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.

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.

Functional brain connectivity when cooperation fails.

PubMed

Balconi, Michela; Vanutelli, Maria Elide; Gatti, Laura

2018-06-01

Functional connectivity during cooperative actions is an important topic in social neuroscience that has yet to be answered. Here, we examined the effects of administration of (fictitious) negative social feedback in relation to cooperative capabilities. Cognitive performance and neural activation underlying the execution of joint actions was recorded with functional near-infrared spectroscopy (fNIRS) on prefrontal regions during a task where pairs of participants received negative feedback after their joint action. Performance (error rates (ERs) and response times (RTs)) and intra- and inter-brain connectivity indices were computed, along with the ConIndex (inter-brain/intra-brain connectivity). Finally, correlational measures were considered to assess the relation between these different measures. Results showed that the negative feedback was able to modulate participants' responses for both behavioral and neural components. Cognitive performance was decreased after the feedback. Moreover, decreased inter-brain connectivity and increased intra-brain connectivity was induced by the feedback, whereas the cooperative task pre-feedback condition was able to increase the brain-to-brain coupling, mainly localized within the dorsolateral prefrontal cortex (DLPFC). Finally, the presence of significant correlations between RTs and inter-brain connectivity revealed that ineffective joint action produces the worst cognitive performance and a more 'individual strategy' for brain activity, limiting the inter-brain connectivity. The present study provides a significant contribution to the identification of patterns of intra- and inter-brain functional connectivity when negative social reinforcement is provided in relation to cooperative actions. Copyright © 2018 Elsevier Inc. All rights reserved.

The Human Brainnetome Atlas: A New Brain Atlas Based on Connectional Architecture.

PubMed

Fan, Lingzhong; Li, Hai; Zhuo, Junjie; Zhang, Yu; Wang, Jiaojian; Chen, Liangfu; Yang, Zhengyi; Chu, Congying; Xie, Sangma; Laird, Angela R; Fox, Peter T; Eickhoff, Simon B; Yu, Chunshui; Jiang, Tianzi

2016-08-01

The human brain atlases that allow correlating brain anatomy with psychological and cognitive functions are in transition from ex vivo histology-based printed atlases to digital brain maps providing multimodal in vivo information. Many current human brain atlases cover only specific structures, lack fine-grained parcellations, and fail to provide functionally important connectivity information. Using noninvasive multimodal neuroimaging techniques, we designed a connectivity-based parcellation framework that identifies the subdivisions of the entire human brain, revealing the in vivo connectivity architecture. The resulting human Brainnetome Atlas, with 210 cortical and 36 subcortical subregions, provides a fine-grained, cross-validated atlas and contains information on both anatomical and functional connections. Additionally, we further mapped the delineated structures to mental processes by reference to the BrainMap database. It thus provides an objective and stable starting point from which to explore the complex relationships between structure, connectivity, and function, and eventually improves understanding of how the human brain works. The human Brainnetome Atlas will be made freely available for download at http://atlas.brainnetome.org, so that whole brain parcellations, connections, and functional data will be readily available for researchers to use in their investigations into healthy and pathological states. © The Author 2016. Published by Oxford University Press.

Enhanced functional connectivity and volume between cognitive and reward centers of naïve rodent brain produced by pro-dopaminergic agent KB220Z

PubMed Central

Badgaiyan, Rajendra D.; Thanos, Panayotis K.; Kulkarni, Praveen; Giordano, John; Baron, David; Gold, Mark S.

2017-01-01

Dopaminergic reward dysfunction in addictive behaviors is well supported in the literature. There is evidence that alterations in synchronous neural activity between brain regions subserving reward and various cognitive functions may significantly contribute to substance-related disorders. This study presents the first evidence showing that a pro-dopaminergic nutraceutical (KB220Z) significantly enhances, above placebo, functional connectivity between reward and cognitive brain areas in the rat. These include the nucleus accumbens, anterior cingulate gyrus, anterior thalamic nuclei, hippocampus, prelimbic and infralimbic loci. Significant functional connectivity, increased brain connectivity volume recruitment (potentially neuroplasticity), and dopaminergic functionality were found across the brain reward circuitry. Increases in functional connectivity were specific to these regions and were not broadly distributed across the brain. While these initial findings have been observed in drug naïve rodents, this robust, yet selective response implies clinical relevance for addicted individuals at risk for relapse, who show reductions in functional connectivity after protracted withdrawal. Future studies will evaluate KB220Z in animal models of addiction. PMID:28445527

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.

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

Frontal lobe connectivity and cognitive impairment in pediatric frontal lobe epilepsy.

PubMed

Braakman, Hilde M H; Vaessen, Maarten J; Jansen, Jacobus F A; Debeij-van Hall, Mariette H J A; de Louw, Anton; Hofman, Paul A M; Vles, Johan S H; Aldenkamp, Albert P; Backes, Walter H

2013-03-01

Cognitive impairment is frequent in children with frontal lobe epilepsy (FLE), but its etiology is unknown. With functional magnetic resonance imaging (fMRI), we have explored the relationship between brain activation, functional connectivity, and cognitive functioning in a cohort of pediatric patients with FLE and healthy controls. Thirty-two children aged 8-13 years with FLE of unknown cause and 41 healthy age-matched controls underwent neuropsychological assessment and structural and functional brain MRI. We investigated to which extent brain regions activated in response to a working memory task and assessed functional connectivity between distant brain regions. Data of patients were compared to controls, and patients were grouped as cognitively impaired or unimpaired. Children with FLE showed a global decrease in functional brain connectivity compared to healthy controls, whereas brain activation patterns in children with FLE remained relatively intact. Children with FLE complicated by cognitive impairment typically showed a decrease in frontal lobe connectivity. This decreased frontal lobe connectivity comprised both connections within the frontal lobe as well as connections from the frontal lobe to the parietal lobe, temporal lobe, cerebellum, and basal ganglia. Decreased functional frontal lobe connectivity is associated with cognitive impairment in pediatric FLE. The importance of impairment of functional integrity within the frontal lobe network, as well as its connections to distant areas, provides new insights in the etiology of the broad-range cognitive impairments in children with FLE. Wiley Periodicals, Inc. © 2012 International League Against Epilepsy.

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.

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.

Dynamic Connectivity Patterns in Conscious and Unconscious Brain

PubMed Central

Ma, Yuncong; Hamilton, Christina

2017-01-01

Abstract Brain functional connectivity undergoes dynamic changes from the awake to unconscious states. However, how the dynamics of functional connectivity patterns are linked to consciousness at the behavioral level remains elusive. In this study, we acquired resting-state functional magnetic resonance imaging data during wakefulness and graded levels of consciousness in rats. Data were analyzed using a dynamic approach combining the sliding window method and k-means clustering. Our results demonstrate that whole-brain networks contained several quasi-stable patterns that dynamically recurred from the awake state into anesthetized states. Remarkably, two brain connectivity states with distinct spatial similarity to the structure of anatomical connectivity were strongly biased toward high and low consciousness levels, respectively. These results provide compelling neuroimaging evidence linking the dynamics of whole-brain functional connectivity patterns and states of consciousness at the behavioral level. PMID:27846731

Connectivity and functional profiling of abnormal brain structures in pedophilia

PubMed Central

Poeppl, Timm B.; Eickhoff, Simon B.; Fox, Peter T.; Laird, Angela R.; Rupprecht, Rainer; Langguth, Berthold; Bzdok, Danilo

2015-01-01

Despite its 0.5–1% lifetime prevalence in men and its general societal relevance, neuroimaging investigations in pedophilia are scarce. Preliminary findings indicate abnormal brain structure and function. However, no study has yet linked structural alterations in pedophiles to both connectional and functional properties of the aberrant hotspots. The relationship between morphological alterations and brain function in pedophilia as well as their contribution to its psychopathology thus remain unclear. First, we assessed bimodal connectivity of structurally altered candidate regions using meta-analytic connectivity modeling (MACM) and resting-state correlations employing openly accessible data. We compared the ensuing connectivity maps to the activation likelihood estimation (ALE) maps of a recent quantitative meta-analysis of brain activity during processing of sexual stimuli. Second, we functionally characterized the structurally altered regions employing meta-data of a large-scale neuroimaging database. Candidate regions were functionally connected to key areas for processing of sexual stimuli. Moreover, we found that the functional role of structurally altered brain regions in pedophilia relates to nonsexual emotional as well as neurocognitive and executive functions, previously reported to be impaired in pedophiles. Our results suggest that structural brain alterations affect neural networks for sexual processing by way of disrupted functional connectivity, which may entail abnormal sexual arousal patterns. The findings moreover indicate that structural alterations account for common affective and neurocognitive impairments in pedophilia. The present multi-modal integration of brain structure and function analyses links sexual and nonsexual psychopathology in pedophilia. PMID:25733379

Connectivity and functional profiling of abnormal brain structures in pedophilia.

PubMed

Poeppl, Timm B; Eickhoff, Simon B; Fox, Peter T; Laird, Angela R; Rupprecht, Rainer; Langguth, Berthold; Bzdok, Danilo

2015-06-01

Despite its 0.5-1% lifetime prevalence in men and its general societal relevance, neuroimaging investigations in pedophilia are scarce. Preliminary findings indicate abnormal brain structure and function. However, no study has yet linked structural alterations in pedophiles to both connectional and functional properties of the aberrant hotspots. The relationship between morphological alterations and brain function in pedophilia as well as their contribution to its psychopathology thus remain unclear. First, we assessed bimodal connectivity of structurally altered candidate regions using meta-analytic connectivity modeling (MACM) and resting-state correlations employing openly accessible data. We compared the ensuing connectivity maps to the activation likelihood estimation (ALE) maps of a recent quantitative meta-analysis of brain activity during processing of sexual stimuli. Second, we functionally characterized the structurally altered regions employing meta-data of a large-scale neuroimaging database. Candidate regions were functionally connected to key areas for processing of sexual stimuli. Moreover, we found that the functional role of structurally altered brain regions in pedophilia relates to nonsexual emotional as well as neurocognitive and executive functions, previously reported to be impaired in pedophiles. Our results suggest that structural brain alterations affect neural networks for sexual processing by way of disrupted functional connectivity, which may entail abnormal sexual arousal patterns. The findings moreover indicate that structural alterations account for common affective and neurocognitive impairments in pedophilia. The present multimodal integration of brain structure and function analyses links sexual and nonsexual psychopathology in pedophilia. © 2015 Wiley Periodicals, Inc.

Altered resting-state functional connectivity of the frontal-striatal reward system in social anxiety disorder.

PubMed

Manning, Joshua; Reynolds, Gretchen; Saygin, Zeynep M; Hofmann, Stefan G; Pollack, Mark; Gabrieli, John D E; Whitfield-Gabrieli, Susan

2015-01-01

We investigated differences in the intrinsic functional brain organization (functional connectivity) of the human reward system between healthy control participants and patients with social anxiety disorder. Functional connectivity was measured in the resting-state via functional magnetic resonance imaging (fMRI). 53 patients with social anxiety disorder and 33 healthy control participants underwent a 6-minute resting-state fMRI scan. Functional connectivity of the reward system was analyzed by calculating whole-brain temporal correlations with a bilateral nucleus accumbens seed and a ventromedial prefrontal cortex seed. Patients with social anxiety disorder, relative to the control group, had (1) decreased functional connectivity between the nucleus accumbens seed and other regions associated with reward, including ventromedial prefrontal cortex; (2) decreased functional connectivity between the ventromedial prefrontal cortex seed and lateral prefrontal regions, including the anterior and dorsolateral prefrontal cortices; and (3) increased functional connectivity between both the nucleus accumbens seed and the ventromedial prefrontal cortex seed with more posterior brain regions, including anterior cingulate cortex. Social anxiety disorder appears to be associated with widespread differences in the functional connectivity of the reward system, including markedly decreased functional connectivity between reward regions and between reward regions and lateral prefrontal cortices, and markedly increased functional connectivity between reward regions and posterior brain regions.

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.

Measuring Brain Connectivity: Diffusion Tensor Imaging Validates Resting State Temporal Correlations

PubMed Central

Skudlarski, Pawel; Jagannathan, Kanchana; Calhoun, Vince D.; Hampson, Michelle; Skudlarska, Beata A.; Pearlson, Godfrey

2015-01-01

Diffusion tensor imaging (DTI) and resting state temporal correlations (RSTC) are two leading techniques for investigating the connectivity of the human brain. They have been widely used to investigate the strength of anatomical and functional connections between distant brain regions in healthy subjects, and in clinical populations. Though they are both based on magnetic resonance imaging (MRI) they have not yet been compared directly. In this work both techniques were employed to create global connectivity matrices covering the whole brain gray matter. This allowed for direct comparisons between functional connectivity measured by RSTC with anatomical connectivity quantified using DTI tractography. We found that connectivity matrices obtained using both techniques showed significant agreement. Connectivity maps created for a priori defined anatomical regions showed significant correlation, and furthermore agreement was especially high in regions showing strong overall connectivity, such as those belonging to the default mode network. Direct comparison between functional RSTC and anatomical DTI connectivity, presented here for the first time, links two powerful approaches for investigating brain connectivity and shows their strong agreement. It provides a crucial multi-modal validation for resting state correlations as representing neuronal connectivity. The combination of both techniques presented here allows for further combining them to provide richer representation of brain connectivity both in the healthy brain and in clinical conditions. PMID:18771736

Measuring brain connectivity: diffusion tensor imaging validates resting state temporal correlations.

PubMed

Skudlarski, Pawel; Jagannathan, Kanchana; Calhoun, Vince D; Hampson, Michelle; Skudlarska, Beata A; Pearlson, Godfrey

2008-11-15

Diffusion tensor imaging (DTI) and resting state temporal correlations (RSTC) are two leading techniques for investigating the connectivity of the human brain. They have been widely used to investigate the strength of anatomical and functional connections between distant brain regions in healthy subjects, and in clinical populations. Though they are both based on magnetic resonance imaging (MRI) they have not yet been compared directly. In this work both techniques were employed to create global connectivity matrices covering the whole brain gray matter. This allowed for direct comparisons between functional connectivity measured by RSTC with anatomical connectivity quantified using DTI tractography. We found that connectivity matrices obtained using both techniques showed significant agreement. Connectivity maps created for a priori defined anatomical regions showed significant correlation, and furthermore agreement was especially high in regions showing strong overall connectivity, such as those belonging to the default mode network. Direct comparison between functional RSTC and anatomical DTI connectivity, presented here for the first time, links two powerful approaches for investigating brain connectivity and shows their strong agreement. It provides a crucial multi-modal validation for resting state correlations as representing neuronal connectivity. The combination of both techniques presented here allows for further combining them to provide richer representation of brain connectivity both in the healthy brain and in clinical conditions.

Connectivity dynamics in typical development and its relationship to autistic traits and autism spectrum disorder.

PubMed

Rashid, Barnaly; Blanken, Laura M E; Muetzel, Ryan L; Miller, Robyn; Damaraju, Eswar; Arbabshirani, Mohammad R; Erhardt, Erik B; Verhulst, Frank C; van der Lugt, Aad; Jaddoe, Vincent W V; Tiemeier, Henning; White, Tonya; Calhoun, Vince

2018-03-30

Recent advances in neuroimaging techniques have provided significant insights into developmental trajectories of human brain function. Characterizations of typical neurodevelopment provide a framework for understanding altered neurodevelopment, including differences in brain function related to developmental disorders and psychopathology. Historically, most functional connectivity studies of typical and atypical development operate under the assumption that connectivity remains static over time. We hypothesized that relaxing stationarity assumptions would reveal novel features of both typical brain development related to children on the autism spectrum. We employed a "chronnectomic" (recurring, time-varying patterns of connectivity) approach to evaluate transient states of connectivity using resting-state functional MRI in a population-based sample of 774 6- to 10-year-old children. Dynamic connectivity was evaluated using a sliding-window approach, and revealed four transient states. Internetwork connectivity increased with age in modularized dynamic states, illustrating an important pattern of connectivity in the developing brain. Furthermore, we demonstrated that higher levels of autistic traits and ASD diagnosis were associated with longer dwell times in a globally disconnected state. These results provide a roadmap to the chronnectomic organization of the developing brain and suggest that characteristics of functional brain connectivity are related to children on the autism spectrum. © 2018 Wiley Periodicals, Inc.

A probabilistic framework to infer brain functional connectivity from anatomical connections.

PubMed

Deligianni, Fani; Varoquaux, Gael; Thirion, Bertrand; Robinson, Emma; Sharp, David J; Edwards, A David; Rueckert, Daniel

2011-01-01

We present a novel probabilistic framework to learn across several subjects a mapping from brain anatomical connectivity to functional connectivity, i.e. the covariance structure of brain activity. This prediction problem must be formulated as a structured-output learning task, as the predicted parameters are strongly correlated. We introduce a model selection framework based on cross-validation with a parametrization-independent loss function suitable to the manifold of covariance matrices. Our model is based on constraining the conditional independence structure of functional activity by the anatomical connectivity. Subsequently, we learn a linear predictor of a stationary multivariate autoregressive model. This natural parameterization of functional connectivity also enforces the positive-definiteness of the predicted covariance and thus matches the structure of the output space. Our results show that functional connectivity can be explained by anatomical connectivity on a rigorous statistical basis, and that a proper model of functional connectivity is essential to assess this link.

State-Dependent Changes of Connectivity Patterns and Functional Brain Network Topology in Autism Spectrum Disorder

ERIC Educational Resources Information Center

Barttfeld, Pablo; Wicker, Bruno; Cukier, Sebastian; Navarta, Silvana; Lew, Sergio; Leiguarda, Ramon; Sigman, Mariano

2012-01-01

Anatomical and functional brain studies have converged to the hypothesis that autism spectrum disorders (ASD) are associated with atypical connectivity. Using a modified resting-state paradigm to drive subjects' attention, we provide evidence of a very marked interaction between ASD brain functional connectivity and cognitive state. We show that…

Multivariate Heteroscedasticity Models for Functional Brain Connectivity.

PubMed

Seiler, Christof; Holmes, Susan

2017-01-01

Functional brain connectivity is the co-occurrence of brain activity in different areas during resting and while doing tasks. The data of interest are multivariate timeseries measured simultaneously across brain parcels using resting-state fMRI (rfMRI). We analyze functional connectivity using two heteroscedasticity models. Our first model is low-dimensional and scales linearly in the number of brain parcels. Our second model scales quadratically. We apply both models to data from the Human Connectome Project (HCP) comparing connectivity between short and conventional sleepers. We find stronger functional connectivity in short than conventional sleepers in brain areas consistent with previous findings. This might be due to subjects falling asleep in the scanner. Consequently, we recommend the inclusion of average sleep duration as a covariate to remove unwanted variation in rfMRI studies. A power analysis using the HCP data shows that a sample size of 40 detects 50% of the connectivity at a false discovery rate of 20%. We provide implementations using R and the probabilistic programming language Stan.

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.

In vivo Visuotopic Brain Mapping with Manganese-Enhanced MRI and Resting-State Functional Connectivity MRI

PubMed Central

Chan, Kevin C.; Fan, Shu-Juan; Chan, Russell W.; Cheng, Joe S.; Zhou, Iris Y.; Wu, Ed X.

2014-01-01

The rodents are an increasingly important model for understanding the mechanisms of development, plasticity, functional specialization and disease in the visual system. However, limited tools have been available for assessing the structural and functional connectivity of the visual brain network globally, in vivo and longitudinally. There are also ongoing debates on whether functional brain connectivity directly reflects structural brain connectivity. In this study, we explored the feasibility of manganese-enhanced MRI (MEMRI) via 3 different routes of Mn2+ administration for visuotopic brain mapping and understanding of physiological transport in normal and visually deprived adult rats. In addition, resting-state functional connectivity MRI (RSfcMRI) was performed to evaluate the intrinsic functional network and structural-functional relationships in the corresponding anatomical visual brain connections traced by MEMRI. Upon intravitreal, subcortical, and intracortical Mn2+ injection, different topographic and layer-specific Mn enhancement patterns could be revealed in the visual cortex and subcortical visual nuclei along retinal, callosal, cortico-subcortical, transsynaptic and intracortical horizontal connections. Loss of visual input upon monocular enucleation to adult rats appeared to reduce interhemispheric polysynaptic Mn2+ transfer but not intra- or inter-hemispheric monosynaptic Mn2+ transport after Mn2+ injection into visual cortex. In normal adults, both structural and functional connectivity by MEMRI and RSfcMRI was stronger interhemispherically between bilateral primary/secondary visual cortex (V1/V2) transition zones (TZ) than between V1/V2 TZ and other cortical nuclei. Intrahemispherically, structural and functional connectivity was stronger between visual cortex and subcortical visual nuclei than between visual cortex and other subcortical nuclei. The current results demonstrated the sensitivity of MEMRI and RSfcMRI for assessing the neuroarchitecture, neurophysiology and structural-functional relationships of the visual brains in vivo. These may possess great potentials for effective monitoring and understanding of the basic anatomical and functional connections in the visual system during development, plasticity, disease, pharmacological interventions and genetic modifications in future studies. PMID:24394694

Joint brain connectivity estimation from diffusion and functional MRI data

NASA Astrophysics Data System (ADS)

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

2015-03-01

Estimating brain wiring patterns is critical to better understand the brain organization and function. Anatomical brain connectivity models axonal pathways, while the functional brain connectivity characterizes the statistical dependencies and correlation between the activities of various brain regions. The synchronization of brain activity can be inferred through the variation of blood-oxygen-level dependent (BOLD) signal from functional MRI (fMRI) and the neural connections can be estimated using tractography from diffusion MRI (dMRI). Functional connections between brain regions are supported by anatomical connections, and the synchronization of brain activities arises through sharing of information in the form of electro-chemical signals on axon pathways. Jointly modeling fMRI and dMRI data may improve the accuracy in constructing anatomical connectivity as well as functional connectivity. Such an approach may lead to novel multimodal biomarkers potentially able to better capture functional and anatomical connectivity variations. We present a novel brain network model which jointly models the dMRI and fMRI data to improve the anatomical connectivity estimation and extract the anatomical subnetworks associated with specific functional modes by constraining the anatomical connections as structural supports to the functional connections. The key idea is similar to a multi-commodity flow optimization problem that minimizes the cost or maximizes the efficiency for flow configuration and simultaneously fulfills the supply-demand constraint for each commodity. In the proposed network, the nodes represent the grey matter (GM) regions providing brain functionality, and the links represent white matter (WM) fiber bundles connecting those regions and delivering information. The commodities can be thought of as the information corresponding to brain activity patterns as obtained for instance by independent component analysis (ICA) of fMRI data. The concept of information flow is introduced and used to model the propagation of information between GM areas through WM fiber bundles. The link capacity, i.e., ability to transfer information, is characterized by the relative strength of fiber bundles, e.g., fiber count gathered from the tractography of dMRI data. The node information demand is considered to be proportional to the correlation between neural activity at various cortical areas involved in a particular functional mode (e.g. visual, motor, etc.). These two properties lead to the link capacity and node demand constraints in the proposed model. Moreover, the information flow of a link cannot exceed the demand from either end node. This is captured by the feasibility constraints. Two different cost functions are considered in the optimization formulation in this paper. The first cost function, the reciprocal of fiber strength represents the unit cost for information passing through the link. In the second cost function, a min-max (minimizing the maximal link load) approach is used to balance the usage of each link. Optimizing the first cost function selects the pathway with strongest fiber strength for information propagation. In the second case, the optimization procedure finds all the possible propagation pathways and allocates the flow proportionally to their strength. Additionally, a penalty term is incorporated with both the cost functions to capture the possible missing and weak anatomical connections. With this set of constraints and the proposed cost functions, solving the network optimization problem recovers missing and weak anatomical connections supported by the functional information and provides the functional-associated anatomical subnetworks. Feasibility is demonstrated using realistic diffusion and functional MRI phantom data. It is shown that the proposed model recovers the maximum number of true connections, with fewest number of false connections when compared with the connectivity derived from a joint probabilistic model using the expectation-maximization (EM) algorithm presented in a prior work. We also apply the proposed method to data provided by the Human Connectome Project (HCP).

Functional connectivity in the mouse brain imaged by B-mode photoacoustic microscopy

NASA Astrophysics Data System (ADS)

Nasiriavanaki, Mohammadreza; Xing, Wenxin; Xia, Jun; Wang, Lihong V.

2014-03-01

The increasing use of mouse models for human brain disease studies, coupled with the fact that existing functional imaging modalities cannot be easily applied to mice, presents an emerging need for a new functional imaging modality. Utilizing acoustic-resolution photoacoustic microscopy (AR-PAM), we imaged spontaneous cerebral hemodynamic fluctuations and their associated functional connections in the mouse brain. The images were acquired noninvasively in B-scan mode with a fast frame rate, a large field of view, and a high spatial resolution. At a location relative to the bregma 0, correlations were investigated inter-hemispherically between bilaterally homologous regions, as well as intra-hemispherically within the same functional regions. The functional connectivity in different functional regions was studied. The locations of these regions agreed well with the Paxinos mouse brain atlas. The functional connectivity map obtained in this study can then be used in the investigation of brain disorders such as stroke, Alzheimer's, schizophrenia, multiple sclerosis, autism, and epilepsy. Our experiments show that photoacoustic microscopy is capable to detect connectivities between different functional regions in B-scan mode, promising a powerful functional imaging modality for future brain research.

A resting state functional magnetic resonance imaging study of concussion in collegiate athletes.

PubMed

Czerniak, Suzanne M; Sikoglu, Elif M; Liso Navarro, Ana A; McCafferty, Joseph; Eisenstock, Jordan; Stevenson, J Herbert; King, Jean A; Moore, Constance M

2015-06-01

Sports-related concussions are currently diagnosed through multi-domain assessment by a medical professional and may utilize neurocognitive testing as an aid. However, these tests have only been able to detect differences in the days to week post-concussion. Here, we investigate a measure of brain function, namely resting state functional connectivity, which may detect residual brain differences in the weeks to months after concussion. Twenty-one student athletes (9 concussed within 6 months of enrollment; 12 non-concussed; between ages 18 and 22 years) were recruited for this study. All participants completed the Wisconsin Card Sorting Task and the Color-Word Interference Test. Neuroimaging data, specifically resting state functional Magnetic Resonance Imaging data, were acquired to examine resting state functional connectivity. Two sample t-tests were used to compare the neurocognitive scores and resting state functional connectivity patterns among concussed and non-concussed participants. Correlations between neurocognitive scores and resting state functional connectivity measures were also determined across all subjects. There were no significant differences in neurocognitive performance between concussed and non-concussed groups. Concussed subjects had significantly increased connections between areas of the brain that underlie executive function. Across all subjects, better neurocognitive performance corresponded to stronger brain connectivity. Even at rest, brains of concussed athletes may have to 'work harder' than their healthy peers to achieve similar neurocognitive results. Resting state brain connectivity may be able to detect prolonged brain differences in concussed athletes in a more quantitative manner than neurocognitive test scores.

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.

Abnormal rich club organization and functional brain dynamics in schizophrenia.

PubMed

van den Heuvel, Martijn P; Sporns, Olaf; Collin, Guusje; Scheewe, Thomas; Mandl, René C W; Cahn, Wiepke; Goñi, Joaquín; Hulshoff Pol, Hilleke E; Kahn, René S

2013-08-01

The human brain forms a large-scale structural network of regions and interregional pathways. Recent studies have reported the existence of a selective set of highly central and interconnected hub regions that may play a crucial role in the brain's integrative processes, together forming a central backbone for global brain communication. Abnormal brain connectivity may have a key role in the pathophysiology of schizophrenia. To examine the structure of the rich club in schizophrenia and its role in global functional brain dynamics. Structural diffusion tensor imaging and resting-state functional magnetic resonance imaging were performed in patients with schizophrenia and matched healthy controls. Department of Psychiatry, Rudolf Magnus Institute of Neuroscience, University Medical Center Utrecht, Utrecht, the Netherlands. Forty-eight patients and 45 healthy controls participated in the study. An independent replication data set of 41 patients and 51 healthy controls was included to replicate and validate significant findings. MAIN OUTCOME(S) AND MEASURES: Measures of rich club organization, connectivity density of rich club connections and connections linking peripheral regions to brain hubs, measures of global brain network efficiency, and measures of coupling between brain structure and functional dynamics. Rich club organization between high-degree hub nodes was significantly affected in patients, together with a reduced density of rich club connections predominantly comprising the white matter pathways that link the midline frontal, parietal, and insular hub regions. This reduction in rich club density was found to be associated with lower levels of global communication capacity, a relationship that was absent for other white matter pathways. In addition, patients had an increase in the strength of structural connectivity-functional connectivity coupling. Our findings provide novel biological evidence that schizophrenia is characterized by a selective disruption of brain connectivity among central hub regions of the brain, potentially leading to reduced communication capacity and altered functional brain dynamics.

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

Brain hyperconnectivity in children with autism and its links to social deficits.

PubMed

Supekar, Kaustubh; Uddin, Lucina Q; Khouzam, Amirah; Phillips, Jennifer; Gaillard, William D; Kenworthy, Lauren E; Yerys, Benjamin E; Vaidya, Chandan J; Menon, Vinod

2013-11-14

Autism spectrum disorder (ASD), a neurodevelopmental disorder affecting nearly 1 in 88 children, is thought to result from aberrant brain connectivity. Remarkably, there have been no systematic attempts to characterize whole-brain connectivity in children with ASD. Here, we use neuroimaging to show that there are more instances of greater functional connectivity in the brains of children with ASD in comparison to those of typically developing children. Hyperconnectivity in ASD was observed at the whole-brain and subsystems levels, across long- and short-range connections, and was associated with higher levels of fluctuations in regional brain signals. Brain hyperconnectivity predicted symptom severity in ASD, such that children with greater functional connectivity exhibited more severe social deficits. We replicated these findings in two additional independent cohorts, demonstrating again that at earlier ages, the brain of children with ASD is largely functionally hyperconnected in ways that contribute to social dysfunction. Our findings provide unique insights into brain mechanisms underlying childhood autism. Copyright © 2013 The Authors. Published by Elsevier Inc. All rights reserved.

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.

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.

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.

