulate anxiety network connectivity. This investigation demonstrates that the cingulate is an important component of both the rodent DMN-like and anxiety networks. PMID:22125628

Effect of Resting-State fNIRS Scanning Duration on Functional Brain Connectivity and Graph Theory Metrics of Brain Network.

PubMed

Geng, Shujie; Liu, Xiangyu; Biswal, Bharat B; Niu, Haijing

2017-01-01

As an emerging brain imaging technique, functional near infrared spectroscopy (fNIRS) has attracted widespread attention for advancing resting-state functional connectivity (FC) and graph theoretical analyses of brain networks. However, it remains largely unknown how the duration of the fNIRS signal scanning is related to stable and reproducible functional brain network features. To answer this question, we collected resting-state fNIRS signals (10-min duration, two runs) from 18 participants and then truncated the hemodynamic time series into 30-s time bins that ranged from 1 to 10 min. Measures of nodal efficiency, nodal betweenness, network local efficiency, global efficiency, and clustering coefficient were computed for each subject at each fNIRS signal acquisition duration. Analyses of the stability and between-run reproducibility were performed to identify optimal time length for each measure. We found that the FC, nodal efficiency and nodal betweenness stabilized and were reproducible after 1 min of fNIRS signal acquisition, whereas network clustering coefficient, local and global efficiencies stabilized after 1 min and were reproducible after 5 min of fNIRS signal acquisition for only local and global efficiencies. These quantitative results provide direct evidence regarding the choice of the resting-state fNIRS scanning duration for functional brain connectivity and topological metric stability of brain network connectivity.

Obesity is marked by distinct functional connectivity in brain networks involved in food reward and salience.

PubMed

Wijngaarden, M A; Veer, I M; Rombouts, S A R B; van Buchem, M A; Willems van Dijk, K; Pijl, H; van der Grond, J

2015-01-01

We hypothesized that brain circuits involved in reward and salience respond differently to fasting in obese versus lean individuals. We compared functional connectivity networks related to food reward and saliency after an overnight fast (baseline) and after a prolonged fast of 48 h in lean versus obese subjects. We included 13 obese (2 males, 11 females, BMI 35.4 ± 1.2 kg/m(2), age 31 ± 3 years) and 11 lean subjects (2 males, 9 females, BMI 23.2 ± 0.5 kg/m(2), age 28 ± 3 years). Resting-state functional magnetic resonance imaging scans were made after an overnight fast (baseline) and after a prolonged 48 h fast. Functional connectivity of the amygdala, hypothalamus and posterior cingulate cortex (default-mode) networks was assessed using seed-based correlations. At baseline, we found a stronger connectivity between hypothalamus and left insula in the obese subjects. This effect diminished upon the prolonged fast. After prolonged fasting, connectivity of the hypothalamus with the dorsal anterior cingulate cortex (dACC) increased in lean subjects and decreased in obese subjects. Amygdala connectivity with the ventromedial prefrontal cortex was stronger in lean subjects at baseline, which did not change upon the prolonged fast. No differences in posterior cingulate cortex connectivity were observed. In conclusion, obesity is marked by alterations in functional connectivity networks involved in food reward and salience. Prolonged fasting differentially affected hypothalamic connections with the dACC and the insula between obese and lean subjects. Our data support the idea that food reward and nutrient deprivation are differently perceived and/or processed in obesity. Copyright © 2015 Elsevier B.V. All rights reserved.

Network structure shapes spontaneous functional connectivity dynamics.

PubMed

Shen, Kelly; Hutchison, R Matthew; Bezgin, Gleb; Everling, Stefan; McIntosh, Anthony R

2015-04-08

The structural organization of the brain constrains the range of interactions between different regions and shapes ongoing information processing. Therefore, it is expected that large-scale dynamic functional connectivity (FC) patterns, a surrogate measure of coordination between brain regions, will be closely tied to the fiber pathways that form the underlying structural network. Here, we empirically examined the influence of network structure on FC dynamics by comparing resting-state FC (rsFC) obtained using BOLD-fMRI in macaques (Macaca fascicularis) to structural connectivity derived from macaque axonal tract tracing studies. Consistent with predictions from simulation studies, the correspondence between rsFC and structural connectivity increased as the sample duration increased. Regions with reciprocal structural connections showed the most stable rsFC across time. The data suggest that the transient nature of FC is in part dependent on direct underlying structural connections, but also that dynamic coordination can occur via polysynaptic pathways. Temporal stability was found to be dependent on structural topology, with functional connections within the rich-club core exhibiting the greatest stability over time. We discuss these findings in light of highly variable functional hubs. The results further elucidate how large-scale dynamic functional coordination exists within a fixed structural architecture. Copyright © 2015 the authors 0270-6474/15/355579-10$15.00/0.

Functional neural networks underlying response inhibition in adolescents and adults.

PubMed

Stevens, Michael C; Kiehl, Kent A; Pearlson, Godfrey D; Calhoun, Vince D

2007-07-19

This study provides the first description of neural network dynamics associated with response inhibition in healthy adolescents and adults. Functional and effective connectivity analyses of whole brain hemodynamic activity elicited during performance of a Go/No-Go task were used to identify functionally integrated neural networks and characterize their causal interactions. Three response inhibition circuits formed a hierarchical, inter-dependent system wherein thalamic modulation of input to premotor cortex by fronto-striatal regions led to response suppression. Adolescents differed from adults in the degree of network engagement, regional fronto-striatal-thalamic connectivity, and network dynamics. We identify and characterize several age-related differences in the function of neural circuits that are associated with behavioral performance changes across adolescent development.

Functional neural networks underlying response inhibition in adolescents and adults

PubMed Central

Stevens, Michael C.; Kiehl, Kent A.; Pearlson, Godfrey D.; Calhoun, Vince D.

2008-01-01

This study provides the first description of neural network dynamics associated with response inhibition in healthy adolescents and adults. Functional and effective connectivity analyses of whole brain hemodynamic activity elicited during performance of a Go/No-Go task were used to identify functionally-integrated neural networks and characterize their causal interactions. Three response inhibition circuits formed a hierarchical, inter-dependent system wherein thalamic modulation of input to premotor cortex by frontostriatal regions led to response suppression. Adolescents differed from adults in the degree of network engagement, regional fronto-striatal-thalamic connectivity, and network dynamics. We identify and characterize several age-related differences in the function of neural circuits that are associated with behavioral performance changes across adolescent development. PMID:17467816

Network-targeted cerebellar transcranial magnetic stimulation improves attentional control

PubMed Central

Esterman, Michael; Thai, Michelle; Okabe, Hidefusa; DeGutis, Joseph; Saad, Elyana; Laganiere, Simon E.; Halko, Mark A.

2018-01-01

Developing non-invasive brain stimulation interventions to improve attentional control is extremely relevant to a variety of neurologic and psychiatric populations, yet few studies have identified reliable biomarkers that can be readily modified to improve attentional control. One potential biomarker of attention is functional connectivity in the core cortical network supporting attention - the dorsal attention network (DAN). We used a network-targeted cerebellar transcranial magnetic stimulation (TMS) procedure, intended to enhance cortical functional connectivity in the DAN. Specifically, in healthy young adults we administered intermittent theta burst TMS (iTBS) to the midline cerebellar node of the DAN and, as a control, the right cerebellar node of the default mode network (DMN). These cerebellar targets were localized using individual resting-state fMRI scans. Participants completed assessments of both sustained (gradual onset continuous performance task, gradCPT) and transient attentional control (attentional blink) immediately before and after stimulation, in two sessions (cerebellar DAN and DMN). Following cerebellar DAN stimulation, participants had significantly fewer attentional lapses (lower commission error rates) on the gradCPT. In contrast, stimulation to the cerebellar DMN did not affect gradCPT performance. Further, in the DAN condition, individuals with worse baseline gradCPT performance showed the greatest enhancement in gradCPT performance. These results suggest that temporarily increasing functional connectivity in the DAN via network-targeted cerebellar stimulation can enhance sustained attention, particularly in those with poor baseline performance. With regard to transient attention, TMS stimulation improved attentional blink performance across both stimulation sites, suggesting increasing functional connectivity in both networks can enhance this aspect of attention. These findings have important implications for intervention applications of TMS and theoretical models of functional connectivity. PMID:28495634

Functional connectivity within and between intrinsic brain networks correlates with trait mind wandering.

PubMed

Godwin, Christine A; Hunter, Michael A; Bezdek, Matthew A; Lieberman, Gregory; Elkin-Frankston, Seth; Romero, Victoria L; Witkiewitz, Katie; Clark, Vincent P; Schumacher, Eric H

2017-08-01

Individual differences across a variety of cognitive processes are functionally associated with individual differences in intrinsic networks such as the default mode network (DMN). The extent to which these networks correlate or anticorrelate has been associated with performance in a variety of circumstances. Despite the established role of the DMN in mind wandering processes, little research has investigated how large-scale brain networks at rest relate to mind wandering tendencies outside the laboratory. Here we examine the extent to which the DMN, along with the dorsal attention network (DAN) and frontoparietal control network (FPCN) correlate with the tendency to mind wander in daily life. Participants completed the Mind Wandering Questionnaire and a 5-min resting state fMRI scan. In addition, participants completed measures of executive function, fluid intelligence, and creativity. We observed significant positive correlations between trait mind wandering and 1) increased DMN connectivity at rest and 2) increased connectivity between the DMN and FPCN at rest. Lastly, we found significant positive correlations between trait mind wandering and fluid intelligence (Ravens) and creativity (Remote Associates Task). We interpret these findings within the context of current theories of mind wandering and executive function and discuss the possibility that certain instances of mind wandering may not be inherently harmful. Due to the controversial nature of global signal regression (GSReg) in functional connectivity analyses, we performed our analyses with and without GSReg and contrast the results from each set of analyses. Copyright © 2017 Elsevier Ltd. All rights reserved.

Independent Component Analysis of Resting-State Functional Magnetic Resonance Imaging in Pedophiles.

PubMed

Cantor, J M; Lafaille, S J; Hannah, J; Kucyi, A; Soh, D W; Girard, T A; Mikulis, D J

2016-10-01

Neuroimaging and other studies have changed the common view that pedophilia is a result of childhood sexual abuse and instead is a neurologic phenomenon with prenatal origins. Previous research has identified differences in the structural connectivity of the brain in pedophilia. To identify analogous differences in functional connectivity. Functional magnetic resonance images were recorded from three groups of participants while they were at rest: pedophilic men with a history of sexual offenses against children (n = 37) and two control groups: non-pedophilic men who committed non-sexual offenses (n = 28) and non-pedophilic men with no criminal history (n = 39). Functional magnetic resonance imaging data were subjected to independent component analysis to identify known functional networks of the brain, and groups were compared to identify differences in connectivity with those networks (or "components"). The pedophilic group demonstrated wide-ranging increases in functional connectivity with the default mode network compared with controls and regional differences (increases and decreases) with the frontoparietal network. Of these brain regions (total = 23), 20 have been identified by meta-analytic studies to respond to sexually relevant stimuli. Conversely, of the brain areas known to be those that respond to sexual stimuli, nearly all emerged in the present data as significantly different in pedophiles. This study confirms the presence of significant differences in the functional connectivity of the brain in pedophilia consistent with previously reported differences in structural connectivity. The connectivity differences detected here and elsewhere are opposite in direction from those associated with anti-sociality, arguing against anti-sociality and for pedophilia as the source of the neuroanatomic differences detected. Copyright © 2016 International Society for Sexual Medicine. Published by Elsevier Inc. All rights reserved.

Uniting functional network topology and oscillations in the fronto-parietal single unit network of behaving primates

PubMed Central

Dann, Benjamin; Michaels, Jonathan A; Schaffelhofer, Stefan; Scherberger, Hansjörg

2016-01-01

The functional communication of neurons in cortical networks underlies higher cognitive processes. Yet, little is known about the organization of the single neuron network or its relationship to the synchronization processes that are essential for its formation. Here, we show that the functional single neuron network of three fronto-parietal areas during active behavior of macaque monkeys is highly complex. The network was closely connected (small-world) and consisted of functional modules spanning these areas. Surprisingly, the importance of different neurons to the network was highly heterogeneous with a small number of neurons contributing strongly to the network function (hubs), which were in turn strongly inter-connected (rich-club). Examination of the network synchronization revealed that the identified rich-club consisted of neurons that were synchronized in the beta or low frequency range, whereas other neurons were mostly non-oscillatory synchronized. Therefore, oscillatory synchrony may be a central communication mechanism for highly organized functional spiking networks. DOI: http://dx.doi.org/10.7554/eLife.15719.001 PMID:27525488

Algebraic Topology of Multi-Brain Connectivity Networks Reveals Dissimilarity in Functional Patterns during Spoken Communications

PubMed Central

Tadić, Bosiljka; Andjelković, Miroslav; Boshkoska, Biljana Mileva; Levnajić, Zoran

2016-01-01

Human behaviour in various circumstances mirrors the corresponding brain connectivity patterns, which are suitably represented by functional brain networks. While the objective analysis of these networks by graph theory tools deepened our understanding of brain functions, the multi-brain structures and connections underlying human social behaviour remain largely unexplored. In this study, we analyse the aggregate graph that maps coordination of EEG signals previously recorded during spoken communications in two groups of six listeners and two speakers. Applying an innovative approach based on the algebraic topology of graphs, we analyse higher-order topological complexes consisting of mutually interwoven cliques of a high order to which the identified functional connections organise. Our results reveal that the topological quantifiers provide new suitable measures for differences in the brain activity patterns and inter-brain synchronisation between speakers and listeners. Moreover, the higher topological complexity correlates with the listener’s concentration to the story, confirmed by self-rating, and closeness to the speaker’s brain activity pattern, which is measured by network-to-network distance. The connectivity structures of the frontal and parietal lobe consistently constitute distinct clusters, which extend across the listener’s group. Formally, the topology quantifiers of the multi-brain communities exceed the sum of those of the participating individuals and also reflect the listener’s rated attributes of the speaker and the narrated subject. In the broader context, the presented study exposes the relevance of higher topological structures (besides standard graph measures) for characterising functional brain networks under different stimuli. PMID:27880802

Fitness, but not physical activity, is related to functional integrity of brain networks associated with aging.

PubMed

Voss, Michelle W; Weng, Timothy B; Burzynska, Agnieszka Z; Wong, Chelsea N; Cooke, Gillian E; Clark, Rachel; Fanning, Jason; Awick, Elizabeth; Gothe, Neha P; Olson, Erin A; McAuley, Edward; Kramer, Arthur F

2016-05-01

Greater physical activity and cardiorespiratory fitness are associated with reduced age-related cognitive decline and lower risk for dementia. However, significant gaps remain in the understanding of how physical activity and fitness protect the brain from adverse effects of brain aging. The primary goal of the current study was to empirically evaluate the independent relationships between physical activity and fitness with functional brain health among healthy older adults, as measured by the functional connectivity of cognitively and clinically relevant resting state networks. To build context for fitness and physical activity associations in older adults, we first demonstrate that young adults have greater within-network functional connectivity across a broad range of cortical association networks. Based on these results and previous research, we predicted that individual differences in fitness and physical activity would be most strongly associated with functional integrity of the networks most sensitive to aging. Consistent with this prediction, and extending on previous research, we showed that cardiorespiratory fitness has a positive relationship with functional connectivity of several cortical networks associated with age-related decline, and effects were strongest in the default mode network (DMN). Furthermore, our results suggest that the positive association of fitness with brain function can occur independent of habitual physical activity. Overall, our findings provide further support that cardiorespiratory fitness is an important factor in moderating the adverse effects of aging on cognitively and clinically relevant functional brain networks. Copyright © 2015 Elsevier Inc. All rights reserved.

Fitness, but not physical activity, is related to functional integrity of brain networks associated with aging

PubMed Central

Voss, Michelle W.; Weng, Timothy B.; Burzynska, Agnieszka Z.; Wong, Chelsea N.; Cooke, Gillian E.; Clark, Rachel; Fanning, Jason; Awick, Elizabeth; Gothe, Neha P.; Olson, Erin A.; McAuley, Edward; Kramer, Arthur F.

2015-01-01

Greater physical activity and cardiorespiratory fitness are associated with reduced age-related cognitive decline and lower risk for dementia. However, significant gaps remain in the understanding of how physical activity and fitness protect the brain from adverse effects of brain aging. The primary goal of the current study was to empirically evaluate the independent relationships between physical activity and fitness with functional brain health among healthy older adults, as measured by the functional connectivity of cognitively and clinically relevant resting state networks. To build context for fitness and physical activity associations in older adults, we first demonstrate that young adults have greater within-network functional connectivity across a broad range of cortical association networks. Based on these results and previous research, we predicted that individual differences in fitness and physical activity would be most strongly associated with functional integrity of the networks most sensitive to aging. Consistent with this prediction, and extending on previous research, we showed that cardiorespiratory fitness has a positive relationship with functional connectivity of several cortical networks associated with age-related decline, and effects were strongest in the Default Mode Network (DMN). Furthermore, our results suggest that the positive association of fitness with brain function can occur independent of habitual physical activity. Overall, our findings provide further support that cardiorespiratory fitness is an important factor in moderating the adverse effects of aging on cognitively and clinically relevant functional brain networks. PMID:26493108

Two distinct neural networks support the mapping of meaning to a novel word.