The Anatomical Distance of Functional Connections Predicts Brain Network Topology in Health and Schizophrenia

PubMed Central

Vértes, Petra E.; Stidd, Reva; Lalonde, François; Clasen, Liv; Rapoport, Judith; Giedd, Jay; Bullmore, Edward T.; Gogtay, Nitin

2013-01-01

The human brain is a topologically complex network embedded in anatomical space. Here, we systematically explored relationships between functional connectivity, complex network topology, and anatomical (Euclidean) distance between connected brain regions, in the resting-state functional magnetic resonance imaging brain networks of 20 healthy volunteers and 19 patients with childhood-onset schizophrenia (COS). Normal between-subject differences in average distance of connected edges in brain graphs were strongly associated with variation in topological properties of functional networks. In addition, a club or subset of connector hubs was identified, in lateral temporal, parietal, dorsal prefrontal, and medial prefrontal/cingulate cortical regions. In COS, there was reduced strength of functional connectivity over short distances especially, and therefore, global mean connection distance of thresholded graphs was significantly greater than normal. As predicted from relationships between spatial and topological properties of normal networks, this disorder-related proportional increase in connection distance was associated with reduced clustering and modularity and increased global efficiency of COS networks. Between-group differences in connection distance were localized specifically to connector hubs of multimodal association cortex. In relation to the neurodevelopmental pathogenesis of schizophrenia, we argue that the data are consistent with the interpretation that spatial and topological disturbances of functional network organization could arise from excessive “pruning” of short-distance functional connections in schizophrenia. PMID:22275481

IMAGING OF BRAIN FUNCTION BASED ON THE ANALYSIS OF FUNCTIONAL CONNECTIVITY - IMAGING ANALYSIS OF BRAIN FUNCTION BY FMRI AFTER ACUPUNCTURE AT LR3 IN HEALTHY INDIVIDUALS.

PubMed

Zheng, Yu; Wang, Yuying; Lan, Yujun; Qu, Xiaodong; Lin, Kelin; Zhang, Jiping; Qu, Shanshan; Wang, Yanjie; Tang, Chunzhi; Huang, Yong

2016-01-01

This Study observed the relevant brain areas activated by acupuncture at the Taichong acupoint (LR3) and analyzed the functional connectivity among brain areas using resting state functional magnetic resonance imaging (fMRI) to explore the acupoint specificity of the Taichong acupoint. A total of 45 healthy subjects were randomly divided into the Taichong (LR3) group, sham acupuncture group and sham acupoint group. Subjects received resting state fMRI before acupuncture, after true (sham) acupuncture in each group. Analysis of changes in connectivity among the brain areas was performed using the brain functional connectivity method. The right cerebrum temporal lobe was selected as the seed point to analyze the functional connectivity. It had a functional connectivity with right cerebrum superior frontal gyrus, limbic lobe cingulate gyrus and left cerebrum inferior temporal gyrus (BA 37), inferior parietal lobule compared by before vs. after acupuncture at LR3, and right cerebrum sub-lobar insula and left cerebrum middle frontal gyrus, medial frontal gyrus compared by true vs. sham acupuncture at LR3, and right cerebrum occipital lobe cuneus, occipital lobe sub-gyral, parietal lobe precuneus and left cerebellum anterior lobe culmen by acupuncture at LR3 vs. sham acupoint. Acupuncture at LR3 mainly specifically activated the brain functional network that participates in visual function, associative function, and emotion cognition, which are similar to the features on LR3 in tradition Chinese medicine. These brain areas constituted a neural network structure with specific functions that had specific reference values for the interpretation of the acupoint specificity of the Taichong acupoint.

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

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

Prediction of individual brain maturity using fMRI.

PubMed

Dosenbach, Nico U F; Nardos, Binyam; Cohen, Alexander L; Fair, Damien A; Power, Jonathan D; Church, Jessica A; Nelson, Steven M; Wig, Gagan S; Vogel, Alecia C; Lessov-Schlaggar, Christina N; Barnes, Kelly Anne; Dubis, Joseph W; Feczko, Eric; Coalson, Rebecca S; Pruett, John R; Barch, Deanna M; Petersen, Steven E; Schlaggar, Bradley L

2010-09-10

Group functional connectivity magnetic resonance imaging (fcMRI) studies have documented reliable changes in human functional brain maturity over development. Here we show that support vector machine-based multivariate pattern analysis extracts sufficient information from fcMRI data to make accurate predictions about individuals' brain maturity across development. The use of only 5 minutes of resting-state fcMRI data from 238 scans of typically developing volunteers (ages 7 to 30 years) allowed prediction of individual brain maturity as a functional connectivity maturation index. The resultant functional maturation curve accounted for 55% of the sample variance and followed a nonlinear asymptotic growth curve shape. The greatest relative contribution to predicting individual brain maturity was made by the weakening of short-range functional connections between the adult brain's major functional networks.

Disrupted Cerebro-cerebellar Intrinsic Functional Connectivity in Young Adults with High-functioning Autism Spectrum Disorder: A Data-driven, Whole-brain, High Temporal Resolution fMRI Study.

PubMed

Arnold Anteraper, Sheeba; Guell, Xavier; D'Mello, Anila; Joshi, Neha; Whitfield-Gabrieli, Susan; Joshi, Gagan

2018-06-13

To examine the resting-state functional-connectivity (RsFc) in young adults with high-functioning autism spectrum disorder (HF-ASD) using state-of-the-art fMRI data acquisition and analysis techniques. Simultaneous multi-slice, high temporal resolution fMRI acquisition; unbiased whole-brain connectome-wide multivariate pattern analysis (MVPA) techniques for assessing RsFc; and post-hoc whole-brain seed-to-voxel analyses using MVPA results as seeds. MVPA revealed two clusters of abnormal connectivity in the cerebellum. Whole-brain seed-based functional connectivity analyses informed by MVPA-derived clusters showed significant under connectivity between the cerebellum and social, emotional, and language brain regions in the HF-ASD group compared to healthy controls. The results we report are coherent with existing structural, functional, and RsFc literature in autism, extend previous literature reporting cerebellar abnormalities in the neuropathology of autism, and highlight the cerebellum as a potential target for therapeutic, diagnostic, predictive, and prognostic developments in ASD. The description of functional connectivity abnormalities using whole-brain, data-driven analyses as reported in the present study may crucially advance the development of ASD biomarkers, targets for therapeutic interventions, and neural predictors for measuring treatment response.

The mean-variance relationship reveals two possible strategies for dynamic brain connectivity analysis in fMRI.

PubMed

Thompson, William H; Fransson, Peter

2015-01-01

When studying brain connectivity using fMRI, signal intensity time-series are typically correlated with each other in time to compute estimates of the degree of interaction between different brain regions and/or networks. In the static connectivity case, the problem of defining which connections that should be considered significant in the analysis can be addressed in a rather straightforward manner by a statistical thresholding that is based on the magnitude of the correlation coefficients. More recently, interest has come to focus on the dynamical aspects of brain connectivity and the problem of deciding which brain connections that are to be considered relevant in the context of dynamical changes in connectivity provides further options. Since we, in the dynamical case, are interested in changes in connectivity over time, the variance of the correlation time-series becomes a relevant parameter. In this study, we discuss the relationship between the mean and variance of brain connectivity time-series and show that by studying the relation between them, two conceptually different strategies to analyze dynamic functional brain connectivity become available. Using resting-state fMRI data from a cohort of 46 subjects, we show that the mean of fMRI connectivity time-series scales negatively with its variance. This finding leads to the suggestion that magnitude- versus variance-based thresholding strategies will induce different results in studies of dynamic functional brain connectivity. Our assertion is exemplified by showing that the magnitude-based strategy is more sensitive to within-resting-state network (RSN) connectivity compared to between-RSN connectivity whereas the opposite holds true for a variance-based analysis strategy. The implications of our findings for dynamical functional brain connectivity studies are discussed.

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.

Anomalous brain functional connectivity contributing to poor adaptive behavior in Down syndrome.

PubMed

Pujol, Jesus; del Hoyo, Laura; Blanco-Hinojo, Laura; de Sola, Susana; Macià, Dídac; Martínez-Vilavella, Gerard; Amor, Marta; Deus, Joan; Rodríguez, Joan; Farré, Magí; Dierssen, Mara; de la Torre, Rafael

2015-03-01

Research in Down syndrome has substantially progressed in the understanding of the effect of gene overexpression at the molecular level, but there is a paucity of information on the ultimate consequences on overall brain functional organization. We have assessed the brain functional status in Down syndrome using functional connectivity MRI. Resting-state whole-brain connectivity degree maps were generated in 20 Down syndrome individuals and 20 control subjects to identify sites showing anomalous synchrony with other areas. A subsequent region-of-interest mapping served to detail the anomalies and to assess their potential contribution to poor adaptive behavior. Down syndrome individuals showed higher regional connectivity in a ventral brain system involving the amygdala/anterior temporal region and the ventral aspect of both the anterior cingulate and frontal cortices. By contrast, lower functional connectivity was identified in dorsal executive networks involving dorsal prefrontal and anterior cingulate cortices and posterior insula. Both functional connectivity increases and decreases contributed to account for patient scoring on adaptive behavior related to communication skills. The data overall suggest a distinctive functional organization with system-specific anomalies associated with reduced adaptive efficiency. Opposite effects were identified on distinct frontal and anterior temporal structures and relative sparing of posterior brain areas, which is generally consistent with Down syndrome cognitive profile. Relevantly, measurable connectivity changes, as a marker of the brain functional anomaly, could have a role in the development of therapeutic strategies addressed to improve the quality of life in Down syndrome individuals. Copyright © 2014 Elsevier Ltd. All rights reserved.

Defining functional SMA and pre-SMA subregions in human MFC using resting state fMRI: functional connectivity-based parcellation method.

PubMed

Kim, Jae-Hun; Lee, Jong-Min; Jo, Hang Joon; Kim, Sook Hui; Lee, Jung Hee; Kim, Sung Tae; Seo, Sang Won; Cox, Robert W; Na, Duk L; Kim, Sun I; Saad, Ziad S

2010-02-01

Noninvasive parcellation of the human cerebral cortex is an important goal for understanding and examining brain functions. Recently, the patterns of anatomical connections using diffusion tensor imaging (DTI) have been used to parcellate brain regions. Here, we present a noninvasive parcellation approach that uses "functional fingerprints" obtained by correlation measures on resting state functional magnetic resonance imaging (fMRI) data to parcellate brain regions. In other terms, brain regions are parcellated based on the similarity of their connection--as reflected by correlation during resting state--to the whole brain. The proposed method was used to parcellate the medial frontal cortex (MFC) into supplementary motor areas (SMA) and pre-SMA subregions. In agreement with anatomical landmark-based parcellation, we find that functional fingerprint clustering of the MFC results in anterior and posterior clusters. The probabilistic maps from 12 subjects showed that the anterior cluster is mainly located rostral to the vertical commissure anterior (VCA) line, whereas the posterior cluster is mainly located caudal to VCA line, suggesting the homologues of pre-SMA and SMA. The functional connections from the putative pre-SMA cluster were connected to brain regions which are responsible for complex/cognitive motor control, whereas those from the putative SMA cluster were connected to brain regions which are related to the simple motor control. These findings demonstrate the feasibility of the functional connectivity-based parcellation of the human cerebral cortex using resting state fMRI. Copyright (c) 2009 Elsevier Inc. All rights reserved.

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

Assessing dynamic brain graphs of time-varying connectivity in fMRI data: application to healthy controls and patients with schizophrenia

PubMed Central

Yu, Qingbao; Erhardt, Erik B.; Sui, Jing; Du, Yuhui; He, Hao; Hjelm, Devon; Cetin, Mustafa S.; Rachakonda, Srinivas; Miller, Robyn L.; Pearlson, Godfrey; Calhoun, Vince D.

2014-01-01

Graph theory-based analysis has been widely employed in brain imaging studies, and altered topological properties of brain connectivity have emerged as important features of mental diseases such as schizophrenia. However, most previous studies have focused on graph metrics of stationary brain graphs, ignoring that brain connectivity exhibits fluctuations over time. Here we develop a new framework for accessing dynamic graph properties of time-varying functional brain connectivity in resting state fMRI data and apply it to healthy controls (HCs) and patients with schizophrenia (SZs). Specifically, nodes of brain graphs are defined by intrinsic connectivity networks (ICNs) identified by group independent component analysis (ICA). Dynamic graph metrics of the time-varying brain connectivity estimated by the correlation of sliding time-windowed ICA time courses of ICNs are calculated. First- and second-level connectivity states are detected based on the correlation of nodal connectivity strength between time-varying brain graphs. Our results indicate that SZs show decreased variance in the dynamic graph metrics. Consistent with prior stationary functional brain connectivity works, graph measures of identified first-level connectivity states show lower values in SZs. In addition, more first-level connectivity states are disassociated with the second-level connectivity state which resembles the stationary connectivity pattern computed by the entire scan. Collectively, the findings provide new evidence about altered dynamic brain graphs in schizophrenia which may underscore the abnormal brain performance in this mental illness. PMID:25514514

Graph analysis of functional brain networks for cognitive control of action in traumatic brain injury.

PubMed

Caeyenberghs, Karen; Leemans, Alexander; Heitger, Marcus H; Leunissen, Inge; Dhollander, Thijs; Sunaert, Stefan; Dupont, Patrick; Swinnen, Stephan P

2012-04-01

Patients with traumatic brain injury show clear impairments in behavioural flexibility and inhibition that often persist beyond the time of injury, affecting independent living and psychosocial functioning. Functional magnetic resonance imaging studies have shown that patients with traumatic brain injury typically show increased and more broadly dispersed frontal and parietal activity during performance of cognitive control tasks. We constructed binary and weighted functional networks and calculated their topological properties using a graph theoretical approach. Twenty-three adults with traumatic brain injury and 26 age-matched controls were instructed to switch between coordination modes while making spatially and temporally coupled circular motions with joysticks during event-related functional magnetic resonance imaging. Results demonstrated that switching performance was significantly lower in patients with traumatic brain injury compared with control subjects. Furthermore, although brain networks of both groups exhibited economical small-world topology, altered functional connectivity was demonstrated in patients with traumatic brain injury. In particular, compared with controls, patients with traumatic brain injury showed increased connectivity degree and strength, and higher values of local efficiency, suggesting adaptive mechanisms in this group. Finally, the degree of increased connectivity was significantly correlated with poorer switching task performance and more severe brain injury. We conclude that analysing the functional brain network connectivity provides new insights into understanding cognitive control changes following brain injury.

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

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.

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

Strong Functional Connectivity among Homotopic Brain Areas Is Vital for Motor Control in Unilateral Limb Movement.

PubMed

Wei, Pengxu; Zhang, Zuting; Lv, Zeping; Jing, Bin

2017-01-01

The mechanism underlying brain region organization for motor control in humans remains poorly understood. In this functional magnetic resonance imaging (fMRI) study, right-handed volunteers were tasked to maintain unilateral foot movements on the right and left sides as consistently as possible. We aimed to identify the similarities and differences between brain motor networks of the two conditions. We recruited 18 right-handed healthy volunteers aged 25 ± 2.3 years and used a whole-body 3T system for magnetic resonance (MR) scanning. Image analysis was performed using SPM8, Conn toolbox and Brain Connectivity Toolbox. We determined a craniocaudally distributed, mirror-symmetrical modular structure. The functional connectivity between homotopic brain areas was generally stronger than the intrahemispheric connections, and such strong connectivity led to the abovementioned modular structure. Our findings indicated that the interhemispheric functional interaction between homotopic brain areas is more intensive than the interaction along the conventional top-down and bottom-up pathways within the brain during unilateral limb movement. The detected strong interhemispheric horizontal functional interaction is an important aspect of motor control but often neglected or underestimated. The strong interhemispheric connectivity may explain the physiological phenomena and effects of promising therapeutic approaches. Further accurate and effective therapeutic methods may be developed on the basis of our findings.

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

Validity of semi-quantitative scale for brain MRI in unilateral cerebral palsy due to periventricular white matter lesions: Relationship with hand sensorimotor function and structural connectivity.

PubMed

Fiori, Simona; Guzzetta, Andrea; Pannek, Kerstin; Ware, Robert S; Rossi, Giuseppe; Klingels, Katrijn; Feys, Hilde; Coulthard, Alan; Cioni, Giovanni; Rose, Stephen; Boyd, Roslyn N

2015-01-01

To provide first evidence of construct validity of a semi-quantitative scale for brain structural MRI (sqMRI scale) in children with unilateral cerebral palsy (UCP) secondary to periventricular white matter (PWM) lesions, by examining the relationship with hand sensorimotor function and whole brain structural connectivity. Cross-sectional study of 50 children with UCP due to PWM lesions using 3 T (MRI), diffusion MRI and assessment of hand sensorimotor function. We explored the relationship of lobar, hemispheric and global scores on the sqMRI scale, with fractional anisotropy (FA), as a measure of brain white matter microstructure, and with hand sensorimotor measures (Assisting Hand Assessment, AHA; Jebsen-Taylor Test for Hand Function, JTTHF; Melbourne Assessment of Unilateral Upper Limb Function, MUUL; stereognosis; 2-point discrimination). Lobar and hemispheric scores on the sqMRI scale contralateral to the clinical side of hemiplegia correlated with sensorimotor paretic hand function measures and FA of a number of brain structural connections, including connections of brain areas involved in motor control (postcentral, precentral and paracentral gyri in the parietal lobe). More severe lesions correlated with lower sensorimotor performance, with the posterior limb of internal capsule score being the strongest contributor to impaired hand function. The sqMRI scale demonstrates first evidence of construct validity against impaired motor and sensory function measures and brain structural connectivity in a cohort of children with UCP due to PWM lesions. More severe lesions correlated with poorer paretic hand sensorimotor function and impaired structural connectivity in the hemisphere contralateral to the clinical side of hemiplegia. The quantitative structural MRI scoring may be a useful clinical tool for studying brain structure-function relationships but requires further validation in other populations of CP.

Addiction Related Alteration in Resting-state Brain Connectivity

PubMed Central

Ma, Ning; Liu, Ying; Li, Nan; Wang, Chang-Xin; Zhang, Hao; Jiang, Xiao-Feng; Xu, Hu-Sheng; Fu, Xian-Ming; Hu, Xiaoping; Zhang, Da-Ren

2009-01-01

It is widely accepted that addictive drug use is related to abnormal functional organization in the user’s brain. The present study aimed to identify this type of abnormality within the brain networks implicated in addiction by resting-state functional connectivity measured with functional magnetic resonance imaging (fMRI). With fMRI data acquired during resting state from 14 chronic heroin users (12 of whom were being treated with methadone) and 13 non-addicted controls, we investigated the addiction related alteration in functional connectivity between the regions in the circuits implicated in addiction with seed-based correlation analysis. Compared with controls, chronic heroin users showed increased functional connectivity between nucleus accumbens and ventral/rostral anterior cingulate cortex (ACC), and orbital frontal cortex (OFC), between amygdala and OFC; and reduced functional connectivity between prefrontal cortex and OFC, and ACC. These observations of altered resting-state functional connectivity suggested abnormal functional organization in the addicted brain and may provide additional evidence supporting the theory of addiction that emphasizes enhanced salience value of a drug and its related cues but weakened cognitive control in the addictive state. PMID:19703568

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.

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.

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.

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.

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

Reduced hippocampal functional connectivity in Alzheimer disease.

PubMed

Allen, Greg; Barnard, Holly; McColl, Roderick; Hester, Andrea L; Fields, Julie A; Weiner, Myron F; Ringe, Wendy K; Lipton, Anne M; Brooker, Matthew; McDonald, Elizabeth; Rubin, Craig D; Cullum, C Munro

2007-10-01

To determine if functional connectivity of the hippocampus is reduced in patients with Alzheimer disease. Functional connectivity magnetic resonance imaging was used to investigate coherence in the magnetic resonance signal between the hippocampus and all other regions of the brain. Eight patients with probable Alzheimer disease and 8 healthy volunteers. Control subjects showed hippocampal functional connectivity with diffuse cortical, subcortical, and cerebellar sites, while patients demonstrated markedly reduced functional connectivity, including an absence of connectivity with the frontal lobes. These findings suggest a functional disconnection between the hippocampus and other brain regions in patients with Alzheimer disease.

Determination of Vascular Dementia Brain in Distinct Frequency Bands with Whole Brain Functional Connectivity Patterns

PubMed Central

Zhang, Delong; Liu, Bo; Chen, Jun; Peng, Xiaoling; Liu, Xian; Fan, Yuanyuan; Liu, Ming; Huang, Ruiwang

2013-01-01

Recent studies have shown that multivariate pattern analysis (MVPA) can be useful for distinguishing brain disorders into categories. Such analyses can substantially enrich and facilitate clinical diagnoses. Using MPVA methods, whole brain functional networks, especially those derived using different frequency windows, can be applied to detect brain states. We constructed whole brain functional networks for groups of vascular dementia (VaD) patients and controls using resting state BOLD-fMRI (rsfMRI) data from three frequency bands - slow-5 (0.01∼0.027 Hz), slow-4 (0.027∼0.073 Hz), and whole-band (0.01∼0.073 Hz). Then we used the support vector machine (SVM), a type of MVPA classifier, to determine the patterns of functional connectivity. Our results showed that the brain functional networks derived from rsfMRI data (19 VaD patients and 20 controls) in these three frequency bands appear to reflect neurobiological changes in VaD patients. Such differences could be used to differentiate the brain states of VaD patients from those of healthy individuals. We also found that the functional connectivity patterns of the human brain in the three frequency bands differed, as did their ability to differentiate brain states. Specifically, the ability of the functional connectivity pattern to differentiate VaD brains from healthy ones was more efficient in the slow-5 (0.01∼0.027 Hz) band than in the other two frequency bands. Our findings suggest that the MVPA approach could be used to detect abnormalities in the functional connectivity of VaD patients in distinct frequency bands. Identifying such abnormalities may contribute to our understanding of the pathogenesis of VaD. PMID:23359801

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

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.

Fine-Grained Parcellation of Brain Connectivity Improves Differentiation of States of Consciousness During Graded Propofol Sedation.

PubMed

Liu, Xiaolin; Lauer, Kathryn K; Ward, B Douglas; Roberts, Christopher J; Liu, Suyan; Gollapudy, Suneeta; Rohloff, Robert; Gross, William; Xu, Zhan; Chen, Guangyu; Binder, Jeffrey R; Li, Shi-Jiang; Hudetz, Anthony G

2017-08-01

Conscious perception relies on interactions between spatially and functionally distinct modules of the brain at various spatiotemporal scales. These interactions are altered by anesthesia, an intervention that leads to fading consciousness. Relatively little is known about brain functional connectivity and its anesthetic modulation at a fine spatial scale. Here, we used functional imaging to examine propofol-induced changes in functional connectivity in brain networks defined at a fine-grained parcellation based on a combination of anatomical and functional features. Fifteen healthy volunteers underwent resting-state functional imaging in wakeful baseline, mild sedation, deep sedation, and recovery of consciousness. Compared with wakeful baseline, propofol produced widespread, dose-dependent functional connectivity changes that scaled with the extent to which consciousness was altered. The dominant changes in connectivity were associated with the frontal lobes. By examining node pairs that demonstrated a trend of functional connectivity change between wakefulness and deep sedation, quadratic discriminant analysis differentiated the states of consciousness in individual participants more accurately at a fine-grained parcellation (e.g., 2000 nodes) than at a coarse-grained parcellation (e.g., 116 anatomical nodes). Our study suggests that defining brain networks at a high granularity may provide a superior imaging-based distinction of the graded effect of anesthesia on consciousness.

Resting State Functional Connectivity in Mild Traumatic Brain Injury at the Acute Stage: Independent Component and Seed-Based Analyses

PubMed Central

Iraji, Armin; Benson, Randall R.; Welch, Robert D.; O'Neil, Brian J.; Woodard, John L.; Imran Ayaz, Syed; Kulek, Andrew; Mika, Valerie; Medado, Patrick; Soltanian-Zadeh, Hamid; Liu, Tianming; Haacke, E. Mark

2015-01-01

Abstract Mild traumatic brain injury (mTBI) accounts for more than 1 million emergency visits each year. Most of the injured stay in the emergency department for a few hours and are discharged home without a specific follow-up plan because of their negative clinical structural imaging. Advanced magnetic resonance imaging (MRI), particularly functional MRI (fMRI), has been reported as being sensitive to functional disturbances after brain injury. In this study, a cohort of 12 patients with mTBI were prospectively recruited from the emergency department of our local Level-1 trauma center for an advanced MRI scan at the acute stage. Sixteen age- and sex-matched controls were also recruited for comparison. Both group-based and individual-based independent component analysis of resting-state fMRI (rsfMRI) demonstrated reduced functional connectivity in both posterior cingulate cortex (PCC) and precuneus regions in comparison with controls, which is part of the default mode network (DMN). Further seed-based analysis confirmed reduced functional connectivity in these two regions and also demonstrated increased connectivity between these regions and other regions of the brain in mTBI. Seed-based analysis using the thalamus, hippocampus, and amygdala regions further demonstrated increased functional connectivity between these regions and other regions of the brain, particularly in the frontal lobe, in mTBI. Our data demonstrate alterations of multiple brain networks at the resting state, particularly increased functional connectivity in the frontal lobe, in response to brain concussion at the acute stage. Resting-state functional connectivity of the DMN could serve as a potential biomarker for improved detection of mTBI in the acute setting. PMID:25285363

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.

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.

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.

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

Resting-state functional connectivity imaging of the mouse brain using photoacoustic tomography

NASA Astrophysics Data System (ADS)

Nasiriavanaki, Mohammadreza; Xia, Jun; Wan, Hanlin; Bauer, Adam Q.; Culver, Joseph P.; Wang, Lihong V.

2014-03-01

Resting-state functional connectivity (RSFC) imaging is an emerging neuroimaging approach that aims to identify spontaneous cerebral hemodynamic fluctuations and their associated functional connections. Clinical studies have demonstrated that RSFC is altered in brain disorders such as stroke, Alzheimer's, autism, and epilepsy. However, conventional neuroimaging modalities cannot easily be applied to mice, the most widely used model species for human brain disease studies. For instance, functional magnetic resonance imaging (fMRI) of mice requires a very high magnetic field to obtain a sufficient signal-to-noise ratio and spatial resolution. Functional connectivity mapping with optical intrinsic signal imaging (fcOIS) is an alternative method. Due to the diffusion of light in tissue, the spatial resolution of fcOIS is limited, and experiments have been performed using an exposed skull preparation. In this study, we show for the first time, the use of photoacoustic computed tomography (PACT) to noninvasively image resting-state functional connectivity in the mouse brain, with a large field of view and a high spatial resolution. Bilateral correlations were observed in eight regions, as well as several subregions. These findings agreed well with the Paxinos mouse brain atlas. This study showed that PACT is a promising, non-invasive modality for small-animal functional brain imaging.

A review on functional and structural brain connectivity in numerical cognition

PubMed Central

Moeller, Korbinian; Willmes, Klaus; Klein, Elise

2015-01-01

Only recently has the complex anatomo-functional system underlying numerical cognition become accessible to evaluation in the living brain. We identified 27 studies investigating brain connectivity in numerical cognition. Despite considerable heterogeneity regarding methodological approaches, populations investigated, and assessment procedures implemented, the results provided largely converging evidence regarding the underlying brain connectivity involved in numerical cognition. Analyses of both functional/effective as well as structural connectivity have consistently corroborated the assumption that numerical cognition is subserved by a fronto-parietal network including (intra)parietal as well as (pre)frontal cortex sites. Evaluation of structural connectivity has indicated the involvement of fronto-parietal association fibers encompassing the superior longitudinal fasciculus dorsally and the external capsule/extreme capsule system ventrally. Additionally, commissural fibers seem to connect the bilateral intraparietal sulci when number magnitude information is processed. Finally, the identification of projection fibers such as the superior corona radiata indicates connections between cortex and basal ganglia as well as the thalamus in numerical cognition. Studies on functional/effective connectivity further indicated a specific role of the hippocampus. These specifications of brain connectivity augment the triple-code model of number processing and calculation with respect to how gray matter areas associated with specific number-related representations may work together. PMID:26029075

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.

The Exercising Brain: Changes in Functional Connectivity Induced by an Integrated Multimodal Cognitive and Whole-Body Coordination Training

PubMed Central

Demirakca, Traute; Cardinale, Vita; Dehn, Sven; Ruf, Matthias; Ende, Gabriele

2016-01-01

This study investigated the impact of “life kinetik” training on brain plasticity in terms of an increased functional connectivity during resting-state functional magnetic resonance imaging (rs-fMRI). The training is an integrated multimodal training that combines motor and cognitive aspects and challenges the brain by introducing new and unfamiliar coordinative tasks. Twenty-one subjects completed at least 11 one-hour-per-week “life kinetik” training sessions in 13 weeks as well as before and after rs-fMRI scans. Additionally, 11 control subjects with 2 rs-fMRI scans were included. The CONN toolbox was used to conduct several seed-to-voxel analyses. We searched for functional connectivity increases between brain regions expected to be involved in the exercises. Connections to brain regions representing parts of the default mode network, such as medial frontal cortex and posterior cingulate cortex, did not change. Significant connectivity alterations occurred between the visual cortex and parts of the superior parietal area (BA7). Premotor area and cingulate gyrus were also affected. We can conclude that the constant challenge of unfamiliar combinations of coordination tasks, combined with visual perception and working memory demands, seems to induce brain plasticity expressed in enhanced connectivity strength of brain regions due to coactivation. PMID:26819776

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.

Structure-function relationships during segregated and integrated network states of human brain functional connectivity.

PubMed

Fukushima, Makoto; Betzel, Richard F; He, Ye; van den Heuvel, Martijn P; Zuo, Xi-Nian; Sporns, Olaf

2018-04-01

Structural white matter connections are thought to facilitate integration of neural information across functionally segregated systems. Recent studies have demonstrated that changes in the balance between segregation and integration in brain networks can be tracked by time-resolved functional connectivity derived from resting-state functional magnetic resonance imaging (rs-fMRI) data and that fluctuations between segregated and integrated network states are related to human behavior. However, how these network states relate to structural connectivity is largely unknown. To obtain a better understanding of structural substrates for these network states, we investigated how the relationship between structural connectivity, derived from diffusion tractography, and functional connectivity, as measured by rs-fMRI, changes with fluctuations between segregated and integrated states in the human brain. We found that the similarity of edge weights between structural and functional connectivity was greater in the integrated state, especially at edges connecting the default mode and the dorsal attention networks. We also demonstrated that the similarity of network partitions, evaluated between structural and functional connectivity, increased and the density of direct structural connections within modules in functional networks was elevated during the integrated state. These results suggest that, when functional connectivity exhibited an integrated network topology, structural connectivity and functional connectivity were more closely linked to each other and direct structural connections mediated a larger proportion of neural communication within functional modules. Our findings point out the possibility of significant contributions of structural connections to integrative neural processes underlying human behavior.

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

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.

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 Bias in the Prefrontal Cortex of Psychopaths.

PubMed

Contreras-Rodríguez, Oren; Pujol, Jesus; Batalla, Iolanda; Harrison, Ben J; Soriano-Mas, Carles; Deus, Joan; López-Solà, Marina; Macià, Dídac; Pera, Vanessa; Hernández-Ribas, Rosa; Pifarré, Josep; Menchón, José M; Cardoner, Narcís

2015-11-01

Psychopathy is characterized by a distinctive interpersonal style that combines callous-unemotional traits with inflexible and antisocial behavior. Traditional emotion-based perspectives link emotional impairment mostly to alterations in amygdala-ventromedial frontal circuits. However, these models alone cannot explain why individuals with psychopathy can regularly benefit from emotional information when placed on their focus of attention and why they are more resistant to interference from nonaffective contextual cues. The present study aimed to identify abnormal or distinctive functional links between and within emotional and cognitive brain systems in the psychopathic brain to characterize further the neural bases of psychopathy. High-resolution anatomic magnetic resonance imaging with a functional sequence acquired in the resting state was used to assess 22 subjects with psychopathy and 22 control subjects. Anatomic and functional connectivity alterations were investigated first using a whole-brain analysis. Brain regions showing overlapping anatomic and functional changes were examined further using seed-based functional connectivity mapping. Subjects with psychopathy showed gray matter reduction involving prefrontal cortex, paralimbic, and limbic structures. Anatomic changes overlapped with areas showing increased degree of functional connectivity at the medial-dorsal frontal cortex. Subsequent functional seed-based connectivity mapping revealed a pattern of reduced functional connectivity of prefrontal areas with limbic-paralimbic structures and enhanced connectivity within the dorsal frontal lobe in subjects with psychopathy. Our results suggest that a weakened link between emotional and cognitive domains in the psychopathic brain may combine with enhanced functional connections within frontal executive areas. The identified functional alterations are discussed in the context of potential contributors to the inflexible behavior displayed by individuals with psychopathy. Copyright © 2015 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

Functional connectivity during phonemic and semantic verbal fluency test: a multi-channel near infrared spectroscopy study (Conference Presentation)

NASA Astrophysics Data System (ADS)

Huang, Chun-Jung; Sun, Chia-Wei; Chou, Po-Han; Chuang, Ching-Cheng

2016-03-01

Verbal fluency tests (VFT) are widely used neuropsychological tests of frontal lobe and have been frequently used in various functional brain mapping studies. There are two versions of VFT based on the type of cue: the letter fluency task (LFT) and the category fluency task (CFT). However, the fundamental aspect of the brain connectivity across spatial regions of the fronto-temporal regions during the VFTs has not been elucidated to date. In this study we hypothesized that different cortical functional connectivity over bilateral fronto-temporal regions can be observed by means of multi-channel fNIRS in the LFT and the CFT respectively. Our results from fNIRS (ETG-4000) showed different patterns of brain functional connectivity consistent with these different cognitive requirements. We demonstrate more brain functional connectivity over frontal and temporal regions during LFT than CFT, and this was in line with previous brain activity studies using fNIRS demonstrating increased frontal and temporal region activation during LFT and CFT and more pronounced frontal activation by the LFT.

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.

Hierarchical functional modularity in the resting-state human brain.

PubMed

Ferrarini, Luca; Veer, Ilya M; Baerends, Evelinda; van Tol, Marie-José; Renken, Remco J; van der Wee, Nic J A; Veltman, Dirk J; Aleman, André; Zitman, Frans G; Penninx, Brenda W J H; van Buchem, Mark A; Reiber, Johan H C; Rombouts, Serge A R B; Milles, Julien

2009-07-01

Functional magnetic resonance imaging (fMRI) studies have shown that anatomically distinct brain regions are functionally connected during the resting state. Basic topological properties in the brain functional connectivity (BFC) map have highlighted the BFC's small-world topology. Modularity, a more advanced topological property, has been hypothesized to be evolutionary advantageous, contributing to adaptive aspects of anatomical and functional brain connectivity. However, current definitions of modularity for complex networks focus on nonoverlapping clusters, and are seriously limited by disregarding inclusive relationships. Therefore, BFC's modularity has been mainly qualitatively investigated. Here, we introduce a new definition of modularity, based on a recently improved clustering measurement, which overcomes limitations of previous definitions, and apply it to the study of BFC in resting state fMRI of 53 healthy subjects. Results show hierarchical functional modularity in the brain. Copyright 2009 Wiley-Liss, Inc

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.

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 During Exposure to Favorite-Food, Stress, and Neutral-Relaxing Imagery Differs Between Smokers and Nonsmokers.

PubMed

Garrison, Kathleen A; Sinha, Rajita; Lacadie, Cheryl M; Scheinost, Dustin; Jastreboff, Ania M; Constable, R Todd; Potenza, Marc N

2016-09-01

Tobacco-use disorder is a complex condition involving multiple brain networks and presenting with multiple behavioral correlates including changes in diet and stress. In a previous functional magnetic resonance imaging (fMRI) study of neural responses to favorite-food, stress, and neutral-relaxing imagery, smokers versus nonsmokers demonstrated blunted corticostriatal-limbic responses to favorite-food cues. Based on other recent reports of alterations in functional brain networks in smokers, the current study examined functional connectivity during exposure to favorite-food, stress, and neutral-relaxing imagery in smokers and nonsmokers, using the same dataset. The intrinsic connectivity distribution was measured to identify brain regions that differed in degree of functional connectivity between groups during each imagery condition. Resulting clusters were evaluated for seed-to-voxel connectivity to identify the specific connections that differed between groups during each imagery condition. During exposure to favorite-food imagery, smokers versus nonsmokers showed lower connectivity in the supramarginal gyrus, and differences in connectivity between the supramarginal gyrus and the corticostriatal-limbic system. During exposure to neutral-relaxing imagery, smokers versus nonsmokers showed greater connectivity in the precuneus, and greater connectivity between the precuneus and the posterior insula and rolandic operculum. During exposure to stress imagery, smokers versus nonsmokers showed lower connectivity in the cerebellum. These findings provide data-driven insights into smoking-related alterations in brain functional connectivity patterns related to appetitive, relaxing, and stressful states. This study uses a data-driven approach to demonstrate that smokers and nonsmokers show differential patterns of functional connectivity during guided imagery related to personalized favorite-food, stress, and neutral-relaxing cues, in brain regions implicated in attention, reward-related, emotional, and motivational processes. For smokers, these differences in connectivity may impact appetite, stress, and relaxation, and may interfere with smoking cessation. © The Author 2016. Published by Oxford University Press on behalf of the Society for Research on Nicotine and Tobacco. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Functional Connectivity During Exposure to Favorite-Food, Stress, and Neutral-Relaxing Imagery Differs Between Smokers and Nonsmokers

PubMed Central

Sinha, Rajita; Lacadie, Cheryl M.; Scheinost, Dustin; Jastreboff, Ania M.; Constable, R. Todd; Potenza, Marc N.

2016-01-01

Introduction: Tobacco-use disorder is a complex condition involving multiple brain networks and presenting with multiple behavioral correlates including changes in diet and stress. In a previous functional magnetic resonance imaging (fMRI) study of neural responses to favorite-food, stress, and neutral-relaxing imagery, smokers versus nonsmokers demonstrated blunted corticostriatal-limbic responses to favorite-food cues. Based on other recent reports of alterations in functional brain networks in smokers, the current study examined functional connectivity during exposure to favorite-food, stress, and neutral-relaxing imagery in smokers and nonsmokers, using the same dataset. Methods: The intrinsic connectivity distribution was measured to identify brain regions that differed in degree of functional connectivity between groups during each imagery condition. Resulting clusters were evaluated for seed-to-voxel connectivity to identify the specific connections that differed between groups during each imagery condition. Results: During exposure to favorite-food imagery, smokers versus nonsmokers showed lower connectivity in the supramarginal gyrus, and differences in connectivity between the supramarginal gyrus and the corticostriatal-limbic system. During exposure to neutral-relaxing imagery, smokers versus nonsmokers showed greater connectivity in the precuneus, and greater connectivity between the precuneus and the posterior insula and rolandic operculum. During exposure to stress imagery, smokers versus nonsmokers showed lower connectivity in the cerebellum. Conclusions: These findings provide data-driven insights into smoking-related alterations in brain functional connectivity patterns related to appetitive, relaxing, and stressful states. Implications: This study uses a data-driven approach to demonstrate that smokers and nonsmokers show differential patterns of functional connectivity during guided imagery related to personalized favorite-food, stress, and neutral-relaxing cues, in brain regions implicated in attention, reward-related, emotional, and motivational processes. For smokers, these differences in connectivity may impact appetite, stress, and relaxation, and may interfere with smoking cessation. PMID:26995796

Compensation through Functional Hyperconnectivity: A Longitudinal Connectome Assessment of Mild Traumatic Brain Injury

PubMed Central

Iraji, Armin; Chen, Hanbo; Wiseman, Natalie; Welch, Robert D.; O'Neil, Brian J.; Haacke, E. Mark; Liu, Tianming; Kou, Zhifeng

2016-01-01

Mild traumatic brain injury (mTBI) is a major public health concern. Functional MRI has reported alterations in several brain networks following mTBI. However, the connectome-scale brain network changes are still unknown. In this study, sixteen mTBI patients were prospectively recruited from an emergency department and followed up at 4–6 weeks after injury. Twenty-four healthy controls were also scanned twice with the same time interval. Three hundred fifty-eight brain landmarks that preserve structural and functional correspondence of brain networks across individuals were used to investigate longitudinal brain connectivity. Network-based statistic (NBS) analysis did not find significant difference in the group-by-time interaction and time effects. However, 258 functional pairs show group differences in which mTBI patients have higher functional connectivity. Meta-analysis showed that “Action” and “Cognition” are the most affected functional domains. Categorization of connectomic signatures using multiview group-wise cluster analysis identified two patterns of functional hyperconnectivity among mTBI patients: (I) between the posterior cingulate cortex and the association areas of the brain and (II) between the occipital and the frontal lobes of the brain. Our results demonstrate that brain concussion renders connectome-scale brain network connectivity changes, and the brain tends to be hyperactivated to compensate the pathophysiological disturbances. PMID:26819765

Compensation through Functional Hyperconnectivity: A Longitudinal Connectome Assessment of Mild Traumatic Brain Injury.

PubMed

Iraji, Armin; Chen, Hanbo; Wiseman, Natalie; Welch, Robert D; O'Neil, Brian J; Haacke, E Mark; Liu, Tianming; Kou, Zhifeng

2016-01-01

Mild traumatic brain injury (mTBI) is a major public health concern. Functional MRI has reported alterations in several brain networks following mTBI. However, the connectome-scale brain network changes are still unknown. In this study, sixteen mTBI patients were prospectively recruited from an emergency department and followed up at 4-6 weeks after injury. Twenty-four healthy controls were also scanned twice with the same time interval. Three hundred fifty-eight brain landmarks that preserve structural and functional correspondence of brain networks across individuals were used to investigate longitudinal brain connectivity. Network-based statistic (NBS) analysis did not find significant difference in the group-by-time interaction and time effects. However, 258 functional pairs show group differences in which mTBI patients have higher functional connectivity. Meta-analysis showed that "Action" and "Cognition" are the most affected functional domains. Categorization of connectomic signatures using multiview group-wise cluster analysis identified two patterns of functional hyperconnectivity among mTBI patients: (I) between the posterior cingulate cortex and the association areas of the brain and (II) between the occipital and the frontal lobes of the brain. Our results demonstrate that brain concussion renders connectome-scale brain network connectivity changes, and the brain tends to be hyperactivated to compensate the pathophysiological disturbances.

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.

Integrated Analysis and Visualization of Group Differences in Structural and Functional Brain Connectivity: Applications in Typical Ageing and Schizophrenia.

PubMed

Langen, Carolyn D; White, Tonya; Ikram, M Arfan; Vernooij, Meike W; Niessen, Wiro J

2015-01-01

Structural and functional brain connectivity are increasingly used to identify and analyze group differences in studies of brain disease. This study presents methods to analyze uni- and bi-modal brain connectivity and evaluate their ability to identify differences. Novel visualizations of significantly different connections comparing multiple metrics are presented. On the global level, "bi-modal comparison plots" show the distribution of uni- and bi-modal group differences and the relationship between structure and function. Differences between brain lobes are visualized using "worm plots". Group differences in connections are examined with an existing visualization, the "connectogram". These visualizations were evaluated in two proof-of-concept studies: (1) middle-aged versus elderly subjects; and (2) patients with schizophrenia versus controls. Each included two measures derived from diffusion weighted images and two from functional magnetic resonance images. The structural measures were minimum cost path between two anatomical regions according to the "Statistical Analysis of Minimum cost path based Structural Connectivity" method and the average fractional anisotropy along the fiber. The functional measures were Pearson's correlation and partial correlation of mean regional time series. The relationship between structure and function was similar in both studies. Uni-modal group differences varied greatly between connectivity types. Group differences were identified in both studies globally, within brain lobes and between regions. In the aging study, minimum cost path was highly effective in identifying group differences on all levels; fractional anisotropy and mean correlation showed smaller differences on the brain lobe and regional levels. In the schizophrenia study, minimum cost path and fractional anisotropy showed differences on the global level and within brain lobes; mean correlation showed small differences on the lobe level. Only fractional anisotropy and mean correlation showed regional differences. The presented visualizations were helpful in comparing and evaluating connectivity measures on multiple levels in both studies.

Individual Functional ROI Optimization via Maximization of Group-wise Consistency of Structural and Functional Profiles

PubMed Central

Li, Kaiming; Guo, Lei; Zhu, Dajiang; Hu, Xintao; Han, Junwei; Liu, Tianming

2013-01-01

Studying connectivities among functional brain regions and the functional dynamics on brain networks has drawn increasing interest. A fundamental issue that affects functional connectivity and dynamics studies is how to determine the best possible functional brain regions or ROIs (regions of interest) for a group of individuals, since the connectivity measurements are heavily dependent on ROI locations. Essentially, identification of accurate, reliable and consistent corresponding ROIs is challenging due to the unclear boundaries between brain regions, variability across individuals, and nonlinearity of the ROIs. In response to these challenges, this paper presents a novel methodology to computationally optimize ROIs locations derived from task-based fMRI data for individuals so that the optimized ROIs are more consistent, reproducible and predictable across brains. Our computational strategy is to formulate the individual ROI location optimization as a group variance minimization problem, in which group-wise consistencies in functional/structural connectivity patterns and anatomic profiles are defined as optimization constraints. Our experimental results from multimodal fMRI and DTI data show that the optimized ROIs have significantly improved consistency in structural and functional profiles across individuals. These improved functional ROIs with better consistency could contribute to further study of functional interaction and dynamics in the human brain. PMID:22281931

Resting state fMRI: A review on methods in resting state connectivity analysis and resting state networks.

PubMed

Smitha, K A; Akhil Raja, K; Arun, K M; Rajesh, P G; Thomas, Bejoy; Kapilamoorthy, T R; Kesavadas, Chandrasekharan

2017-08-01

The inquisitiveness about what happens in the brain has been there since the beginning of humankind. Functional magnetic resonance imaging is a prominent tool which helps in the non-invasive examination, localisation as well as lateralisation of brain functions such as language, memory, etc. In recent years, there is an apparent shift in the focus of neuroscience research to studies dealing with a brain at 'resting state'. Here the spotlight is on the intrinsic activity within the brain, in the absence of any sensory or cognitive stimulus. The analyses of functional brain connectivity in the state of rest have revealed different resting state networks, which depict specific functions and varied spatial topology. However, different statistical methods have been introduced to study resting state functional magnetic resonance imaging connectivity, yet producing consistent results. In this article, we introduce the concept of resting state functional magnetic resonance imaging in detail, then discuss three most widely used methods for analysis, describe a few of the resting state networks featuring the brain regions, associated cognitive functions and clinical applications of resting state functional magnetic resonance imaging. This review aims to highlight the utility and importance of studying resting state functional magnetic resonance imaging connectivity, underlining its complementary nature to the task-based functional magnetic resonance imaging.

Modafinil Reverses Phencyclidine-Induced Deficits in Cognitive Flexibility, Cerebral Metabolism, and Functional Brain Connectivity

PubMed Central

Dawson, Neil; Thompson, Rhiannon J.; McVie, Allan; Thomson, David M.; Morris, Brian J.; Pratt, Judith A.

2012-01-01

Objective: In the present study, we employ mathematical modeling (partial least squares regression, PLSR) to elucidate the functional connectivity signatures of discrete brain regions in order to identify the functional networks subserving PCP-induced disruption of distinct cognitive functions and their restoration by the procognitive drug modafinil. Methods: We examine the functional connectivity signatures of discrete brain regions that show overt alterations in metabolism, as measured by semiquantitative 2-deoxyglucose autoradiography, in an animal model (subchronic phencyclidine [PCP] treatment), which shows cognitive inflexibility with relevance to the cognitive deficits seen in schizophrenia. Results: We identify the specific components of functional connectivity that contribute to the rescue of this cognitive inflexibility and to the restoration of overt cerebral metabolism by modafinil. We demonstrate that modafinil reversed both the PCP-induced deficit in the ability to switch attentional set and the PCP-induced hypometabolism in the prefrontal (anterior prelimbic) and retrosplenial cortices. Furthermore, modafinil selectively enhanced metabolism in the medial prelimbic cortex. The functional connectivity signatures of these regions identified a unifying functional subsystem underlying the influence of modafinil on cerebral metabolism and cognitive flexibility that included the nucleus accumbens core and locus coeruleus. In addition, these functional connectivity signatures identified coupling events specific to each brain region, which relate to known anatomical connectivity. Conclusions: These data support clinical evidence that modafinil may alleviate cognitive deficits in schizophrenia and also demonstrate the benefit of applying PLSR modeling to characterize functional brain networks in translational models relevant to central nervous system dysfunction. PMID:20810469

The role of long-range connectivity for the characterization of the functional-anatomical organization of the cortex.

PubMed

Knösche, Thomas R; Tittgemeyer, Marc

2011-01-01

This review focuses on the role of long-range connectivity as one element of brain structure that is of key importance for the functional-anatomical organization of the cortex. In this context, we discuss the putative guiding principles for mapping brain function and structure onto the cortical surface. Such mappings reveal a high degree of functional-anatomical segregation. Given that brain regions frequently maintain characteristic connectivity profiles and the functional repertoire of a cortical area is closely related to its anatomical connections, long-range connectivity may be used to define segregated cortical areas. This methodology is called connectivity-based parcellation. Within this framework, we investigate different techniques to estimate connectivity profiles with emphasis given to non-invasive methods based on diffusion magnetic resonance imaging (dMRI) and diffusion tractography. Cortical parcellation is then defined based on similarity between diffusion tractograms, and different clustering approaches are discussed. We conclude that the use of non-invasively acquired connectivity estimates to characterize the functional-anatomical organization of the brain is a valid, relevant, and necessary endeavor. Current and future developments in dMRI technology, tractography algorithms, and models of the similarity structure hold great potential for a substantial improvement and enrichment of the results of the technique.

Adrenergic Blockade Bi-directionally and Asymmetrically Alters Functional Brain-Heart Communication and Prolongs Electrical Activities of the Brain and Heart during Asphyxic Cardiac Arrest

PubMed Central

Tian, Fangyun; Liu, Tiecheng; Xu, Gang; Li, Duan; Ghazi, Talha; Shick, Trevor; Sajjad, Azeem; Wang, Michael M.; Farrehi, Peter; Borjigin, Jimo

2018-01-01

Sudden cardiac arrest is a leading cause of death in the United States. The neurophysiological mechanism underlying sudden death is not well understood. Previously we have shown that the brain is highly stimulated in dying animals and that asphyxia-induced death could be delayed by blocking the intact brain-heart neuronal connection. These studies suggest that the autonomic nervous system plays an important role in mediating sudden cardiac arrest. In this study, we tested the effectiveness of phentolamine and atenolol, individually or combined, in prolonging functionality of the vital organs in CO2-mediated asphyxic cardiac arrest model. Rats received either saline, phentolamine, atenolol, or phentolamine plus atenolol, 30 min before the onset of asphyxia. Electrocardiogram (ECG) and electroencephalogram (EEG) signals were simultaneously collected from each rat during the entire process and investigated for cardiac and brain functions using a battery of analytic tools. We found that adrenergic blockade significantly suppressed the initial decline of cardiac output, prolonged electrical activities of both brain and heart, asymmetrically altered functional connectivity within the brain, and altered, bi-directionally and asymmetrically, functional, and effective connectivity between the brain and heart. The protective effects of adrenergic blockers paralleled the suppression of brain and heart connectivity, especially in the right hemisphere associated with central regulation of sympathetic function. Collectively, our results demonstrate that blockade of brain-heart connection via alpha- and beta-adrenergic blockers significantly prolonged the detectable activities of both the heart and the brain in asphyxic rat. The beneficial effects of combined alpha and beta blockers may help extend the survival of cardiac arrest patients. PMID:29487541

Adrenergic Blockade Bi-directionally and Asymmetrically Alters Functional Brain-Heart Communication and Prolongs Electrical Activities of the Brain and Heart during Asphyxic Cardiac Arrest.

PubMed

Tian, Fangyun; Liu, Tiecheng; Xu, Gang; Li, Duan; Ghazi, Talha; Shick, Trevor; Sajjad, Azeem; Wang, Michael M; Farrehi, Peter; Borjigin, Jimo

2018-01-01

Sudden cardiac arrest is a leading cause of death in the United States. The neurophysiological mechanism underlying sudden death is not well understood. Previously we have shown that the brain is highly stimulated in dying animals and that asphyxia-induced death could be delayed by blocking the intact brain-heart neuronal connection. These studies suggest that the autonomic nervous system plays an important role in mediating sudden cardiac arrest. In this study, we tested the effectiveness of phentolamine and atenolol, individually or combined, in prolonging functionality of the vital organs in CO 2 -mediated asphyxic cardiac arrest model. Rats received either saline, phentolamine, atenolol, or phentolamine plus atenolol, 30 min before the onset of asphyxia. Electrocardiogram (ECG) and electroencephalogram (EEG) signals were simultaneously collected from each rat during the entire process and investigated for cardiac and brain functions using a battery of analytic tools. We found that adrenergic blockade significantly suppressed the initial decline of cardiac output, prolonged electrical activities of both brain and heart, asymmetrically altered functional connectivity within the brain, and altered, bi-directionally and asymmetrically, functional, and effective connectivity between the brain and heart. The protective effects of adrenergic blockers paralleled the suppression of brain and heart connectivity, especially in the right hemisphere associated with central regulation of sympathetic function. Collectively, our results demonstrate that blockade of brain-heart connection via alpha- and beta-adrenergic blockers significantly prolonged the detectable activities of both the heart and the brain in asphyxic rat. The beneficial effects of combined alpha and beta blockers may help extend the survival of cardiac arrest patients.

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

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.

Mechanisms of interactive specialization and emergence of functional brain circuits supporting cognitive development in children

NASA Astrophysics Data System (ADS)

Battista, Christian; Evans, Tanya M.; Ngoon, Tricia J.; Chen, Tianwen; Chen, Lang; Kochalka, John; Menon, Vinod

2018-01-01

Cognitive development is thought to depend on the refinement and specialization of functional circuits over time, yet little is known about how this process unfolds over the course of childhood. Here we investigated growth trajectories of functional brain circuits and tested an interactive specialization model of neurocognitive development which posits that the refinement of task-related functional networks is driven by a shared history of co-activation between cortical regions. We tested this model in a longitudinal cohort of 30 children with behavioral and task-related functional brain imaging data at multiple time points spanning childhood and adolescence, focusing on the maturation of parietal circuits associated with numerical problem solving and learning. Hierarchical linear modeling revealed selective strengthening as well as weakening of functional brain circuits. Connectivity between parietal and prefrontal cortex decreased over time, while connectivity within posterior brain regions, including intra-hemispheric and inter-hemispheric parietal connectivity, as well as parietal connectivity with ventral temporal occipital cortex regions implicated in quantity manipulation and numerical symbol recognition, increased over time. Our study provides insights into the longitudinal maturation of functional circuits in the human brain and the mechanisms by which interactive specialization shapes children's cognitive development and learning.

Brain Imaging of Human Sexual Response: Recent Developments and Future Directions.

PubMed

Ruesink, Gerben B; Georgiadis, Janniko R

2017-01-01

The purpose of this study is to provide a comprehensive summary of the latest developments in the experimental brain study of human sexuality, focusing on brain connectivity during the sexual response. Stable patterns of brain activation have been established for different phases of the sexual response, especially with regard to the wanting phase, and changes in these patterns can be linked to sexual response variations, including sexual dysfunctions. From this solid basis, connectivity studies of the human sexual response have begun to add a deeper understanding of the brain network function and structure involved. The study of "sexual" brain connectivity is still very young. Yet, by approaching the brain as a connected organ, the essence of brain function is captured much more accurately, increasing the likelihood of finding useful biomarkers and targets for intervention in sexual dysfunction.

Validity of semi-quantitative scale for brain MRI in unilateral cerebral palsy due to periventricular white matter lesions: Relationship with hand sensorimotor function and structural connectivity

PubMed Central

Fiori, Simona; Guzzetta, Andrea; Pannek, Kerstin; Ware, Robert S.; Rossi, Giuseppe; Klingels, Katrijn; Feys, Hilde; Coulthard, Alan; Cioni, Giovanni; Rose, Stephen; Boyd, Roslyn N.

2015-01-01

Aim To provide first evidence of construct validity of a semi-quantitative scale for brain structural MRI (sqMRI scale) in children with unilateral cerebral palsy (UCP) secondary to periventricular white matter (PWM) lesions, by examining the relationship with hand sensorimotor function and whole brain structural connectivity. Methods Cross-sectional study of 50 children with UCP due to PWM lesions using 3 T (MRI), diffusion MRI and assessment of hand sensorimotor function. We explored the relationship of lobar, hemispheric and global scores on the sqMRI scale, with fractional anisotropy (FA), as a measure of brain white matter microstructure, and with hand sensorimotor measures (Assisting Hand Assessment, AHA; Jebsen–Taylor Test for Hand Function, JTTHF; Melbourne Assessment of Unilateral Upper Limb Function, MUUL; stereognosis; 2-point discrimination). Results Lobar and hemispheric scores on the sqMRI scale contralateral to the clinical side of hemiplegia correlated with sensorimotor paretic hand function measures and FA of a number of brain structural connections, including connections of brain areas involved in motor control (postcentral, precentral and paracentral gyri in the parietal lobe). More severe lesions correlated with lower sensorimotor performance, with the posterior limb of internal capsule score being the strongest contributor to impaired hand function. Conclusion The sqMRI scale demonstrates first evidence of construct validity against impaired motor and sensory function measures and brain structural connectivity in a cohort of children with UCP due to PWM lesions. More severe lesions correlated with poorer paretic hand sensorimotor function and impaired structural connectivity in the hemisphere contralateral to the clinical side of hemiplegia. The quantitative structural MRI scoring may be a useful clinical tool for studying brain structure–function relationships but requires further validation in other populations of CP. PMID:26106533

Tinnitus alters resting state functional connectivity (RSFC) in human auditory and non-auditory brain regions as measured by functional near-infrared spectroscopy (fNIRS)

PubMed Central

Hu, Xiao-Su; Issa, Mohamad; Bisconti, Silvia; Kovelman, Ioulia; Kileny, Paul; Basura, Gregory

2017-01-01

Tinnitus, or phantom sound perception, leads to increased spontaneous neural firing rates and enhanced synchrony in central auditory circuits in animal models. These putative physiologic correlates of tinnitus to date have not been well translated in the brain of the human tinnitus sufferer. Using functional near-infrared spectroscopy (fNIRS) we recently showed that tinnitus in humans leads to maintained hemodynamic activity in auditory and adjacent, non-auditory cortices. Here we used fNIRS technology to investigate changes in resting state functional connectivity between human auditory and non-auditory brain regions in normal-hearing, bilateral subjective tinnitus and controls before and after auditory stimulation. Hemodynamic activity was monitored over the region of interest (primary auditory cortex) and non-region of interest (adjacent non-auditory cortices) and functional brain connectivity was measured during a 60-second baseline/period of silence before and after a passive auditory challenge consisting of alternating pure tones (750 and 8000Hz), broadband noise and silence. Functional connectivity was measured between all channel-pairs. Prior to stimulation, connectivity of the region of interest to the temporal and fronto-temporal region was decreased in tinnitus participants compared to controls. Overall, connectivity in tinnitus was differentially altered as compared to controls following sound stimulation. Enhanced connectivity was seen in both auditory and non-auditory regions in the tinnitus brain, while controls showed a decrease in connectivity following sound stimulation. In tinnitus, the strength of connectivity was increased between auditory cortex and fronto-temporal, fronto-parietal, temporal, occipito-temporal and occipital cortices. Together these data suggest that central auditory and non-auditory brain regions are modified in tinnitus and that resting functional connectivity measured by fNIRS technology may contribute to conscious phantom sound perception and potentially serve as an objective measure of central neural pathology. PMID:28604786

Altered caudate connectivity is associated with executive dysfunction after traumatic brain injury

PubMed Central

De Simoni, Sara; Jenkins, Peter O; Bourke, Niall J; Fleminger, Jessica J; Jolly, Amy E; Patel, Maneesh C; Leech, Robert; Sharp, David J

2018-01-01

Abstract Traumatic brain injury often produces executive dysfunction. This characteristic cognitive impairment often causes long-term problems with behaviour and personality. Frontal lobe injuries are associated with executive dysfunction, but it is unclear how these injuries relate to corticostriatal interactions that are known to play an important role in behavioural control. We hypothesized that executive dysfunction after traumatic brain injury would be associated with abnormal corticostriatal interactions, a question that has not previously been investigated. We used structural and functional MRI measures of connectivity to investigate this. Corticostriatal functional connectivity in healthy individuals was initially defined using a data-driven approach. A constrained independent component analysis approach was applied in 100 healthy adult dataset from the Human Connectome Project. Diffusion tractography was also performed to generate white matter tracts. The output of this analysis was used to compare corticostriatal functional connectivity and structural integrity between groups of 42 patients with traumatic brain injury and 21 age-matched controls. Subdivisions of the caudate and putamen had distinct patterns of functional connectivity. Traumatic brain injury patients showed disruption to functional connectivity between the caudate and a distributed set of cortical regions, including the anterior cingulate cortex. Cognitive impairments in the patients were mainly seen in processing speed and executive function, as well as increased levels of apathy and fatigue. Abnormalities of caudate functional connectivity correlated with these cognitive impairments, with reductions in right caudate connectivity associated with increased executive dysfunction, information processing speed and memory impairment. Structural connectivity, measured using diffusion tensor imaging between the caudate and anterior cingulate cortex was impaired and this also correlated with measures of executive dysfunction. We show for the first time that altered subcortical connectivity is associated with large-scale network disruption in traumatic brain injury and that this disruption is related to the cognitive impairments seen in these patients. PMID:29186356

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.

Spectral mapping of brain functional connectivity from diffusion imaging.