PubMed

Ye, Zheng; Mestres-Missé, Anna; Rodriguez-Fornells, Antoni; Münte, Thomas F

2011-07-01

Children can learn the meaning of a new word from context during normal reading or listening, without any explicit instruction. It is unclear how such meaning acquisition is supported and achieved in human brain. In this functional magnetic resonance imaging (fMRI) study we investigated neural networks supporting word learning with a functional connectivity approach. Participants were exposed to a new word presented in two successive sentences and needed to derive the meaning of the new word. We observed two neural networks involved in mapping the meaning to the new word. One network connected the left inferior frontal gyrus (LIFG) with the middle frontal gyrus (MFG), medial superior frontal gyrus, caudate nucleus, thalamus, and inferior parietal lobule. The other network connected the left middle temporal gyrus (LMTG) with the MFG, anterior and posterior cingulate cortex. The LIFG network showed stronger interregional interactions for new than real words, whereas the LMTG network showed similar connectivity patterns for new and real words. We proposed that these two networks support different functions during word learning. The LIFG network appears to select the most appropriate meaning from competing candidates and to map the selected meaning onto the new word. The LMTG network may be recruited to integrate the word into sentential context, regardless of whether the word is real or new. The LIFG and the LMTG networks share a common node, the MFG, suggesting that these two networks communicate in working memory. Copyright © 2010 Wiley-Liss, Inc.

Whole-brain analytic measures of network communication reveal increased structure-function correlation in right temporal lobe epilepsy.

PubMed

Wirsich, Jonathan; Perry, Alistair; Ridley, Ben; Proix, Timothée; Golos, Mathieu; Bénar, Christian; Ranjeva, Jean-Philippe; Bartolomei, Fabrice; Breakspear, Michael; Jirsa, Viktor; Guye, Maxime

2016-01-01

The in vivo structure-function relationship is key to understanding brain network reorganization due to pathologies. This relationship is likely to be particularly complex in brain network diseases such as temporal lobe epilepsy, in which disturbed large-scale systems are involved in both transient electrical events and long-lasting functional and structural impairments. Herein, we estimated this relationship by analyzing the correlation between structural connectivity and functional connectivity in terms of analytical network communication parameters. As such, we targeted the gradual topological structure-function reorganization caused by the pathology not only at the whole brain scale but also both in core and peripheral regions of the brain. We acquired diffusion (dMRI) and resting-state fMRI (rsfMRI) data in seven right-lateralized TLE (rTLE) patients and fourteen healthy controls and analyzed the structure-function relationship by using analytical network communication metrics derived from the structural connectome. In rTLE patients, we found a widespread hypercorrelated functional network. Network communication analysis revealed greater unspecific branching of the shortest path (search information) in the structural connectome and a higher global correlation between the structural and functional connectivity for the patient group. We also found evidence for a preserved structural rich-club in the patient group. In sum, global augmentation of structure-function correlation might be linked to a smaller functional repertoire in rTLE patients, while sparing the central core of the brain which may represent a pathway that facilitates the spread of seizures.

Early Functional Connectome Integrity and 1-Year Recovery in Comatose Survivors of Cardiac Arrest.

PubMed

Sair, Haris I; Hannawi, Yousef; Li, Shanshan; Kornbluth, Joshua; Demertzi, Athena; Di Perri, Carol; Chabanne, Russell; Jean, Betty; Benali, Habib; Perlbarg, Vincent; Pekar, James; Luyt, Charles-Edouard; Galanaud, Damien; Velly, Lionel; Puybasset, Louis; Laureys, Steven; Caffo, Brian; Stevens, Robert D

2018-04-01

Purpose To assess whether early brain functional connectivity is associated with functional recovery 1 year after cardiac arrest (CA). Materials and Methods Enrolled in this prospective multicenter cohort were 46 patients who were comatose after CA. Principal outcome was cerebral performance category at 12 months, with favorable outcome (FO) defined as cerebral performance category 1 or 2. All participants underwent multiparametric structural and functional magnetic resonance (MR) imaging less than 4 weeks after CA. Within- and between-network connectivity was measured in dorsal attention network (DAN), default-mode network (DMN), salience network (SN), and executive control network (ECN) by using seed-based analysis of resting-state functional MR imaging data. Structural changes identified with fluid-attenuated inversion recovery and diffusion-weighted imaging sequences were analyzed by using validated morphologic scales. The association between connectivity measures, structural changes, and the principal outcome was explored with multivariable modeling. Results Patients underwent MR imaging a mean 12.6 days ± 5.6 (standard deviation) after CA. At 12 months, 11 patients had an FO. Patients with FO had higher within-DMN connectivity and greater anticorrelation between SN and DMN and between SN and ECN compared with patients with unfavorable outcome, an effect that was maintained after multivariable adjustment. Anticorrelation of SN-DMN predicted outcomes with higher accuracy than fluid-attenuated inversion recovery or diffusion-weighted imaging scores (area under the receiver operating characteristic curves, respectively, 0.88, 0.74, and 0.71). Conclusion MR imaging-based measures of cerebral functional network connectivity obtained in the acute phase of CA were independently associated with FO at 1 year, warranting validation as early markers of long-term recovery potential in patients with anoxic-ischemic encephalopathy. © RSNA, 2017.

Large-scale network dysfunction in Major Depressive Disorder: Meta-analysis of resting-state functional connectivity

PubMed Central

Kaiser, Roselinde H.; Andrews-Hanna, Jessica R.; Wager, Tor D.; Pizzagalli, Diego A.

2015-01-01

IMPORTANCE Major depressive disorder (MDD) has been linked to imbalanced communication among large-scale brain networks, as reflected by abnormal resting-state functional connectivity (rsFC). However, given variable methods and results across studies, identifying consistent patterns of network dysfunction in MDD has been elusive. OBJECTIVE To investigate network dysfunction in MDD through the first meta-analysis of rsFC studies. DATA SOURCES Seed-based voxel-wise rsFC studies comparing MDD with healthy individuals (published before June 30, 2014) were retrieved from electronic databases (PubMed, Web-of-Science, EMBASE), and authors contacted for additional data. STUDY SELECTION Twenty-seven datasets from 25 publications (556 MDD adults/teens; 518 controls) were included in the meta-analysis. DATA EXTRACTION AND SYNTHESIS Coordinates of seed regions-of-interest and between-group effects were extracted. Seeds were categorized into “seed-networks” by their location within a priori functional networks. Multilevel kernel density analysis of between-group effects identified brain systems in which MDD was associated with hyperconnectivity (increased positive, or reduced negative, connectivity) or hypoconnectivity (increased negative, or reduced positive, connectivity) with each seed-network. RESULTS MDD was characterized by hypoconnectivity within the frontoparietal network (FN), a set of regions involved in cognitive control of attention and emotion regulation, and hypoconnectivity between frontoparietal systems and parietal regions of the dorsal attention network (DAN) involved in attending to the external environment. MDD was also associated with hyperconnectivity within the default network (DN), a network believed to support internally-oriented and self-referential thought, and hyperconnectivity between FN control systems and regions of DN. Finally, MDD groups exhibited hypoconnectivity between neural systems involved in processing emotion or salience and midline cortical regions that may mediate top-down regulation of such functions. CONCLUSIONS AND RELEVANCE Reduced connectivity within frontoparietal control systems, and imbalanced connectivity between control systems and networks involved in internal- or external-attention, may reflect depressive biases towards internal thoughts at the cost of engaging with the external world. Meanwhile, altered connectivity between neural systems involved in cognitive control and those that support salience or emotion processing may relate to deficits regulating mood. These findings provide an empirical foundation for a neurocognitive model in which network dysfunction underlies core cognitive and affective abnormalities in depression. PMID:25785575

Functional connectivity pattern during rest within the episodic memory network in association with episodic memory performance in bipolar disorder.

PubMed

Oertel-Knöchel, Viola; Reinke, Britta; Matura, Silke; Prvulovic, David; Linden, David E J; van de Ven, Vincent

2015-02-28

In this study, we sought to examine the intrinsic functional organization of the episodic memory network during rest in bipolar disorder (BD). The previous work suggests that deficits in intrinsic functional connectivity may account for impaired memory performance. We hypothesized that regions involved in episodic memory processing would reveal aberrant functional connectivity in patients with bipolar disorder. We examined 21 patients with BD and 21 healthy matched controls who underwent functional magnetic resonance imaging (fMRI) during a resting condition. We did a seed-based functional connectivity analysis (SBA), using the regions of the episodic memory network that showed a significantly different activation pattern during task-related fMRI as seeds. The functional connectivity scores (FC) were further correlated with episodic memory task performance. Our results revealed decreased FC scores within frontal areas and between frontal and temporal/hippocampal/limbic regions in BD patients in comparison with controls. We observed higher FC in BD patients compared with controls between frontal and limbic regions. The decrease in fronto-frontal functional connectivity in BD patients showed a significant positive association with episodic memory performance. The association between task-independent dysfunctional frontal-limbic FC and episodic memory performance may be relevant for current pathophysiological models of the disease. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Dynamic Functional Connectivity States Reflecting Psychotic-like Experiences.

PubMed

Barber, Anita D; Lindquist, Martin A; DeRosse, Pamela; Karlsgodt, Katherine H

2018-05-01

Psychotic-like experiences (PLEs) are associated with lower social and occupational functioning, and lower executive function. Emerging evidence also suggests that PLEs reflect neural dysfunction resembling that of psychotic disorders. The present study examined dynamic connectivity related to a measure of PLEs derived from the Achenbach Adult Self-Report, in an otherwise-healthy sample of adults from the Human Connectome Project. A total of 76 PLE-endorsing and 153 control participants were included in the final sample. To characterize network dysfunction, dynamic connectivity states were examined across large-scale resting-state networks using dynamic conditional correlation and k-means clustering. Three dynamic states were identified. The PLE-endorsing group spent more time than the control group in state 1, a state reflecting hyperconnectivity within visual regions and hypoconnectivity within the default mode network, and less time in state 2, a state characterized by robust within-network connectivity for all networks and strong default mode network anticorrelations. Within the PLE-endorsing group, worse executive function was associated with more time spent in and more transitions into state 1 and less time spent in and fewer transitions into state 3. PLEs are associated with altered large-scale brain dynamics, which tip the system away from spending more time in states reflecting more "typical" connectivity patterns toward more time in states reflecting visual hyperconnectivity and default mode hypoconnectivity. Copyright © 2017 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

Functional Connectivity Evidence of Cortico-Cortico Inhibition in Temporal Lobe Epilepsy

PubMed Central

Tracy, Joseph I.; Osipowicz, Karol; Spechler, Philip; Sharan, Ashwini; Skidmore, Christopher; Doucet, Gaelle; Sperling, Michael R.

2012-01-01

Epileptic seizures can initiate a neural circuit and lead to aberrant neural communication with brain areas outside the epileptogenic region. We focus on interictal activity in focal temporal lobe epilepsy and evaluate functional connectivity differences that emerge as function of bilateral versus strictly unilateral epileptiform activity. We assess the strength of functional connectivity at rest between the ictal and non-ictal temporal lobes, in addition to whole brain connectivity with the ictal temporal lobe. Results revealed strong connectivity between the temporal lobes for both patient groups, but this did not vary as a function of unilateral versus bilateral interictal status. Both the left and right unilateral temporal lobe groups showed significant anti-correlated activity in regions outside the epileptogenic temporal lobe, primarily involving the contralateral (non-ictal/non-pathologic) hemisphere, with precuneus involvement prominent. The bilateral groups did not show this contralateral anti-correlated activity. This anti-correlated connectivity may represent a form of protective and adaptive inhibition, helping to constrain epileptiform activity to the pathologic temporal lobe. The absence of this activity in the bilateral groups may be indicative of flawed inhibitory mechanisms, helping to explain their more widespread epileptiform activity. Our data suggest that the location and build up of epilepsy networks in the brain are not truly random, and are not limited to the formation of strictly epileptogenic networks. Functional networks may develop to take advantage of the regulatory function of structures such as the precuneus to instantiate an anti-correlated network, generating protective cortico-cortico inhibition for the purpose of limiting seizure spread or epileptogenesis. PMID:22987774

Default mode of brain function in monkeys.

PubMed

Mantini, Dante; Gerits, Annelis; Nelissen, Koen; Durand, Jean-Baptiste; Joly, Olivier; Simone, Luciano; Sawamura, Hiromasa; Wardak, Claire; Orban, Guy A; Buckner, Randy L; Vanduffel, Wim

2011-09-07

Human neuroimaging has revealed a specific network of brain regions-the default-mode network (DMN)-that reduces its activity during goal-directed behavior. So far, evidence for a similar network in monkeys is mainly indirect, since, except for one positron emission tomography study, it is all based on functional connectivity analysis rather than activity increases during passive task states. Here, we tested whether a consistent DMN exists in monkeys using its defining property. We performed a meta-analysis of functional magnetic resonance imaging data collected in 10 awake monkeys to reveal areas in which activity consistently decreases when task demands shift from passive tasks to externally oriented processing. We observed task-related spatially specific deactivations across 15 experiments, implying in the monkey a functional equivalent of the human DMN. We revealed by resting-state connectivity that prefrontal and medial parietal regions, including areas 9/46d and 31, respectively, constitute the DMN core, being functionally connected to all other DMN areas. We also detected two distinct subsystems composed of DMN areas with stronger functional connections between each other. These clusters included areas 24/32, 8b, and TPOC and areas 23, v23, and PGm, respectively. Such a pattern of functional connectivity largely fits, but is not completely consistent with anatomical tract tracing data in monkeys. Also, analysis of afferent and efferent connections between DMN areas suggests a multisynaptic network structure. Like humans, monkeys increase activity during passive epochs in heteromodal and limbic association regions, suggesting that they also default to internal modes of processing when not actively interacting with the environment.

Default Mode of Brain Function in Monkeys

PubMed Central

Mantini, Dante; Gerits, Annelis; Nelissen, Koen; Durand, Jean-Baptiste; Joly, Olivier; Simone, Luciano; Sawamura, Hiromasa; Wardak, Claire; Orban, Guy A.; Buckner, Randy L.; Vanduffel, Wim

2013-01-01

Human neuroimaging has revealed a specific network of brain regions—the default-mode network (DMN)—that reduces its activity during goal-directed behavior. So far, evidence for a similar network in monkeys is mainly indirect, since, except for one positron emission tomography study, it is all based on functional connectivity analysis rather than activity increases during passive task states. Here, we tested whether a consistent DMN exists in monkeys using its defining property. We performed a meta-analysis of functional magnetic resonance imaging data collected in 10 awake monkeys to reveal areas in which activity consistently decreases when task demands shift from passive tasks to externally oriented processing. We observed task-related spatially specific deactivations across 15 experiments, implying in the monkey a functional equivalent of the human DMN. We revealed by resting-state connectivity that prefrontal and medial parietal regions, including areas 9/46d and 31, respectively, constitute the DMN core, being functionally connected to all other DMN areas. We also detected two distinct subsystems composed of DMN areas with stronger functional connections between each other. These clusters included areas 24/32, 8b, and TPOC and areas 23, v23, and PGm, respectively. Such a pattern of functional connectivity largely fits, but is not completely consistent with anatomical tract tracing data in monkeys. Also, analysis of afferent and efferent connections between DMN areas suggests a multisynaptic network structure. Like humans, monkeys increase activity during passive epochs in heteromodal and limbic association regions, suggesting that they also default to internal modes of processing when not actively interacting with the environment. PMID:21900574

Brain networks for visual creativity: a functional connectivity study of planning a visual artwork.

PubMed

De Pisapia, Nicola; Bacci, Francesca; Parrott, Danielle; Melcher, David

2016-12-19

Throughout recorded history, and across cultures, humans have made visual art. In recent years, the neural bases of creativity, including artistic creativity, have become a topic of interest. In this study we investigated the neural bases of the visual creative process with both professional artists and a group of control participants. We tested the idea that creativity (planning an artwork) would influence the functional connectivity between regions involved in the default mode network (DMN), implicated in divergent thinking and generating novel ideas, and the executive control network (EN), implicated in evaluating and selecting ideas. We measured functional connectivity with functional Magnetic Resonance Imaging (fMRI) during three different conditions: rest, visual imagery of the alphabet and planning an artwork to be executed immediately after the scanning session. Consistent with our hypothesis, we found stronger connectivity between areas of the DMN and EN during the creative task, and this difference was enhanced in professional artists. These findings suggest that creativity involves an expert balance of two brain networks typically viewed as being in opposition.