PubMed

Becker, Cassiano O; Pequito, Sérgio; Pappas, George J; Miller, Michael B; Grafton, Scott T; Bassett, Danielle S; Preciado, Victor M

2018-01-23

Understanding the relationship between the dynamics of neural processes and the anatomical substrate of the brain is a central question in neuroscience. On the one hand, modern neuroimaging technologies, such as diffusion tensor imaging, can be used to construct structural graphs representing the architecture of white matter streamlines linking cortical and subcortical structures. On the other hand, temporal patterns of neural activity can be used to construct functional graphs representing temporal correlations between brain regions. Although some studies provide evidence that whole-brain functional connectivity is shaped by the underlying anatomy, the observed relationship between function and structure is weak, and the rules by which anatomy constrains brain dynamics remain elusive. In this article, we introduce a methodology to map the functional connectivity of a subject at rest from his or her structural graph. Using our methodology, we are able to systematically account for the role of structural walks in the formation of functional correlations. Furthermore, in our empirical evaluations, we observe that the eigenmodes of the mapped functional connectivity are associated with activity patterns associated with different cognitive systems.

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.

Medial reward and lateral non-reward orbitofrontal cortex circuits change in opposite directions in depression.

PubMed

Cheng, Wei; Rolls, Edmund T; Qiu, Jiang; Liu, Wei; Tang, Yanqing; Huang, Chu-Chung; Wang, XinFa; Zhang, Jie; Lin, Wei; Zheng, Lirong; Pu, JunCai; Tsai, Shih-Jen; Yang, Albert C; Lin, Ching-Po; Wang, Fei; Xie, Peng; Feng, Jianfeng

2016-12-01

The first brain-wide voxel-level resting state functional connectivity neuroimaging analysis of depression is reported, with 421 patients with major depressive disorder and 488 control subjects. Resting state functional connectivity between different voxels reflects correlations of activity between those voxels and is a fundamental tool in helping to understand the brain regions with altered connectivity and function in depression. One major circuit with altered functional connectivity involved the medial orbitofrontal cortex Brodmann area 13, which is implicated in reward, and which had reduced functional connectivity in depression with memory systems in the parahippocampal gyrus and medial temporal lobe, especially involving the perirhinal cortex Brodmann area 36 and entorhinal cortex Brodmann area 28. The Hamilton Depression Rating Scale scores were correlated with weakened functional connectivity of the medial orbitofrontal cortex Brodmann area 13. Thus in depression there is decreased reward-related and memory system functional connectivity, and this is related to the depressed symptoms. The lateral orbitofrontal cortex Brodmann area 47/12, involved in non-reward and punishing events, did not have this reduced functional connectivity with memory systems. Second, the lateral orbitofrontal cortex Brodmann area 47/12 had increased functional connectivity with the precuneus, the angular gyrus, and the temporal visual cortex Brodmann area 21. This enhanced functional connectivity of the non-reward/punishment system (Brodmann area 47/12) with the precuneus (involved in the sense of self and agency), and the angular gyrus (involved in language) is thus related to the explicit affectively negative sense of the self, and of self-esteem, in depression. A comparison of the functional connectivity in 185 depressed patients not receiving medication and 182 patients receiving medication showed that the functional connectivity of the lateral orbitofrontal cortex Brodmann area 47/12 with these three brain areas was lower in the medicated than the unmedicated patients. This is consistent with the hypothesis that the increased functional connectivity of the lateral orbitofrontal cortex Brodmann area 47/12 is related to depression. Relating the changes in cortical connectivity to our understanding of the functions of different parts of the orbitofrontal cortex in emotion helps to provide new insight into the brain changes related to depression. © 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.

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.

Functional Connectivity Parcellation of the Human Thalamus by Independent Component Analysis.

PubMed

Zhang, Sheng; Li, Chiang-Shan R

2017-11-01

As a key structure to relay and integrate information, the thalamus supports multiple cognitive and affective functions through the connectivity between its subnuclei and cortical and subcortical regions. Although extant studies have largely described thalamic regional functions in anatomical terms, evidence accumulates to suggest a more complex picture of subareal activities and connectivities of the thalamus. In this study, we aimed to parcellate the thalamus and examine whole-brain connectivity of its functional clusters. With resting state functional magnetic resonance imaging data from 96 adults, we used independent component analysis (ICA) to parcellate the thalamus into 10 components. On the basis of the independence assumption, ICA helps to identify how subclusters overlap spatially. Whole brain functional connectivity of each subdivision was computed for independent component's time course (ICtc), which is a unique time series to represent an IC. For comparison, we computed seed-region-based functional connectivity using the averaged time course across all voxels within a thalamic subdivision. The results showed that, at p < 10 -6 , corrected, 49% of voxels on average overlapped among subdivisions. Compared with seed-region analysis, ICtc analysis revealed patterns of connectivity that were more distinguished between thalamic clusters. ICtc analysis demonstrated thalamic connectivity to the primary motor cortex, which has eluded the analysis as well as previous studies based on averaged time series, and clarified thalamic connectivity to the hippocampus, caudate nucleus, and precuneus. The new findings elucidate functional organization of the thalamus and suggest that ICA clustering in combination with ICtc rather than seed-region analysis better distinguishes whole-brain connectivities among functional clusters of a brain region.

Altered resting-state functional connectivity in patients with chronic bilateral vestibular failure.

PubMed

Göttlich, Martin; Jandl, Nico M; Wojak, Jann F; Sprenger, Andreas; von der Gablentz, Janina; Münte, Thomas F; Krämer, Ulrike M; Helmchen, Christoph

2014-01-01

Patients with bilateral vestibular failure (BVF) suffer from gait unsteadiness, oscillopsia and impaired spatial orientation. Brain imaging studies applying caloric irrigation to patients with BVF have shown altered neural activity of cortical visual-vestibular interaction: decreased bilateral neural activity in the posterior insula and parietal operculum and decreased deactivations in the visual cortex. It is unknown how this affects functional connectivity in the resting brain and how changes in connectivity are related to vestibular impairment. We applied a novel data driven approach based on graph theory to investigate altered whole-brain resting-state functional connectivity in BVF patients (n= 22) compared to age- and gender-matched healthy controls (n= 25) using resting-state fMRI. Changes in functional connectivity were related to subjective (vestibular scores) and objective functional parameters of vestibular impairment, specifically, the adaptive changes during active (self-guided) and passive (investigator driven) head impulse test (HIT) which reflects the integrity of the vestibulo-ocular reflex (VOR). BVF patients showed lower bilateral connectivity in the posterior insula and parietal operculum but higher connectivity in the posterior cerebellum compared to controls. Seed-based analysis revealed stronger connectivity from the right posterior insula to the precuneus, anterior insula, anterior cingulate cortex and the middle frontal gyrus. Excitingly, functional connectivity in the supramarginal gyrus (SMG) of the inferior parietal lobe and posterior cerebellum correlated with the increase of VOR gain during active as compared to passive HIT, i.e., the larger the adaptive VOR changes the larger was the increase in regional functional connectivity. Using whole brain resting-state connectivity analysis in BVF patients we show that enduring bilateral deficient or missing vestibular input leads to changes in resting-state connectivity of the brain. These changes in the resting brain are robust and task-independent as they were found in the absence of sensory stimulation and without a region-related a priori hypothesis. Therefore they may indicate a fundamental disease-related change in the resting brain. They may account for the patients' persistent deficits in visuo-spatial attention, spatial orientation and unsteadiness. The relation of increasing connectivity in the inferior parietal lobe, specifically SMG, to improvement of VOR during active head movements reflects cortical plasticity in BVF and may play a clinical role in vestibular rehabilitation.

Individual variation in functional brain connectivity: implications for personalized approaches to psychiatric disease.

PubMed

Finn, Emily S; Todd Constable, R

2016-09-01

Functional brain connectivity measured with functional magnetic resonance imaging (fMRI) is a popular technique for investigating neural organization in both healthy subjects and patients with mental illness. Despite a rapidly growing body of literature, however, functional connectivity research has yet to deliver biomarkers that can aid psychiatric diagnosis or prognosis at the single-subject level. One impediment to developing such practical tools has been uncertainty regarding the ratio of intra- to interindividual variability in functional connectivity; in other words, how much variance is state- versus trait-related. Here, we review recent evidence that functional connectivity profiles are both reliable within subjects and unique across subjects, and that features of these profiles relate to behavioral phenotypes. Together, these results suggest the potential to discover reliable correlates of present and future illness and/or response to treatment in the strength of an individual's functional brain connections. Ultimately, this work could help develop personalized approaches to psychiatric illness.

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.

Whole-brain functional connectivity identification of functional dyspepsia.

PubMed

Nan, Jiaofen; Liu, Jixin; Li, Guoying; Xiong, Shiwei; Yan, Xuemei; Yin, Qing; Zeng, Fang; von Deneen, Karen M; Liang, Fanrong; Gong, Qiyong; Qin, Wei; Tian, Jie

2013-01-01

Recent neuroimaging studies have shown local brain aberrations in functional dyspepsia (FD) patients, yet little attention has been paid to the whole-brain resting-state functional network abnormalities. The purpose of this study was to investigate whether FD disrupts the patterns of whole-brain networks and the abnormal functional connectivity could reflect the severity of the disease. The dysfunctional interactions between brain regions at rest were investigated in FD patients as compared with 40 age- and gender- matched healthy controls. Multivariate pattern analysis was used to evaluate the discriminative power of our results for classifying patients from controls. In our findings, the abnormal brain functional connections were mainly situated within or across the limbic/paralimbic system, the prefrontal cortex, the tempo-parietal areas and the visual cortex. About 96% of the subjects among the original dataset were correctly classified by a leave one-out cross-validation approach, and 88% accuracy was also validated in a replication dataset. The classification features were significantly associated with the patients' dyspepsia symptoms, the self-rating depression scale and self-rating anxiety scale, but it was not correlated with duration of FD patients (p>0.05). Our results may indicate the effectiveness of the altered brain functional connections reflecting the disease pathophysiology underling FD. These dysfunctional connections may be the epiphenomena or causative agents of FD, which may be affected by clinical severity and its related emotional dimension of the disease rather than the clinical course.

Altered functional connectivity architecture of the brain in medication overuse headache using resting state fMRI.

PubMed

Chen, Zhiye; Chen, Xiaoyan; Liu, Mengqi; Dong, Zhao; Ma, Lin; Yu, Shengyuan

2017-12-01

Functional connectivity density (FCD) could identify the abnormal intrinsic and spontaneous activity over the whole brain, and a seed-based resting-state functional connectivity (RSFC) could further reveal the altered functional network with the identified brain regions. This may be an effective assessment strategy for headache research. This study is to investigate the RSFC architecture changes of the brain in the patients with medication overuse headache (MOH) using FCD and RSFC methods. 3D structure images and resting-state functional MRI data were obtained from 37 MOH patients, 18 episodic migraine (EM) patients and 32 normal controls (NCs). FCD was calculated to detect the brain regions with abnormal functional activity over the whole brain, and the seed-based RSFC was performed to explore the functional network changes in MOH and EM. The decreased FCD located in right parahippocampal gyrus, and the increased FCD located in left inferior parietal gyrus and right supramarginal gyrus in MOH compared with NC, and in right caudate and left insula in MOH compared with EM. RSFC revealed that decreased functional connectivity of the brain regions with decreased FCD anchored in the right dorsal-lateral prefrontal cortex, right frontopolar cortex in MOH, and in left temporopolar cortex and bilateral visual cortices in EM compared with NC, and in frontal-temporal-parietal pattern in MOH compared with EM. These results provided evidence that MOH and EM suffered from altered intrinsic functional connectivity architecture, and the current study presented a new perspective for understanding the neuromechanism of MOH and EM pathogenesis.

Connectivity-based parcellation of human cingulate cortex and its relation to functional specialization.

PubMed

Beckmann, Matthias; Johansen-Berg, Heidi; Rushworth, Matthew F S

2009-01-28

Whole-brain neuroimaging studies have demonstrated regional variations in function within human cingulate cortex. At the same time, regional variations in cingulate anatomical connections have been found in animal models. It has, however, been difficult to estimate the relationship between connectivity and function throughout the whole cingulate cortex within the human brain. In this study, magnetic resonance diffusion tractography was used to investigate cingulate probabilistic connectivity in the human brain with two approaches. First, an algorithm was used to search for regional variations in the probabilistic connectivity profiles of all cingulate cortex voxels with the whole of the rest of the brain. Nine subregions with distinctive connectivity profiles were identified. It was possible to characterize several distinct areas in the dorsal cingulate sulcal region. Several distinct regions were also found in subgenual and perigenual cortex. Second, the probabilities of connection between cingulate cortex and 11 predefined target regions of interest were calculated. Cingulate voxels with a high probability of connection with the different targets formed separate clusters within cingulate cortex. Distinct connectivity fingerprints characterized the likelihood of connections between the extracingulate target regions and the nine cingulate subregions. Last, a meta-analysis of 171 functional studies reporting cingulate activation was performed. Seven different cognitive conditions were selected and peak activation coordinates were plotted to create maps of functional localization within the cingulate cortex. Regional functional specialization was found to be related to regional differences in probabilistic anatomical connectivity.

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

Structural connectivity asymmetry in the neonatal brain.

PubMed

Ratnarajah, Nagulan; Rifkin-Graboi, Anne; Fortier, Marielle V; Chong, Yap Seng; Kwek, Kenneth; Saw, Seang-Mei; Godfrey, Keith M; Gluckman, Peter D; Meaney, Michael J; Qiu, Anqi

2013-07-15

Asymmetry of the neonatal brain is not yet understood at the level of structural connectivity. We utilized DTI deterministic tractography and structural network analysis based on graph theory to determine the pattern of structural connectivity asymmetry in 124 normal neonates. We tracted white matter axonal pathways characterizing interregional connections among brain regions and inferred asymmetry in left and right anatomical network properties. Our findings revealed that in neonates, small-world characteristics were exhibited, but did not differ between the two hemispheres, suggesting that neighboring brain regions connect tightly with each other, and that one region is only a few paths away from any other region within each hemisphere. Moreover, the neonatal brain showed greater structural efficiency in the left hemisphere than that in the right. In neonates, brain regions involved in motor, language, and memory functions play crucial roles in efficient communication in the left hemisphere, while brain regions involved in emotional processes play crucial roles in efficient communication in the right hemisphere. These findings suggest that even at birth, the topology of each cerebral hemisphere is organized in an efficient and compact manner that maps onto asymmetric functional specializations seen in adults, implying lateralized brain functions in infancy. Copyright © 2013 Elsevier Inc. All rights reserved.

Brain Events Underlying Episodic Memory Changes in Aging: A Longitudinal Investigation of Structural and Functional Connectivity.

PubMed

Fjell, Anders M; Sneve, Markus H; Storsve, Andreas B; Grydeland, Håkon; Yendiki, Anastasia; Walhovd, Kristine B

2016-03-01

Episodic memories are established and maintained by close interplay between hippocampus and other cortical regions, but degradation of a fronto-striatal network has been suggested to be a driving force of memory decline in aging. We wanted to directly address how changes in hippocampal-cortical versus striatal-cortical networks over time impact episodic memory with age. We followed 119 healthy participants (20-83 years) for 3.5 years with repeated tests of episodic verbal memory and magnetic resonance imaging for quantification of functional and structural connectivity and regional brain atrophy. While hippocampal-cortical functional connectivity predicted memory change in young, changes in cortico-striatal functional connectivity were related to change in recall in older adults. Within each age group, effects of functional and structural connectivity were anatomically closely aligned. Interestingly, the relationship between functional connectivity and memory was strongest in the age ranges where the rate of reduction of the relevant brain structure was lowest, implying selective impacts of the different brain events on memory. Together, these findings suggest a partly sequential and partly simultaneous model of brain events underlying cognitive changes in aging, where different functional and structural events are more or less important in various time windows, dismissing a simple uni-factorial view on neurocognitive aging. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

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

Antidepressant Effects of Electroconvulsive Therapy Correlate With Subgenual Anterior Cingulate Activity and Connectivity in Depression

PubMed Central

Liu, Yi; Du, Lian; Li, Yongmei; Liu, Haixia; Zhao, Wenjing; Liu, Dan; Zeng, Jinkun; Li, Xingbao; Fu, Yixiao; Qiu, Haitang; Li, Xirong; Qiu, Tian; Hu, Hua; Meng, Huaqing; Luo, Qinghua

2015-01-01

Abstract The mechanisms underlying the effects of electroconvulsive therapy (ECT) in major depressive disorder (MDD) are not fully understood. Resting-state functional magnetic resonance imaging (rs-fMRI) is a new tool to study the effects of brain stimulation interventions, particularly ECT. The authors aim to investigate the mechanisms of ECT in MDD by rs-fMRI. They used rs-fMRI to measure functional changes in the brain of first-episode, treatment-naive MDD patients (n = 23) immediately before and then following 8 ECT sessions (brief-pulse square-wave apparatus, bitemporal). They also computed voxel-wise amplitude of low-frequency fluctuation (ALFF) as a measure of regional brain activity and selected the left subgenual anterior cingulate cortex (sgACC) to evaluate functional connectivity between the sgACC and other brain regions. Increased regional brain activity measured by ALFF mainly in the left sgACC following ECT. Functional connectivity of the left sgACC increased in the ipsilateral parahippocampal gyrus, pregenual ACC, contralateral middle temporal pole, and orbitofrontal cortex. Importantly, reduction in depressive symptoms were negatively correlated with increased ALFF in the left sgACC and left hippocampus, and with distant functional connectivity between the left sgACC and contralateral middle temporal pole. That is, across subjects, as depression improved, regional brain activity in sgACC and its functional connectivity increased in the brain. Eight ECT sessions in MDD patients modulated activity in the sgACC and its networks. The antidepressant effects of ECT were negatively correlated with sgACC brain activity and connectivity. These findings suggest that sgACC-associated prefrontal-limbic structures are associated with the therapeutic effects of ECT in MDD. PMID:26559309

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.

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.

The CLAIR model: Extension of Brodmann areas based on brain oscillations and connectivity.

PubMed

Başar, Erol; Düzgün, Aysel

2016-05-01

Since the beginning of the last century, the localization of brain function has been represented by Brodmann areas, maps of the anatomic organization of the brain. They are used to broadly represent cortical structures with their given sensory-cognitive functions. In recent decades, the analysis of brain oscillations has become important in the correlation of brain functions. Moreover, spectral connectivity can provide further information on the dynamic connectivity between various structures. In addition, brain responses are dynamic in nature and structural localization is almost impossible, according to Luria (1966). Therefore, brain functions are very difficult to localize; hence, a combined analysis of oscillation and event-related coherences is required. In this study, a model termed as "CLAIR" is described to enrich and possibly replace the concept of the Brodmann areas. A CLAIR model with optimum function may take several years to develop, but this study sets out to lay its foundation. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

Decreased Cerebellar-Orbitofrontal Connectivity Correlates with Stuttering Severity: Whole-Brain Functional and Structural Connectivity Associations with Persistent Developmental Stuttering.

PubMed

Sitek, Kevin R; Cai, Shanqing; Beal, Deryk S; Perkell, Joseph S; Guenther, Frank H; Ghosh, Satrajit S

2016-01-01

Persistent developmental stuttering is characterized by speech production disfluency and affects 1% of adults. The degree of impairment varies widely across individuals and the neural mechanisms underlying the disorder and this variability remain poorly understood. Here we elucidate compensatory mechanisms related to this variability in impairment using whole-brain functional and white matter connectivity analyses in persistent developmental stuttering. We found that people who stutter had stronger functional connectivity between cerebellum and thalamus than people with fluent speech, while stutterers with the least severe symptoms had greater functional connectivity between left cerebellum and left orbitofrontal cortex (OFC). Additionally, people who stutter had decreased functional and white matter connectivity among the perisylvian auditory, motor, and speech planning regions compared to typical speakers, but greater functional connectivity between the right basal ganglia and bilateral temporal auditory regions. Structurally, disfluency ratings were negatively correlated with white matter connections to left perisylvian regions and to the brain stem. Overall, we found increased connectivity among subcortical and reward network structures in people who stutter compared to controls. These connections were negatively correlated with stuttering severity, suggesting the involvement of cerebellum and OFC may underlie successful compensatory mechanisms by more fluent stutterers.

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

Functional Imaging and Migraine: New Connections?

PubMed Central

Schwedt, Todd J.; Chong, Catherine D.

2015-01-01

Purpose of Review Over the last several years, a growing number of brain functional imaging studies have provided insights into mechanisms underlying migraine. This manuscript reviews the recent migraine functional neuroimaging literature and provides recommendations for future studies that will help fill knowledge gaps. Recent Findings Positron emission tomography (PET) and functional magnetic resonance imaging (fMRI) studies have identified brain regions that might be responsible for mediating the onset of a migraine attack and those associated with migraine symptoms. Enhanced activation of brain regions that facilitate processing of sensory stimuli suggests a mechanism by which migraineurs are hypersensitive to visual, olfactory, and cutaneous stimuli. Resting state functional connectivity MRI studies have identified numerous brain regions and functional networks with atypical functional connectivity in migraineurs, suggesting that migraine is associated with aberrant brain functional organization. Summary fMRI and PET studies that have identified brain regions and brain networks that are atypical in migraine have helped to describe the neurofunctional basis for migraine symptoms. Future studies should compare functional imaging findings in migraine to other headache and pain disorders and should explore the utility of functional imaging data as biomarkers for diagnostic and treatment purposes. PMID:25887764

Functional Connectivity Magnetic Resonance Imaging Classification of Autism

ERIC Educational Resources Information Center

Anderson, Jeffrey S.; Nielsen, Jared A.; Froehlich, Alyson L.; DuBray, Molly B.; Druzgal, T. Jason; Cariello, Annahir N.; Cooperrider, Jason R.; Zielinski, Brandon A.; Ravichandran, Caitlin; Fletcher, P. Thomas; Alexander, Andrew L.; Bigler, Erin D.; Lange, Nicholas; Lainhart, Janet E.

2011-01-01

Group differences in resting state functional magnetic resonance imaging connectivity between individuals with autism and typically developing controls have been widely replicated for a small number of discrete brain regions, yet the whole-brain distribution of connectivity abnormalities in autism is not well characterized. It is also unclear…

Disrupted Functional Connectivity with Dopaminergic Midbrain in Cocaine Abusers

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

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

Chronic cocaine use is associated with disrupted dopaminergic neurotransmission but how this disruption affects overall brain function (other than reward/motivation) is yet to be fully investigated. Here we test the hypothesis that cocaine addicted subjects will have disrupted functional connectivity between the midbrain (where dopamine neurons are located) and cortical and subcortical brain regions during the performance of a sustained attention task. We measured brain activation and functional connectivity with fMRI in 20 cocaine abusers and 20 matched controls. When compared to controls, cocaine abusers had lower positive functional connectivity of midbrain with thalamus, cerebellum, and rostral cingulate, and thismore » was associated with decreased activation in thalamus and cerebellum and enhanced deactivation in rostral cingulate. These findings suggest that decreased functional connectivity of the midbrain interferes with the activation and deactivation signals associated with sustained attention in cocaine addicts.« less

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

Disruption of functional networks in dyslexia: a whole-brain, data-driven analysis of connectivity.

PubMed

Finn, Emily S; Shen, Xilin; Holahan, John M; Scheinost, Dustin; Lacadie, Cheryl; Papademetris, Xenophon; Shaywitz, Sally E; Shaywitz, Bennett A; Constable, R Todd

2014-09-01

Functional connectivity analyses of functional magnetic resonance imaging data are a powerful tool for characterizing brain networks and how they are disrupted in neural disorders. However, many such analyses examine only one or a small number of a priori seed regions. Studies that consider the whole brain frequently rely on anatomic atlases to define network nodes, which might result in mixing distinct activation time-courses within a single node. Here, we improve upon previous methods by using a data-driven brain parcellation to compare connectivity profiles of dyslexic (DYS) versus non-impaired (NI) readers in the first whole-brain functional connectivity analysis of dyslexia. Whole-brain connectivity was assessed in children (n = 75; 43 NI, 32 DYS) and adult (n = 104; 64 NI, 40 DYS) readers. Compared to NI readers, DYS readers showed divergent connectivity within the visual pathway and between visual association areas and prefrontal attention areas; increased right-hemisphere connectivity; reduced connectivity in the visual word-form area (part of the left fusiform gyrus specialized for printed words); and persistent connectivity to anterior language regions around the inferior frontal gyrus. Together, findings suggest that NI readers are better able to integrate visual information and modulate their attention to visual stimuli, allowing them to recognize words on the basis of their visual properties, whereas DYS readers recruit altered reading circuits and rely on laborious phonology-based "sounding out" strategies into adulthood. These results deepen our understanding of the neural basis of dyslexia and highlight the importance of synchrony between diverse brain regions for successful reading. © 2013 Society of Biological Psychiatry Published by Society of Biological Psychiatry All rights reserved.

Brain functional connectivity changes in children that differ in impulsivity temperamental trait

PubMed Central

Inuggi, Alberto; Sanz-Arigita, Ernesto; González-Salinas, Carmen; Valero-García, Ana V.; García-Santos, Jose M.; Fuentes, Luis J.

2014-01-01

Impulsivity is a core personality trait forming part of normal behavior and contributing to adaptive functioning. However, in typically developing children, altered patterns of impulsivity constitute a risk factor for the development of behavioral problems. Since both pathological and non-pathological states are commonly characterized by continuous transitions, we used a correlative approach to investigate the potential link between personality and brain dynamics. We related brain functional connectivity of typically developing children, measured with magnetic resonance imaging at rest, with their impulsivity scores obtained from a questionnaire completed by their parents. We first looked for areas within the default mode network (DMN) whose functional connectivity might be modulated by trait impulsivity. Then, we calculated the functional connectivity among these regions and the rest of the brain in order to assess if impulsivity trait altered their relationships. We found two DMN clusters located at the posterior cingulate cortex and the right angular gyrus which were negatively correlated with impulsivity scores. The whole-brain correlation analysis revealed the classic network of correlating and anti-correlating areas with respect to the DMN. The impulsivity trait modulated such pattern showing that the canonical anti-phasic relation between DMN and action-related network was reduced in high impulsive children. These results represent the first evidence that the impulsivity, measured as personality trait assessed through parents' report, exerts a modulatory influence over the functional connectivity of resting state brain networks in typically developing children. The present study goes further to connect developmental approaches, mainly based on data collected through the use of questionnaires, and behavioral neuroscience, interested in how differences in brain structure and functions reflect in differences in behavior. PMID:24834038

Brain functional connectivity changes in children that differ in impulsivity temperamental trait.

PubMed

Inuggi, Alberto; Sanz-Arigita, Ernesto; González-Salinas, Carmen; Valero-García, Ana V; García-Santos, Jose M; Fuentes, Luis J

2014-01-01

Impulsivity is a core personality trait forming part of normal behavior and contributing to adaptive functioning. However, in typically developing children, altered patterns of impulsivity constitute a risk factor for the development of behavioral problems. Since both pathological and non-pathological states are commonly characterized by continuous transitions, we used a correlative approach to investigate the potential link between personality and brain dynamics. We related brain functional connectivity of typically developing children, measured with magnetic resonance imaging at rest, with their impulsivity scores obtained from a questionnaire completed by their parents. We first looked for areas within the default mode network (DMN) whose functional connectivity might be modulated by trait impulsivity. Then, we calculated the functional connectivity among these regions and the rest of the brain in order to assess if impulsivity trait altered their relationships. We found two DMN clusters located at the posterior cingulate cortex and the right angular gyrus which were negatively correlated with impulsivity scores. The whole-brain correlation analysis revealed the classic network of correlating and anti-correlating areas with respect to the DMN. The impulsivity trait modulated such pattern showing that the canonical anti-phasic relation between DMN and action-related network was reduced in high impulsive children. These results represent the first evidence that the impulsivity, measured as personality trait assessed through parents' report, exerts a modulatory influence over the functional connectivity of resting state brain networks in typically developing children. The present study goes further to connect developmental approaches, mainly based on data collected through the use of questionnaires, and behavioral neuroscience, interested in how differences in brain structure and functions reflect in differences in behavior.

Effect of deafferentation from spinal anesthesia on pain sensitivity and resting-state functional brain connectivity in healthy male volunteers.

PubMed

Niesters, Marieke; Sitsen, Elske; Oudejans, Linda; Vuyk, Jaap; Aarts, Leon P H J; Rombouts, Serge A R B; de Rover, Mischa; Khalili-Mahani, Najmeh; Dahan, Albert

2014-08-01

Patients may perceive paradoxical heat sensation during spinal anesthesia. This could be due to deafferentation-related functional changes at cortical, subcortical, or spinal levels. In the current study, the effect of spinal deafferentation on sensory (pain) sensitivity was studied and linked to whole-brain functional connectivity as assessed by resting-state functional magnetic resonance imaging (RS-fMRI) imaging. Deafferentation was induced by sham or spinal anesthesia (15 mg bupivacaine injected at L3-4) in 12 male volunteers. RS-fMRI brain connectivity was determined in relation to eight predefined and seven thalamic resting-state networks (RSNs) and measured before, and 1 and 2 h after spinal/sham injection. To measure the effect of deafferentation on pain sensitivity, responses to heat pain were measured at 15-min intervals on nondeafferented skin and correlated to RS-fMRI connectivity data. Spinal anesthesia altered functional brain connectivity within brain regions involved in the sensory discriminative (i.e., pain intensity related) and affective dimensions of pain perception in relation to somatosensory and thalamic RSNs. A significant enhancement of pain sensitivity on nondeafferented skin was observed after spinal anesthesia compared to sham (area-under-the-curve [mean (SEM)]: 190.4 [33.8] versus 13.7 [7.2]; p<0.001), which significantly correlated to functional connectivity changes observed within the thalamus in relation to the thalamo-prefrontal network, and in the anterior cingulate cortex and insula in relation to the thalamo-parietal network. Enhanced pain sensitivity from spinal deafferentation correlated with functional connectivity changes within brain regions involved in affective and sensory pain processing and areas involved in descending control of pain.

Evoked itch perception is associated with changes in functional brain connectivity.

PubMed

Desbordes, Gaëlle; Li, Ang; Loggia, Marco L; Kim, Jieun; Schalock, Peter C; Lerner, Ethan; Tran, Thanh N; Ring, Johannes; Rosen, Bruce R; Kaptchuk, Ted J; Pfab, Florian; Napadow, Vitaly

2015-01-01

Chronic itch, a highly debilitating condition, has received relatively little attention in the neuroimaging literature. Recent studies suggest that brain regions supporting itch in chronic itch patients encompass sensorimotor and salience networks, and corticostriatal circuits involved in motor preparation for scratching. However, how these different brain areas interact with one another in the context of itch is still unknown. We acquired BOLD fMRI scans in 14 atopic dermatitis patients to investigate resting-state functional connectivity before and after allergen-induced itch exacerbated the clinical itch perception in these patients. A seed-based analysis revealed decreased functional connectivity from baseline resting state to the evoked-itch state between several itch-related brain regions, particularly the insular and cingulate cortices and basal ganglia, where decreased connectivity was significantly correlated with increased levels of perceived itch. In contrast, evoked itch increased connectivity between key nodes of the frontoparietal control network (superior parietal lobule and dorsolateral prefrontal cortex), where higher increase in connectivity was correlated with a lesser increase in perceived itch, suggesting that greater interaction between nodes of this executive attention network serves to limit itch sensation via enhanced top-down regulation. Overall, our results provide the first evidence of itch-dependent changes in functional connectivity across multiple brain regions.