Brain networks for visual creativity: a functional connectivity study of planning a visual artwork

PubMed Central

De Pisapia, Nicola; Bacci, Francesca; Parrott, Danielle; Melcher, David

2016-01-01

Throughout recorded history, and across cultures, humans have made visual art. In recent years, the neural bases of creativity, including artistic creativity, have become a topic of interest. In this study we investigated the neural bases of the visual creative process with both professional artists and a group of control participants. We tested the idea that creativity (planning an artwork) would influence the functional connectivity between regions involved in the default mode network (DMN), implicated in divergent thinking and generating novel ideas, and the executive control network (EN), implicated in evaluating and selecting ideas. We measured functional connectivity with functional Magnetic Resonance Imaging (fMRI) during three different conditions: rest, visual imagery of the alphabet and planning an artwork to be executed immediately after the scanning session. Consistent with our hypothesis, we found stronger connectivity between areas of the DMN and EN during the creative task, and this difference was enhanced in professional artists. These findings suggest that creativity involves an expert balance of two brain networks typically viewed as being in opposition. PMID:27991592

Movement of feeder-using songbirds: the influence of urban features.

PubMed

Cox, Daniel T C; Inger, Richard; Hancock, Steven; Anderson, Karen; Gaston, Kevin J

2016-11-23

Private gardens provide vital opportunities for people to interact with nature. The most popular form of interaction is through garden bird feeding. Understanding how landscape features and seasons determine patterns of movement of feeder-using songbirds is key to maximising the well-being benefits they provide. To determine these patterns we established three networks of automated data loggers along a gradient of greenspace fragmentation. Over a 12-month period we tracked 452 tagged blue tits Cyantistes caeruleus and great tits Parus major moving between feeder pairs 9,848 times, to address two questions: (i) Do urban features within different forms, and season, influence structural (presence-absence of connections between feeders by birds) and functional (frequency of these connections) connectivity? (ii) Are there general patterns of structural and functional connectivity across forms? Vegetation cover increased connectivity in all three networks, whereas the presence of road gaps negatively affected functional but not structural connectivity. Across networks structural connectivity was lowest in the summer when birds maintain breeding territories, however patterns of functional connectivity appeared to vary with habitat fragmentation. Using empirical data this study shows how key urban features and season influence movement of feeder-using songbirds, and we provide evidence that this is related to greenspace fragmentation.

Altered functional brain connectivity in children and young people with opsoclonus-myoclonus syndrome.

PubMed

Chekroud, Adam M; Anand, Geetha; Yong, Jean; Pike, Michael; Bridge, Holly

2017-01-01

Opsoclonus-myoclonus syndrome (OMS) is a rare, poorly understood condition that can result in long-term cognitive, behavioural, and motor sequelae. Several studies have investigated structural brain changes associated with this condition, but little is known about changes in function. This study aimed to investigate changes in brain functional connectivity in patients with OMS. Seven patients with OMS and 10 age-matched comparison participants underwent 3T magnetic resonance imaging (MRI) to acquire resting-state functional MRI data (whole-brain echo-planar images; 2mm isotropic voxels; multiband factor ×2) for a cross-sectional study. A seed-based analysis identified brain regions in which signal changes over time correlated with the cerebellum. Model-free analysis was used to determine brain networks showing altered connectivity. In patients with OMS, the motor cortex showed significantly reduced connectivity, and the occipito-parietal region significantly increased connectivity with the cerebellum relative to the comparison group. A model-free analysis also showed extensive connectivity within a visual network, including the cerebellum and basal ganglia, not present in the comparison group. No other networks showed any differences between groups. Patients with OMS showed reduced connectivity between the cerebellum and motor cortex, but increased connectivity with occipito-parietal regions. This pattern of change supports widespread brain involvement in OMS. © 2016 Mac Keith Press.

White matter integrity in brain networks relevant to anxiety and depression: evidence from the human connectome project dataset.

PubMed

De Witte, Nele A J; Mueller, Sven C

2017-12-01

Anxiety and depression are associated with altered communication within global brain networks and between these networks and the amygdala. Functional connectivity studies demonstrate an effect of anxiety and depression on four critical brain networks involved in top-down attentional control (fronto-parietal network; FPN), salience detection and error monitoring (cingulo-opercular network; CON), bottom-up stimulus-driven attention (ventral attention network; VAN), and default mode (default mode network; DMN). However, structural evidence on the white matter (WM) connections within these networks and between these networks and the amygdala is lacking. The current study in a large healthy sample (n = 483) observed that higher trait anxiety-depression predicted lower WM integrity in the connections between amygdala and specific regions of the FPN, CON, VAN, and DMN. We discuss the possible consequences of these anatomical alterations for cognitive-affective functioning and underscore the need for further theory-driven research on individual differences in anxiety and depression on brain structure.

Altered Resting State Effective Connectivity of Anterior Insula in Depression.

PubMed

Kandilarova, Sevdalina; Stoyanov, Drozdstoy; Kostianev, Stefan; Specht, Karsten

2018-01-01

Depression has been associated with changes in both functional and effective connectivity of large scale brain networks, including the default mode network, executive network, and salience network. However, studies of effective connectivity by means of spectral dynamic causal modeling (spDCM) are still rare and the interaction between the different resting state networks has not been investigated in detail. Thus, we aimed at exploring differences in effective connectivity among eight right hemisphere brain areas-anterior insula, inferior frontal gyrus, middle frontal gyrus (MFG), frontal eye field, anterior cingulate cortex, superior parietal lobe, amygdala, and hippocampus, between a group of healthy controls ( N  = 20) and medicated depressed patients ( N  = 20). We found that patients not only had significantly reduced strength of the connection from the anterior insula to the MFG (i.e., dorsolateral prefrontal cortex) but also a significant connection between the amygdala and the anterior insula. Moreover, depression severity correlated with connectivity of the hippocampal node. In conclusion, the results from this resting state spDCM study support and enrich previous data on the role of the right anterior insula in the pathophysiology of depression. Furthermore, our findings add to the growing evidence of an association between depression severity and disturbances of the hippocampal function in terms of impaired connectivity with other brain regions.

Altered Resting State Effective Connectivity of Anterior Insula in Depression

PubMed Central

Kandilarova, Sevdalina; Stoyanov, Drozdstoy; Kostianev, Stefan; Specht, Karsten

2018-01-01

Depression has been associated with changes in both functional and effective connectivity of large scale brain networks, including the default mode network, executive network, and salience network. However, studies of effective connectivity by means of spectral dynamic causal modeling (spDCM) are still rare and the interaction between the different resting state networks has not been investigated in detail. Thus, we aimed at exploring differences in effective connectivity among eight right hemisphere brain areas—anterior insula, inferior frontal gyrus, middle frontal gyrus (MFG), frontal eye field, anterior cingulate cortex, superior parietal lobe, amygdala, and hippocampus, between a group of healthy controls (N = 20) and medicated depressed patients (N = 20). We found that patients not only had significantly reduced strength of the connection from the anterior insula to the MFG (i.e., dorsolateral prefrontal cortex) but also a significant connection between the amygdala and the anterior insula. Moreover, depression severity correlated with connectivity of the hippocampal node. In conclusion, the results from this resting state spDCM study support and enrich previous data on the role of the right anterior insula in the pathophysiology of depression. Furthermore, our findings add to the growing evidence of an association between depression severity and disturbances of the hippocampal function in terms of impaired connectivity with other brain regions. PMID:29599728

Axon and dendrite geography predict the specificity of synaptic connections in a functioning spinal cord network.

PubMed

Li, Wen-Chang; Cooke, Tom; Sautois, Bart; Soffe, Stephen R; Borisyuk, Roman; Roberts, Alan

2007-09-10

How specific are the synaptic connections formed as neuronal networks develop and can simple rules account for the formation of functioning circuits? These questions are assessed in the spinal circuits controlling swimming in hatchling frog tadpoles. This is possible because detailed information is now available on the identity and synaptic connections of the main types of neuron. The probabilities of synapses between 7 types of identified spinal neuron were measured directly by making electrical recordings from 500 pairs of neurons. For the same neuron types, the dorso-ventral distributions of axons and dendrites were measured and then used to calculate the probabilities that axons would encounter particular dendrites and so potentially form synaptic connections. Surprisingly, synapses were found between all types of neuron but contact probabilities could be predicted simply by the anatomical overlap of their axons and dendrites. These results suggested that synapse formation may not require axons to recognise specific, correct dendrites. To test the plausibility of simpler hypotheses, we first made computational models that were able to generate longitudinal axon growth paths and reproduce the axon distribution patterns and synaptic contact probabilities found in the spinal cord. To test if probabilistic rules could produce functioning spinal networks, we then made realistic computational models of spinal cord neurons, giving them established cell-specific properties and connecting them into networks using the contact probabilities we had determined. A majority of these networks produced robust swimming activity. Simple factors such as morphogen gradients controlling dorso-ventral soma, dendrite and axon positions may sufficiently constrain the synaptic connections made between different types of neuron as the spinal cord first develops and allow functional networks to form. Our analysis implies that detailed cellular recognition between spinal neuron types may not be necessary for the reliable formation of functional networks to generate early behaviour like swimming.

Disconnection and hyper-connectivity underlie reorganization after TBI: A rodent functional connectomic analysis

PubMed Central

Harris, N.G.; Verley, D.R.; Gutman, B.A.; Thompson, P.M.; Yeh, H.J.; Brown, J.A.

2016-01-01

While past neuroimaging methods have contributed greatly to our understanding of brain function after traumatic brain injury (TBI), resting state functional MRI (rsfMRI) connectivity methods have more recently provided a far more unbiased approach with which to monitor brain circuitry compared to task-based approaches. However, current knowledge on the physiologic underpinnings of the correlated blood oxygen level dependent signal, and how changes in functional connectivity relate to reorganizational processes that occur following injury is limited. The degree and extent of this relationship remain to be determined in order that rsfMRI methods can be fully adapted for determining the optimal timing and type of rehabilitative interventions that can be used post-TBI to achieve the best outcome. Very few rsfMRI studies exist after experimental TBI and therefore we chose to acquire rsfMRI data before and at 7, 14 and 28 days after experimental TBI using a well-known, clinically-relevant, unilateral controlled cortical impact injury (CCI) adult rat model of TBI. This model was chosen since it has widespread axonal injury, a well-defined time-course of reorganization including spine, dendrite, axonal and cortical map changes, as well as spontaneous recovery of sensorimotor function by 28 d post-injury from which to interpret alterations in functional connectivity. Data were co-registered to a parcellated rat template to generate adjacency matrices for network analysis by graph theory. Making no assumptions about direction of change, we used two-tailed statistical analysis over multiple brain regions in a data-driven approach to access global and regional changes in network topology in order to assess brain connectivity in an unbiased way. Our main hypothesis was that deficits in functional connectivity would become apparent in regions known to be structurally altered or deficient in axonal connectivity in this model. The data show the loss of functional connectivity predicted by the structural deficits, not only within the primary sensorimotor injury site and pericontused regions, but the normally connected homotopic cortex, as well as subcortical regions, all of which persisted chronically. Especially novel in this study is the unanticipated finding of widespread increases in connection strength that dwarf both the degree and extent of the functional disconnections, and which persist chronically in some sensorimotor and subcortically connected regions. Exploratory global network analysis showed changes in network parameters indicative of possible acutely increased random connectivity and temporary reductions in modularity that were matched by local increases in connectedness and increased efficiency among more weakly connected regions. The global network parameters: shortest path-length, clustering coefficient and modularity that were most affected by trauma also scaled with the severity of injury, so that the corresponding regional measures were correlated to the injury severity most notably at 7 and 14 days and especially within, but not limited to, the contralateral cortex. These changes in functional network parameters are discussed in relation to the known time-course of physiologic and anatomic data that underlie structural and functional reorganization in this experiment model of TBI. PMID:26730520

Disconnection and hyper-connectivity underlie reorganization after TBI: A rodent functional connectomic analysis.

PubMed

Harris, N G; Verley, D R; Gutman, B A; Thompson, P M; Yeh, H J; Brown, J A

2016-03-01

While past neuroimaging methods have contributed greatly to our understanding of brain function after traumatic brain injury (TBI), resting state functional MRI (rsfMRI) connectivity methods have more recently provided a far more unbiased approach with which to monitor brain circuitry compared to task-based approaches. However, current knowledge on the physiologic underpinnings of the correlated blood oxygen level dependent signal, and how changes in functional connectivity relate to reorganizational processes that occur following injury is limited. The degree and extent of this relationship remain to be determined in order that rsfMRI methods can be fully adapted for determining the optimal timing and type of rehabilitative interventions that can be used post-TBI to achieve the best outcome. Very few rsfMRI studies exist after experimental TBI and therefore we chose to acquire rsfMRI data before and at 7, 14 and 28 days after experimental TBI using a well-known, clinically-relevant, unilateral controlled cortical impact injury (CCI) adult rat model of TBI. This model was chosen since it has widespread axonal injury, a well-defined time-course of reorganization including spine, dendrite, axonal and cortical map changes, as well as spontaneous recovery of sensorimotor function by 28 d post-injury from which to interpret alterations in functional connectivity. Data were co-registered to a parcellated rat template to generate adjacency matrices for network analysis by graph theory. Making no assumptions about direction of change, we used two-tailed statistical analysis over multiple brain regions in a data-driven approach to access global and regional changes in network topology in order to assess brain connectivity in an unbiased way. Our main hypothesis was that deficits in functional connectivity would become apparent in regions known to be structurally altered or deficient in axonal connectivity in this model. The data show the loss of functional connectivity predicted by the structural deficits, not only within the primary sensorimotor injury site and pericontused regions, but the normally connected homotopic cortex, as well as subcortical regions, all of which persisted chronically. Especially novel in this study is the unanticipated finding of widespread increases in connection strength that dwarf both the degree and extent of the functional disconnections, and which persist chronically in some sensorimotor and subcortically connected regions. Exploratory global network analysis showed changes in network parameters indicative of possible acutely increased random connectivity and temporary reductions in modularity that were matched by local increases in connectedness and increased efficiency among more weakly connected regions. The global network parameters: shortest path-length, clustering coefficient and modularity that were most affected by trauma also scaled with the severity of injury, so that the corresponding regional measures were correlated to the injury severity most notably at 7 and 14 days and especially within, but not limited to, the contralateral cortex. These changes in functional network parameters are discussed in relation to the known time-course of physiologic and anatomic data that underlie structural and functional reorganization in this experiment model of TBI. Copyright © 2015 Elsevier Inc. All rights reserved.

Atypical functional brain connectivity during rest in autism spectrum disorders.

PubMed

Doyle-Thomas, Krissy A R; Lee, Wayne; Foster, Nicholas E V; Tryfon, Ana; Ouimet, Tia; Hyde, Krista L; Evans, Alan C; Lewis, John; Zwaigenbaum, Lonnie; Anagnostou, Evdokia

2015-05-01

Connectivity atypicalities in autism spectrum disorders (ASD) have been extensively proposed. The default mode network (DMN) is critical in this study, given the insight it provides for long-distance connectivity, and the importance of regions in this network for introspection and social emotion processing, areas affected in ASD. However, study of this network has largely been limited to adults; research earlier in development is lacking. The objective of this study was to examine DMN connectivity in children/adolescents with ASD. A total of 115 children/adolescents, aged 6 to 17 years (71 males with ASD and 44 group age-matched TD males) were included in these analyses. We examined group differences in (1) functional connectivity between the posterior cingulate cortex and regions across the brain, (2) connectivity within the DMN as a function of age and intelligence quotient (IQ), and (3) the association between DMN connectivity and empathic accuracy. Individuals with ASD, relative to controls, showed either stronger or weaker connectivity between the posterior cingulate cortex (PCC) and DMN regions, depending on the region, but also showed stronger connectivity with non-DMN regions. A significant group-by-age interaction was observed in functional connectivity between the PCC and medial prefrontal cortex; connectivity increased with age in controls, but decreased in individuals with ASD. No effects of IQ were found. There was a significant group difference in the relation between DMN connectivity and empathic accuracy. Differences in functional connectivity may suggest the presence of neural atypicalities that impact the development of typical connectivity in ASD. In addition to affecting DMN dynamics, these atypicalities may also impact social-cognitive abilities. © 2015 American Neurological Association.

Mesial temporal lobe epilepsy diminishes functional connectivity during emotion perception.

PubMed

Steiger, Bettina K; Muller, Angela M; Spirig, Esther; Toller, Gianina; Jokeit, Hennric

2017-08-01

Unilateral mesial temporal lobe epilepsy (MTLE) has been associated with impaired recognition of emotional facial expressions. Correspondingly, imaging studies showed decreased activity of the amygdala and cortical face processing regions in response to emotional faces. However, functional connectivity among regions involved in emotion perception has not been studied so far. To address this, we examined intrinsic functional connectivity (FC) modulated by the perception of dynamic fearful faces among the amygdala and limbic, frontal, temporal and brainstem regions. Regions of interest were identified in an activation analysis by presenting a block-design with dynamic fearful faces and dynamic landscapes to 15 healthy individuals. This led to 10 predominately right-hemispheric regions. Functional connectivity between these regions during the perception of fearful faces was examined in drug-refractory patients with left- (n=16) or right-sided (n=17) MTLE, epilepsy patients with extratemporal seizure onset (n=15) and a second group of 15 healthy controls. Healthy controls showed a widespread functional network modulated by the perception of fearful faces that encompassed bilateral amygdalae, limbic, cortical, subcortical and brainstem regions. In patients with left MTLE, a downsized network of frontal and temporal regions centered on the right amygdala was present. Patients with right MTLE showed almost no significant functional connectivity. A maintained network in the epilepsy control group indicates that findings in mesial temporal lobe epilepsy could not be explained by clinical factors such as seizures and antiepileptic medication. Functional networks underlying facial emotion perception are considerably changed in left and right MTLE. Alterations are present for both hemispheres in either MTLE group, but are more pronounced in right MTLE. Disruption of the functional network architecture possibly contributes to deficits in facial emotion recognition frequently reported in MTLE. Copyright © 2017 Elsevier B.V. All rights reserved.

Functional Brain Network Modularity Captures Inter- and Intra-Individual Variation in Working Memory Capacity

PubMed Central

Stevens, Alexander A.; Tappon, Sarah C.; Garg, Arun; Fair, Damien A.

2012-01-01

Background Cognitive abilities, such as working memory, differ among people; however, individuals also vary in their own day-to-day cognitive performance. One potential source of cognitive variability may be fluctuations in the functional organization of neural systems. The degree to which the organization of these functional networks is optimized may relate to the effective cognitive functioning of the individual. Here we specifically examine how changes in the organization of large-scale networks measured via resting state functional connectivity MRI and graph theory track changes in working memory capacity. Methodology/Principal Findings Twenty-two participants performed a test of working memory capacity and then underwent resting-state fMRI. Seventeen subjects repeated the protocol three weeks later. We applied graph theoretic techniques to measure network organization on 34 brain regions of interest (ROI). Network modularity, which measures the level of integration and segregation across sub-networks, and small-worldness, which measures global network connection efficiency, both predicted individual differences in memory capacity; however, only modularity predicted intra-individual variation across the two sessions. Partial correlations controlling for the component of working memory that was stable across sessions revealed that modularity was almost entirely associated with the variability of working memory at each session. Analyses of specific sub-networks and individual circuits were unable to consistently account for working memory capacity variability. Conclusions/Significance The results suggest that the intrinsic functional organization of an a priori defined cognitive control network measured at rest provides substantial information about actual cognitive performance. The association of network modularity to the variability in an individual's working memory capacity suggests that the organization of this network into high connectivity within modules and sparse connections between modules may reflect effective signaling across brain regions, perhaps through the modulation of signal or the suppression of the propagation of noise. PMID:22276205

The contributions of resting state and task-based functional connectivity studies to our understanding of adolescent brain network maturation.

PubMed

Stevens, Michael C

2016-11-01

This review summarizes functional magnetic resonance imaging (fMRI) research done over the past decade that examined changes in the function and organization of brain networks across human adolescence. Its over-arching goal is to highlight how both resting state functional connectivity (rs-fcMRI) and task-based functional connectivity (t-fcMRI) have jointly contributed - albeit in different ways - to our understanding of the scope and types of network organization changes that occur from puberty until young adulthood. These two approaches generally have tested different types of hypotheses using different analysis techniques. This has hampered the convergence of findings. Although much has been learned about system-wide changes to adolescents' neural network organization, if both rs-fcMRI and t-fcMRI approaches draw upon each other's methodology and ask broader questions, it will produce a more detailed connectome-informed theory of adolescent neurodevelopment to guide physiological, clinical, and other lines of research. Copyright © 2016 Elsevier Ltd. All rights reserved.

Classification of functional interactions from multi-electrodes data using conditional modularity analysis

NASA Astrophysics Data System (ADS)

Makhtar, Siti Noormiza; Senik, Mohd Harizal

2018-02-01

The availability of massive amount of neuronal signals are attracting widespread interest in functional connectivity analysis. Functional interactions estimated by multivariate partial coherence analysis in the frequency domain represent the connectivity strength in this study. Modularity is a network measure for the detection of community structure in network analysis. The discovery of community structure for the functional neuronal network was implemented on multi-electrode array (MEA) signals recorded from hippocampal regions in isoflurane-anaesthetized Lister-hooded rats. The analysis is expected to show modularity changes before and after local unilateral kainic acid (KA)-induced epileptiform activity. The result is presented using color-coded graphic of conditional modularity measure for 19 MEA nodes. This network is separated into four sub-regions to show the community detection within each sub-region. The results show that classification of neuronal signals into the inter- and intra-modular nodes is feasible using conditional modularity analysis. Estimation of segregation properties using conditional modularity analysis may provide further information about functional connectivity from MEA data.

Early Development of Functional Network Segregation Revealed by Connectomic Analysis of the Preterm Human Brain.

PubMed

Cao, Miao; He, Yong; Dai, Zhengjia; Liao, Xuhong; Jeon, Tina; Ouyang, Minhui; Chalak, Lina; Bi, Yanchao; Rollins, Nancy; Dong, Qi; Huang, Hao

2017-03-01

Human brain functional networks are topologically organized with nontrivial connectivity characteristics such as small-worldness and densely linked hubs to support highly segregated and integrated information processing. However, how they emerge and change at very early developmental phases remains poorly understood. Here, we used resting-state functional MRI and voxel-based graph theory analysis to systematically investigate the topological organization of whole-brain networks in 40 infants aged around 31 to 42 postmenstrual weeks. The functional connectivity strength and heterogeneity increased significantly in primary motor, somatosensory, visual, and auditory regions, but much less in high-order default-mode and executive-control regions. The hub and rich-club structures in primary regions were already present at around 31 postmenstrual weeks and exhibited remarkable expansions with age, accompanied by increased local clustering and shortest path length, indicating a transition from a relatively random to a more organized configuration. Moreover, multivariate pattern analysis using support vector regression revealed that individual brain maturity of preterm babies could be predicted by the network connectivity patterns. Collectively, we highlighted a gradually enhanced functional network segregation manner in the third trimester, which is primarily driven by the rapid increases of functional connectivity of the primary regions, providing crucial insights into the topological development patterns prior to birth. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Dissociable relations between amygdala subregional networks and psychopathy trait dimensions in conduct-disordered juvenile offenders.

PubMed

Aghajani, Moji; Colins, Olivier F; Klapwijk, Eduard T; Veer, Ilya M; Andershed, Henrik; Popma, Arne; van der Wee, Nic J; Vermeiren, Robert R J M

2016-11-01

Psychopathy is a serious psychiatric phenomenon characterized by a pathological constellation of affective (e.g., callous, unemotional), interpersonal (e.g., manipulative, egocentric), and behavioral (e.g., impulsive, irresponsible) personality traits. Though amygdala subregional defects are suggested in psychopathy, the functionality and connectivity of different amygdala subnuclei is typically disregarded in neurocircuit-level analyses of psychopathic personality. Hence, little is known of how amygdala subregional networks may contribute to psychopathy and its underlying trait assemblies in severely antisocial people. We addressed this important issue by uniquely examining the intrinsic functional connectivity of basolateral (BLA) and centromedial (CMA) amygdala networks in relation to affective, interpersonal, and behavioral traits of psychopathy, in conduct-disordered juveniles with a history of serious delinquency (N = 50, mean age = 16.83 ± 1.32). As predicted, amygdalar connectivity profiles exhibited dissociable relations with different traits of psychopathy. Interpersonal psychopathic traits not only related to increased connectivity of BLA and CMA with a corticostriatal network formation accommodating reward processing, but also predicted stronger CMA connectivity with a network of cortical midline structures supporting sociocognitive processes. In contrast, affective psychopathic traits related to diminished CMA connectivity with a frontolimbic network serving salience processing and affective responding. Finally, behavioral psychopathic traits related to heightened BLA connectivity with a frontoparietal cluster implicated in regulatory executive functioning. We suggest that these trait-specific shifts in amygdalar connectivity could be particularly relevant to the psychopathic phenotype, as they may fuel a self-centered, emotionally cold, and behaviorally disinhibited profile. Hum Brain Mapp 37:4017-4033, 2016. © 2016 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc. © 2016 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

Dissociable relations between amygdala subregional networks and psychopathy trait dimensions in conduct‐disordered juvenile offenders

PubMed Central

Colins, Olivier F.; Klapwijk, Eduard T.; Veer, Ilya M.; Andershed, Henrik; Popma, Arne; van der Wee, Nic J.; Vermeiren, Robert R.J.M.

2016-01-01

Abstract Psychopathy is a serious psychiatric phenomenon characterized by a pathological constellation of affective (e.g., callous, unemotional), interpersonal (e.g., manipulative, egocentric), and behavioral (e.g., impulsive, irresponsible) personality traits. Though amygdala subregional defects are suggested in psychopathy, the functionality and connectivity of different amygdala subnuclei is typically disregarded in neurocircuit‐level analyses of psychopathic personality. Hence, little is known of how amygdala subregional networks may contribute to psychopathy and its underlying trait assemblies in severely antisocial people. We addressed this important issue by uniquely examining the intrinsic functional connectivity of basolateral (BLA) and centromedial (CMA) amygdala networks in relation to affective, interpersonal, and behavioral traits of psychopathy, in conduct‐disordered juveniles with a history of serious delinquency (N = 50, mean age = 16.83 ± 1.32). As predicted, amygdalar connectivity profiles exhibited dissociable relations with different traits of psychopathy. Interpersonal psychopathic traits not only related to increased connectivity of BLA and CMA with a corticostriatal network formation accommodating reward processing, but also predicted stronger CMA connectivity with a network of cortical midline structures supporting sociocognitive processes. In contrast, affective psychopathic traits related to diminished CMA connectivity with a frontolimbic network serving salience processing and affective responding. Finally, behavioral psychopathic traits related to heightened BLA connectivity with a frontoparietal cluster implicated in regulatory executive functioning. We suggest that these trait‐specific shifts in amygdalar connectivity could be particularly relevant to the psychopathic phenotype, as they may fuel a self‐centered, emotionally cold, and behaviorally disinhibited profile. Hum Brain Mapp 37:4017–4033, 2016. © 2016 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc. PMID:27453465

Quantifying the Spatial Ecology of Wide-Ranging Marine Species in the Gulf of California: Implications for Marine Conservation Planning

PubMed Central

Anadón, José Daniel; D'Agrosa, Caterina; Gondor, Anne; Gerber, Leah R.

2011-01-01

There is growing interest in systematic establishment of marine protected area (MPA) networks and representative conservation sites. This movement toward networks of no-take zones requires that reserves are deliberately and adequately spaced for connectivity. Here, we test the network functionality of an ecoregional assessment configuration of marine conservation areas by evaluating the habitat protection and connectivity offered to wide-ranging fauna in the Gulf of California (GOC, Mexico). We first use expert opinion to identify representative species of wide-ranging fauna of the GOC. These include leopard grouper, hammerhead sharks, California brown pelicans and green sea turtles. Analyzing habitat models with both structural and functional connectivity indexes, our results indicate that the configuration includes large proportions of biologically important habitat for the four species considered (25–40%), particularly, the best quality habitats (46–57%). Our results also show that connectivity levels offered by the conservation area design for these four species may be similar to connectivity levels offered by the entire Gulf of California, thus indicating that connectivity offered by the areas may resemble natural connectivity. The selected focal species comprise different life histories among marine or marine-related vertebrates and are associated with those habitats holding the most biodiversity values (i.e. coastal habitats); our results thus suggest that the proposed configuration may function as a network for connectivity and may adequately represent the marine megafauna in the GOC, including the potential connectivity among habitat patches. This work highlights the range of approaches that can be used to quantify habitat protection and connectivity for wide-ranging marine species in marine reserve networks. PMID:22163013

Quantifying the spatial ecology of wide-ranging marine species in the Gulf of California: implications for marine conservation planning.

PubMed

Anadón, José Daniel; D'Agrosa, Caterina; Gondor, Anne; Gerber, Leah R

2011-01-01

There is growing interest in systematic establishment of marine protected area (MPA) networks and representative conservation sites. This movement toward networks of no-take zones requires that reserves are deliberately and adequately spaced for connectivity. Here, we test the network functionality of an ecoregional assessment configuration of marine conservation areas by evaluating the habitat protection and connectivity offered to wide-ranging fauna in the Gulf of California (GOC, Mexico). We first use expert opinion to identify representative species of wide-ranging fauna of the GOC. These include leopard grouper, hammerhead sharks, California brown pelicans and green sea turtles. Analyzing habitat models with both structural and functional connectivity indexes, our results indicate that the configuration includes large proportions of biologically important habitat for the four species considered (25-40%), particularly, the best quality habitats (46-57%). Our results also show that connectivity levels offered by the conservation area design for these four species may be similar to connectivity levels offered by the entire Gulf of California, thus indicating that connectivity offered by the areas may resemble natural connectivity. The selected focal species comprise different life histories among marine or marine-related vertebrates and are associated with those habitats holding the most biodiversity values (i.e. coastal habitats); our results thus suggest that the proposed configuration may function as a network for connectivity and may adequately represent the marine megafauna in the GOC, including the potential connectivity among habitat patches. This work highlights the range of approaches that can be used to quantify habitat protection and connectivity for wide-ranging marine species in marine reserve networks.

Predicting the cumulative effect of multiple disturbances on seagrass connectivity.

PubMed

Grech, Alana; Hanert, Emmanuel; McKenzie, Len; Rasheed, Michael; Thomas, Christopher; Tol, Samantha; Wang, Mingzhu; Waycott, Michelle; Wolter, Jolan; Coles, Rob

2018-03-15

The rate of exchange, or connectivity, among populations effects their ability to recover after disturbance events. However, there is limited information on the extent to which populations are connected or how multiple disturbances affect connectivity, especially in coastal and marine ecosystems. We used network analysis and the outputs of a biophysical model to measure potential functional connectivity and predict the impact of multiple disturbances on seagrasses in the central Great Barrier Reef World Heritage Area (GBRWHA), Australia. The seagrass networks were densely connected, indicating that seagrasses are resilient to the random loss of meadows. Our analysis identified discrete meadows that are important sources of seagrass propagules and that serve as stepping stones connecting various different parts of the network. Several of these meadows were close to urban areas or ports and likely to be at risk from coastal development. Deep water meadows were highly connected to coastal meadows and may function as a refuge, but only for non-foundation species. We evaluated changes to the structure and functioning of the seagrass networks when one or more discrete meadows were removed due to multiple disturbance events. The scale of disturbance required to disconnect the seagrass networks into two or more components was on average >245 km, about half the length of the metapopulation. The densely connected seagrass meadows of the central GBRWHA are not limited by the supply of propagules; therefore, management should focus on improving environmental conditions that support natural seagrass recruitment and recovery processes. Our study provides a new framework for assessing the impact of global change on the connectivity and persistence of coastal and marine ecosystems. Without this knowledge, management actions, including coastal restoration, may prove unnecessary and be unsuccessful. © 2018 John Wiley & Sons Ltd.

Corticocortical evoked potentials reveal projectors and integrators in human brain networks.

PubMed

Keller, Corey J; Honey, Christopher J; Entz, Laszlo; Bickel, Stephan; Groppe, David M; Toth, Emilia; Ulbert, Istvan; Lado, Fred A; Mehta, Ashesh D

2014-07-02

The cerebral cortex is composed of subregions whose functional specialization is largely determined by their incoming and outgoing connections with each other. In the present study, we asked which cortical regions can exert the greatest influence over other regions and the cortical network as a whole. Previous research on this question has relied on coarse anatomy (mapping large fiber pathways) or functional connectivity (mapping inter-regional statistical dependencies in ongoing activity). Here we combined direct electrical stimulation with recordings from the cortical surface to provide a novel insight into directed, inter-regional influence within the cerebral cortex of awake humans. These networks of directed interaction were reproducible across strength thresholds and across subjects. Directed network properties included (1) a decrease in the reciprocity of connections with distance; (2) major projector nodes (sources of influence) were found in peri-Rolandic cortex and posterior, basal and polar regions of the temporal lobe; and (3) major receiver nodes (receivers of influence) were found in anterolateral frontal, superior parietal, and superior temporal regions. Connectivity maps derived from electrical stimulation and from resting electrocorticography (ECoG) correlations showed similar spatial distributions for the same source node. However, higher-level network topology analysis revealed differences between electrical stimulation and ECoG that were partially related to the reciprocity of connections. Together, these findings inform our understanding of large-scale corticocortical influence as well as the interpretation of functional connectivity networks. Copyright © 2014 the authors 0270-6474/14/349152-12$15.00/0.