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

Altered functional connectivity links in neuroleptic-naïve and neuroleptic-treated patients with schizophrenia, and their relation to symptoms including volition

PubMed Central

Pu, Weidan; Rolls, Edmund T.; Guo, Shuixia; Liu, Haihong; Yu, Yun; Xue, Zhimin; Feng, Jianfeng; Liu, Zhening

2014-01-01

In order to analyze functional connectivity in untreated and treated patients with schizophrenia, resting-state fMRI data were obtained for whole-brain functional connectivity analysis from 22 first-episode neuroleptic-naïve schizophrenia (NNS), 61 first-episode neuroleptic-treated schizophrenia (NTS) patients, and 60 healthy controls (HC). Reductions were found in untreated and treated patients in the functional connectivity between the posterior cingulate gyrus and precuneus, and this was correlated with the reduction in volition from the Positive and Negative Symptoms Scale (PANSS), that is in the willful initiation, sustenance, and control of thoughts, behavior, movements, and speech, and with the general and negative symptoms. In addition in both patient groups interhemispheric functional connectivity was weaker between the orbitofrontal cortex, amygdala and temporal pole. These functional connectivity changes and the related symptoms were not treated by the neuroleptics. Differences between the patient groups were that there were more strong functional connectivity links in the NNS patients (including in hippocampal, frontal, and striatal circuits) than in the NTS patients. These findings with a whole brain analysis in untreated and treated patients with schizophrenia provide evidence on some of the brain regions implicated in the volitional, other general, and negative symptoms, of schizophrenia that are not treated by neuroleptics so have implications for the development of other treatments; and provide evidence on some brain systems in which neuroleptics do alter the functional connectivity. PMID:25389520

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

Functional connectivity analysis of the neural bases of emotion regulation: A comparison of independent component method with density-based k-means clustering method.

PubMed

Zou, Ling; Guo, Qian; Xu, Yi; Yang, Biao; Jiao, Zhuqing; Xiang, Jianbo

2016-04-29

Functional magnetic resonance imaging (fMRI) is an important tool in neuroscience for assessing connectivity and interactions between distant areas of the brain. To find and characterize the coherent patterns of brain activity as a means of identifying brain systems for the cognitive reappraisal of the emotion task, both density-based k-means clustering and independent component analysis (ICA) methods can be applied to characterize the interactions between brain regions involved in cognitive reappraisal of emotion. Our results reveal that compared with the ICA method, the density-based k-means clustering method provides a higher sensitivity of polymerization. In addition, it is more sensitive to those relatively weak functional connection regions. Thus, the study concludes that in the process of receiving emotional stimuli, the relatively obvious activation areas are mainly distributed in the frontal lobe, cingulum and near the hypothalamus. Furthermore, density-based k-means clustering method creates a more reliable method for follow-up studies of brain functional connectivity.

Connectivity-based neurofeedback: Dynamic causal modeling for real-time fMRI☆

PubMed Central

Koush, Yury; Rosa, Maria Joao; Robineau, Fabien; Heinen, Klaartje; W. Rieger, Sebastian; Weiskopf, Nikolaus; Vuilleumier, Patrik; Van De Ville, Dimitri; Scharnowski, Frank

2013-01-01

Neurofeedback based on real-time fMRI is an emerging technique that can be used to train voluntary control of brain activity. Such brain training has been shown to lead to behavioral effects that are specific to the functional role of the targeted brain area. However, real-time fMRI-based neurofeedback so far was limited to mainly training localized brain activity within a region of interest. Here, we overcome this limitation by presenting near real-time dynamic causal modeling in order to provide feedback information based on connectivity between brain areas rather than activity within a single brain area. Using a visual–spatial attention paradigm, we show that participants can voluntarily control a feedback signal that is based on the Bayesian model comparison between two predefined model alternatives, i.e. the connectivity between left visual cortex and left parietal cortex vs. the connectivity between right visual cortex and right parietal cortex. Our new approach thus allows for training voluntary control over specific functional brain networks. Because most mental functions and most neurological disorders are associated with network activity rather than with activity in a single brain region, this novel approach is an important methodological innovation in order to more directly target functionally relevant brain networks. PMID:23668967

The Psychoactive Designer Drug and Bath Salt Constituent MDPV Causes Widespread Disruption of Brain Functional Connectivity

PubMed Central

Colon-Perez, Luis M; Tran, Kelvin; Thompson, Khalil; Pace, Michael C; Blum, Kenneth; Goldberger, Bruce A; Gold, Mark S; Bruijnzeel, Adriaan W; Setlow, Barry; Febo, Marcelo

2016-01-01

The abuse of ‘bath salts' has raised concerns because of their adverse effects, which include delirium, violent behavior, and suicide ideation in severe cases. The bath salt constituent 3,4-methylenedioxypyrovalerone (MDPV) has been closely linked to these and other adverse effects. The abnormal behavioral pattern produced by acute high-dose MDPV intake suggests possible disruptions of neural communication between brain regions. Therefore, we determined if MDPV exerts disruptive effects on brain functional connectivity, particularly in areas of the prefrontal cortex. Male rats were imaged following administration of a single dose of MDPV (0.3, 1.0, or 3.0 mg/kg) or saline. Resting state brain blood oxygenation level-dependent (BOLD) images were acquired at 4.7 T. To determine the role of dopamine transmission in MDPV-induced changes in functional connectivity, a group of rats received the dopamine D1/D2 receptor antagonist cis-flupenthixol (0.5 mg/kg) 30 min before MDPV. MDPV dose-dependently reduced functional connectivity. Detailed analysis of its effects revealed that connectivity between frontal cortical and striatal areas was reduced. This included connectivity between the prelimbic prefrontal cortex and other areas of the frontal cortex and the insular cortex with hypothalamic, ventral, and dorsal striatal areas. Although the reduced connectivity appeared widespread, connectivity between these regions and somatosensory cortex was not as severely affected. Dopamine receptor blockade did not prevent the MDPV-induced decrease in functional connectivity. The results provide a novel signature of MDPV's in vivo mechanism of action. Reduced brain functional connectivity has been reported in patients suffering from psychosis and has been linked to cognitive dysfunction, audiovisual hallucinations, and negative affective states akin to those reported for MDPV-induced intoxication. The present results suggest that disruption of functional connectivity networks involving frontal cortical and striatal regions could contribute to the adverse effects of MDPV. PMID:26997298

Mapping Resting-State Brain Networks in Conscious Animals

PubMed Central

Zhang, Nanyin; Rane, Pallavi; Huang, Wei; Liang, Zhifeng; Kennedy, David; Frazier, Jean A.; King, Jean

2010-01-01

In the present study we mapped brain functional connectivity in the conscious rat at the “resting state” based on intrinsic blood-oxygenation-level dependent (BOLD) fluctuations. The conscious condition eliminated potential confounding effects of anesthetic agents on the connectivity between brain regions. Indeed, using correlational analysis we identified multiple cortical and subcortical regions that demonstrated temporally synchronous variation with anatomically well-defined regions that are crucial to cognitive and emotional information processing including the prefrontal cortex (PFC), thalamus and retrosplenial cortex. The functional connectivity maps created were stringently validated by controlling for false positive detection of correlation, the physiologic basis of the signal source, as well as quantitatively evaluating the reproducibility of maps. Taken together, the present study has demonstrated the feasibility of assessing functional connectivity in conscious animals using fMRI and thus provided a convenient and non-invasive tool to systematically investigate the connectional architecture of selected brain networks in multiple animal models. PMID:20382183

Fractionation of social brain circuits in autism spectrum disorders.

PubMed

Gotts, Stephen J; Simmons, W Kyle; Milbury, Lydia A; Wallace, Gregory L; Cox, Robert W; Martin, Alex

2012-09-01

Autism spectrum disorders are developmental disorders characterized by impairments in social and communication abilities and repetitive behaviours. Converging neuroscientific evidence has suggested that the neuropathology of autism spectrum disorders is widely distributed, involving impaired connectivity throughout the brain. Here, we evaluate the hypothesis that decreased connectivity in high-functioning adolescents with an autism spectrum disorder relative to typically developing adolescents is concentrated within domain-specific circuits that are specialized for social processing. Using a novel whole-brain connectivity approach in functional magnetic resonance imaging, we found that not only are decreases in connectivity most pronounced between regions of the social brain but also they are selective to connections between limbic-related brain regions involved in affective aspects of social processing from other parts of the social brain that support language and sensorimotor processes. This selective pattern was independently obtained for correlations with measures of social symptom severity, implying a fractionation of the social brain in autism spectrum disorders at the level of whole circuits.

Fractionation of social brain circuits in autism spectrum disorders

PubMed Central

Simmons, W. Kyle; Milbury, Lydia A.; Wallace, Gregory L.; Cox, Robert W.; Martin, Alex

2012-01-01

Autism spectrum disorders are developmental disorders characterized by impairments in social and communication abilities and repetitive behaviours. Converging neuroscientific evidence has suggested that the neuropathology of autism spectrum disorders is widely distributed, involving impaired connectivity throughout the brain. Here, we evaluate the hypothesis that decreased connectivity in high-functioning adolescents with an autism spectrum disorder relative to typically developing adolescents is concentrated within domain-specific circuits that are specialized for social processing. Using a novel whole-brain connectivity approach in functional magnetic resonance imaging, we found that not only are decreases in connectivity most pronounced between regions of the social brain but also they are selective to connections between limbic-related brain regions involved in affective aspects of social processing from other parts of the social brain that support language and sensorimotor processes. This selective pattern was independently obtained for correlations with measures of social symptom severity, implying a fractionation of the social brain in autism spectrum disorders at the level of whole circuits. PMID:22791801

Differences in brain functional connectivity at resting state in neonates born to healthy obese or normal-weight mothers

USDA-ARS?s Scientific Manuscript database

Recent studies have shown associations between maternal obesity at pre- or early pregnancy and long-term neurodevelopment in children, suggesting in utero effects of maternal obesity on offspring brain development. In this study, we examined whether brain functional connectivity to the prefrontal lo...

Joint Analysis of Band-Specific Functional Connectivity and Signal Complexity in Autism

ERIC Educational Resources Information Center

Ghanbari, Yasser; Bloy, Luke; Edgar, J. Christopher; Blaskey, Lisa; Verma, Ragini; Roberts, Timothy P. L.

2015-01-01

Examination of resting state brain activity using electrophysiological measures like complexity as well as functional connectivity is of growing interest in the study of autism spectrum disorders (ASD). The present paper jointly examined complexity and connectivity to obtain a more detailed characterization of resting state brain activity in ASD.…

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.

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

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.

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.

Finding the imposter: brain connectivity of lesions causing delusional misidentifications.

PubMed

Darby, R Ryan; Laganiere, Simon; Pascual-Leone, Alvaro; Prasad, Sashank; Fox, Michael D

2017-02-01

SEE MCKAY AND FURL DOI101093/AWW323 FOR A SCIENTIFIC COMMENTARY ON THIS ARTICLE: Focal brain injury can sometimes lead to bizarre symptoms, such as the delusion that a family member has been replaced by an imposter (Capgras syndrome). How a single brain lesion could cause such a complex disorder is unclear, leading many to speculate that concurrent delirium, psychiatric disease, dementia, or a second lesion is required. Here we instead propose that Capgras and other delusional misidentification syndromes arise from single lesions at unique locations within the human brain connectome. This hypothesis is motivated by evidence that symptoms emerge from sites functionally connected to a lesion location, not just the lesion location itself. First, 17 cases of lesion-induced delusional misidentifications were identified and lesion locations were mapped to a common brain atlas. Second, lesion network mapping was used to identify brain regions functionally connected to the lesion locations. Third, regions involved in familiarity perception and belief evaluation, two processes thought to be abnormal in delusional misidentifications, were identified using meta-analyses of previous functional magnetic resonance imaging studies. We found that all 17 lesion locations were functionally connected to the left retrosplenial cortex, the region most activated in functional magnetic resonance imaging studies of familiarity. Similarly, 16 of 17 lesion locations were functionally connected to the right frontal cortex, the region most activated in functional magnetic resonance imaging studies of expectation violation, a component of belief evaluation. This connectivity pattern was highly specific for delusional misidentifications compared to four other lesion-induced neurological syndromes (P < 0.0001). Finally, 15 lesions causing other types of delusions were connected to expectation violation (P < 0.0001) but not familiarity regions, demonstrating specificity for delusion content. Our results provide potential neuroanatomical correlates for impaired familiarity perception and belief evaluation in patients with delusional misidentifications. More generally, we demonstrate a mechanism by which a single lesion can cause a complex neuropsychiatric syndrome based on that lesion's unique pattern of functional connectivity, without the need for pre-existing or hidden pathology. © 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.

Decreased integration and information capacity in stroke measured by whole brain models of resting state activity.

PubMed

Adhikari, Mohit H; Hacker, Carl D; Siegel, Josh S; Griffa, Alessandra; Hagmann, Patric; Deco, Gustavo; Corbetta, Maurizio

2017-04-01

While several studies have shown that focal lesions affect the communication between structurally normal regions of the brain, and that these changes may correlate with behavioural deficits, their impact on brain's information processing capacity is currently unknown. Here we test the hypothesis that focal lesions decrease the brain's information processing capacity, of which changes in functional connectivity may be a measurable correlate. To measure processing capacity, we turned to whole brain computational modelling to estimate the integration and segregation of information in brain networks. First, we measured functional connectivity between different brain areas with resting state functional magnetic resonance imaging in healthy subjects (n = 26), and subjects who had suffered a cortical stroke (n = 36). We then used a whole-brain network model that coupled average excitatory activities of local regions via anatomical connectivity. Model parameters were optimized in each healthy or stroke participant to maximize correlation between model and empirical functional connectivity, so that the model's effective connectivity was a veridical representation of healthy or lesioned brain networks. Subsequently, we calculated two model-based measures: 'integration', a graph theoretical measure obtained from functional connectivity, which measures the connectedness of brain networks, and 'information capacity', an information theoretical measure that cannot be obtained empirically, representative of the segregative ability of brain networks to encode distinct stimuli. We found that both measures were decreased in stroke patients, as compared to healthy controls, particularly at the level of resting-state networks. Furthermore, we found that these measures, especially information capacity, correlate with measures of behavioural impairment and the segregation of resting-state networks empirically measured. This study shows that focal lesions affect the brain's ability to represent stimuli and task states, and that information capacity measured through whole brain models is a theory-driven measure of processing capacity that could be used as a biomarker of injury for outcome prediction or target for rehabilitation intervention. © The Author (2017). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

A whole-brain computational modeling approach to explain the alterations in resting-state functional connectivity during progression of Alzheimer's disease.

PubMed

Demirtaş, Murat; Falcon, Carles; Tucholka, Alan; Gispert, Juan Domingo; Molinuevo, José Luis; Deco, Gustavo

2017-01-01

Alzheimer's disease (AD) is the most common dementia with dramatic consequences. The research in structural and functional neuroimaging showed altered brain connectivity in AD. In this study, we investigated the whole-brain resting state functional connectivity (FC) of the subjects with preclinical Alzheimer's disease (PAD), mild cognitive impairment due to AD (MCI) and mild dementia due to Alzheimer's disease (AD), the impact of APOE4 carriership, as well as in relation to variations in core AD CSF biomarkers. The synchronization in the whole-brain was monotonously decreasing during the course of the disease progression. Furthermore, in AD patients we found widespread significant decreases in functional connectivity (FC) strengths particularly in the brain regions with high global connectivity. We employed a whole-brain computational modeling approach to study the mechanisms underlying these alterations. To characterize the causal interactions between brain regions, we estimated the effective connectivity (EC) in the model. We found that the significant EC differences in AD were primarily located in left temporal lobe. Then, we systematically manipulated the underlying dynamics of the model to investigate simulated changes in FC based on the healthy control subjects. Furthermore, we found distinct patterns involving CSF biomarkers of amyloid-beta (Aβ1 - 42) total tau (t-tau) and phosphorylated tau (p-tau). CSF Aβ1 - 42 was associated to the contrast between healthy control subjects and clinical groups. Nevertheless, tau CSF biomarkers were associated to the variability in whole-brain synchronization and sensory integration regions. These associations were robust across clinical groups, unlike the associations that were found for CSF Aβ1 - 42. APOE4 carriership showed no significant correlations with the connectivity measures.

Long-term neural and physiological phenotyping of a single human

PubMed Central

Poldrack, Russell A.; Laumann, Timothy O.; Koyejo, Oluwasanmi; Gregory, Brenda; Hover, Ashleigh; Chen, Mei-Yen; Gorgolewski, Krzysztof J.; Luci, Jeffrey; Joo, Sung Jun; Boyd, Ryan L.; Hunicke-Smith, Scott; Simpson, Zack Booth; Caven, Thomas; Sochat, Vanessa; Shine, James M.; Gordon, Evan; Snyder, Abraham Z.; Adeyemo, Babatunde; Petersen, Steven E.; Glahn, David C.; Reese Mckay, D.; Curran, Joanne E.; Göring, Harald H. H.; Carless, Melanie A.; Blangero, John; Dougherty, Robert; Leemans, Alexander; Handwerker, Daniel A.; Frick, Laurie; Marcotte, Edward M.; Mumford, Jeanette A.

2015-01-01

Psychiatric disorders are characterized by major fluctuations in psychological function over the course of weeks and months, but the dynamic characteristics of brain function over this timescale in healthy individuals are unknown. Here, as a proof of concept to address this question, we present the MyConnectome project. An intensive phenome-wide assessment of a single human was performed over a period of 18 months, including functional and structural brain connectivity using magnetic resonance imaging, psychological function and physical health, gene expression and metabolomics. A reproducible analysis workflow is provided, along with open access to the data and an online browser for results. We demonstrate dynamic changes in brain connectivity over the timescales of days to months, and relations between brain connectivity, gene expression and metabolites. This resource can serve as a testbed to study the joint dynamics of human brain and metabolic function over time, an approach that is critical for the development of precision medicine strategies for brain disorders. PMID:26648521

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.

Disruption of functional networks in dyslexia: A whole-brain, data-driven analysis of connectivity

PubMed Central

Finn, Emily S.; Shen, Xilin; Holahan, John M.; Scheinost, Dustin; Lacadie, Cheryl; Papademetris, Xenophon; Shaywitz, Sally E.; Shaywitz, Bennett A.; Constable, R. Todd

2013-01-01

Background Functional connectivity analyses of fMRI data are a powerful tool for characterizing brain networks and how they are disrupted in neural disorders. However, many such analyses examine only one or a small number of a priori seed regions. Studies that consider the whole brain frequently rely on anatomic atlases to define network nodes, which may result in mixing distinct activation timecourses within a single node. Here, we improve upon previous methods by using a data-driven brain parcellation to compare connectivity profiles of dyslexic (DYS) versus non-impaired (NI) readers in the first whole-brain functional connectivity analysis of dyslexia. Methods Whole-brain connectivity was assessed in children (n = 75; 43 NI, 32 DYS) and adult (n = 104; 64 NI, 40 DYS) readers. Results Compared to NI readers, DYS readers showed divergent connectivity within the visual pathway and between visual association areas and prefrontal attention areas; increased right-hemisphere connectivity; reduced connectivity in the visual word-form area (part of the left fusiform gyrus specialized for printed words); and persistent connectivity to anterior language regions around the inferior frontal gyrus. Conclusions Together, findings suggest that NI readers are better able to integrate visual information and modulate their attention to visual stimuli, allowing them to recognize words based on their visual properties, while DYS readers recruit altered reading circuits and rely on laborious phonology-based “sounding out” strategies into adulthood. These results deepen our understanding of the neural basis of dyslexia and highlight the importance of synchrony between diverse brain regions for successful reading. PMID:24124929

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,…

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

Normalisation of brain connectivity through compensatory behaviour, despite congenital hand absence.

PubMed

Hahamy, Avital; Sotiropoulos, Stamatios N; Henderson Slater, David; Malach, Rafael; Johansen-Berg, Heidi; Makin, Tamar R

2015-01-06

Previously we showed, using task-evoked fMRI, that compensatory intact hand usage after amputation facilitates remapping of limb representations in the cortical territory of the missing hand (Makin et al., 2013a). Here we show that compensatory arm usage in individuals born without a hand (one-handers) reflects functional connectivity of spontaneous brain activity in the cortical hand region. Compared with two-handed controls, one-handers showed reduced symmetry of hand region inter-hemispheric resting-state functional connectivity and corticospinal white matter microstructure. Nevertheless, those one-handers who more frequently use their residual (handless) arm for typically bimanual daily tasks also showed more symmetrical functional connectivity of the hand region, demonstrating that adaptive behaviour drives long-range brain organisation. We therefore suggest that compensatory arm usage maintains symmetrical sensorimotor functional connectivity in one-handers. Since variability in spontaneous functional connectivity in our study reflects ecological behaviour, we propose that inter-hemispheric symmetry, typically observed in resting sensorimotor networks, depends on coordinated motor behaviour in daily life.

Microstructural and functional connectivity in the developing preterm brain

PubMed Central

Lubsen, Julia; Vohr, Betty; Myers, Eliza; Hampson, Michelle; Lacadie, Cheryl; Schneider, Karen C.; Katz, Karol H.; Constable, R. Todd; Ment, Laura R.

2011-01-01

Prematurely born children are at increased risk for cognitive deficits, but the neurobiological basis of these findings remains poorly understood. Since variations in neural circuitry may influence performance on cognitive tasks, recent investigations have explored the impact of preterm birth on connectivity in the developing brain. Diffusion tensor imaging studies demonstrate widespread alterations in fractional anisotropy, a measure of axonal integrity and microstructural connectivity, throughout the developing preterm brain. Functional connectivity studies report that preterm neonates, children and adolescents exhibit alterations in both resting state and task-based connectivity when compared to term control subjects. Taken together, these data suggest that neurodevelopmental impairment following preterm birth may represent a disease of neural connectivity. PMID:21255705

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

Decreased Cerebellar-Orbitofrontal Connectivity Correlates with Stuttering Severity: Whole-Brain Functional and Structural Connectivity Associations with Persistent Developmental Stuttering

PubMed Central

Sitek, Kevin R.; Cai, Shanqing; Beal, Deryk S.; Perkell, Joseph S.; Guenther, Frank H.; Ghosh, Satrajit S.

2016-01-01

Persistent developmental stuttering is characterized by speech production disfluency and affects 1% of adults. The degree of impairment varies widely across individuals and the neural mechanisms underlying the disorder and this variability remain poorly understood. Here we elucidate compensatory mechanisms related to this variability in impairment using whole-brain functional and white matter connectivity analyses in persistent developmental stuttering. We found that people who stutter had stronger functional connectivity between cerebellum and thalamus than people with fluent speech, while stutterers with the least severe symptoms had greater functional connectivity between left cerebellum and left orbitofrontal cortex (OFC). Additionally, people who stutter had decreased functional and white matter connectivity among the perisylvian auditory, motor, and speech planning regions compared to typical speakers, but greater functional connectivity between the right basal ganglia and bilateral temporal auditory regions. Structurally, disfluency ratings were negatively correlated with white matter connections to left perisylvian regions and to the brain stem. Overall, we found increased connectivity among subcortical and reward network structures in people who stutter compared to controls. These connections were negatively correlated with stuttering severity, suggesting the involvement of cerebellum and OFC may underlie successful compensatory mechanisms by more fluent stutterers. PMID:27199712

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

A Complex Interplay of Vitamin B1 and B6 Metabolism with Cognition, Brain Structure, and Functional Connectivity in Older Adults.

PubMed

Jannusch, Kai; Jockwitz, Christiane; Bidmon, Hans-Jürgen; Moebus, Susanne; Amunts, Katrin; Caspers, Svenja

2017-01-01

Aging is associated with brain atrophy, functional brain network reorganization and decline of cognitive performance, albeit characterized by high interindividual variability. Among environmental influencing factors accounting for this variability, nutrition and particularly vitamin supply is thought to play an important role. While evidence exists that supplementation of vitamins B6 and B1 might be beneficial for cognition and brain structure, at least in deficient states and neurodegenerative diseases, little is known about this relation during healthy aging and in relation to reorganization of functional brain networks. We thus assessed the relation between blood levels of vitamins B1 and B6 and cognitive performance, cortical folding, and functional resting-state connectivity in a large sample of older adults ( N > 600; age: 55-85 years), drawn from the population-based 1000BRAINS study. In addition to blood sampling, subjects underwent structural and functional resting-state neuroimaging as well as extensive neuropsychological testing in the domains of executive functions, (working) memory, attention, and language. Brain regions showing changes in the local gyrification index as calculated using FreeSurfer in relation to vitamin levels were used for subsequent seed-based resting-state functional connectivity analysis. For B6, a positive correlation with local cortical folding was found throughout the brain, while only slight changes in functional connectivity were observed. Contrarily, for B1, a negative correlation with cortical folding as well as problem solving and visuo-spatial working memory performance was found, which was accompanied by pronounced increases of interhemispheric and decreases of intrahemispheric functional connectivity. While the effects for B6 expand previous knowledge on beneficial effects of B6 supplementation on brain structure, they also showed that additional effects on cognition might not be recognizable in healthy older subjects with normal B6 blood levels. The cortical atrophy and pronounced functional reorganization associated with B1, contrarily, was more in line with the theory of a disturbed B1 metabolism in older adults, leading to B1 utilization deficits, and thus, an effective B1 deficiency in the brain, despite normal to high-normal blood levels.

A Complex Interplay of Vitamin B1 and B6 Metabolism with Cognition, Brain Structure, and Functional Connectivity in Older Adults

PubMed Central

Jannusch, Kai; Jockwitz, Christiane; Bidmon, Hans-Jürgen; Moebus, Susanne; Amunts, Katrin; Caspers, Svenja

2017-01-01

Aging is associated with brain atrophy, functional brain network reorganization and decline of cognitive performance, albeit characterized by high interindividual variability. Among environmental influencing factors accounting for this variability, nutrition and particularly vitamin supply is thought to play an important role. While evidence exists that supplementation of vitamins B6 and B1 might be beneficial for cognition and brain structure, at least in deficient states and neurodegenerative diseases, little is known about this relation during healthy aging and in relation to reorganization of functional brain networks. We thus assessed the relation between blood levels of vitamins B1 and B6 and cognitive performance, cortical folding, and functional resting-state connectivity in a large sample of older adults (N > 600; age: 55–85 years), drawn from the population-based 1000BRAINS study. In addition to blood sampling, subjects underwent structural and functional resting-state neuroimaging as well as extensive neuropsychological testing in the domains of executive functions, (working) memory, attention, and language. Brain regions showing changes in the local gyrification index as calculated using FreeSurfer in relation to vitamin levels were used for subsequent seed-based resting-state functional connectivity analysis. For B6, a positive correlation with local cortical folding was found throughout the brain, while only slight changes in functional connectivity were observed. Contrarily, for B1, a negative correlation with cortical folding as well as problem solving and visuo-spatial working memory performance was found, which was accompanied by pronounced increases of interhemispheric and decreases of intrahemispheric functional connectivity. While the effects for B6 expand previous knowledge on beneficial effects of B6 supplementation on brain structure, they also showed that additional effects on cognition might not be recognizable in healthy older subjects with normal B6 blood levels. The cortical atrophy and pronounced functional reorganization associated with B1, contrarily, was more in line with the theory of a disturbed B1 metabolism in older adults, leading to B1 utilization deficits, and thus, an effective B1 deficiency in the brain, despite normal to high-normal blood levels. PMID:29163003

From Structure to Circuits: The Contribution of MEG Connectivity Studies to Functional Neurosurgery.

PubMed

Pang, Elizabeth W; Snead Iii, O C

2016-01-01

New advances in structural neuroimaging have revealed the intricate and extensive connections within the brain, data which have informed a number of ambitious projects such as the mapping of the human connectome. Elucidation of the structural connections of the brain, at both the macro and micro levels, promises new perspectives on brain structure and function that could translate into improved outcomes in functional neurosurgery. The understanding of neuronal structural connectivity afforded by these data now offers a vista on the brain, in both healthy and diseased states, that could not be seen with traditional neuroimaging. Concurrent with these developments in structural imaging, a complementary modality called magnetoencephalography (MEG) has been garnering great attention because it too holds promise for being able to shed light on the intricacies of functional brain connectivity. MEG is based upon the elemental principle of physics that an electrical current generates a magnetic field. Hence, MEG uses highly sensitive biomagnetometers to measure extracranial magnetic fields produced by intracellular neuronal currents. Put simply then, MEG is a measure of neurophysiological activity, which captures the magnetic fields generated by synchronized intraneuronal electrical activity. As such, MEG recordings offer exquisite resolution in the time and oscillatory domain and, as well, when co-registered with magnetic resonance imaging (MRI), offer excellent resolution in the spatial domain. Recent advances in MEG computational and graph theoretical methods have led to studies of connectivity in the time-frequency domain. As such, MEG can elucidate a neurophysiological-based functional circuitry that may enhance what is seen with MRI connectivity studies. In particular, MEG may offer additional insight not possible by MRI when used to study complex eloquent function, where the precise timing and coordination of brain areas is critical. This article will review the traditional use of MEG for functional neurosurgery, describe recent advances in MEG connectivity analyses, and consider the additional benefits that could be gained with the inclusion of MEG connectivity studies. Since MEG has been most widely applied to the study of epilepsy, we will frame this article within the context of epilepsy surgery and functional neurosurgery for epilepsy.

Using Structural Equation Modeling to Assess Functional Connectivity in the Brain: Power and Sample Size Considerations

ERIC Educational Resources Information Center

Sideridis, Georgios; Simos, Panagiotis; Papanicolaou, Andrew; Fletcher, Jack

2014-01-01

The present study assessed the impact of sample size on the power and fit of structural equation modeling applied to functional brain connectivity hypotheses. The data consisted of time-constrained minimum norm estimates of regional brain activity during performance of a reading task obtained with magnetoencephalography. Power analysis was first…

Classifying Different Emotional States by Means of EEG-Based Functional Connectivity Patterns

PubMed Central

Lee, You-Yun; Hsieh, Shulan

2014-01-01

This study aimed to classify different emotional states by means of EEG-based functional connectivity patterns. Forty young participants viewed film clips that evoked the following emotional states: neutral, positive, or negative. Three connectivity indices, including correlation, coherence, and phase synchronization, were used to estimate brain functional connectivity in EEG signals. Following each film clip, participants were asked to report on their subjective affect. The results indicated that the EEG-based functional connectivity change was significantly different among emotional states. Furthermore, the connectivity pattern was detected by pattern classification analysis using Quadratic Discriminant Analysis. The results indicated that the classification rate was better than chance. We conclude that estimating EEG-based functional connectivity provides a useful tool for studying the relationship between brain activity and emotional states. PMID:24743695

Multimodal connectivity of motor learning-related dorsal premotor cortex.