An Efficient and Reliable Statistical Method for Estimating Functional Connectivity in Large Scale Brain Networks Using Partial Correlation

PubMed Central

Wang, Yikai; Kang, Jian; Kemmer, Phebe B.; Guo, Ying

2016-01-01

Currently, network-oriented analysis of fMRI data has become an important tool for understanding brain organization and brain networks. Among the range of network modeling methods, partial correlation has shown great promises in accurately detecting true brain network connections. However, the application of partial correlation in investigating brain connectivity, especially in large-scale brain networks, has been limited so far due to the technical challenges in its estimation. In this paper, we propose an efficient and reliable statistical method for estimating partial correlation in large-scale brain network modeling. Our method derives partial correlation based on the precision matrix estimated via Constrained L1-minimization Approach (CLIME), which is a recently developed statistical method that is more efficient and demonstrates better performance than the existing methods. To help select an appropriate tuning parameter for sparsity control in the network estimation, we propose a new Dens-based selection method that provides a more informative and flexible tool to allow the users to select the tuning parameter based on the desired sparsity level. Another appealing feature of the Dens-based method is that it is much faster than the existing methods, which provides an important advantage in neuroimaging applications. Simulation studies show that the Dens-based method demonstrates comparable or better performance with respect to the existing methods in network estimation. We applied the proposed partial correlation method to investigate resting state functional connectivity using rs-fMRI data from the Philadelphia Neurodevelopmental Cohort (PNC) study. Our results show that partial correlation analysis removed considerable between-module marginal connections identified by full correlation analysis, suggesting these connections were likely caused by global effects or common connection to other nodes. Based on partial correlation, we find that the most significant direct connections are between homologous brain locations in the left and right hemisphere. When comparing partial correlation derived under different sparse tuning parameters, an important finding is that the sparse regularization has more shrinkage effects on negative functional connections than on positive connections, which supports previous findings that many of the negative brain connections are due to non-neurophysiological effects. An R package “DensParcorr” can be downloaded from CRAN for implementing the proposed statistical methods. PMID:27242395

An Efficient and Reliable Statistical Method for Estimating Functional Connectivity in Large Scale Brain Networks Using Partial Correlation.

PubMed

Wang, Yikai; Kang, Jian; Kemmer, Phebe B; Guo, Ying

2016-01-01

Currently, network-oriented analysis of fMRI data has become an important tool for understanding brain organization and brain networks. Among the range of network modeling methods, partial correlation has shown great promises in accurately detecting true brain network connections. However, the application of partial correlation in investigating brain connectivity, especially in large-scale brain networks, has been limited so far due to the technical challenges in its estimation. In this paper, we propose an efficient and reliable statistical method for estimating partial correlation in large-scale brain network modeling. Our method derives partial correlation based on the precision matrix estimated via Constrained L1-minimization Approach (CLIME), which is a recently developed statistical method that is more efficient and demonstrates better performance than the existing methods. To help select an appropriate tuning parameter for sparsity control in the network estimation, we propose a new Dens-based selection method that provides a more informative and flexible tool to allow the users to select the tuning parameter based on the desired sparsity level. Another appealing feature of the Dens-based method is that it is much faster than the existing methods, which provides an important advantage in neuroimaging applications. Simulation studies show that the Dens-based method demonstrates comparable or better performance with respect to the existing methods in network estimation. We applied the proposed partial correlation method to investigate resting state functional connectivity using rs-fMRI data from the Philadelphia Neurodevelopmental Cohort (PNC) study. Our results show that partial correlation analysis removed considerable between-module marginal connections identified by full correlation analysis, suggesting these connections were likely caused by global effects or common connection to other nodes. Based on partial correlation, we find that the most significant direct connections are between homologous brain locations in the left and right hemisphere. When comparing partial correlation derived under different sparse tuning parameters, an important finding is that the sparse regularization has more shrinkage effects on negative functional connections than on positive connections, which supports previous findings that many of the negative brain connections are due to non-neurophysiological effects. An R package "DensParcorr" can be downloaded from CRAN for implementing the proposed statistical methods.

Resting-state brain networks revealed by granger causal connectivity in frogs.

PubMed

Xue, Fei; Fang, Guangzhan; Yue, Xizi; Zhao, Ermi; Brauth, Steven E; Tang, Yezhong

2016-10-15

Resting-state networks (RSNs) refer to the spontaneous brain activity generated under resting conditions, which maintain the dynamic connectivity of functional brain networks for automatic perception or higher order cognitive functions. Here, Granger causal connectivity analysis (GCCA) was used to explore brain RSNs in the music frog (Babina daunchina) during different behavioral activity phases. The results reveal that a causal network in the frog brain can be identified during the resting state which reflects both brain lateralization and sexual dimorphism. Specifically (1) ascending causal connections from the left mesencephalon to both sides of the telencephalon are significantly higher than those from the right mesencephalon, while the right telencephalon gives rise to the strongest efferent projections among all brain regions; (2) causal connections from the left mesencephalon in females are significantly higher than those in males and (3) these connections are similar during both the high and low behavioral activity phases in this species although almost all electroencephalograph (EEG) spectral bands showed higher power in the high activity phase for all nodes. The functional features of this network match important characteristics of auditory perception in this species. Thus we propose that this causal network maintains auditory perception during the resting state for unexpected auditory inputs as resting-state networks do in other species. These results are also consistent with the idea that females are more sensitive to auditory stimuli than males during the reproductive season. In addition, these results imply that even when not behaviorally active, the frogs remain vigilant for detecting external stimuli. Copyright © 2016 IBRO. Published by Elsevier Ltd. All rights reserved.

Functional Organization of the Action Observation Network in Autism: A Graph Theory Approach.

PubMed

Alaerts, Kaat; Geerlings, Franca; Herremans, Lynn; Swinnen, Stephan P; Verhoeven, Judith; Sunaert, Stefan; Wenderoth, Nicole

2015-01-01

The ability to recognize, understand and interpret other's actions and emotions has been linked to the mirror system or action-observation-network (AON). Although variations in these abilities are prevalent in the neuro-typical population, persons diagnosed with autism spectrum disorders (ASD) have deficits in the social domain and exhibit alterations in this neural network. Here, we examined functional network properties of the AON using graph theory measures and region-to-region functional connectivity analyses of resting-state fMRI-data from adolescents and young adults with ASD and typical controls (TC). Overall, our graph theory analyses provided convergent evidence that the network integrity of the AON is altered in ASD, and that reductions in network efficiency relate to reductions in overall network density (i.e., decreased overall connection strength). Compared to TC, individuals with ASD showed significant reductions in network efficiency and increased shortest path lengths and centrality. Importantly, when adjusting for overall differences in network density between ASD and TC groups, participants with ASD continued to display reductions in network integrity, suggesting that also network-level organizational properties of the AON are altered in ASD. While differences in empirical connectivity contributed to reductions in network integrity, graph theoretical analyses provided indications that also changes in the high-level network organization reduced integrity of the AON.

A New Measure of Centrality for Brain Networks

PubMed Central

Joyce, Karen E.; Laurienti, Paul J.; Burdette, Jonathan H.; Hayasaka, Satoru

2010-01-01

Recent developments in network theory have allowed for the study of the structure and function of the human brain in terms of a network of interconnected components. Among the many nodes that form a network, some play a crucial role and are said to be central within the network structure. Central nodes may be identified via centrality metrics, with degree, betweenness, and eigenvector centrality being three of the most popular measures. Degree identifies the most connected nodes, whereas betweenness centrality identifies those located on the most traveled paths. Eigenvector centrality considers nodes connected to other high degree nodes as highly central. In the work presented here, we propose a new centrality metric called leverage centrality that considers the extent of connectivity of a node relative to the connectivity of its neighbors. The leverage centrality of a node in a network is determined by the extent to which its immediate neighbors rely on that node for information. Although similar in concept, there are essential differences between eigenvector and leverage centrality that are discussed in this manuscript. Degree, betweenness, eigenvector, and leverage centrality were compared using functional brain networks generated from healthy volunteers. Functional cartography was also used to identify neighborhood hubs (nodes with high degree within a network neighborhood). Provincial hubs provide structure within the local community, and connector hubs mediate connections between multiple communities. Leverage proved to yield information that was not captured by degree, betweenness, or eigenvector centrality and was more accurate at identifying neighborhood hubs. We propose that this metric may be able to identify critical nodes that are highly influential within the network. PMID:20808943

Core networks and their reconfiguration patterns across cognitive loads.

PubMed

Zuo, Nianming; Yang, Zhengyi; Liu, Yong; Li, Jin; Jiang, Tianzi

2018-04-20

Different cognitively demanding tasks recruit globally distributed but functionally specific networks. However, the configuration of core networks and their reconfiguration patterns across cognitive loads remain unclear, as does whether these patterns are indicators for the performance of cognitive tasks. In this study, we analyzed functional magnetic resonance imaging data of a large cohort of 448 subjects, acquired with the brain at resting state and executing N-back working memory (WM) tasks. We discriminated core networks by functional interaction strength and connection flexibility. Results demonstrated that the frontoparietal network (FPN) and default mode network (DMN) were core networks, but each exhibited different patterns across cognitive loads. The FPN and DMN both showed strengthened internal connections at the low demand state (0-back) compared with the resting state (control level); whereas, from the low (0-back) to high demand state (2-back), some connections to the FPN weakened and were rewired to the DMN (whose connections all remained strong). Of note, more intensive reconfiguration of both the whole brain and core networks (but no other networks) across load levels indicated relatively poor cognitive performance. Collectively these findings indicate that the FPN and DMN have distinct roles and reconfiguration patterns across cognitively demanding loads. This study advances our understanding of the core networks and their reconfiguration patterns across cognitive loads and provides a new feature to evaluate and predict cognitive capability (e.g., WM performance) based on brain networks. © 2018 Wiley Periodicals, Inc.

Development of thalamocortical connectivity during infancy and its cognitive correlations.

PubMed

Alcauter, Sarael; Lin, Weili; Smith, J Keith; Short, Sarah J; Goldman, Barbara D; Reznick, J Steven; Gilmore, John H; Gao, Wei

2014-07-02

Although commonly viewed as a sensory information relay center, the thalamus has been increasingly recognized as an essential node in various higher-order cognitive circuits, and the underlying thalamocortical interaction mechanism has attracted increasing scientific interest. However, the development of thalamocortical connections and how such development relates to cognitive processes during the earliest stages of life remain largely unknown. Leveraging a large human pediatric sample (N = 143) with longitudinal resting-state fMRI scans and cognitive data collected during the first 2 years of life, we aimed to characterize the age-dependent development of thalamocortical connectivity patterns by examining the functional relationship between the thalamus and nine cortical functional networks and determine the correlation between thalamocortical connectivity and cognitive performance at ages 1 and 2 years. Our results revealed that the thalamus-sensorimotor and thalamus-salience connectivity networks were already present in neonates, whereas the thalamus-medial visual and thalamus-default mode network connectivity emerged later, at 1 year of age. More importantly, brain-behavior analyses based on the Mullen Early Learning Composite Score and visual-spatial working memory performance measured at 1 and 2 years of age highlighted significant correlations with the thalamus-salience network connectivity. These results provide new insights into the understudied early functional brain development process and shed light on the behavioral importance of the emerging thalamocortical connectivity during infancy. Copyright © 2014 the authors 0270-6474/14/349067-09$15.00/0.

Asynchronous networks: modularization of dynamics theorem

NASA Astrophysics Data System (ADS)

Bick, Christian; Field, Michael

2017-02-01

Building on the first part of this paper, we develop the theory of functional asynchronous networks. We show that a large class of functional asynchronous networks can be (uniquely) represented as feedforward networks connecting events or dynamical modules. For these networks we can give a complete description of the network function in terms of the function of the events comprising the network: the modularization of dynamics theorem. We give examples to illustrate the main results.

Large-scale changes in network interactions as a physiological signature of spatial neglect.

PubMed

Baldassarre, Antonello; Ramsey, Lenny; Hacker, Carl L; Callejas, Alicia; Astafiev, Serguei V; Metcalf, Nicholas V; Zinn, Kristi; Rengachary, Jennifer; Snyder, Abraham Z; Carter, Alex R; Shulman, Gordon L; Corbetta, Maurizio

2014-12-01

The relationship between spontaneous brain activity and behaviour following focal injury is not well understood. Here, we report a large-scale study of resting state functional connectivity MRI and spatial neglect following stroke in a large (n=84) heterogeneous sample of first-ever stroke patients (within 1-2 weeks). Spatial neglect, which is typically more severe after right than left hemisphere injury, includes deficits of spatial attention and motor actions contralateral to the lesion, and low general attention due to impaired vigilance/arousal. Patients underwent structural and resting state functional MRI scans, and spatial neglect was measured using the Posner spatial cueing task, and Mesulam and Behavioural Inattention Test cancellation tests. A principal component analysis of the behavioural tests revealed a main factor accounting for 34% of variance that captured three correlated behavioural deficits: visual neglect of the contralesional visual field, visuomotor neglect of the contralesional field, and low overall performance. In an independent sample (21 healthy subjects), we defined 10 resting state networks consisting of 169 brain regions: visual-fovea and visual-periphery, sensory-motor, auditory, dorsal attention, ventral attention, language, fronto-parietal control, cingulo-opercular control, and default mode. We correlated the neglect factor score with the strength of resting state functional connectivity within and across the 10 resting state networks. All damaged brain voxels were removed from the functional connectivity:behaviour correlational analysis. We found that the correlated behavioural deficits summarized by the factor score were associated with correlated multi-network patterns of abnormal functional connectivity involving large swaths of cortex. Specifically, dorsal attention and sensory-motor networks showed: (i) reduced interhemispheric functional connectivity; (ii) reduced anti-correlation with fronto-parietal and default mode networks in the right hemisphere; and (iii) increased intrahemispheric connectivity with the basal ganglia. These patterns of functional connectivity:behaviour correlations were stronger in patients with right- as compared to left-hemisphere damage and were independent of lesion volume. Our findings identify large-scale changes in resting state network interactions that are a physiological signature of spatial neglect and may relate to its right hemisphere lateralization. © The Author (2014). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Network Disruption and Cerebrospinal Fluid Amyloid-Beta and Phospho-Tau Levels in Mild Cognitive Impairment.

PubMed

Canuet, Leonides; Pusil, Sandra; López, María Eugenia; Bajo, Ricardo; Pineda-Pardo, José Ángel; Cuesta, Pablo; Gálvez, Gerardo; Gaztelu, José María; Lourido, Daniel; García-Ribas, Guillermo; Maestú, Fernando

2015-07-15

Synaptic dysfunction is a core deficit in Alzheimer's disease, preceding hallmark pathological abnormalities. Resting-state magnetoencephalography (MEG) was used to assess whether functional connectivity patterns, as an index of synaptic dysfunction, are associated with CSF biomarkers [i.e., phospho-tau (p-tau) and amyloid beta (Aβ42) levels]. We studied 12 human subjects diagnosed with mild cognitive impairment due to Alzheimer's disease, comparing those with normal and abnormal CSF levels of the biomarkers. We also evaluated the association between aberrant functional connections and structural connectivity abnormalities, measured with diffusion tensor imaging, as well as the convergent impact of cognitive deficits and CSF variables on network disorganization. One-third of the patients converted to Alzheimer's disease during a follow-up period of 2.5 years. Patients with abnomal CSF p-tau and Aβ42 levels exhibited both reduced and increased functional connectivity affecting limbic structures such as the anterior/posterior cingulate cortex, orbitofrontal cortex, and medial temporal areas in different frequency bands. A reduction in posterior cingulate functional connectivity mediated by p-tau was associated with impaired axonal integrity of the hippocampal cingulum. We noted that several connectivity abnormalities were predicted by CSF biomarkers and cognitive scores. These preliminary results indicate that CSF markers of amyloid deposition and neuronal injury in early Alzheimer's disease associate with a dual pattern of cortical network disruption, affecting key regions of the default mode network and the temporal cortex. MEG is useful to detect early synaptic dysfunction associated with Alzheimer's disease brain pathology in terms of functional network organization. In this preliminary study, we used magnetoencephalography and an integrative approach to explore the impact of CSF biomarkers, neuropsychological scores, and white matter structural abnormalities on neural function in mild cognitive impairment. Disruption in functional connectivity between several pairs of cortical regions associated with abnormal levels of biomarkers, cognitive deficits, or with impaired axonal integrity of hippocampal tracts. Amyloid deposition and tau protein-related neuronal injury in early Alzheimer's disease are associated with synaptic dysfunction and a dual pattern of cortical network disorganization (i.e., desynchronization and hypersynchronization) that affects key regions of the default mode network and temporal areas. Copyright © 2015 the authors 0270-6474/15/3510326-06$15.00/0.