PubMed

Hardwick, Robert M; Lesage, Elise; Eickhoff, Claudia R; Clos, Mareike; Fox, Peter; Eickhoff, Simon B

2015-12-01

The dorsal premotor cortex (dPMC) is a key region for motor learning and sensorimotor integration, yet we have limited understanding of its functional interactions with other regions. Previous work has started to examine functional connectivity in several brain areas using resting state functional connectivity (RSFC) and meta-analytical connectivity modelling (MACM). More recently, structural covariance (SC) has been proposed as a technique that may also allow delineation of functional connectivity. Here, we applied these three approaches to provide a comprehensive characterization of functional connectivity with a seed in the left dPMC that a previous meta-analysis of functional neuroimaging studies has identified as playing a key role in motor learning. Using data from two sources (the Rockland sample, containing resting state data and anatomical scans from 132 participants, and the BrainMap database, which contains peak activation foci from over 10,000 experiments), we conducted independent whole-brain functional connectivity mapping analyses of a dPMC seed. RSFC and MACM revealed similar connectivity maps spanning prefrontal, premotor, and parietal regions, while the SC map identified more widespread frontal regions. Analyses indicated a relatively consistent pattern of functional connectivity between RSFC and MACM that was distinct from that identified by SC. Notably, results indicate that the seed is functionally connected to areas involved in visuomotor control and executive functions, suggesting that the dPMC acts as an interface between motor control and cognition. Copyright © 2015 Elsevier Inc. All rights reserved.

Altered functional connectivity in early Alzheimer's disease: a resting-state fMRI study.

PubMed

Wang, Kun; Liang, Meng; Wang, Liang; Tian, Lixia; Zhang, Xinqing; Li, Kuncheng; Jiang, Tianzi

2007-10-01

Previous studies have led to the proposal that patients with Alzheimer's disease (AD) may have disturbed functional connectivity between different brain regions. Furthermore, recent resting-state functional magnetic resonance imaging (fMRI) studies have also shown that low-frequency (<0.08 Hz) fluctuations (LFF) of the blood oxygenation level-dependent signals were abnormal in several brain areas of AD patients. However, few studies have investigated disturbed LFF connectivity in AD patients. By using resting-state fMRI, this study sought to investigate the abnormal functional connectivities throughout the entire brain of early AD patients, and analyze the global distribution of these abnormalities. For this purpose, the authors divided the whole brain into 116 regions and identified abnormal connectivities by comparing the correlation coefficients of each pair. Compared with healthy controls, AD patients had decreased positive correlations between the prefrontal and parietal lobes, but increased positive correlations within the prefrontal lobe, parietal lobe, and occipital lobe. The AD patients also had decreased negative correlations (closer to zero) between two intrinsically anti-correlated networks that had previously been found in the resting brain. By using resting-state fMRI, our results supported previous studies that have reported an anterior-posterior disconnection phenomenon and increased within-lobe functional connectivity in AD patients. In addition, the results also suggest that AD may disturb the correlation/anti-correlation effect in the two intrinsically anti-correlated networks. Wiley-Liss, Inc.

Compensatory Hyperconnectivity in Developing Brains of Young Children With Type 1 Diabetes.

PubMed

Saggar, Manish; Tsalikian, Eva; Mauras, Nelly; Mazaika, Paul; White, Neil H; Weinzimer, Stuart; Buckingham, Bruce; Hershey, Tamara; Reiss, Allan L

2017-03-01

Sustained dysregulation of blood glucose (hyper- or hypoglycemia) associated with type 1 diabetes (T1D) has been linked to cognitive deficits and altered brain anatomy and connectivity. However, a significant gap remains with respect to how T1D affects spontaneous at-rest connectivity in young developing brains. Here, using a large multisite study, resting-state functional MRI data were examined in young children with T1D ( n = 57; mean age = 7.88 years; 27 females) as compared with age-matched control subjects without diabetes ( n = 26; mean age = 7.43 years; 14 females). Using both model-driven seed-based analysis and model-free independent component analysis and controlling for age, data acquisition site, and sex, converging results were obtained, suggesting increased connectivity in young children with T1D as compared with control subjects without diabetes. Further, increased connectivity in children with T1D was observed to be positively associated with cognitive functioning. The observed positive association of connectivity with cognitive functioning in T1D, without overall group differences in cognitive function, suggests a putative compensatory role of hyperintrinsic connectivity in the brain in children with this condition. Altogether, our study attempts to fill a critical gap in knowledge regarding how dysglycemia in T1D might affect the brain's intrinsic connectivity at very young ages. © 2017 by the American Diabetes Association.

Resting state functional MRI in Parkinson’s disease: the impact of deep brain stimulation on ‘effective’ connectivity

PubMed Central

Kahan, Joshua; Urner, Maren; Moran, Rosalyn; Flandin, Guillaume; Marreiros, Andre; Mancini, Laura; White, Mark; Thornton, John; Yousry, Tarek; Zrinzo, Ludvic; Hariz, Marwan; Limousin, Patricia; Friston, Karl

2014-01-01

Depleted of dopamine, the dynamics of the parkinsonian brain impact on both ‘action’ and ‘resting’ motor behaviour. Deep brain stimulation has become an established means of managing these symptoms, although its mechanisms of action remain unclear. Non-invasive characterizations of induced brain responses, and the effective connectivity underlying them, generally appeals to dynamic causal modelling of neuroimaging data. When the brain is at rest, however, this sort of characterization has been limited to correlations (functional connectivity). In this work, we model the ‘effective’ connectivity underlying low frequency blood oxygen level-dependent fluctuations in the resting Parkinsonian motor network—disclosing the distributed effects of deep brain stimulation on cortico-subcortical connections. Specifically, we show that subthalamic nucleus deep brain stimulation modulates all the major components of the motor cortico-striato-thalamo-cortical loop, including the cortico-striatal, thalamo-cortical, direct and indirect basal ganglia pathways, and the hyperdirect subthalamic nucleus projections. The strength of effective subthalamic nucleus afferents and efferents were reduced by stimulation, whereas cortico-striatal, thalamo-cortical and direct pathways were strengthened. Remarkably, regression analysis revealed that the hyperdirect, direct, and basal ganglia afferents to the subthalamic nucleus predicted clinical status and therapeutic response to deep brain stimulation; however, suppression of the sensitivity of the subthalamic nucleus to its hyperdirect afferents by deep brain stimulation may subvert the clinical efficacy of deep brain stimulation. Our findings highlight the distributed effects of stimulation on the resting motor network and provide a framework for analysing effective connectivity in resting state functional MRI with strong a priori hypotheses. PMID:24566670

Resting state functional MRI in Parkinson's disease: the impact of deep brain stimulation on 'effective' connectivity.

PubMed

Kahan, Joshua; Urner, Maren; Moran, Rosalyn; Flandin, Guillaume; Marreiros, Andre; Mancini, Laura; White, Mark; Thornton, John; Yousry, Tarek; Zrinzo, Ludvic; Hariz, Marwan; Limousin, Patricia; Friston, Karl; Foltynie, Tom

2014-04-01

Depleted of dopamine, the dynamics of the parkinsonian brain impact on both 'action' and 'resting' motor behaviour. Deep brain stimulation has become an established means of managing these symptoms, although its mechanisms of action remain unclear. Non-invasive characterizations of induced brain responses, and the effective connectivity underlying them, generally appeals to dynamic causal modelling of neuroimaging data. When the brain is at rest, however, this sort of characterization has been limited to correlations (functional connectivity). In this work, we model the 'effective' connectivity underlying low frequency blood oxygen level-dependent fluctuations in the resting Parkinsonian motor network-disclosing the distributed effects of deep brain stimulation on cortico-subcortical connections. Specifically, we show that subthalamic nucleus deep brain stimulation modulates all the major components of the motor cortico-striato-thalamo-cortical loop, including the cortico-striatal, thalamo-cortical, direct and indirect basal ganglia pathways, and the hyperdirect subthalamic nucleus projections. The strength of effective subthalamic nucleus afferents and efferents were reduced by stimulation, whereas cortico-striatal, thalamo-cortical and direct pathways were strengthened. Remarkably, regression analysis revealed that the hyperdirect, direct, and basal ganglia afferents to the subthalamic nucleus predicted clinical status and therapeutic response to deep brain stimulation; however, suppression of the sensitivity of the subthalamic nucleus to its hyperdirect afferents by deep brain stimulation may subvert the clinical efficacy of deep brain stimulation. Our findings highlight the distributed effects of stimulation on the resting motor network and provide a framework for analysing effective connectivity in resting state functional MRI with strong a priori hypotheses.

An information theory framework for dynamic functional domain connectivity.

PubMed

Vergara, Victor M; Miller, Robyn; Calhoun, Vince

2017-06-01

Dynamic functional network connectivity (dFNC) analyzes time evolution of coherent activity in the brain. In this technique dynamic changes are considered for the whole brain. This paper proposes an information theory framework to measure information flowing among subsets of functional networks call functional domains. Our method aims at estimating bits of information contained and shared among domains. The succession of dynamic functional states is estimated at the domain level. Information quantity is based on the probabilities of observing each dynamic state. Mutual information measurement is then obtained from probabilities across domains. Thus, we named this value the cross domain mutual information (CDMI). Strong CDMIs were observed in relation to the subcortical domain. Domains related to sensorial input, motor control and cerebellum form another CDMI cluster. Information flow among other domains was seldom found. Other methods of dynamic connectivity focus on whole brain dFNC matrices. In the current framework, information theory is applied to states estimated from pairs of multi-network functional domains. In this context, we apply information theory to measure information flow across functional domains. Identified CDMI clusters point to known information pathways in the basal ganglia and also among areas of sensorial input, patterns found in static functional connectivity. In contrast, CDMI across brain areas of higher level cognitive processing follow a different pattern that indicates scarce information sharing. These findings show that employing information theory to formally measured information flow through brain domains reveals additional features of functional connectivity. Copyright © 2017 Elsevier B.V. All rights reserved.

Financial literacy is associated with medial brain region functional connectivity in old age.

PubMed

Han, S Duke; Boyle, Patricia A; Yu, Lei; Fleischman, Debra A; Arfanakis, Konstantinos; Leurgans, Sue; Bennett, David A

2014-01-01

Financial literacy refers to the ability to access and utilize financial information in ways that promote better outcomes. In old age, financial literacy has been associated with a wide range of positive characteristics; however, the neural correlates remain unclear. Recent work has suggested greater co-activity between anterior-posterior medial brain regions is associated with better brain functioning. We hypothesized financial literacy would be associated with this pattern. We assessed whole-brain functional connectivity to a posterior cingulate cortex (PCC) seed region of interest (ROI) in 138 participants of the Rush Memory and Aging Project. Results revealed financial literacy was associated with greater functional connectivity between the PCC and three regions: the right ventromedial prefrontal cortex (vmPFC), the left postcentral gyrus, and the right precuneus. Results also revealed financial literacy was associated negatively with functional connectivity between the PCC and left caudate. Post hoc analyses showed the PCC-vmPFC relationship accounted for the most variance in a regression model adjusted for all four significant functional connectivity relationships, demographic factors, and global cognition. These findings provide information on the neural mechanisms associated with financial literacy in old age. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Financial Literacy is Associated with Medial Brain Region Functional Connectivity in Old Age

PubMed Central

Han, S. Duke; Boyle, Patricia A.; Yu, Lei; Fleischman, Debra A.; Arfanakis, Konstantinos; Leurgans, Sue; Bennett, David A.

2014-01-01

Financial literacy refers to the ability to access and utilize financial information in ways that promote better outcomes. In old age, financial literacy has been associated with a wide range of positive characteristics; however, the neural correlates remain unclear. Recent work has suggested greater co-activity between anterior-posterior medial brain regions is associated with better brain functioning. We hypothesized financial literacy would be associated with this pattern. We assessed whole-brain functional connectivity to a posterior cingulate cortex (PCC) seed region of interest in 138 participants of the Rush Memory and Aging Project. Results revealed financial literacy was associated with greater functional connectivity between the PCC and three regions: the right ventromedial prefrontal cortex (vmPFC), the left postcentral gyrus, and the right precuneus. Results also revealed financial literacy was associated negatively with functional connectivity between the PCC and left caudate. Post-hoc analyses showed the PCC-vmPFC relationship accounted for the most variance in a regression model adjusted for all four significant functional connectivity relationships, demographic factors, and global cognition. These findings provide information on the neural mechanisms associated with financial literacy in old age. PMID:24893911

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

Regional homogeneity, resting-state functional connectivity and amplitude of low frequency fluctuation associated with creativity measured by divergent thinking in a sex-specific manner.

PubMed

Takeuchi, Hikaru; Taki, Yasuyuki; Nouchi, Rui; Yokoyama, Ryoichi; Kotozaki, Yuka; Nakagawa, Seishu; Sekiguchi, Atsushi; Iizuka, Kunio; Yamamoto, Yuki; Hanawa, Sugiko; Araki, Tsuyoshi; Makoto Miyauchi, Carlos; Shinada, Takamitsu; Sakaki, Kohei; Nozawa, Takayuki; Ikeda, Shigeyuki; Yokota, Susumu; Daniele, Magistro; Sassa, Yuko; Kawashima, Ryuta

2017-05-15

Brain connectivity is traditionally thought to be important for creativity. Here we investigated the associations of creativity measured by divergent thinking (CMDT) with resting-state functional magnetic imaging (fMRI) measures and their sex differences. We examined these relationships in the brains of 1277 healthy young adults. Whole-brain analyses revealed a significant interaction between verbal CMDT and sex on (a) regional homogeneity within an area from the left anterior temporal lobe (b) on the resting state functional connectivity (RSFC) between the mPFC and the left inferior frontal gyrus and (c) on fractional amplitude of low frequency fluctuations (fALFF) in several distinct areas, including the precuneus and middle cingulate gyrus, left middle temporal gyrus, right middle frontal gyrus, and cerebellum. These interactions were mediated by positive correlations in females and negative correlations in males. These findings suggest that greater CMDT in females is reflected by (a) regional coherence (regional homogeneity) of brain areas responsible for representing and combining concepts as well as (b) the efficient functional connection (RSFC) between the key areas for the default state of cognitive activity and speech production, and (c) greater spontaneous neural activity (fALFF) during the resting of brain areas involved in frontal lobe functions, default cognitive activities, and language functions. Furthermore, these findings suggest that the associations between creativity and resting state brain connectivity patterns are different between males and females. Copyright © 2017 Elsevier Inc. All rights reserved.

Hyperconnectivity is a fundamental response to neurological disruption.

PubMed

Hillary, Frank G; Roman, Cristina A; Venkatesan, Umesh; Rajtmajer, Sarah M; Bajo, Ricardo; Castellanos, Nazareth D

2015-01-01

In the cognitive and clinical neurosciences, the past decade has been marked by dramatic growth in a literature examining brain "connectivity" using noninvasive methods. We offer a critical review of the blood oxygen level dependent functional MRI (BOLD fMRI) literature examining neural connectivity changes in neurological disorders with focus on brain injury and dementia. The goal is to demonstrate that there are identifiable shifts in local and large-scale network connectivity that can be predicted by the degree of pathology. We anticipate that the most common network response to neurological insult is hyperconnectivity but that this response depends upon demand and resource availability. To examine this hypothesis, we initially reviewed the results from 1,426 studies examining functional brain connectivity in individuals diagnosed with multiple sclerosis, traumatic brain injury, mild cognitive impairment, and Alzheimer's disease. Based upon inclusionary criteria, 126 studies were included for detailed analysis. RESULTS from 126 studies examining local and whole brain connectivity demonstrated increased connectivity in traumatic brain injury and multiple sclerosis. This finding is juxtaposed with findings in mild cognitive impairment and Alzheimer's disease where there is a shift to diminished connectivity as degeneration progresses. This summary of the functional imaging literature using fMRI methods reveals that hyperconnectivity is a common response to neurological disruption and that it may be differentially observable across brain regions. We discuss the factors contributing to both hyper- and hypoconnectivity results after neurological disruption and the implications these findings have for network plasticity. PsycINFO Database Record (c) 2015 APA, all rights reserved.

Brain activity and connectivity changes in response to glucose ingestion.

PubMed

van Opstal, A M; Hafkemeijer, A; van den Berg-Huysmans, A A; Hoeksma, M; Blonk, C; Pijl, H; Rombouts, S A R B; van der Grond, J

2018-05-27

The regulatory role of the brain in directing eating behavior becomes increasingly recognized. Although many areas in the brain have been found to respond to food cues, very little data is available after actual caloric intake. The aim of this study was to determine normal whole brain functional responses to ingestion of glucose after an overnight fast. Twenty-five normal weight, adult males underwent functional MRI on two separate visits. In a single-blind randomized study setup, participants received either glucose solution (50 g/300 ml of water) or plain water. We studied changes in Blood Oxygen Level Dependent (BOLD) signal, voxel-based connectivity by Eigenvector Centrality Mapping, and functional network connectivity. Ingestion of glucose led to increased centrality in the thalamus and to decreases in BOLD signal in various brain areas. Decreases in connectivity in the sensory-motor and dorsal visual stream networks were found. Ingestion of water resulted in increased centrality across the brain, and increases in connectivity in the medial and lateral visual cortex network. Increased BOLD intensity was found in the intracalcarine and cingulate cortex. Our data show that ingestion of glucose leads to decreased activity and connectivity in brain areas and networks linked to energy seeking and satiation. In contrast, drinking plain water leads to increased connectivity probably associated with continued food seeking and unfulfilled reward. Trail registration: This study combines data of two studies registered at clinicaltrails.gov under numbers NCT03202342 and NCT03247114.

Decreased functional connectivity in an executive control network is related to impaired executive function in Internet gaming disorder.

PubMed

Dong, Guangheng; Lin, Xiao; Potenza, Marc N

2015-03-03

Resting brain spontaneous neural activities across cortical regions have been correlated with specific functional properties in psychiatric groups. Individuals with Internet gaming disorder (IGD) demonstrate impaired executive control. Thus, it is important to examine executive control networks (ECNs) during resting states and their relationships to executive control during task performance. Thirty-five IGD and 36 healthy control participants underwent a resting-state fMRI scan and performed a Stroop task inside and outside of the MRI scanner. Correlations between Stroop effect and functional connectivity among ECN regions of interest (ROIs) were calculated within and between groups. IGD subjects show lower functional connectivity in ECNs than do HC participants during resting state; functional-connectivity measures in ECNs were negatively correlated with Stroop effect and positively correlated with brain activations in executive-control regions across groups. Within groups, negative trends were found between Stroop effect and functional connectivity in ECNs in IGD and HC groups, separately; positive trends were found between functional connectivity in ECNs and brain activations in Stroop task in IGD and HC groups, separately. Higher functional connectivity in ECNs may underlie better executive control and may provide resilience with respect to IGD. Lower functional connectivity in ECNs may represent an important feature in understanding and treating IGD. Copyright © 2013 Elsevier Inc. All rights reserved.

Abnormal functional brain connectivity and personality traits in myotonic dystrophy type 1.

PubMed

Serra, Laura; Silvestri, Gabriella; Petrucci, Antonio; Basile, Barbara; Masciullo, Marcella; Makovac, Elena; Torso, Mario; Spanò, Barbara; Mastropasqua, Chiara; Harrison, Neil A; Bianchi, Maria L E; Giacanelli, Manlio; Caltagirone, Carlo; Cercignani, Mara; Bozzali, Marco

2014-05-01

Myotonic dystrophy type 1 (DM1), the most common muscular dystrophy observed in adults, is a genetic multisystem disorder affecting several other organs besides skeletal muscle, including the brain. Cognitive and personality abnormalities have been reported; however, no studies have investigated brain functional networks and their relationship with personality traits/disorders in patients with DM1. To use resting-state functional magnetic resonance imaging to assess the potential relationship between personality traits/disorders and changes to functional connectivity within the default mode network (DMN) in patients with DM1. We enrolled 27 patients with genetically confirmed DM1 and 16 matched healthy control individuals. Patients underwent personality assessment using clinical interview and Minnesota Multiphasic Personality Inventory-2 administration; all participants underwent resting-state functional magnetic resonance imaging. Investigations were conducted at the Istituto di Ricovero e Cura a Carattere Scientifico Santa Lucia Foundation, Catholic University of Sacred Heart, and Azienda Ospedaliera San Camillo Forlanini. Resting-state functional magnetic resonance imaging. Measures of personality traits in patients and changes in functional connectivity within the DMN in patients and controls. Changes in functional connectivity and atypical personality traits in patients were correlated. We combined results obtained from the Minnesota Multiphasic Personality Inventory-2 and clinical interview to identify a continuum of atypical personality profiles ranging from schizotypal personality traits to paranoid personality disorder within our DM1 patients. We also demonstrated an increase in functional connectivity in the bilateral posterior cingulate and left parietal DMN nodes in DM1 patients compared with controls. Moreover, patients with DM1 showed strong associations between DMN functional connectivity and schizotypal-paranoid traits. Our findings provide novel biological evidence that DM1 is a clinical condition that also involves an alteration of functional connectivity of the brain. We speculate that these functional brain abnormalities, similarly to frank psychiatric disorders, may account for the atypical personality traits observed in patients with DM1.

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.

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

From Brain-Environment Connections to Temporal Dynamics and Social Interaction: Principles of Human Brain Function.

PubMed

Hari, Riitta

2017-06-07

Experimental data about brain function accumulate faster than does our understanding of how the brain works. To tackle some general principles at the grain level of behavior, I start from the omnipresent brain-environment connection that forces regularities of the physical world to shape the brain. Based on top-down processing, added by sparse sensory information, people are able to form individual "caricature worlds," which are similar enough to be shared among other people and which allow quick and purposeful reactions to abrupt changes. Temporal dynamics and social interaction in natural environments serve as further essential organizing principles of human brain function. Copyright © 2017 Elsevier Inc. All rights reserved.

Scopolamine effects on functional brain connectivity: a pharmacological model of Alzheimer's disease.

PubMed

Bajo, R; Pusil, S; López, M E; Canuet, L; Pereda, E; Osipova, D; Maestú, F; Pekkonen, E

2015-07-01

Scopolamine administration may be considered as a psychopharmacological model of Alzheimer's disease (AD). Here, we studied a group of healthy elderly under scopolamine to test whether it elicits similar changes in brain connectivity as those observed in AD, thereby verifying a possible model of AD impairment. We did it by testing healthy elderly subjects in two experimental conditions: glycopyrrolate (placebo) and scopolamine administration. We then analyzed magnetoencephalographic (MEG) data corresponding to both conditions in resting-state with eyes closed. This analysis was performed in source space by combining a nonlinear frequency band-specific measure of functional connectivity (phase locking value, PLV) with network analysis methods. Under scopolamine, functional connectivity between several brain areas was significantly reduced as compared to placebo, in most frequency bands analyzed. Besides, regarding the two complex network indices studied (clustering and shortest path length), clustering significantly decreased in the alpha band while shortest path length significantly increased also in alpha band both after scopolamine administration. Overall our findings indicate that both PLV and graph analysis are suitable tools to measure brain connectivity changes induced by scopolamine, which causes alterations in brain connectivity apparently similar to those reported in AD.

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

Reduced Global Functional Connectivity of the Medial Prefrontal Cortex in Major Depressive Disorder

PubMed Central

Murrough, James W.; Abdallah, Chadi G.; Anticevic, Alan; Collins, Katherine A.; Geha, Paul; Averill, Lynnette A.; Schwartz, Jaclyn; DeWilde, Kaitlin E.; Averill, Christopher; Yang, Genevieve Jia-wei; Wong, Edmund; Tang, Cheuk Y.; Krystal, John H.; Iosifescu, Dan V.; Charney, Dennis S.

2016-01-01

Background Major depressive disorder is a disabling neuropsychiatric condition that is associated with disrupted functional connectivity across brain networks. The precise nature of altered connectivity, however, remains incompletely understood. The current study was designed to examine the coherence of large-scale connectivity in depression using a recently developed technique termed global brain connectivity. Methods A total of 82 subjects, including medication-free patients with major depression (n=57) and healthy volunteers (n=25) underwent functional magnetic resonance imaging with resting data acquisition for functional connectivity analysis. Global brain connectivity was computed as the mean of each voxel’s time series correlation with every other voxel and compared between study groups. Relationships between global connectivity and depressive symptom severity measured using the Montgomery-Åsberg Depression Rating Scale were examined by means of linear correlation. Results Relative to the healthy group, patients with depression evidenced reduced global connectivity bilaterally within multiple regions of medial and lateral prefrontal cortex. The largest between-group difference was observed within the right subgenual anterior cingulate cortex, extending into ventromedial prefrontal cortex bilaterally (Hedges’ g = −1.48, p<0.000001). Within the depressed group, patients with the lowest connectivity evidenced the highest symptom severity within ventromedial prefrontal cortex (r = −0.47, p=0.0005). Conclusions Patients with major depressive evidenced abnormal large-scale functional coherence in the brain that was centered within the subgenual cingulate cortex, and medial prefrontal cortex more broadly. These data extend prior studies of connectivity in depression and demonstrate that functional disconnection of the medial prefrontal cortex is a key pathological feature of the disorder. PMID:27144347

Radiation-induced functional connectivity alterations in nasopharyngeal carcinoma patients with radiotherapy.

PubMed

Ma, Qiongmin; Wu, Donglin; Zeng, Ling-Li; Shen, Hui; Hu, Dewen; Qiu, Shijun

2016-07-01

The study aims to investigate the radiation-induced brain functional alterations in nasopharyngeal carcinoma (NPC) patients who received radiotherapy (RT) using functional magnetic resonance imaging (fMRI) and statistic scale.The fMRI data of 35 NPC patients with RT and 24 demographically matched untreated NPC patients were acquired. Montreal Cognitive Assessment (MoCA) was also measured to evaluate their global cognition performance. Multivariate pattern analysis was performed to find the significantly altered functional connections between these 2 groups, while the linear correlation level was detected between the altered functional connections and the MoCA scores.Forty-five notably altered functional connections were found, which were mainly located between 3 brain networks, the cerebellum, sensorimotor, and cingulo-opercular. With strictly false discovery rate correction, 5 altered functional connections were shown to have significant linear correlations with the MoCA scores, that is, the connections between the vermis and hippocampus, cerebellum lobule VI and dorsolateral prefrontal cortex, precuneus and dorsal frontal cortex, cuneus and middle occipital lobe, and insula and cuneus. Besides, the connectivity between the vermis and hippocampus was also significantly correlated with the attention score, 1 of the 7 subscores of the MoCA.The present study provides new insights into the radiation-induced functional connectivity impairments in NPC patients. The results showed that the RT may induce the cognitive impairments, especially the attention alterations. The 45 altered functional connections, especially the 5 altered functional connections that were significantly correlated to the MoCA scores, may serve as the potential biomarkers of the RT-induced brain functional impairments and provide valuable targets for further functional recovery treatment.

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.

Novel MRI methodology to detect human whole-brain connectivity changes after ingestion of fructose or glucose

NASA Astrophysics Data System (ADS)

Tsao, Sinchai; Wilkins, Bryce; Page, Kathleen A.; Singh, Manbir

2012-03-01

A novel MRI protocol has been developed to investigate the differential effects of glucose or fructose consumption on whole-brain functional brain connectivity. A previous study has reported a decrease in the fMRI blood oxygen level dependent (BOLD) signal of the hypothalamus following glucose ingestion, but due to technical limitations, was restricted to a single slice covering the hypothalamus, and thus unable to detect whole-brain connectivity. In another previous study, a protocol was devised to acquire whole-brain fMRI data following food intake, but only after restricting image acquisition to an MR sampling or repetition time (TR) of 20s, making the protocol unsuitable to detect functional connectivity above 0.025Hz. We have successfully implemented a continuous 36-min, 40 contiguous slices, whole-brain BOLD acquisition protocol on a 3T scanner with TR=4.5s to ensure detection of up to 0.1Hz frequencies for whole-brain functional connectivity analysis. Human data were acquired first with ingestion of water only, followed by a glucose or fructose drink within the scanner, without interrupting the scanning. Whole-brain connectivity was analyzed using standard correlation methodology in the 0.01-0.1 Hz range. The correlation coefficient differences between fructose and glucose ingestion among targeted regions were converted to t-scores using the water-only correlation coefficients as a null condition. Results show a dramatic increase in the hypothalamic connectivity to the hippocampus, amygdala, insula, caudate and the nucleus accumben for fructose over glucose. As these regions are known to be key components of the feeding and reward brain circuits, these results suggest a preference for fructose ingestion.

What We Know About the Brain Structure-Function Relationship.

PubMed

Batista-García-Ramó, Karla; Fernández-Verdecia, Caridad Ivette

2018-04-18

How the human brain works is still a question, as is its implication with brain architecture: the non-trivial structure–function relationship. The main hypothesis is that the anatomic architecture conditions, but does not determine, the neural network dynamic. The functional connectivity cannot be explained only considering the anatomical substrate. This involves complex and controversial aspects of the neuroscience field and that the methods and methodologies to obtain structural and functional connectivity are not always rigorously applied. The goal of the present article is to discuss about the progress made to elucidate the structure–function relationship of the Central Nervous System, particularly at the brain level, based on results from human and animal studies. The current novel systems and neuroimaging techniques with high resolutive physio-structural capacity have brought about the development of an integral framework of different structural and morphometric tools such as image processing, computational modeling and graph theory. Different laboratories have contributed with in vivo, in vitro and computational/mathematical models to study the intrinsic neural activity patterns based on anatomical connections. We conclude that multi-modal techniques of neuroimaging are required such as an improvement on methodologies for obtaining structural and functional connectivity. Even though simulations of the intrinsic neural activity based on anatomical connectivity can reproduce much of the observed patterns of empirical functional connectivity, future models should be multifactorial to elucidate multi-scale relationships and to infer disorder mechanisms.

Structural and functional rich club organization of the brain in children and adults.

PubMed

Grayson, David S; Ray, Siddharth; Carpenter, Samuel; Iyer, Swathi; Dias, Taciana G Costa; Stevens, Corinne; Nigg, Joel T; Fair, Damien A

2014-01-01

Recent studies using Magnetic Resonance Imaging (MRI) have proposed that the brain's white matter is organized as a rich club, whereby the most highly connected regions of the brain are also highly connected to each other. Here we use both functional and diffusion-weighted MRI in the human brain to investigate whether the rich club phenomena is present with functional connectivity, and how this organization relates to the structural phenomena. We also examine whether rich club regions serve to integrate information between distinct brain systems, and conclude with a brief investigation of the developmental trajectory of rich-club phenomena. In agreement with prior work, both adults and children showed robust structural rich club organization, comprising regions of the superior medial frontal/dACC, medial parietal/PCC, insula, and inferior temporal cortex. We also show that these regions were highly integrated across the brain's major networks. Functional brain networks were found to have rich club phenomena in a similar spatial layout, but a high level of segregation between systems. While no significant differences between adults and children were found structurally, adults showed significantly greater functional rich club organization. This difference appeared to be driven by a specific set of connections between superior parietal, insula, and supramarginal cortex. In sum, this work highlights the existence of both a structural and functional rich club in adult and child populations with some functional changes over development. It also offers a potential target in examining atypical network organization in common developmental brain disorders, such as ADHD and Autism.