On the Reliability of Individual Brain Activity Networks.

PubMed

Cassidy, Ben; Bowman, F DuBois; Rae, Caroline; Solo, Victor

2018-02-01

There is intense interest in fMRI research on whole-brain functional connectivity, and however, two fundamental issues are still unresolved: the impact of spatiotemporal data resolution (spatial parcellation and temporal sampling) and the impact of the network construction method on the reliability of functional brain networks. In particular, the impact of spatiotemporal data resolution on the resulting connectivity findings has not been sufficiently investigated. In fact, a number of studies have already observed that functional networks often give different conclusions across different parcellation scales. If the interpretations from functional networks are inconsistent across spatiotemporal scales, then the whole validity of the functional network paradigm is called into question. This paper investigates the consistency of resting state network structure when using different temporal sampling or spatial parcellation, or different methods for constructing the networks. To pursue this, we develop a novel network comparison framework based on persistent homology from a topological data analysis. We use the new network comparison tools to characterize the spatial and temporal scales under which consistent functional networks can be constructed. The methods are illustrated on Human Connectome Project data, showing that the DISCOH 2 network construction method outperforms other approaches at most data spatiotemporal resolutions.

Altered Intrinsic Functional Brain Architecture in Children at Familial Risk of Major Depression.

PubMed

Chai, Xiaoqian J; Hirshfeld-Becker, Dina; Biederman, Joseph; Uchida, Mai; Doehrmann, Oliver; Leonard, Julia A; Salvatore, John; Kenworthy, Tara; Brown, Ariel; Kagan, Elana; de Los Angeles, Carlo; Gabrieli, John D E; Whitfield-Gabrieli, Susan

2016-12-01

Neuroimaging studies of patients with major depression have revealed abnormal intrinsic functional connectivity measured during the resting state in multiple distributed networks. However, it is unclear whether these findings reflect the state of major depression or reflect trait neurobiological underpinnings of risk for major depression. We compared resting-state functional connectivity, measured with functional magnetic resonance imaging, between unaffected children of parents who had documented histories of major depression (at-risk, n = 27; 8-14 years of age) and age-matched children of parents with no lifetime history of depression (control subjects, n = 16). At-risk children exhibited hyperconnectivity between the default mode network and subgenual anterior cingulate cortex/orbital frontal cortex, and the magnitude of connectivity positively correlated with individual symptom scores. At-risk children also exhibited 1) hypoconnectivity within the cognitive control network, which also lacked the typical anticorrelation with the default mode network; 2) hypoconnectivity between left dorsolateral prefrontal cortex and subgenual anterior cingulate cortex; and 3) hyperconnectivity between the right amygdala and right inferior frontal gyrus, a key region for top-down modulation of emotion. Classification between at-risk children and control subjects based on resting-state connectivity yielded high accuracy with high sensitivity and specificity that was superior to clinical rating scales. Children at familial risk for depression exhibited atypical functional connectivity in the default mode, cognitive control, and affective networks. Such task-independent functional brain measures of risk for depression in children could be used to promote early intervention to reduce the likelihood of developing depression. Copyright © 2016 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

Small Worldness in Dense and Weighted Connectomes

NASA Astrophysics Data System (ADS)

Colon-Perez, Luis; Couret, Michelle; Triplett, William; Price, Catherine; Mareci, Thomas

2016-05-01

The human brain is a heterogeneous network of connected functional regions; however, most brain network studies assume that all brain connections can be described in a framework of binary connections. The brain is a complex structure of white matter tracts connected by a wide range of tract sizes, which suggests a broad range of connection strengths. Therefore, the assumption that the connections are binary yields an incomplete picture of the brain. Various thresholding methods have been used to remove spurious connections and reduce the graph density in binary networks. But these thresholds are arbitrary and make problematic the comparison of networks created at different thresholds. The heterogeneity of connection strengths can be represented in graph theory by applying weights to the network edges. Using our recently introduced edge weight parameter, we estimated the topological brain network organization using a complimentary weighted connectivity framework to the traditional framework of a binary network. To examine the reproducibility of brain networks in a controlled condition, we studied the topological network organization of a single healthy individual by acquiring 10 repeated diffusion-weighted magnetic resonance image datasets, over a one-month period on the same scanner, and analyzing these networks with deterministic tractography. We applied a threshold to both the binary and weighted networks and determined that the extra degree of freedom that comes with the framework of weighting network connectivity provides a robust result as any threshold level. The proposed weighted connectivity framework provides a stable result and is able to demonstrate the small world property of brain networks in situations where the binary framework is inadequate and unable to demonstrate this network property.

The impacts of pesticide and nicotine exposures on functional brain networks in Latino immigrant workers.

PubMed

Bahrami, Mohsen; Laurienti, Paul J; Quandt, Sara A; Talton, Jennifer; Pope, Carey N; Summers, Phillip; Burdette, Jonathan H; Chen, Haiying; Liu, Jing; Howard, Timothy D; Arcury, Thomas A; Simpson, Sean L

2017-09-01

Latino immigrants that work on farms experience chronic exposures to potential neurotoxicants, such as pesticides, as part of their work. For tobacco farmworkers there is the additional risk of exposure to moderate to high doses of nicotine. Pesticide and nicotine exposures have been associated with neurological changes in the brain. Long-term exposure to cholinesterase-inhibiting pesticides, such as organophosphates and carbamates, and nicotine place this vulnerable population at risk for developing neurological dysfunction. In this study we examined whole-brain connectivity patterns and brain network properties of Latino immigrant workers. Comparisons were made between farmworkers and non-farmworkers using resting-state functional magnetic resonance imaging data and a mixed-effects modeling framework. We also evaluated how measures of pesticide and nicotine exposures contributed to the findings. Our results indicate that despite having the same functional connectivity density and strength, brain networks in farmworkers had more clustered and modular structures when compared to non-farmworkers. Our findings suggest increased functional specificity and decreased functional integration in farmworkers when compared to non-farmworkers. Cholinesterase activity was associated with population differences in community structure and the strength of brain network functional connections. Urinary cotinine, a marker of nicotine exposure, was associated with the differences in network community structure. Brain network differences between farmworkers and non-farmworkers, as well as pesticide and nicotine exposure effects on brain functional connections in this study, may illuminate underlying mechanisms that cause neurological implications in later life. Copyright © 2017 Elsevier B.V. All rights reserved.

Defense strategies for cloud computing multi-site server infrastructures

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rao, Nageswara S.; Ma, Chris Y. T.; He, Fei

We consider cloud computing server infrastructures for big data applications, which consist of multiple server sites connected over a wide-area network. The sites house a number of servers, network elements and local-area connections, and the wide-area network plays a critical, asymmetric role of providing vital connectivity between them. We model this infrastructure as a system of systems, wherein the sites and wide-area network are represented by their cyber and physical components. These components can be disabled by cyber and physical attacks, and also can be protected against them using component reinforcements. The effects of attacks propagate within the systems, andmore » also beyond them via the wide-area network.We characterize these effects using correlations at two levels using: (a) aggregate failure correlation function that specifies the infrastructure failure probability given the failure of an individual site or network, and (b) first-order differential conditions on system survival probabilities that characterize the component-level correlations within individual systems. We formulate a game between an attacker and a provider using utility functions composed of survival probability and cost terms. At Nash Equilibrium, we derive expressions for the expected capacity of the infrastructure given by the number of operational servers connected to the network for sum-form, product-form and composite utility functions.« less

Brain Connectivity in Pathological and Pharmacological Coma

PubMed Central

Noirhomme, Quentin; Soddu, Andrea; Lehembre, Rémy; Vanhaudenhuyse, Audrey; Boveroux, Pierre; Boly, Mélanie; Laureys, Steven

2010-01-01

Recent studies in patients with disorders of consciousness (DOC) tend to support the view that awareness is not related to activity in a single brain region but to thalamo-cortical connectivity in the frontoparietal network. Functional neuroimaging studies have shown preserved albeit disconnected low-level cortical activation in response to external stimulation in patients in a “vegetative state” or unresponsive wakefulness syndrome. While activation of these “primary” sensory cortices does not necessarily reflect conscious awareness, activation in higher-order associative cortices in minimally conscious state patients seems to herald some residual perceptual awareness. PET studies have identified a metabolic dysfunction in a widespread frontoparietal “global neuronal workspace” in DOC patients including the midline default mode network (“intrinsic” system) and the lateral frontoparietal cortices or “extrinsic system.” Recent studies have investigated the relation of awareness to the functional connectivity within intrinsic and extrinsic networks, and with the thalami in both pathological and pharmacological coma. In brain damaged patients, connectivity in all default network areas was found to be non-linearly correlated with the degree of clinical consciousness impairment, ranging from healthy controls and locked-in syndrome to minimally conscious, vegetative, coma, and brain dead patients. Anesthesia-induced loss of consciousness was also shown to correlate with a global decrease in cortico-cortical and thalamo-cortical connectivity in both intrinsic and extrinsic networks, but not in auditory, or visual networks. In anesthesia, unconsciousness was also associated with a loss of cross-modal interactions between networks. These results suggest that conscious awareness critically depends on the functional integrity of thalamo-cortical and cortico-cortical frontoparietal connectivity within and between “intrinsic” and “extrinsic” brain networks. PMID:21191476

Functional Network Disruption in the Degenerative Dementias

PubMed Central

Pievani, Michela; de Haan, Willem; Wu, Tao; Seeley, William W; Frisoni, Giovanni B

2011-01-01

Despite considerable advances toward understanding the molecular pathophysiology of the neurodegenerative dementias, the mechanisms linking molecular changes to neuropathology and the latter to clinical symptoms remain largely obscure. Connectivity is a distinctive feature of the brain and the integrity of functional network dynamics is critical for normal functioning. A better understanding of network disruption in the neurodegenerative dementias may help bridge the gap between molecular changes, pathology and symptoms. Recent findings on functional network disruption as assessed with “resting-state” or intrinsic connectivity fMRI and EEG/MEG have shown distinct patterns of network disruption across the major neurodegenerative diseases. These network abnormalities are relatively specific to the clinical syndromes, and in Alzheimer's disease and frontotemporal dementia network disruption tracks the pattern of pathological changes. These findings may have a practical impact on diagnostic accuracy, allowing earlier detection of neurodegenerative diseases even at the pre-symptomatic stage, and tracking of disease progression. PMID:21778116

Functional brain networks for learning predictive statistics.

PubMed

Giorgio, Joseph; Karlaftis, Vasilis M; Wang, Rui; Shen, Yuan; Tino, Peter; Welchman, Andrew; Kourtzi, Zoe

2017-08-18

Making predictions about future events relies on interpreting streams of information that may initially appear incomprehensible. This skill relies on extracting regular patterns in space and time by mere exposure to the environment (i.e., without explicit feedback). Yet, we know little about the functional brain networks that mediate this type of statistical learning. Here, we test whether changes in the processing and connectivity of functional brain networks due to training relate to our ability to learn temporal regularities. By combining behavioral training and functional brain connectivity analysis, we demonstrate that individuals adapt to the environment's statistics as they change over time from simple repetition to probabilistic combinations. Further, we show that individual learning of temporal structures relates to decision strategy. Our fMRI results demonstrate that learning-dependent changes in fMRI activation within and functional connectivity between brain networks relate to individual variability in strategy. In particular, extracting the exact sequence statistics (i.e., matching) relates to changes in brain networks known to be involved in memory and stimulus-response associations, while selecting the most probable outcomes in a given context (i.e., maximizing) relates to changes in frontal and striatal networks. Thus, our findings provide evidence that dissociable brain networks mediate individual ability in learning behaviorally-relevant statistics. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Study on the Relationships between Intrinsic Functional Connectivity of the Default Mode Network and Transient Epileptic Activity.

PubMed

Lopes, Renaud; Moeller, Friederike; Besson, Pierre; Ogez, François; Szurhaj, William; Leclerc, Xavier; Siniatchkin, Michael; Chipaux, Mathilde; Derambure, Philippe; Tyvaert, Louise

2014-01-01

Simultaneous recording of electroencephalogram and functional MRI (EEG-fMRI) is a powerful tool for localizing epileptic networks via the detection of hemodynamic changes correlated with interictal epileptic discharges (IEDs). fMRI can be used to study the long-lasting effect of epileptic activity by assessing stationary functional connectivity during the resting-state period [especially, the connectivity of the default mode network (DMN)]. Temporal lobe epilepsy (TLE) and idiopathic generalized epilepsy (IGE) are associated with low responsiveness and disruption of DMN activity. A dynamic functional connectivity approach might enable us to determine the effect of IEDs on DMN connectivity and to better understand the correlation between DMN connectivity changes and altered consciousness. We studied dynamic changes in DMN intrinsic connectivity and their relation to IEDs. Six IGE patients (with generalized spike and slow-waves) and 6 TLE patients (with unilateral left temporal spikes) were included. Functional connectivity before, during, and after IEDs was estimated using a sliding window approach and compared with the baseline period. No dependence on window size was observed. The baseline DMN connectivity was decreased in the left hemisphere (ipsilateral to the epileptic focus) in TLEs and was less strong but remained bilateral in IGEs. We observed an overall increase in DMN intrinsic connectivity prior to the onset of IEDs in both IGEs and TLEs. After IEDs in TLEs, we found that DMN connectivity increased before it returned to baseline values. Most of the DMN regions with increased connectivity before and after IEDs were lateralized to the left hemisphere in TLE (i.e., ipsilateral to the epileptic focus). RESULTS suggest that DMN connectivity may facilitate IED generation and may be affected at the time of the IED. However, these results need to be confirmed in a larger independent cohort.

The evolution of cost-efficiency in neural networks during recovery from traumatic brain injury.

PubMed

Roy, Arnab; Bernier, Rachel A; Wang, Jianli; Benson, Monica; French, Jerry J; Good, David C; Hillary, Frank G

2017-01-01

A somewhat perplexing finding in the systems neuroscience has been the observation that physical injury to neural systems may result in enhanced functional connectivity (i.e., hyperconnectivity) relative to the typical network response. The consequences of local or global enhancement of functional connectivity remain uncertain and this is particularly true for the overall metabolic cost of the network. We examine the hyperconnectivity hypothesis in a sample of 14 individuals with TBI with data collected at approximately 3, 6, and 12 months following moderate and severe TBI. As anticipated, individuals with TBI showed increased network strength and cost early after injury, but by one-year post injury hyperconnectivity was more circumscribed to frontal DMN and temporal-parietal attentional control regions. Cost in these subregions was a significant predictor of cognitive performance. Cost-efficiency analysis in the Power 264 data parcellation suggested that at 6 months post injury the network requires higher cost connections to achieve high efficiency as compared to the network 12 months post injury. These results demonstrate that networks self-organize to re-establish connectivity while balancing cost-efficiency trade-offs.

The evolution of cost-efficiency in neural networks during recovery from traumatic brain injury

PubMed Central

Roy, Arnab; Bernier, Rachel A.; Wang, Jianli; Benson, Monica; French, Jerry J.; Good, David C.; Hillary, Frank G.

2017-01-01

A somewhat perplexing finding in the systems neuroscience has been the observation that physical injury to neural systems may result in enhanced functional connectivity (i.e., hyperconnectivity) relative to the typical network response. The consequences of local or global enhancement of functional connectivity remain uncertain and this is particularly true for the overall metabolic cost of the network. We examine the hyperconnectivity hypothesis in a sample of 14 individuals with TBI with data collected at approximately 3, 6, and 12 months following moderate and severe TBI. As anticipated, individuals with TBI showed increased network strength and cost early after injury, but by one-year post injury hyperconnectivity was more circumscribed to frontal DMN and temporal-parietal attentional control regions. Cost in these subregions was a significant predictor of cognitive performance. Cost-efficiency analysis in the Power 264 data parcellation suggested that at 6 months post injury the network requires higher cost connections to achieve high efficiency as compared to the network 12 months post injury. These results demonstrate that networks self-organize to re-establish connectivity while balancing cost-efficiency trade-offs. PMID:28422992

Analyzing and Assessing Brain Structure with Graph Connectivity Measures

DTIC Science & Technology

2014-05-09

structural brain networks, i.e. determining which regions of the brain are physically connected. Meanwhile, functional MRI ( fMRI ) yields an image of...produced by fMRI is a map of which parts are of the brain are active and which are not at a given time. In creating functional networks, regions of...the brain which often activitate together, i.e., often show up on fMRI as deoxygenated regions together, are considered connected. DTI allows the

Neurobiological changes of schizotypy: evidence from both volume-based morphometric analysis and resting-state functional connectivity.

PubMed

Wang, Yi; Yan, Chao; Yin, Da-zhi; Fan, Ming-xia; Cheung, Eric F C; Pantelis, Christos; Chan, Raymond C K

2015-03-01

The current study sought to examine the underlying brain changes in individuals with high schizotypy by integrating networks derived from brain structural and functional imaging. Individuals with high schizotypy (n = 35) and low schizotypy (n = 34) controls were screened using the Schizotypal Personality Questionnaire and underwent brain structural and resting-state functional magnetic resonance imaging on a 3T scanner. Voxel-based morphometric analysis and graph theory-based functional network analysis were conducted. Individuals with high schizotypy showed reduced gray matter (GM) density in the insula and the dorsolateral prefrontal gyrus. The graph theoretical analysis showed that individuals with high schizotypy showed similar global properties in their functional networks as low schizotypy individuals. Several hubs of the functional network were identified in both groups, including the insula, the lingual gyrus, the postcentral gyrus, and the rolandic operculum. More hubs in the frontal lobe and fewer hubs in the occipital lobe were identified in individuals with high schizotypy. By comparing the functional connectivity between clusters with abnormal GM density and the whole brain, individuals with high schizotypy showed weaker functional connectivity between the left insula and the putamen, but stronger connectivity between the cerebellum and the medial frontal gyrus. Taken together, our findings suggest that individuals with high schizotypy present changes in terms of GM and resting-state functional connectivity, especially in the frontal lobe. © The Author 2014. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Comparison of Functional Network Connectivity for Passive-Listening and Active-Response Narrative Comprehension in Adolescents

PubMed Central

Holland, Scott K.

2014-01-01

Abstract Comprehension of narrative stories plays an important role in the development of language skills. In this study, we compared brain activity elicited by a passive-listening version and an active-response (AR) version of a narrative comprehension task by using independent component (IC) analysis on functional magnetic resonance imaging data from 21 adolescents (ages 14–18 years). Furthermore, we explored differences in functional network connectivity engaged by two versions of the task and investigated the relationship between the online response time and the strength of connectivity between each pair of ICs. Despite similar brain region involvements in auditory, temporoparietal, and frontoparietal language networks for both versions, the AR version engages some additional network elements including the left dorsolateral prefrontal, anterior cingulate, and sensorimotor networks. These additional involvements are likely associated with working memory and maintenance of attention, which can be attributed to the differences in cognitive strategic aspects of the two versions. We found significant positive correlation between the online response time and the strength of connectivity between an IC in left inferior frontal region and an IC in sensorimotor region. An explanation for this finding is that longer reaction time indicates stronger connection between the frontal and sensorimotor networks caused by increased activation in adolescents who require more effort to complete the task. PMID:24689887

Functional resting-state connectivity of the human motor network: differences between right- and left-handers.

PubMed

Pool, Eva-Maria; Rehme, Anne K; Eickhoff, Simon B; Fink, Gereon R; Grefkes, Christian

2015-04-01

Handedness is associated with differences in activation levels in various motor tasks performed with the dominant or non-dominant hand. Here we tested whether handedness is reflected in the functional architecture of the motor system even in the absence of an overt motor task. Using resting-state functional magnetic resonance imaging we investigated 18 right- and 18 left-handers. Whole-brain functional connectivity maps of the primary motor cortex (M1), supplementary motor area (SMA), dorsolateral premotor cortex (PMd), pre-SMA, inferior frontal junction and motor putamen were compared between right- and left-handers. We further used a multivariate linear support vector machine (SVM) classifier to reveal the specificity of brain regions for classifying handedness based on individual resting-state maps. Using left M1 as seed region, functional connectivity analysis revealed stronger interhemispheric functional connectivity between left M1 and right PMd in right-handers as compared to left-handers. This connectivity cluster contributed to the individual classification of right- and left-handers with 86.2% accuracy. Consistently, also seeding from right PMd yielded a similar handedness-dependent effect in left M1, albeit with lower classification accuracy (78.1%). Control analyses of the other resting-state networks including the speech and the visual network revealed no significant differences in functional connectivity related to handedness. In conclusion, our data revealed an intrinsically higher functional connectivity in right-handers. These results may help to explain that hand preference is more lateralized in right-handers than in left-handers. Furthermore, enhanced functional connectivity between left M1 and right PMd may serve as an individual marker of handedness. Copyright © 2015 Elsevier Inc. All rights reserved.

Functional resting-state connectivity of the human motor network: Differences between right- and left-handers

PubMed Central

Pool, Eva-Maria; Rehme, Anne K.; Eickhoff, Simon B.; Fink, Gereon R.; Grefkes, Christian

2016-01-01

Handedness is associated with differences in activation levels in various motor tasks performed with the dominant or non-dominant hand. Here we tested whether handedness is reflected in the functional architecture of the motor system even in the absence of an overt motor task. Using resting-state functional magnetic resonance imaging we investigated 18 right- and 18 left-handers. Whole-brain functional connectivity maps of the primary motor cortex (M1), supplementary motor area (SMA), dorsolateral premotor cortex (PMd), pre-SMA, inferior frontal junction and motor putamen were compared between right- and left-handers. We further used a multivariate linear support vector machine (SVM) classifier to reveal the specificity of brain regions for classifying handedness based on individual resting-state maps. Using left M1 as seed region, functional connectivity analysis revealed stronger interhemispheric functional connectivity between left M1 and right PMd in right-handers as compared to left-handers. This connectivity cluster contributed to the individual classification of right- and left-handers with 86.2% accuracy. Consistently, also seeding from right PMd yielded a similar handedness-dependent effect in left M1, albeit with lower classification accuracy (78.1%). Control analyses of the other resting-state networks including the speech and the visual network revealed no significant differences in functional connectivity related to handedness. In conclusion, our data revealed an intrinsically higher functional connectivity in right-handers. These results may help to explain that hand preference is more lateralized in right-handers than in left-handers. Furthermore, enhanced functional connectivity between left M1 and right PMd may serve as an individual marker of handedness. PMID:25613438

Brain functional networks in syndromic and non-syndromic autism: a graph theoretical study of EEG connectivity

PubMed Central

2013-01-01

Background Graph theory has been recently introduced to characterize complex brain networks, making it highly suitable to investigate altered connectivity in neurologic disorders. A current model proposes autism spectrum disorder (ASD) as a developmental disconnection syndrome, supported by converging evidence in both non-syndromic and syndromic ASD. However, the effects of abnormal connectivity on network properties have not been well studied, particularly in syndromic ASD. To close this gap, brain functional networks of electroencephalographic (EEG) connectivity were studied through graph measures in patients with Tuberous Sclerosis Complex (TSC), a disorder with a high prevalence of ASD, as well as in patients with non-syndromic ASD. Methods EEG data were collected from TSC patients with ASD (n = 14) and without ASD (n = 29), from patients with non-syndromic ASD (n = 16), and from controls (n = 46). First, EEG connectivity was characterized by the mean coherence, the ratio of inter- over intra-hemispheric coherence and the ratio of long- over short-range coherence. Next, graph measures of the functional networks were computed and a resilience analysis was conducted. To distinguish effects related to ASD from those related to TSC, a two-way analysis of covariance (ANCOVA) was applied, using age as a covariate. Results Analysis of network properties revealed differences specific to TSC and ASD, and these differences were very consistent across subgroups. In TSC, both with and without a concurrent diagnosis of ASD, mean coherence, global efficiency, and clustering coefficient were decreased and the average path length was increased. These findings indicate an altered network topology. In ASD, both with and without a concurrent diagnosis of TSC, decreased long- over short-range coherence and markedly increased network resilience were found. Conclusions The altered network topology in TSC represents a functional correlate of structural abnormalities and may play a role in the pathogenesis of neurological deficits. The increased resilience in ASD may reflect an excessively degenerate network with local overconnection and decreased functional specialization. This joint study of TSC and ASD networks provides a unique window to common neurobiological mechanisms in autism. PMID:23445896

Aberrant functional connectivity of default-mode network in type 2 diabetes patients.

PubMed

Cui, Ying; Jiao, Yun; Chen, Hua-Jun; Ding, Jie; Luo, Bing; Peng, Cheng-Yu; Ju, Sheng-Hong; Teng, Gao-Jun

2015-11-01

Type 2 diabetes mellitus is associated with increased risk for dementia. Patients with impaired cognition often show default-mode network disruption. We aimed to investigate the integrity of a default-mode network in diabetic patients by using independent component analysis, and to explore the relationship between network abnormalities, neurocognitive performance and diabetic variables. Forty-two patients with type 2 diabetes and 42 well-matched healthy controls were included and underwent resting-state functional MRI in a 3 Tesla unit. Independent component analysis was adopted to extract the default-mode network, including its anterior and posterior components. Z-maps of both sub-networks were compared between the two groups and correlated with each clinical variable. Patients showed increased connectivity around the medial prefrontal cortex in the anterior sub-network, but decreased connectivity around the posterior cingulate cortex in the posterior sub-network. The decreased connectivity in the posterior part was significantly correlated with the score on Complex Figure Test-delay recall test (r = 0.359, p = 0.020), the time spent on Trail-Making Test-part B (r = -0.346, p = 0.025) and the insulin resistance level (r = -0.404, p = 0.024). Dissociation pattern in the default-mode network was found in diabetic patients, which might provide powerful new insights into the neural mechanisms that underlie the diabetes-related cognitive decline. • Type 2 diabetes mellitus is associated with impaired cognition • Default- mode network plays a central role in maintaining normal cognition • Network connectivity within the default mode was disrupted in type 2 diabetes patients • Decreased network connectivity was correlated with cognitive performance and insulin resistance level • Disrupted default-mode network might explain the impaired cognition in diabetic population.

Attractor neural networks with resource-efficient synaptic connectivity

NASA Astrophysics Data System (ADS)

Pehlevan, Cengiz; Sengupta, Anirvan

Memories are thought to be stored in the attractor states of recurrent neural networks. Here we explore how resource constraints interplay with memory storage function to shape synaptic connectivity of attractor networks. We propose that given a set of memories, in the form of population activity patterns, the neural circuit choses a synaptic connectivity configuration that minimizes a resource usage cost. We argue that the total synaptic weight (l1-norm) in the network measures the resource cost because synaptic weight is correlated with synaptic volume, which is a limited resource, and is proportional to neurotransmitter release and post-synaptic current, both of which cost energy. Using numerical simulations and replica theory, we characterize optimal connectivity profiles in resource-efficient attractor networks. Our theory explains several experimental observations on cortical connectivity profiles, 1) connectivity is sparse, because synapses are costly, 2) bidirectional connections are overrepresented and 3) are stronger, because attractor states need strong recurrence.

Correcting for Blood Arrival Time in Global Mean Regression Enhances Functional Connectivity Analysis of Resting State fMRI-BOLD Signals.

PubMed

Erdoğan, Sinem B; Tong, Yunjie; Hocke, Lia M; Lindsey, Kimberly P; deB Frederick, Blaise

2016-01-01

Resting state functional connectivity analysis is a widely used method for mapping intrinsic functional organization of the brain. Global signal regression (GSR) is commonly employed for removing systemic global variance from resting state BOLD-fMRI data; however, recent studies have demonstrated that GSR may introduce spurious negative correlations within and between functional networks, calling into question the meaning of anticorrelations reported between some networks. In the present study, we propose that global signal from resting state fMRI is composed primarily of systemic low frequency oscillations (sLFOs) that propagate with cerebral blood circulation throughout the brain. We introduce a novel systemic noise removal strategy for resting state fMRI data, "dynamic global signal regression" (dGSR), which applies a voxel-specific optimal time delay to the global signal prior to regression from voxel-wise time series. We test our hypothesis on two functional systems that are suggested to be intrinsically organized into anticorrelated networks: the default mode network (DMN) and task positive network (TPN). We evaluate the efficacy of dGSR and compare its performance with the conventional "static" global regression (sGSR) method in terms of (i) explaining systemic variance in the data and (ii) enhancing specificity and sensitivity of functional connectivity measures. dGSR increases the amount of BOLD signal variance being modeled and removed relative to sGSR while reducing spurious negative correlations introduced in reference regions by sGSR, and attenuating inflated positive connectivity measures. We conclude that incorporating time delay information for sLFOs into global noise removal strategies is of crucial importance for optimal noise removal from resting state functional connectivity maps.

Two Distinct Scene-Processing Networks Connecting Vision and Memory.

PubMed

Baldassano, Christopher; Esteva, Andre; Fei-Fei, Li; Beck, Diane M

2016-01-01

A number of regions in the human brain are known to be involved in processing natural scenes, but the field has lacked a unifying framework for understanding how these different regions are organized and interact. We provide evidence from functional connectivity and meta-analyses for a new organizational principle, in which scene processing relies upon two distinct networks that split the classically defined parahippocampal place area (PPA). The first network of strongly connected regions consists of the occipital place area/transverse occipital sulcus and posterior PPA, which contain retinotopic maps and are not strongly coupled to the hippocampus at rest. The second network consists of the caudal inferior parietal lobule, retrosplenial complex, and anterior PPA, which connect to the hippocampus (especially anterior hippocampus), and are implicated in both visual and nonvisual tasks, including episodic memory and navigation. We propose that these two distinct networks capture the primary functional division among scene-processing regions, between those that process visual features from the current view of a scene and those that connect information from a current scene view with a much broader temporal and spatial context. This new framework for understanding the neural substrates of scene-processing bridges results from many lines of research, and makes specific functional predictions.

Reproducibility of resting state spinal cord networks in healthy volunteers at 7 Tesla.

PubMed

Barry, Robert L; Rogers, Baxter P; Conrad, Benjamin N; Smith, Seth A; Gore, John C

2016-06-01

We recently reported our findings of resting state functional connectivity in the human spinal cord: in a cohort of healthy volunteers we observed robust functional connectivity between left and right ventral (motor) horns and between left and right dorsal (sensory) horns (Barry et al., 2014). Building upon these results, we now quantify the within-subject reproducibility of bilateral motor and sensory networks (intraclass correlation coefficient=0.54-0.56) and explore the impact of including frequencies up to 0.13Hz. Our results suggest that frequencies above 0.08Hz may enhance the detectability of these resting state networks, which would be beneficial for practical studies of spinal cord functional connectivity. Copyright © 2016 Elsevier Inc. All rights reserved.

Altered Network Oscillations and Functional Connectivity Dynamics in Children Born Very Preterm.

PubMed

Moiseev, Alexander; Doesburg, Sam M; Herdman, Anthony T; Ribary, Urs; Grunau, Ruth E

2015-09-01

Structural brain connections develop atypically in very preterm children, and altered functional connectivity is also evident in fMRI studies. Such alterations in brain network connectivity are associated with cognitive difficulties in this population. Little is known, however, about electrophysiological interactions among specific brain networks in children born very preterm. In the present study, we recorded magnetoencephalography while very preterm children and full-term controls performed a visual short-term memory task. Regions expressing task-dependent activity changes were identified using beamformer analysis, and inter-regional phase synchrony was calculated. Very preterm children expressed altered regional recruitment in distributed networks of brain areas, across standard physiological frequency ranges including the theta, alpha, beta and gamma bands. Reduced oscillatory synchrony was observed among task-activated brain regions in very preterm children, particularly for connections involving areas critical for executive abilities, including middle frontal gyrus. These findings suggest that inability to recruit neurophysiological activity and interactions in distributed networks including frontal regions may contribute to difficulties in cognitive development in children born very preterm.

Aberrant functional brain connectome in people with antisocial personality disorder

PubMed Central

Tang, Yan; Long, Jun; Wang, Wei; Liao, Jian; Xie, Hua; Zhao, Guihu; Zhang, Hao

2016-01-01

Antisocial personality disorder (ASPD) is characterised by a disregard for social obligations and callous unconcern for the feelings of others. Studies have demonstrated that ASPD is associated with abnormalities in brain regions and aberrant functional connectivity. In this paper, topological organisation was examined in resting-state fMRI data obtained from 32 ASPD patients and 32 non-ASPD controls. The frequency-dependent functional networks were constructed using wavelet-based correlations over 90 brain regions. The topology of the functional networks of ASPD subjects was analysed via graph theoretical analysis. Furthermore, the abnormal functional connectivity was determined with a network-based statistic (NBS) approach. Our results revealed that, compared with the controls, the ASPD patients exhibited altered topological configuration of the functional connectome in the frequency interval of 0.016–0.031 Hz, as indicated by the increased clustering coefficient and decreased betweenness centrality in the medial superior frontal gyrus, precentral gyrus, Rolandic operculum, superior parietal gyrus, angular gyrus, and middle temporal pole. In addition, the ASPD patients showed increased functional connectivity mainly located in the default-mode network. The present study reveals an aberrant topological organisation of the functional brain network in individuals with ASPD. Our findings provide novel insight into the neuropathological mechanisms of ASPD. PMID:27257047

Aberrant functional brain connectome in people with antisocial personality disorder.