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.

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.

Altered Resting State Functional Connectivity in Young Survivors of Acute Lymphoblastic Leukemia

PubMed Central

Kesler, Shelli R.; Gugel, Meike; Pritchard-Berman, Mika; Lee, Clement; Kutner, Emily; Hosseini, S.M. Hadi; Dahl, Gary; Lacayo, Norman

2014-01-01

Background Chemotherapy treatment for pediatric acute lymphoblastic leukemia (ALL) has been associated with long-term cognitive impairments in some patients. However, the neurobiologic mechanisms underlying these impairments, particularly in young survivors, are not well understood. This study aimed to examine intrinsic functional brain connectivity in pediatric ALL and its relationship with cognitive status. Procedure We obtained resting state functional magnetic resonance imaging (rsfMRI) and cognitive testing data from 15 ALL survivors age 8–15 years and 14 matched healthy children. The ALL group had a history of intrathecal chemotherapy treatment but were off-therapy for at least 6 months at the time of enrollment. We used seed-based analyses to compare intrinsic functional brain network connectivity between the groups. We also explored correlations between connectivity and cognitive performance, demographic, medical, and treatment variables. Results We demonstrated significantly reduced connectivity between bilateral hippocampus, left inferior occipital, left lingual gyrus, bilateral calcarine sulcus, and right amygdala in the ALL group compared to controls. The ALL group also showed regions of functional hyperconnectivity including right lingual gyrus, precuneus, bilateral superior occipital lobe, and right inferior occipital lobe. Functional hypoconnectivity was associated with reduced cognitive function as well as younger age at diagnosis in the ALL group. Conclusions This is the first study to demonstrate that intrinsic functional brain connectivity is disrupted in pediatric ALL following chemotherapy treatment. These results help explain cognitive dysfunction even when objective test performance is seemingly normal. Children diagnosed at a younger age may show increased vulnerability to altered functional brain connectivity. PMID:24619953

Abnormal functional connectivity during visuospatial processing is associated with disrupted organisation of white matter in autism

PubMed Central

McGrath, Jane; Johnson, Katherine; O'Hanlon, Erik; Garavan, Hugh; Leemans, Alexander; Gallagher, Louise

2013-01-01

Disruption of structural and functional neural connectivity has been widely reported in Autism Spectrum Disorder (ASD) but there is a striking lack of research attempting to integrate analysis of functional and structural connectivity in the same study population, an approach that may provide key insights into the specific neurobiological underpinnings of altered functional connectivity in autism. The aims of this study were (1) to determine whether functional connectivity abnormalities were associated with structural abnormalities of white matter (WM) in ASD and (2) to examine the relationships between aberrant neural connectivity and behavior in ASD. Twenty-two individuals with ASD and 22 age, IQ-matched controls completed a high-angular-resolution diffusion MRI scan. Structural connectivity was analysed using constrained spherical deconvolution (CSD) based tractography. Regions for tractography were generated from the results of a previous study, in which 10 pairs of brain regions showed abnormal functional connectivity during visuospatial processing in ASD. WM tracts directly connected 5 of the 10 region pairs that showed abnormal functional connectivity; linking a region in the left occipital lobe (left BA19) and five paired regions: left caudate head, left caudate body, left uncus, left thalamus, and left cuneus. Measures of WM microstructural organization were extracted from these tracts. Fractional anisotropy (FA) reductions in the ASD group relative to controls were significant for WM connecting left BA19 to left caudate head and left BA19 to left thalamus. Using a multimodal imaging approach, this study has revealed aberrant WM microstructure in tracts that directly connect brain regions that are abnormally functionally connected in ASD. These results provide novel evidence to suggest that structural brain pathology may contribute (1) to abnormal functional connectivity and (2) to atypical visuospatial processing in ASD. PMID:24133425

Cross-hemispheric functional connectivity in the human fetal brain.

PubMed

Thomason, Moriah E; Dassanayake, Maya T; Shen, Stephen; Katkuri, Yashwanth; Alexis, Mitchell; Anderson, Amy L; Yeo, Lami; Mody, Swati; Hernandez-Andrade, Edgar; Hassan, Sonia S; Studholme, Colin; Jeong, Jeong-Won; Romero, Roberto

2013-02-20

Compelling evidence indicates that psychiatric and developmental disorders are generally caused by disruptions in the functional connectivity (FC) of brain networks. Events occurring during development, and in particular during fetal life, have been implicated in the genesis of such disorders. However, the developmental timetable for the emergence of neural FC during human fetal life is unknown. We present the results of resting-state functional magnetic resonance imaging performed in 25 healthy human fetuses in the second and third trimesters of pregnancy (24 to 38 weeks of gestation). We report the presence of bilateral fetal brain FC and regional and age-related variation in FC. Significant bilateral connectivity was evident in half of the 42 areas tested, and the strength of FC between homologous cortical brain regions increased with advancing gestational age. We also observed medial to lateral gradients in fetal functional brain connectivity. These findings improve understanding of human fetal central nervous system development and provide a basis for examining the role of insults during fetal life in the subsequent development of disorders in neural FC.

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.

Connectopic mapping with resting-state fMRI.

PubMed

Haak, Koen V; Marquand, Andre F; Beckmann, Christian F

2018-04-15

Brain regions are often topographically connected: nearby locations within one brain area connect with nearby locations in another area. Mapping these connection topographies, or 'connectopies' in short, is crucial for understanding how information is processed in the brain. Here, we propose principled, fully data-driven methods for mapping connectopies using functional magnetic resonance imaging (fMRI) data acquired at rest by combining spectral embedding of voxel-wise connectivity 'fingerprints' with a novel approach to spatial statistical inference. We apply the approach in human primary motor and visual cortex, and show that it can trace biologically plausible, overlapping connectopies in individual subjects that follow these regions' somatotopic and retinotopic maps. As a generic mechanism to perform inference over connectopies, the new spatial statistics approach enables rigorous statistical testing of hypotheses regarding the fine-grained spatial profile of functional connectivity and whether that profile is different between subjects or between experimental conditions. The combined framework offers a fundamental alternative to existing approaches to investigating functional connectivity in the brain, from voxel- or seed-pair wise characterizations of functional association, towards a full, multivariate characterization of spatial topography. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

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

Dopamine Modulates the Functional Organization of the Orbitofrontal Cortex.

PubMed

Kahnt, Thorsten; Tobler, Philippe N

2017-02-08

Neuromodulators such as dopamine can alter the intrinsic firing properties of neurons and may thereby change the configuration of larger functional circuits. The primate orbitofrontal cortex (OFC) receives dopaminergic input from midbrain nuclei, but the role of dopamine in the OFC is still unclear. Here we tested the idea that dopaminergic activity changes the pattern of connectivity between the OFC and the rest of the brain and thereby reconfigures functional networks in the OFC. To this end, we combined double-blind, placebo-controlled pharmacology [D 2 receptor (D2R) antagonist amisulpride] in humans with resting-state functional magnetic resonance imaging and clustering methods. In the placebo group, we replicated previously observed parcellations of the OFC into two and six subregions based on connectivity patterns with the rest of the brain. Most importantly, while the twofold clustering did not differ significantly between groups, blocking D2Rs significantly changed the composition of the sixfold parcellation, suggesting a dopamine-dependent reconfiguration of functional OFC subregions. Moreover, multivariate decoding analyses revealed that amisulpride changed the whole-brain connectivity patterns of individual OFC subregions. In particular, D2R blockade shifted the balance of OFC connectivity from associative areas in the temporal and parietal lobe toward functional connectivity with the frontal cortex. In summary, our results suggest that dopamine alters the composition of functional OFC circuits, possibly indicating a broader role for neuromodulators in the dynamic reconfiguration of functional brain networks. SIGNIFICANCE STATEMENT A key role of any neuromodulator may be the reconfiguration of functional brain circuits. Here we test this idea with regard to dopamine and the organization of functional networks in the orbitofrontal cortex (OFC). We show that blockade of dopamine D 2 receptors has profound effects on the functional connectivity patterns of the OFC, yielding altered connectivity-based subdivisions of this region. Our results suggest that dopamine changes the connectional configuration of the OFC, possibly leading to transitions between different operating modes that favor either sensory input or recurrent processing in the prefrontal cortex. More generally, our findings support a broader role for neuromodulators in the dynamic reconfiguration of functional brain networks and may have clinical implications for understanding the actions of antipsychotic agents. Copyright © 2017 the authors 0270-6474/17/371493-12$15.00/0.

Self-regulation of brain oscillations as a treatment for aberrant brain connections in children with autism.

PubMed

Pineda, J A; Juavinett, A; Datko, M

2012-12-01

Autism is a highly varied developmental disorder typically characterized by deficits in reciprocal social interaction, difficulties with verbal and nonverbal communication, and restricted interests and repetitive behaviors. Although a wide range of behavioral, pharmacological, and alternative medicine strategies have been reported to ameliorate specific symptoms for some individuals, there is at present no cure for the condition. Nonetheless, among the many incompatible observations about aspects of the development, anatomy, and functionality of the autistic brain, it is widely agreed that it is characterized by widespread aberrant connectivity. Such disordered connectivity, be it increased, decreased, or otherwise compromised, may complicate healthy synchronization and communication among and within different neural circuits, thereby producing abnormal processing of sensory inputs necessary for normal social life. It is widely accepted that the innate properties of brain electrical activity produce pacemaker elements and linked networks that oscillate synchronously or asynchronously, likely reflecting a type of functional connectivity. Using phase coherence in multiple frequency EEG bands as a measure of functional connectivity, studies have shown evidence for both global hypoconnectivity and local hyperconnectivity in individuals with ASD. However, the nature of the brain's experience-dependent structural plasticity suggests that these abnormal patterns may be reversed with the proper type of treatment. Indeed, neurofeedback (NF) training, an intervention based on operant conditioning that results in self-regulation of brain electrical oscillations, has shown promise in addressing marked abnormalities in functional and structural connectivity. It is hypothesized that neurofeedback produces positive behavioral changes in ASD children by normalizing the aberrant connections within and between neural circuits. NF exploits the brain's plasticity to normalize aberrant connectivity patterns apparent in the autistic brain. By grounding this training in known anatomical (e.g., mirror neuron system) and functional markers (e.g., mu rhythms) of autism, NF training holds promise to support current treatments for this complex disorder. The proposed hypothesis specifically states that neurofeedback-induced alpha mu (8-12Hz) rhythm suppression or desynchronization, a marker of cortical activation, should induce neuroplastic changes and lead to normalization in relevant mirroring networks that have been associated with higher-order social cognition. Copyright © 2012 Elsevier Ltd. All rights reserved.

Finding the imposter: brain connectivity of lesions causing delusional misidentifications

PubMed Central

Darby, R Ryan; Laganiere, Simon; Pascual-Leone, Alvaro; Prasad, Sashank; Fox, Michael D

2017-01-01

Abstract See McKay and Furl (doi:10.1093/aww323) for a scientific commentary on this article. Focal brain injury can sometimes lead to bizarre symptoms, such as the delusion that a family member has been replaced by an imposter (Capgras syndrome). How a single brain lesion could cause such a complex disorder is unclear, leading many to speculate that concurrent delirium, psychiatric disease, dementia, or a second lesion is required. Here we instead propose that Capgras and other delusional misidentification syndromes arise from single lesions at unique locations within the human brain connectome. This hypothesis is motivated by evidence that symptoms emerge from sites functionally connected to a lesion location, not just the lesion location itself. First, 17 cases of lesion-induced delusional misidentifications were identified and lesion locations were mapped to a common brain atlas. Second, lesion network mapping was used to identify brain regions functionally connected to the lesion locations. Third, regions involved in familiarity perception and belief evaluation, two processes thought to be abnormal in delusional misidentifications, were identified using meta-analyses of previous functional magnetic resonance imaging studies. We found that all 17 lesion locations were functionally connected to the left retrosplenial cortex, the region most activated in functional magnetic resonance imaging studies of familiarity. Similarly, 16 of 17 lesion locations were functionally connected to the right frontal cortex, the region most activated in functional magnetic resonance imaging studies of expectation violation, a component of belief evaluation. This connectivity pattern was highly specific for delusional misidentifications compared to four other lesion-induced neurological syndromes (P < 0.0001). Finally, 15 lesions causing other types of delusions were connected to expectation violation (P < 0.0001) but not familiarity regions, demonstrating specificity for delusion content. Our results provide potential neuroanatomical correlates for impaired familiarity perception and belief evaluation in patients with delusional misidentifications. More generally, we demonstrate a mechanism by which a single lesion can cause a complex neuropsychiatric syndrome based on that lesion’s unique pattern of functional connectivity, without the need for pre-existing or hidden pathology. PMID:28082298

Dynamic brain connectivity is a better predictor of PTSD than static connectivity.

PubMed

Jin, Changfeng; Jia, Hao; Lanka, Pradyumna; Rangaprakash, D; Li, Lingjiang; Liu, Tianming; Hu, Xiaoping; Deshpande, Gopikrishna

2017-09-01

Using resting-state functional magnetic resonance imaging, we test the hypothesis that subjects with post-traumatic stress disorder (PTSD) are characterized by reduced temporal variability of brain connectivity compared to matched healthy controls. Specifically, we test whether PTSD is characterized by elevated static connectivity, coupled with decreased temporal variability of those connections, with the latter providing greater sensitivity toward the pathology than the former. Static functional connectivity (FC; nondirectional zero-lag correlation) and static effective connectivity (EC; directional time-lagged relationships) were obtained over the entire brain using conventional models. Dynamic FC and dynamic EC were estimated by letting the conventional models to vary as a function of time. Statistical separation and discriminability of these metrics between the groups and their ability to accurately predict the diagnostic label of a novel subject were ascertained using separate support vector machine classifiers. Our findings support our hypothesis that PTSD subjects have stronger static connectivity, but reduced temporal variability of connectivity. Further, machine learning classification accuracy obtained with dynamic FC and dynamic EC was significantly higher than that obtained with static FC and static EC, respectively. Furthermore, results also indicate that the ease with which brain regions engage or disengage with other regions may be more sensitive to underlying pathology than the strength with which they are engaged. Future studies must examine whether this is true only in the case of PTSD or is a general organizing principle in the human brain. Hum Brain Mapp 38:4479-4496, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Toward a standardized structural-functional group connectome in MNI space.

PubMed

Horn, Andreas; Blankenburg, Felix

2016-01-01

The analysis of the structural architecture of the human brain in terms of connectivity between its subregions has provided profound insights into its underlying functional organization and has coined the concept of the "connectome", a structural description of the elements forming the human brain and the connections among them. Here, as a proof of concept, we introduce a novel group connectome in standard space based on a large sample of 169 subjects from the Enhanced Nathan Kline Institute-Rockland Sample (eNKI-RS). Whole brain structural connectomes of each subject were estimated with a global tracking approach, and the resulting fiber tracts were warped into standard stereotactic (MNI) space using DARTEL. Employing this group connectome, the results of published tracking studies (i.e., the JHU white matter and Oxford thalamic connectivity atlas) could be largely reproduced directly within MNI space. In a second analysis, a study that examined structural connectivity between regions of a functional network, namely the default mode network, was reproduced. Voxel-wise structural centrality was then calculated and compared to others' findings. Furthermore, including additional resting-state fMRI data from the same subjects, structural and functional connectivity matrices between approximately forty thousand nodes of the brain were calculated. This was done to estimate structure-function agreement indices of voxel-wise whole brain connectivity. Taken together, the combination of a novel whole brain fiber tracking approach and an advanced normalization method led to a group connectome that allowed (at least heuristically) performing fiber tracking directly within MNI space. Such an approach may be used for various purposes like the analysis of structural connectivity and modeling experiments that aim at studying the structure-function relationship of the human connectome. Moreover, it may even represent a first step toward a standard DTI template of the human brain in stereotactic space. The standardized group connectome might thus be a promising new resource to better understand and further analyze the anatomical architecture of the human brain on a population level. Copyright © 2015 Elsevier Inc. All rights reserved.

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.

Corticostriatal Connectivity in Antisocial Personality Disorder by MAO-A Genotype and Its Relationship to Aggressive Behavior.

PubMed

Kolla, Nathan J; Dunlop, Katharine; Meyer, Jeffrey H; Downar, Jonathan

2018-05-09

The influence of genetic variation on resting-state neural networks represents a burgeoning line of inquiry in psychiatric research. Monoamine oxidase A, an X-linked gene, is one example of a molecular target linked to brain activity in psychiatric illness. Monoamine oxidase A genetic variants, including the high and low variable nucleotide tandem repeat polymorphisms, have been shown to differentially affect brain functional connectivity in healthy humans. However, it is currently unknown whether these same polymorphisms influence resting-state brain activity in clinical conditions. Given its high burden on society and strong connection to violent behavior, antisocial personality disorder is a logical condition to study, since in vivo markers of monoamine oxidase A brain enzyme are reduced in key affect-modulating regions, and striatal levels of monoamine oxidase A show a relation with the functional connectivity of this same region. We utilized monoamine oxidase A genotyping and seed-to-voxel-based functional connectivity to investigate the relationship between genotype and corticostriatal connectivity in 21 male participants with severe antisocial personality disorder and 19 male healthy controls. Dorsal striatal connectivity to the frontal pole and anterior cingulate gyrus differentiated antisocial personality disorder subjects and healthy controls by monoamine oxidase A genotype. Furthermore, the linear relationship of proactive aggression to superior ventral striatal-angular gyrus functional connectivity differed by monoamine oxidase A genotype in the antisocial personality disorder groups. These results suggest that monoamine oxidase A genotype may affect corticostriatal connectivity in antisocial personality disorder and that these functional connections may also underlie use of proactive aggression in a genotype-specific manner.

Resting-State Functional Connectivity Differentiates Anxious Apprehension and Anxious Arousal

PubMed Central

Burdwood, Erin N.; Infantolino, Zachary P.; Crocker, Laura D.; Spielberg, Jeffrey M.; Banich, Marie T.; Miller, Gregory A.; Heller, Wendy

2016-01-01

Brain regions in the default mode network (DMN) display greater functional connectivity at rest or during self-referential processing than during goal-directed tasks. The present study assessed resting-state connectivity as a function of anxious apprehension and anxious arousal, independent of depressive symptoms, in order to understand how these dimensions disrupt cognition. Whole-brain, seed-based analyses indicated differences between anxious apprehension and anxious arousal in DMN functional connectivity. Lower connectivity associated with higher anxious apprehension suggests decreased adaptive, inner-focused thought processes, whereas higher connectivity at higher levels of anxious arousal may reflect elevated monitoring of physiological responses to threat. These findings further the conceptualization of anxious apprehension and anxious arousal as distinct psychological dimensions with distinct neural instantiations. PMID:27406406

Changes in Thalamic Connectivity in the Early and Late Stages of Amnestic Mild Cognitive Impairment: A Resting-State Functional Magnetic Resonance Study from ADNI

PubMed Central

Cai, Suping; Huang, Liyu; Zou, Jia; Jing, Longlong; Zhai, Buzhong; Ji, Gongjun; von Deneen, Karen M.; Ren, Junchan; Ren, Aifeng

2015-01-01

We used resting-state functional magnetic resonance imaging (fMRI) to investigate changes in the thalamus functional connectivity in early and late stages of amnestic mild cognitive impairment. Data of 25 late stages of amnestic mild cognitive impairment (LMCI) patients, 30 early stages of amnestic mild cognitive impairment (EMCI) patients and 30 well-matched healthy controls (HC) were analyzed from the Alzheimer’s disease Neuroimaging Initiative (ADNI). We focused on the correlation between low frequency fMRI signal fluctuations in the thalamus and those in all other brain regions. Compared to healthy controls, we found functional connectivity between the left/right thalamus and a set of brain areas was decreased in LMCI and/or EMCI including right fusiform gyrus (FG), left and right superior temporal gyrus, left medial frontal gyrus extending into supplementary motor area, right insula, left middle temporal gyrus (MTG) extending into middle occipital gyrus (MOG). We also observed increased functional connectivity between the left/right thalamus and several regions in LMCI and/or EMCI including left FG, right MOG, left and right precuneus, right MTG and left inferior temporal gyrus. In the direct comparison between the LMCI and EMCI groups, we obtained several brain regions showed thalamus-seeded functional connectivity differences such as the precentral gyrus, hippocampus, FG and MTG. Briefly, these brain regions mentioned above were mainly located in the thalamo-related networks including thalamo-hippocampus, thalamo-temporal, thalamo-visual, and thalamo-default mode network. The decreased functional connectivity of the thalamus might suggest reduced functional integrity of thalamo-related networks and increased functional connectivity indicated that aMCI patients could use additional brain resources to compensate for the loss of cognitive function. Our study provided a new sight to understand the two important states of aMCI and revealed resting-state fMRI is an appropriate method for exploring pathophysiological changes in aMCI. PMID:25679386

Changes in thalamic connectivity in the early and late stages of amnestic mild cognitive impairment: a resting-state functional magnetic resonance study from ADNI.

PubMed

Cai, Suping; Huang, Liyu; Zou, Jia; Jing, Longlong; Zhai, Buzhong; Ji, Gongjun; von Deneen, Karen M; Ren, Junchan; Ren, Aifeng

2015-01-01

We used resting-state functional magnetic resonance imaging (fMRI) to investigate changes in the thalamus functional connectivity in early and late stages of amnestic mild cognitive impairment. Data of 25 late stages of amnestic mild cognitive impairment (LMCI) patients, 30 early stages of amnestic mild cognitive impairment (EMCI) patients and 30 well-matched healthy controls (HC) were analyzed from the Alzheimer's disease Neuroimaging Initiative (ADNI). We focused on the correlation between low frequency fMRI signal fluctuations in the thalamus and those in all other brain regions. Compared to healthy controls, we found functional connectivity between the left/right thalamus and a set of brain areas was decreased in LMCI and/or EMCI including right fusiform gyrus (FG), left and right superior temporal gyrus, left medial frontal gyrus extending into supplementary motor area, right insula, left middle temporal gyrus (MTG) extending into middle occipital gyrus (MOG). We also observed increased functional connectivity between the left/right thalamus and several regions in LMCI and/or EMCI including left FG, right MOG, left and right precuneus, right MTG and left inferior temporal gyrus. In the direct comparison between the LMCI and EMCI groups, we obtained several brain regions showed thalamus-seeded functional connectivity differences such as the precentral gyrus, hippocampus, FG and MTG. Briefly, these brain regions mentioned above were mainly located in the thalamo-related networks including thalamo-hippocampus, thalamo-temporal, thalamo-visual, and thalamo-default mode network. The decreased functional connectivity of the thalamus might suggest reduced functional integrity of thalamo-related networks and increased functional connectivity indicated that aMCI patients could use additional brain resources to compensate for the loss of cognitive function. Our study provided a new sight to understand the two important states of aMCI and revealed resting-state fMRI is an appropriate method for exploring pathophysiological changes in aMCI.

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.

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.

How functional connectivity between emotion regulation structures can be disrupted: preliminary evidence from adolescents with moderate to severe traumatic brain injury.

PubMed

Newsome, Mary R; Scheibel, Randall S; Mayer, Andrew R; Chu, Zili D; Wilde, Elisabeth A; Hanten, Gerri; Steinberg, Joel L; Lin, Xiaodi; Li, Xiaoqi; Merkley, Tricia L; Hunter, Jill V; Vasquez, Ana C; Cook, Lori; Lu, Hanzhang; Vinton, Kami; Levin, Harvey S

2013-09-01

Outcome of moderate to severe traumatic brain injury (TBI) includes impaired emotion regulation. Emotion regulation has been associated with amygdala and rostral anterior cingulate (rACC). However, functional connectivity between the two structures after injury has not been reported. A preliminary examination of functional connectivity of rACC and right amygdala was conducted in adolescents 2 to 3 years after moderate to severe TBI and in typically developing (TD)control adolescents, with the hypothesis that the TBI adolescents would demonstrate altered functional connectivity in the two regions. Functional connectivity was determined by correlating fluctuations in the blood oxygen level dependent(BOLD) signal of the rACC and right amygdala with that of other brain regions. In the TBI adolescents, the rACC was found to be significantly less functionally connected to medial prefrontal cortices and to right temporal regions near the amygdala (height threshold T = 2.5, cluster level p < .05, FDR corrected), while the right amygdala showed a trend in reduced functional connectivity with the rACC (height threshold T = 2.5, cluster level p = .06, FDR corrected). Data suggest disrupted functional connectivity in emotion regulation regions. Limitations include small sample sizes. Studies with larger sample sizes are necessary to characterize the persistent neural damage resulting from moderate to severe TBI during development.

Disrupted cortical connectivity theory as an explanatory model for autism spectrum disorders.

PubMed

Kana, Rajesh K; Libero, Lauren E; Moore, Marie S

2011-12-01

Recent findings of neurological functioning in autism spectrum disorder (ASD) point to altered brain connectivity as a key feature of its pathophysiology. The cortical underconnectivity theory of ASD (Just et al., 2004) provides an integrated framework for addressing these new findings. This theory suggests that weaker functional connections among brain areas in those with ASD hamper their ability to accomplish complex cognitive and social tasks successfully. We will discuss this theory, but will modify the term underconnectivity to 'disrupted cortical connectivity' to capture patterns of both under- and over-connectivity in the brain. In this paper, we will review the existing literature on ASD to marshal supporting evidence for hypotheses formulated on the disrupted cortical connectivity theory. These hypotheses are: 1) underconnectivity in ASD is manifested mainly in long-distance cortical as well as subcortical connections rather than in short-distance cortical connections; 2) underconnectivity in ASD is manifested only in complex cognitive and social functions and not in low-level sensory and perceptual tasks; 3) functional underconnectivity in ASD may be the result of underlying anatomical abnormalities, such as problems in the integrity of white matter; 4) the ASD brain adapts to underconnectivity through compensatory strategies such as overconnectivity mainly in frontal and in posterior brain areas. This may be manifested as deficits in tasks that require frontal-parietal integration. While overconnectivity can be tested by examining the cortical minicolumn organization, long-distance underconnectivity can be tested by cognitively demanding tasks; and 5) functional underconnectivity in brain areas in ASD will be seen not only during complex tasks but also during task-free resting states. We will also discuss some empirical predictions that can be tested in future studies, such as: 1) how disrupted connectivity relates to cognitive impairments in skills such as Theory-of-Mind, cognitive flexibility, and information processing; and 2) how connection abnormalities relate to, and may determine, behavioral symptoms hallmarked by the triad of Impairments in ASD. Furthermore, we will relate the disrupted cortical connectivity model to existing cognitive and neural models of ASD. Published by Elsevier B.V.

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.

Age-related functional brain changes in young children.

PubMed

Long, Xiangyu; Benischek, Alina; Dewey, Deborah; Lebel, Catherine

2017-07-15

Brain function and structure change significantly during the toddler and preschool years. However, most studies focus on older or younger children, so the specific nature of these changes is unclear. In the present study, we analyzed 77 functional magnetic resonance imaging datasets from 44 children aged 2-6 years. We extracted measures of both local (amplitude of low frequency fluctuation and regional homogeneity) and global (eigenvector centrality mapping) activity and connectivity, and examined their relationships with age using robust linear correlation analysis and strict control for head motion. Brain areas within the default mode network and the frontoparietal network, such as the middle frontal gyrus, the inferior parietal lobule and the posterior cingulate cortex, showed increases in local and global functional features with age. Several brain areas such as the superior parietal lobule and superior temporal gyrus presented opposite development trajectories of local and global functional features, suggesting a shifting connectivity framework in early childhood. This development of functional connectivity in early childhood likely underlies major advances in cognitive abilities, including language and development of theory of mind. These findings provide important insight into the development patterns of brain function during the preschool years, and lay the foundation for future studies of altered brain development in young children with brain disorders or injury. Copyright © 2017 Elsevier Inc. All rights reserved.

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.

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.

Distinctive Correspondence Between Separable Visual Attention Functions and Intrinsic Brain Networks

PubMed Central

Ruiz-Rizzo, Adriana L.; Neitzel, Julia; Müller, Hermann J.; Sorg, Christian; Finke, Kathrin

2018-01-01

Separable visual attention functions are assumed to rely on distinct but interacting neural mechanisms. Bundesen's “theory of visual attention” (TVA) allows the mathematical estimation of independent parameters that characterize individuals' visual attentional capacity (i.e., visual processing speed and visual short-term memory storage capacity) and selectivity functions (i.e., top-down control and spatial laterality). However, it is unclear whether these parameters distinctively map onto different brain networks obtained from intrinsic functional connectivity, which organizes slowly fluctuating ongoing brain activity. In our study, 31 demographically homogeneous healthy young participants performed whole- and partial-report tasks and underwent resting-state functional magnetic resonance imaging (rs-fMRI). Report accuracy was modeled using TVA to estimate, individually, the four TVA parameters. Networks encompassing cortical areas relevant for visual attention were derived from independent component analysis of rs-fMRI data: visual, executive control, right and left frontoparietal, and ventral and dorsal attention networks. Two TVA parameters were mapped on particular functional networks. First, participants with higher (vs. lower) visual processing speed showed lower functional connectivity within the ventral attention network. Second, participants with more (vs. less) efficient top-down control showed higher functional connectivity within the dorsal attention network and lower functional connectivity within the visual network. Additionally, higher performance was associated with higher functional connectivity between networks: specifically, between the ventral attention and right frontoparietal networks for visual processing speed, and between the visual and executive control networks for top-down control. The higher inter-network functional connectivity was related to lower intra-network connectivity. These results demonstrate that separable visual attention parameters that are assumed to constitute relatively stable traits correspond distinctly to the functional connectivity both within and between particular functional networks. This implies that individual differences in basic attention functions are represented by differences in the coherence of slowly fluctuating brain activity. PMID:29662444

Distinctive Correspondence Between Separable Visual Attention Functions and Intrinsic Brain Networks.