PubMed

Tang, Yan; Long, Jun; Wang, Wei; Liao, Jian; Xie, Hua; Zhao, Guihu; Zhang, Hao

2016-06-03

Antisocial personality disorder (ASPD) is characterised by a disregard for social obligations and callous unconcern for the feelings of others. Studies have demonstrated that ASPD is associated with abnormalities in brain regions and aberrant functional connectivity. In this paper, topological organisation was examined in resting-state fMRI data obtained from 32 ASPD patients and 32 non-ASPD controls. The frequency-dependent functional networks were constructed using wavelet-based correlations over 90 brain regions. The topology of the functional networks of ASPD subjects was analysed via graph theoretical analysis. Furthermore, the abnormal functional connectivity was determined with a network-based statistic (NBS) approach. Our results revealed that, compared with the controls, the ASPD patients exhibited altered topological configuration of the functional connectome in the frequency interval of 0.016-0.031 Hz, as indicated by the increased clustering coefficient and decreased betweenness centrality in the medial superior frontal gyrus, precentral gyrus, Rolandic operculum, superior parietal gyrus, angular gyrus, and middle temporal pole. In addition, the ASPD patients showed increased functional connectivity mainly located in the default-mode network. The present study reveals an aberrant topological organisation of the functional brain network in individuals with ASPD. Our findings provide novel insight into the neuropathological mechanisms of ASPD.

Interaction of language, auditory and memory brain networks in auditory verbal hallucinations.

PubMed

Ćurčić-Blake, Branislava; Ford, Judith M; Hubl, Daniela; Orlov, Natasza D; Sommer, Iris E; Waters, Flavie; Allen, Paul; Jardri, Renaud; Woodruff, Peter W; David, Olivier; Mulert, Christoph; Woodward, Todd S; Aleman, André

2017-01-01

Auditory verbal hallucinations (AVH) occur in psychotic disorders, but also as a symptom of other conditions and even in healthy people. Several current theories on the origin of AVH converge, with neuroimaging studies suggesting that the language, auditory and memory/limbic networks are of particular relevance. However, reconciliation of these theories with experimental evidence is missing. We review 50 studies investigating functional (EEG and fMRI) and anatomic (diffusion tensor imaging) connectivity in these networks, and explore the evidence supporting abnormal connectivity in these networks associated with AVH. We distinguish between functional connectivity during an actual hallucination experience (symptom capture) and functional connectivity during either the resting state or a task comparing individuals who hallucinate with those who do not (symptom association studies). Symptom capture studies clearly reveal a pattern of increased coupling among the auditory, language and striatal regions. Anatomical and symptom association functional studies suggest that the interhemispheric connectivity between posterior auditory regions may depend on the phase of illness, with increases in non-psychotic individuals and first episode patients and decreases in chronic patients. Leading hypotheses involving concepts as unstable memories, source monitoring, top-down attention, and hybrid models of hallucinations are supported in part by the published connectivity data, although several caveats and inconsistencies remain. Specifically, possible changes in fronto-temporal connectivity are still under debate. Precise hypotheses concerning the directionality of connections deduced from current theoretical approaches should be tested using experimental approaches that allow for discrimination of competing hypotheses. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

The Hierarchical Brain Network for Face Recognition

PubMed Central

Zhen, Zonglei; Fang, Huizhen; Liu, Jia

2013-01-01

Numerous functional magnetic resonance imaging (fMRI) studies have identified multiple cortical regions that are involved in face processing in the human brain. However, few studies have characterized the face-processing network as a functioning whole. In this study, we used fMRI to identify face-selective regions in the entire brain and then explore the hierarchical structure of the face-processing network by analyzing functional connectivity among these regions. We identified twenty-five regions mainly in the occipital, temporal and frontal cortex that showed a reliable response selective to faces (versus objects) across participants and across scan sessions. Furthermore, these regions were clustered into three relatively independent sub-networks in a face-recognition task on the basis of the strength of functional connectivity among them. The functionality of the sub-networks likely corresponds to the recognition of individual identity, retrieval of semantic knowledge and representation of emotional information. Interestingly, when the task was switched to object recognition from face recognition, the functional connectivity between the inferior occipital gyrus and the rest of the face-selective regions were significantly reduced, suggesting that this region may serve as an entry node in the face-processing network. In sum, our study provides empirical evidence for cognitive and neural models of face recognition and helps elucidate the neural mechanisms underlying face recognition at the network level. PMID:23527282

Cerebellum and Integration of Neural Networks in Dual-Task Processing

PubMed Central

Wu, Tao; Liu, Jun; Hallett, Mark; Zheng, Zheng; Chan, Piu

2014-01-01

Performing two tasks simultaneously (dual-task) is common in human daily life. The neural correlates of dual-task processing remain unclear. In the current study, we used a dual motor and counting task with functional MRI (fMRI) to determine whether there are any areas additionally activated for dual-task performance. Moreover, we investigated the functional connectivity of these added activated areas, as well as the training effect on brain activity and connectivity. We found that the right cerebellar vermis, left lobule V of the cerebellar anterior lobe and precuneus are additionally activated for this type of dual-tasking. These cerebellar regions had functional connectivity with extensive motor- and cognitive-related regions. Dual-task training induced less activation in several areas, but increased the functional connectivity between these cerebellar regions and numbers of motor- and cognitive-related areas. Our findings demonstrate that some regions within the cerebellum can be additionally activated with dual-task performance. Their role in dual motor and cognitive task processes is likely to integrate motor and cognitive networks, and may be involved in adjusting these networks to be more efficient in order to perform dual-tasking properly. The connectivity of the precuneus differs from the cerebellar regions. A possible role of the precuneus in dual-task may be monitoring the operation of active brain networks. PMID:23063842

Brain connectivity aberrations in anabolic-androgenic steroid users.

PubMed

Westlye, Lars T; Kaufmann, Tobias; Alnæs, Dag; Hullstein, Ingunn R; Bjørnebekk, Astrid

2017-01-01

Sustained anabolic-androgenic steroid (AAS) use has adverse behavioral consequences, including aggression, violence and impulsivity. Candidate mechanisms include disruptions of brain networks with high concentrations of androgen receptors and critically involved in emotional and cognitive regulation. Here, we tested the effects of AAS on resting-state functional brain connectivity in the largest sample of AAS-users to date. We collected resting-state functional magnetic resonance imaging (fMRI) data from 151 males engaged in heavy resistance strength training. 50 users tested positive for AAS based on the testosterone to epitestosterone (T/E) ratio and doping substances in urine. 16 previous users and 59 controls tested negative. We estimated brain network nodes and their time-series using ICA and dual regression and defined connectivity matrices as the between-node partial correlations. In line with the emotional and behavioral consequences of AAS, current users exhibited reduced functional connectivity between key nodes involved in emotional and cognitive regulation, in particular reduced connectivity between the amygdala and default-mode network (DMN) and between the dorsal attention network (DAN) and a frontal node encompassing the superior and inferior frontal gyri (SFG/IFG) and the anterior cingulate cortex (ACC), with further reductions as a function of dependency, lifetime exposure, and cycle state (on/off).

Intranetwork and internetwork connectivity in patients with Alzheimer disease and the association with cerebrospinal fluid biomarker levels

PubMed Central

Weiler, Marina; de Campos, Brunno Machado; de Ligo Teixeira, Camila Vieira; Casseb, Raphael Fernandes; Mac Knight Carletti-Cassani, Ana Flávia; Vicentini, Jéssica Elias; Magalhães, Thamires Naela Cardoso; Talib, Leda Leme; Forlenza, Orestes Vicente; Balthazar, Marcio Luiz Figueredo

2017-01-01

Background In the last decade, many studies have reported abnormal connectivity within the default mode network (DMN) in patients with Alzheimer disease. Few studies, however, have investigated other networks and their association with pathophysiological proteins obtained from cerebrospinal fluid (CSF). Methods We performed 3 T imaging in patients with mild Alzheimer disease, patients with amnestic mild cognitive impairment (aMCI) and healthy controls, and we collected CSF samples from the patients with aMCI and mild Alzheimer disease. We analyzed 57 regions from 8 networks. Additionally, we performed correlation tests to investigate possible associations between the networks’ functional connectivity and the protein levels obtained from the CSF of patients with aMCI and Alzheimer disease. Results Our sample included 41 patients with Alzheimer disease, 35 with aMCI and 48 controls. We found that the main connectivity abnormalities in those with Alzheimer disease occurred between the DMN and task-positive networks: these patients presented not only a decreased anticorrelation between some regions, but also an inversion of the correlation signal (positive correlation instead of anti-correlation). Those with aMCI did not present statistically different connectivity from patients with Alzheimer disease or controls. Abnormal levels of CSF proteins were associated with functional disconnectivity between several regions in both the aMCI and mild Alzheimer disease groups, extending well beyond the DMN or temporal areas. Limitations The presented data are cross-sectional in nature, and our findings are dependent on the choice of seed regions used. Conclusion We found that the main functional connectivity abnormalities occur between the DMN and task-positive networks and that the pathological levels of CSF biomarkers correlate with functional connectivity disruption in patients with Alzheimer disease. PMID:28375076

Income change alters default mode network connectivity for adolescents in poverty.

PubMed

Weissman, David G; Conger, Rand D; Robins, Richard W; Hastings, Paul D; Guyer, Amanda E

2018-04-01

Experiencing poverty during childhood and adolescence may affect brain function. However, income is dynamic, and studies have not addressed whether income change relates to brain function. In the present study, we investigated whether intrinsic functional connectivity of default mode network (DMN) regions was influenced by mean family income and family income change. Parents of 68 Mexican-origin adolescents (35 females) reported family income annually when adolescents were 10-16 years old. Intercept and slope of income at each of these ages were calculated for each participant. At age 16 years, adolescents completed a resting state functional neuroimaging scan. Adolescents from high and low income families did not differ in their functional connectivity, but for adolescents in families with lower incomes, their connectivity patterns depended on their income slope. Low-income adolescents whose income increased demonstrated greater connectivity between the posterior cingulate cortex (PCC) and the medial prefrontal cortex (mPFC), both DMN regions, and between the PCC and the right inferior frontal gyrus. Increases in income were associated with greater connectivity of the mPFC with the right inferior frontal gyrus and the left superior parietal lobule regardless of mean income. Increases in income, especially among adolescents in poverty, may alleviate stressors, influencing the development of brain networks. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

Decoupling function and anatomy in atlases of functional connectivity patterns: language mapping in tumor patients.

PubMed

Langs, Georg; Sweet, Andrew; Lashkari, Danial; Tie, Yanmei; Rigolo, Laura; Golby, Alexandra J; Golland, Polina

2014-12-01

In this paper we construct an atlas that summarizes functional connectivity characteristics of a cognitive process from a population of individuals. The atlas encodes functional connectivity structure in a low-dimensional embedding space that is derived from a diffusion process on a graph that represents correlations of fMRI time courses. The functional atlas is decoupled from the anatomical space, and thus can represent functional networks with variable spatial distribution in a population. In practice the atlas is represented by a common prior distribution for the embedded fMRI signals of all subjects. We derive an algorithm for fitting this generative model to the observed data in a population. Our results in a language fMRI study demonstrate that the method identifies coherent and functionally equivalent regions across subjects. The method also successfully maps functional networks from a healthy population used as a training set to individuals whose language networks are affected by tumors. Copyright © 2014. Published by Elsevier Inc.

Decoding Lifespan Changes of the Human Brain Using Resting-State Functional Connectivity MRI

PubMed Central

Wang, Lubin; Su, Longfei; Shen, Hui; Hu, Dewen

2012-01-01

The development of large-scale functional brain networks is a complex, lifelong process that can be investigated using resting-state functional connectivity MRI (rs-fcMRI). In this study, we aimed to decode the developmental dynamics of the whole-brain functional network in seven decades (8–79 years) of the human lifespan. We first used parametric curve fitting to examine linear and nonlinear age effect on the resting human brain, and then combined manifold learning and support vector machine methods to predict individuals' “brain ages” from rs-fcMRI data. We found that age-related changes in interregional functional connectivity exhibited spatially and temporally specific patterns. During brain development from childhood to senescence, functional connections tended to linearly increase in the emotion system and decrease in the sensorimotor system; while quadratic trajectories were observed in functional connections related to higher-order cognitive functions. The complex patterns of age effect on the whole-brain functional network could be effectively represented by a low-dimensional, nonlinear manifold embedded in the functional connectivity space, which uncovered the inherent structure of brain maturation and aging. Regression of manifold coordinates with age further showed that the manifold representation extracted sufficient information from rs-fcMRI data to make prediction about individual brains' functional development levels. Our study not only gives insights into the neural substrates that underlie behavioral and cognitive changes over age, but also provides a possible way to quantitatively describe the typical and atypical developmental progression of human brain function using rs-fcMRI. PMID:22952990

Decoding lifespan changes of the human brain using resting-state functional connectivity MRI.

PubMed

Wang, Lubin; Su, Longfei; Shen, Hui; Hu, Dewen

2012-01-01

The development of large-scale functional brain networks is a complex, lifelong process that can be investigated using resting-state functional connectivity MRI (rs-fcMRI). In this study, we aimed to decode the developmental dynamics of the whole-brain functional network in seven decades (8-79 years) of the human lifespan. We first used parametric curve fitting to examine linear and nonlinear age effect on the resting human brain, and then combined manifold learning and support vector machine methods to predict individuals' "brain ages" from rs-fcMRI data. We found that age-related changes in interregional functional connectivity exhibited spatially and temporally specific patterns. During brain development from childhood to senescence, functional connections tended to linearly increase in the emotion system and decrease in the sensorimotor system; while quadratic trajectories were observed in functional connections related to higher-order cognitive functions. The complex patterns of age effect on the whole-brain functional network could be effectively represented by a low-dimensional, nonlinear manifold embedded in the functional connectivity space, which uncovered the inherent structure of brain maturation and aging. Regression of manifold coordinates with age further showed that the manifold representation extracted sufficient information from rs-fcMRI data to make prediction about individual brains' functional development levels. Our study not only gives insights into the neural substrates that underlie behavioral and cognitive changes over age, but also provides a possible way to quantitatively describe the typical and atypical developmental progression of human brain function using rs-fcMRI.

Altered Structural and Functional Connectivity in Late Preterm Preadolescence: An Anatomic Seed-Based Study of Resting State Networks Related to the Posteromedial and Lateral Parietal Cortex

PubMed Central

Degnan, Andrew J.; Wisnowski, Jessica L.; Choi, SoYoung; Ceschin, Rafael; Bhushan, Chitresh; Leahy, Richard M.; Corby, Patricia; Schmithorst, Vincent J.; Panigrahy, Ashok

2015-01-01

Objective Late preterm birth confers increased risk of developmental delay, academic difficulties and social deficits. The late third trimester may represent a critical period of development of neural networks including the default mode network (DMN), which is essential to normal cognition. Our objective is to identify functional and structural connectivity differences in the posteromedial cortex related to late preterm birth. Methods Thirty-eight preadolescents (ages 9–13; 19 born in the late preterm period (≥32 weeks gestational age) and 19 at term) without access to advanced neonatal care were recruited from a low socioeconomic status community in Brazil. Participants underwent neurocognitive testing, 3-dimensional T1-weighted imaging, diffusion-weighted imaging and resting state functional MRI (RS-fMRI). Seed-based probabilistic diffusion tractography and RS-fMRI analyses were performed using unilateral seeds within the posterior DMN (posterior cingulate cortex, precuneus) and lateral parietal DMN (superior marginal and angular gyri). Results Late preterm children demonstrated increased functional connectivity within the posterior default mode networks and increased anti-correlation with the central-executive network when seeded from the posteromedial cortex (PMC). Key differences were demonstrated between PMC components with increased anti-correlation with the salience network seen only with posterior cingulate cortex seeding but not with precuneus seeding. Probabilistic tractography showed increased streamlines within the right inferior longitudinal fasciculus and inferior fronto-occipital fasciculus within late preterm children while decreased intrahemispheric streamlines were also observed. No significant differences in neurocognitive testing were demonstrated between groups. Conclusion Late preterm preadolescence is associated with altered functional connectivity from the PMC and lateral parietal cortex to known distributed functional cortical networks despite no significant executive neurocognitive differences. Selective increased structural connectivity was observed in the setting of decreased posterior interhemispheric connections. Future work is needed to determine if these findings represent a compensatory adaptation employing alternate neural circuitry or could reflect subtle pathology resulting in emotional processing deficits not seen with neurocognitive testing. PMID:26098888