PubMed

Ruiz-Rizzo, Adriana L; Neitzel, Julia; Müller, Hermann J; Sorg, Christian; Finke, Kathrin

2018-01-01

Separable visual attention functions are assumed to rely on distinct but interacting neural mechanisms. Bundesen's "theory of visual attention" (TVA) allows the mathematical estimation of independent parameters that characterize individuals' visual attentional capacity (i.e., visual processing speed and visual short-term memory storage capacity) and selectivity functions (i.e., top-down control and spatial laterality). However, it is unclear whether these parameters distinctively map onto different brain networks obtained from intrinsic functional connectivity, which organizes slowly fluctuating ongoing brain activity. In our study, 31 demographically homogeneous healthy young participants performed whole- and partial-report tasks and underwent resting-state functional magnetic resonance imaging (rs-fMRI). Report accuracy was modeled using TVA to estimate, individually, the four TVA parameters. Networks encompassing cortical areas relevant for visual attention were derived from independent component analysis of rs-fMRI data: visual, executive control, right and left frontoparietal, and ventral and dorsal attention networks. Two TVA parameters were mapped on particular functional networks. First, participants with higher (vs. lower) visual processing speed showed lower functional connectivity within the ventral attention network. Second, participants with more (vs. less) efficient top-down control showed higher functional connectivity within the dorsal attention network and lower functional connectivity within the visual network. Additionally, higher performance was associated with higher functional connectivity between networks: specifically, between the ventral attention and right frontoparietal networks for visual processing speed, and between the visual and executive control networks for top-down control. The higher inter-network functional connectivity was related to lower intra-network connectivity. These results demonstrate that separable visual attention parameters that are assumed to constitute relatively stable traits correspond distinctly to the functional connectivity both within and between particular functional networks. This implies that individual differences in basic attention functions are represented by differences in the coherence of slowly fluctuating brain activity.

Change of Brain Functional Connectivity in Patients With Spinal Cord Injury: Graph Theory Based Approach.

PubMed

Min, Yu-Sun; Chang, Yongmin; Park, Jang Woo; Lee, Jong-Min; Cha, Jungho; Yang, Jin-Ju; Kim, Chul-Hyun; Hwang, Jong-Moon; Yoo, Ji-Na; Jung, Tae-Du

2015-06-01

To investigate the global functional reorganization of the brain following spinal cord injury with graph theory based approach by creating whole brain functional connectivity networks from resting state-functional magnetic resonance imaging (rs-fMRI), characterizing the reorganization of these networks using graph theoretical metrics and to compare these metrics between patients with spinal cord injury (SCI) and age-matched controls. Twenty patients with incomplete cervical SCI (14 males, 6 females; age, 55±14.1 years) and 20 healthy subjects (10 males, 10 females; age, 52.9±13.6 years) participated in this study. To analyze the characteristics of the whole brain network constructed with functional connectivity using rs-fMRI, graph theoretical measures were calculated including clustering coefficient, characteristic path length, global efficiency and small-worldness. Clustering coefficient, global efficiency and small-worldness did not show any difference between controls and SCIs in all density ranges. The normalized characteristic path length to random network was higher in SCI patients than in controls and reached statistical significance at 12%-13% of density (p<0.05, uncorrected). The graph theoretical approach in brain functional connectivity might be helpful to reveal the information processing after SCI. These findings imply that patients with SCI can build on preserved competent brain control. Further analyses, such as topological rearrangement and hub region identification, will be needed for better understanding of neuroplasticity in patients with SCI.

An evaluation of the left-brain vs. right-brain hypothesis with resting state functional connectivity magnetic resonance imaging.

PubMed

Nielsen, Jared A; Zielinski, Brandon A; Ferguson, Michael A; Lainhart, Janet E; Anderson, Jeffrey S

2013-01-01

Lateralized brain regions subserve functions such as language and visuospatial processing. It has been conjectured that individuals may be left-brain dominant or right-brain dominant based on personality and cognitive style, but neuroimaging data has not provided clear evidence whether such phenotypic differences in the strength of left-dominant or right-dominant networks exist. We evaluated whether strongly lateralized connections covaried within the same individuals. Data were analyzed from publicly available resting state scans for 1011 individuals between the ages of 7 and 29. For each subject, functional lateralization was measured for each pair of 7266 regions covering the gray matter at 5-mm resolution as a difference in correlation before and after inverting images across the midsagittal plane. The difference in gray matter density between homotopic coordinates was used as a regressor to reduce the effect of structural asymmetries on functional lateralization. Nine left- and 11 right-lateralized hubs were identified as peaks in the degree map from the graph of significantly lateralized connections. The left-lateralized hubs included regions from the default mode network (medial prefrontal cortex, posterior cingulate cortex, and temporoparietal junction) and language regions (e.g., Broca Area and Wernicke Area), whereas the right-lateralized hubs included regions from the attention control network (e.g., lateral intraparietal sulcus, anterior insula, area MT, and frontal eye fields). Left- and right-lateralized hubs formed two separable networks of mutually lateralized regions. Connections involving only left- or only right-lateralized hubs showed positive correlation across subjects, but only for connections sharing a node. Lateralization of brain connections appears to be a local rather than global property of brain networks, and our data are not consistent with a whole-brain phenotype of greater "left-brained" or greater "right-brained" network strength across individuals. Small increases in lateralization with age were seen, but no differences in gender were observed.

Mapping cell-specific functional connections in the mouse brain using ChR2-evoked hemodynamics (Conference Presentation)

NASA Astrophysics Data System (ADS)

Bauer, Adam Q.; Kraft, Andrew; Baxter, Grant A.; Bruchas, Michael; Lee, Jin-Moo; Culver, Joseph P.

2017-02-01

Functional magnetic resonance imaging (fMRI) has transformed our understanding of the brain's functional organization. However, mapping subunits of a functional network using hemoglobin alone presents several disadvantages. Evoked and spontaneous hemodynamic fluctuations reflect ensemble activity from several populations of neurons making it difficult to discern excitatory vs inhibitory network activity. Still, blood-based methods of brain mapping remain powerful because hemoglobin provides endogenous contrast in all mammalian brains. To add greater specificity to hemoglobin assays, we integrated optical intrinsic signal(OIS) imaging with optogenetic stimulation to create an Opto-OIS mapping tool that combines the cell-specificity of optogenetics with label-free, hemoglobin imaging. Before mapping, titrated photostimuli determined which stimulus parameters elicited linear hemodynamic responses in the cortex. Optimized stimuli were then scanned over the left hemisphere to create a set of optogenetically-defined effective connectivity (Opto-EC) maps. For many sites investigated, Opto-EC maps exhibited higher spatial specificity than those determined using spontaneous hemodynamic fluctuations. For example, resting-state functional connectivity (RS-FC) patterns exhibited widespread ipsilateral connectivity while Opto-EC maps contained distinct short- and long-range constellations of ipsilateral connectivity. Further, RS-FC maps were usually symmetric about midline while Opto-EC maps displayed more heterogeneous contralateral homotopic connectivity. Both Opto-EC and RS-FC patterns were compared to mouse connectivity data from the Allen Institute. Unlike RS-FC maps, Thy1-based maps collected in awake, behaving mice closely recapitulated the connectivity structure derived using ex vivo anatomical tracer methods. Opto-OIS mapping could be a powerful tool for understanding cellular and molecular contributions to network dynamics and processing in the mouse brain.

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.

Connectivity Predicts Deep Brain Stimulation Outcome in Parkinson Disease

PubMed Central

Horn, Andreas; Reich, Martin; Vorwerk, Johannes; Li, Ningfei; Wenzel, Gregor; Fang, Qianqian; Schmitz-Hübsch, Tanja; Nickl, Robert; Kupsch, Andreas; Volkmann, Jens; Kühn, Andrea A.; Fox, Michael D.

2018-01-01

Objective The benefit of deep brain stimulation (DBS) for Parkinson disease (PD) may depend on connectivity between the stimulation site and other brain regions, but which regions and whether connectivity can predict outcome in patients remain unknown. Here, we identify the structural and functional connectivity profile of effective DBS to the subthalamic nucleus (STN) and test its ability to predict outcome in an independent cohort. Methods A training dataset of 51 PD patients with STN DBS was combined with publicly available human connectome data (diffusion tractography and resting state functional connectivity) to identify connections reliably associated with clinical improvement (motor score of the Unified Parkinson Disease Rating Scale [UPDRS]). This connectivity profile was then used to predict outcome in an independent cohort of 44 patients from a different center. Results In the training dataset, connectivity between the DBS electrode and a distributed network of brain regions correlated with clinical response including structural connectivity to supplementary motor area and functional anticorrelation to primary motor cortex (p<0.001). This same connectivity profile predicted response in an independent patient cohort (p<0.01). Structural and functional connectivity were independent predictors of clinical improvement (p<0.001) and estimated response in individual patients with an average error of 15% UPDRS improvement. Results were similar using connectome data from normal subjects or a connectome age, sex, and disease matched to our DBS patients. Interpretation Effective STN DBS for PD is associated with a specific connectivity profile that can predict clinical outcome across independent cohorts. This prediction does not require specialized imaging in PD patients themselves. PMID:28586141

The Interface between Neuroscience and Neuro-Psychoanalysis: Focus on Brain Connectivity

PubMed Central

Salone, Anatolia; Di Giacinto, Alessandra; Lai, Carlo; De Berardis, Domenico; Iasevoli, Felice; Fornaro, Michele; De Risio, Luisa; Santacroce, Rita; Martinotti, Giovanni; Giannantonio, Massimo Di

2016-01-01

Over the past 20 years, the advent of advanced techniques has significantly enhanced our knowledge on the brain. Yet, our understanding of the physiological and pathological functioning of the mind is still far from being exhaustive. Both the localizationist and the reductionist neuroscientific approaches to psychiatric disorders have proven to be largely unsatisfactory and are outdated. Accruing evidence suggests that psychoanalysis can engage the neurosciences in a productive and mutually enriching dialogue that may further our understanding of psychiatric disorders. In particular, advances in brain connectivity research have provided evidence supporting the convergence of neuroscientific findings and psychoanalysis and helped characterize the circuitry and mechanisms that underlie higher brain functions. In the present paper we discuss how knowledge on brain connectivity can impact neuropsychoanalysis, with a particular focus on schizophrenia. Brain connectivity studies in schizophrenic patients indicate complex alterations in brain functioning and circuitry, with particular emphasis on the role of cortical midline structures (CMS) and the default mode network (DMN). These networks seem to represent neural correlates of psychodynamic concepts central to the understanding of schizophrenia and of core psychopathological alterations of this disorder (i.e., ego disturbances and impaired primary process thinking). PMID:26869904

A Multimodal Imaging- and Stimulation-based Method of Evaluating Connectivity-related Brain Excitability in Patients with Epilepsy

PubMed Central

Shafi, Mouhsin M.; Whitfield-Gabrieli, Susan; Chu, Catherine J.; Pascual-Leone, Alvaro; Chang, Bernard S.

2017-01-01

Resting-state functional connectivity MRI (rs-fcMRI) is a technique that identifies connectivity between different brain regions based on correlations over time in the blood-oxygenation level dependent signal. rs-fcMRI has been applied extensively to identify abnormalities in brain connectivity in different neurologic and psychiatric diseases. However, the relationship among rs-fcMRI connectivity abnormalities, brain electrophysiology and disease state is unknown, in part because the causal significance of alterations in functional connectivity in disease pathophysiology has not been established. Transcranial Magnetic Stimulation (TMS) is a technique that uses electromagnetic induction to noninvasively produce focal changes in cortical activity. When combined with electroencephalography (EEG), TMS can be used to assess the brain's response to external perturbations. Here we provide a protocol for combining rs-fcMRI, TMS and EEG to assess the physiologic significance of alterations in functional connectivity in patients with neuropsychiatric disease. We provide representative results from a previously published study in which rs-fcMRI was used to identify regions with abnormal connectivity in patients with epilepsy due to a malformation of cortical development, periventricular nodular heterotopia (PNH). Stimulation in patients with epilepsy resulted in abnormal TMS-evoked EEG activity relative to stimulation of the same sites in matched healthy control patients, with an abnormal increase in the late component of the TMS-evoked potential, consistent with cortical hyperexcitability. This abnormality was specific to regions with abnormal resting-state functional connectivity. Electrical source analysis in a subject with previously recorded seizures demonstrated that the origin of the abnormal TMS-evoked activity co-localized with the seizure-onset zone, suggesting the presence of an epileptogenic circuit. These results demonstrate how rs-fcMRI, TMS and EEG can be utilized together to identify and understand the physiological significance of abnormal brain connectivity in human diseases. PMID:27911366

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

Brain-Wide Analysis of Functional Connectivity in First-Episode and Chronic Stages of Schizophrenia.

PubMed

Li, Tao; Wang, Qiang; Zhang, Jie; Rolls, Edmund T; Yang, Wei; Palaniyappan, Lena; Zhang, Lu; Cheng, Wei; Yao, Ye; Liu, Zhaowen; Gong, Xiaohong; Luo, Qiang; Tang, Yanqing; Crow, Timothy J; Broome, Matthew R; Xu, Ke; Li, Chunbo; Wang, Jijun; Liu, Zhening; Lu, Guangming; Wang, Fei; Feng, Jianfeng

2017-03-01

Published reports of functional abnormalities in schizophrenia remain divergent due to lack of staging point-of-view and whole-brain analysis. To identify key functional-connectivity differences of first-episode (FE) and chronic patients from controls using resting-state functional MRI, and determine changes that are specifically associated with disease onset, a clinical staging model is adopted. We analyze functional-connectivity differences in prodromal, FE (mostly drug naïve), and chronic patients from their matched controls from 6 independent datasets involving a total of 789 participants (343 patients). Brain-wide functional-connectivity analysis was performed in different datasets and the results from the datasets of the same stage were then integrated by meta-analysis, with Bonferroni correction for multiple comparisons. Prodromal patients differed from controls in their pattern of functional-connectivity involving the inferior frontal gyri (Broca's area). In FE patients, 90% of the functional-connectivity changes involved the frontal lobes, mostly the inferior frontal gyrus including Broca's area, and these changes were correlated with delusions/blunted affect. For chronic patients, functional-connectivity differences extended to wider areas of the brain, including reduced thalamo-frontal connectivity, and increased thalamo-temporal and thalamo-sensorimoter connectivity that were correlated with the positive, negative, and general symptoms, respectively. Thalamic changes became prominent at the chronic stage. These results provide evidence for distinct patterns of functional-dysconnectivity across FE and chronic stages of schizophrenia. Importantly, abnormalities in the frontal language networks appear early, at the time of disease onset. The identification of stage-specific pathological processes may help to understand the disease course of schizophrenia and identify neurobiological markers crucial for early diagnosis. © The Author 2016. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Ketamine induces a robust whole-brain connectivity pattern that can be differentially modulated by drugs of different mechanism and clinical profile.

PubMed

Joules, R; Doyle, O M; Schwarz, A J; O'Daly, O G; Brammer, M; Williams, S C; Mehta, M A

2015-11-01

Ketamine, an N-methyl-D-aspartate receptor (NMDAR) antagonist, has been studied in relation to the glutamate hypothesis of schizophrenia and increases dissociation, positive and negative symptom ratings. Ketamine effects brain function through changes in brain activity; these activity patterns can be modulated by pre-treatment of compounds known to attenuate the effects of ketamine on glutamate release. Ketamine also has marked effects on brain connectivity; we predicted that these changes would also be modulated by compounds known to attenuate glutamate release. Here, we perform task-free pharmacological magnetic resonance imaging (phMRI) to investigate the functional connectivity effects of ketamine in the brain and the potential modulation of these effects by pre-treatment of the compounds lamotrigine and risperidone, compounds hypothesised to differentially modulate glutamate release. Connectivity patterns were assessed by combining windowing, graph theory and multivariate Gaussian process classification. We demonstrate that ketamine has a robust effect on the functional connectivity of the human brain compared to saline (87.5 % accuracy). Ketamine produced a shift from a cortically centred, to a subcortically centred pattern of connections. This effect is strongly modulated by pre-treatment with risperidone (81.25 %) but not lamotrigine (43.75 %). Based on the differential effect of these compounds on ketamine response, we suggest the observed connectivity effects are primarily due to NMDAR blockade rather than downstream glutamatergic effects. The connectivity changes contrast with amplitude of response for which no differential effect between pre-treatments was detected, highlighting the necessity of these techniques in forming an informed view of the mechanistic effects of pharmacological compounds in the human brain.

Changes in functional connectivity of the brain associated with a history of sport concussion: A preliminary investigation.

PubMed

Churchill, Nathan; Hutchison, Michael G; Leung, General; Graham, Simon; Schweizer, Tom A

2017-01-01

There is evidence of long-term clinical consequences associated with a history of sport concussion. However, there remains limited information about the underlying changes in brain function. The goal of this study was to identify brain regions where abnormal resting-state function is associated with chronic concussion, for athletes without persistent symptoms. Functional Magnetic Resonance Imaging (fMRI) was performed on a group of athletes with prior concussion (n = 22) and a group without documented injury (n = 21). Multivariate predictive modelling was used to localize reliable changes in brain connectivity that are associated with a history of concussion and with clinical factors, including number of prior concussions and recovery time from last injury. No significant differences were found between athletes with and without a history of concussion, but functional connectivity was significantly associated with clinical history. The number of prior concussions was associated with most extensive connectivity changes, particularly for elements of the visual attention network and cerebellum. The findings of this preliminary study indicate that functional brain abnormalities associated with chronic concussion may be significantly dependent on clinical history. In addition, elements of the visual and cerebellar systems may be most sensitive to the long-term effects of sport concussion.

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.

Computational Modeling of Resting-State Activity Demonstrates Markers of Normalcy in Children with Prenatal or Perinatal Stroke

PubMed Central

Raja Beharelle, Anjali; Griffa, Alessandra; Hagmann, Patric; Solodkin, Ana; McIntosh, Anthony R.; Small, Steven L.; Deco, Gustavo

2015-01-01

Children who sustain a prenatal or perinatal brain injury in the form of a stroke develop remarkably normal cognitive functions in certain areas, with a particular strength in language skills. A dominant explanation for this is that brain regions from the contralesional hemisphere “take over” their functions, whereas the damaged areas and other ipsilesional regions play much less of a role. However, it is difficult to tease apart whether changes in neural activity after early brain injury are due to damage caused by the lesion or by processes related to postinjury reorganization. We sought to differentiate between these two causes by investigating the functional connectivity (FC) of brain areas during the resting state in human children with early brain injury using a computational model. We simulated a large-scale network consisting of realistic models of local brain areas coupled through anatomical connectivity information of healthy and injured participants. We then compared the resulting simulated FC values of healthy and injured participants with the empirical ones. We found that the empirical connectivity values, especially of the damaged areas, correlated better with simulated values of a healthy brain than those of an injured brain. This result indicates that the structural damage caused by an early brain injury is unlikely to have an adverse and sustained impact on the functional connections, albeit during the resting state, of damaged areas. Therefore, these areas could continue to play a role in the development of near-normal function in certain domains such as language in these children. PMID:26063923

From Hippocampus to Whole-Brain: The Role of Integrative Processing in Episodic Memory Retrieval

PubMed Central

Geib, Benjamin R.; Stanley, Matthew L.; Dennis, Nancy A.; Woldorff, Marty G.; Cabeza, Roberto

2017-01-01

Multivariate functional connectivity analyses of neuroimaging data have revealed the importance of complex, distributed interactions between disparate yet interdependent brain regions. Recent work has shown that topological properties of functional brain networks are associated with individual and group differences in cognitive performance, including in episodic memory. After constructing functional whole-brain networks derived from an event-related fMRI study of memory retrieval, we examined differences in functional brain network architecture between forgotten and remembered words. This study yielded three main findings. First, graph theory analyses showed that successfully remembering compared to forgetting was associated with significant changes in the connectivity profile of the left hippocampus and a corresponding increase in efficient communication with the rest of the brain. Second, bivariate functional connectivity analyses indicated stronger interactions between the left hippocampus and a retrieval assembly for remembered versus forgotten items. This assembly included the left precuneus, left caudate, bilateral supramarginal gyrus, and the bilateral dorsolateral superior frontal gyrus. Integrative properties of the retrieval assembly were greater for remembered than forgotten items. Third, whole-brain modularity analyses revealed that successful memory retrieval was marginally significantly associated with a less segregated modular architecture in the network. The magnitude of the decreases in modularity between remembered and forgotten conditions was related to memory performance. These findings indicate that increases in integrative properties at the nodal, retrieval assembly, and whole-brain topological levels facilitate memory retrieval, while also underscoring the potential of multivariate brain connectivity approaches for providing valuable new insights into the neural bases of memory processes. PMID:28112460

Radiation-induced functional connectivity alterations in nasopharyngeal carcinoma patients with radiotherapy

PubMed Central

Ma, Qiongmin; Wu, Donglin; Zeng, Ling-Li; Shen, Hui; Hu, Dewen; Qiu, Shijun

2016-01-01

Abstract The study aims to investigate the radiation-induced brain functional alterations in nasopharyngeal carcinoma (NPC) patients who received radiotherapy (RT) using functional magnetic resonance imaging (fMRI) and statistic scale. The fMRI data of 35 NPC patients with RT and 24 demographically matched untreated NPC patients were acquired. Montreal Cognitive Assessment (MoCA) was also measured to evaluate their global cognition performance. Multivariate pattern analysis was performed to find the significantly altered functional connections between these 2 groups, while the linear correlation level was detected between the altered functional connections and the MoCA scores. Forty-five notably altered functional connections were found, which were mainly located between 3 brain networks, the cerebellum, sensorimotor, and cingulo-opercular. With strictly false discovery rate correction, 5 altered functional connections were shown to have significant linear correlations with the MoCA scores, that is, the connections between the vermis and hippocampus, cerebellum lobule VI and dorsolateral prefrontal cortex, precuneus and dorsal frontal cortex, cuneus and middle occipital lobe, and insula and cuneus. Besides, the connectivity between the vermis and hippocampus was also significantly correlated with the attention score, 1 of the 7 subscores of the MoCA. The present study provides new insights into the radiation-induced functional connectivity impairments in NPC patients. The results showed that the RT may induce the cognitive impairments, especially the attention alterations. The 45 altered functional connections, especially the 5 altered functional connections that were significantly correlated to the MoCA scores, may serve as the potential biomarkers of the RT-induced brain functional impairments and provide valuable targets for further functional recovery treatment. PMID:27442663

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.

Neurobiological markers of exercise-related brain plasticity in older adults

PubMed Central

Voss, Michelle W.; Erickson, Kirk I.; Prakash, Ruchika Shaurya; Chaddock, Laura; Kim, Jennifer S.; Alves, Heloisa; Szabo, Amanda; White, Siobhan M.; Wójcicki, Thomas R.; Mailey, Emily L.; Olson, Erin A.; Gothe, Neha; Potter, Vicki V.; Martin, Stephen A.; Pence, Brandt D.; Cook, Marc D.; Woods, Jeffrey A.; McAuley, Edward; Kramer, Arthur F.

2012-01-01

The current study examined how a randomized one-year aerobic exercise program for healthy older adults would affect serum levels of brain-derived neurotrophic factor (BDNF), insulin-like growth factor type 1 (IGF-1), and vascular endothelial growth factor (VEGF) - putative markers of exercise-induced benefits on brain function. The study also examined whether (a) change in the concentration of these growth factors was associated with alterations in functional connectivity following exercise, and (b) the extent to which pre-intervention growth factor levels were associated with training-related changes in functional connectivity. In 65 participants (mean age = 66.4), we found that although there were no group-level changes in growth factors as a function of the intervention, increased temporal lobe connectivity between the bilateral parahippocampus and the bilateral middle temporal gyrus was associated with increased BDNF, IGF-1, and VEGF for an aerobic walking group but not for a non-aerobic control group, and greater pre-intervention VEGF was associated with greater training-related increases in this functional connection. Results are consistent with animal models of exercise and the brain, but are the first to show in humans that exercise-induced increases in temporal lobe functional connectivity are associated with changes in growth factors and may be augmented by greater baseline VEGF. PMID:23123199

Abnormal resting-state connectivity of motor and cognitive networks in early manifest Huntington's disease.

PubMed

Wolf, R C; Sambataro, F; Vasic, N; Depping, M S; Thomann, P A; Landwehrmeyer, G B; Süssmuth, S D; Orth, M

2014-11-01

Functional magnetic resonance imaging (fMRI) of multiple neural networks during the brain's 'resting state' could facilitate biomarker development in patients with Huntington's disease (HD) and may provide new insights into the relationship between neural dysfunction and clinical symptoms. To date, however, very few studies have examined the functional integrity of multiple resting state networks (RSNs) in manifest HD, and even less is known about whether concomitant brain atrophy affects neural activity in patients. Using MRI, we investigated brain structure and RSN function in patients with early HD (n = 20) and healthy controls (n = 20). For resting-state fMRI data a group-independent component analysis identified spatiotemporally distinct patterns of motor and prefrontal RSNs of interest. We used voxel-based morphometry to assess regional brain atrophy, and 'biological parametric mapping' analyses to investigate the impact of atrophy on neural activity. Compared with controls, patients showed connectivity changes within distinct neural systems including lateral prefrontal, supplementary motor, thalamic, cingulate, temporal and parietal regions. In patients, supplementary motor area and cingulate cortex connectivity indices were associated with measures of motor function, whereas lateral prefrontal connectivity was associated with cognition. This study provides evidence for aberrant connectivity of RSNs associated with motor function and cognition in early manifest HD when controlling for brain atrophy. This suggests clinically relevant changes of RSN activity in the presence of HD-associated cortical and subcortical structural abnormalities.

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

Characterizing dynamic amplitude of low-frequency fluctuation and its relationship with dynamic functional connectivity: An application to schizophrenia.

PubMed

Fu, Zening; Tu, Yiheng; Di, Xin; Du, Yuhui; Pearlson, G D; Turner, J A; Biswal, Bharat B; Zhang, Zhiguo; Calhoun, V D

2017-09-20

The human brain is a highly dynamic system with non-stationary neural activity and rapidly-changing neural interaction. Resting-state dynamic functional connectivity (dFC) has been widely studied during recent years, and the emerging aberrant dFC patterns have been identified as important features of many mental disorders such as schizophrenia (SZ). However, only focusing on the time-varying patterns in FC is not enough, since the local neural activity itself (in contrast to the inter-connectivity) is also found to be highly fluctuating from research using high-temporal-resolution imaging techniques. Exploring the time-varying patterns in brain activity and their relationships with time-varying brain connectivity is important for advancing our understanding of the co-evolutionary property of brain network and the underlying mechanism of brain dynamics. In this study, we introduced a framework for characterizing time-varying brain activity and exploring its associations with time-varying brain connectivity, and applied this framework to a resting-state fMRI dataset including 151 SZ patients and 163 age- and gender matched healthy controls (HCs). In this framework, 48 brain regions were first identified as intrinsic connectivity networks (ICNs) using group independent component analysis (GICA). A sliding window approach was then adopted for the estimation of dynamic amplitude of low-frequency fluctuation (dALFF) and dFC, which were used to measure time-varying brain activity and time-varying brain connectivity respectively. The dALFF was further clustered into six reoccurring states by the k-means clustering method and the group difference in occurrences of dALFF states was explored. Lastly, correlation coefficients between dALFF and dFC were calculated and the group difference in these dALFF-dFC correlations was explored. Our results suggested that 1) ALFF of brain regions was highly fluctuating during the resting-state and such dynamic patterns are altered in SZ, 2) dALFF and dFC were correlated in time and their correlations are altered in SZ. The overall results support and expand prior work on abnormalities of brain activity, static FC (sFC) and dFC in SZ, and provide new evidence on aberrant time-varying brain activity and its associations with brain connectivity in SZ, which might underscore the disrupted brain cognitive functions in this mental disorder. Copyright © 2017 Elsevier Inc. All rights reserved.

The implications of brain connectivity in the neuropsychology of autism

PubMed Central

Maximo, Jose O.; Cadena, Elyse J.; Kana, Rajesh K.

2014-01-01

Autism is a neurodevelopmental disorder that has been associated with atypical brain functioning. Functional connectivity MRI (fcMRI) studies examining neural networks in autism have seen an exponential rise over the last decade. Such investigations have led to characterization of autism as a distributed neural systems disorder. Studies have found widespread cortical underconnectivity, local overconnectivity, and mixed results suggesting disrupted brain connectivity as a potential neural signature of autism. In this review, we summarize the findings of previous fcMRI studies in autism with a detailed examination of their methodology, in order to better understand its potential and to delineate the pitfalls. We also address how a multimodal neuroimaging approach (incorporating different measures of brain connectivity) may help characterize the complex neurobiology of autism at a global level. Finally, we also address the potential of neuroimaging-based markers in assisting neuropsychological assessment of autism. The quest for a biomarker for autism is still ongoing, yet new findings suggest that aberrant brain connectivity may be a promising candidate. PMID:24496901

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

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

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.

Detecting nonlinear dynamics of functional connectivity

NASA Astrophysics Data System (ADS)

LaConte, Stephen M.; Peltier, Scott J.; Kadah, Yasser; Ngan, Shing-Chung; Deshpande, Gopikrishna; Hu, Xiaoping

2004-04-01

Functional magnetic resonance imaging (fMRI) is a technique that is sensitive to correlates of neuronal activity. The application of fMRI to measure functional connectivity of related brain regions across hemispheres (e.g. left and right motor cortices) has great potential for revealing fundamental physiological brain processes. Primarily, functional connectivity has been characterized by linear correlations in resting-state data, which may not provide a complete description of its temporal properties. In this work, we broaden the measure of functional connectivity to study not only linear correlations, but also those arising from deterministic, non-linear dynamics. Here the delta-epsilon approach is extended and applied to fMRI time series. The method of delays is used to reconstruct the joint system defined by a reference pixel and a candidate pixel. The crux of this technique relies on determining whether the candidate pixel provides additional information concerning the time evolution of the reference. As in many correlation-based connectivity studies, we fix the reference pixel. Every brain location is then used as a candidate pixel to estimate the spatial pattern of deterministic coupling with the reference. Our results indicate that measured connectivity is often emphasized in the motor cortex contra-lateral to the reference pixel, demonstrating the suitability of this approach for functional connectivity studies. In addition, discrepancies with traditional correlation analysis provide initial evidence for non-linear dynamical properties of resting-state fMRI data. Consequently, the non-linear characterization provided from our approach may provide a more complete description of the underlying physiology and brain function measured by this type of data.

Additive effects of oxytocin receptor gene polymorphisms on reward circuitry in youth with autism.

PubMed

Hernandez, L M; Krasileva, K; Green, S A; Sherman, L E; Ponting, C; McCarron, R; Lowe, J K; Geschwind, D H; Bookheimer, S Y; Dapretto, M

2017-08-01

Several common alleles in the oxytocin receptor gene (OXTR) are associated with altered brain function in reward circuitry in neurotypical adults and may increase risk for autism spectrum disorders (ASD). Yet, it is currently unknown how variation in the OXTR relates to brain functioning in individuals with ASD, and, critically, whether neural endophenotypes vary as a function of aggregate genetic risk. Here, for we believe the first time, we use a multi-locus approach to examine how genetic variation across several OXTR single-nucleotide polymorphisms (SNPs) affect functional connectivity of the brain's reward network. Using data from 41 children with ASD and 41 neurotypical children, we examined functional connectivity of the nucleus accumbens (NAcc) - a hub of the reward network - focusing on how connectivity varies with OXTR risk-allele dosage. Youth with ASD showed reduced NAcc connectivity with other areas in the reward circuit as a function of increased OXTR risk-allele dosage, as well as a positive association between risk-allele dosage and symptom severity, whereas neurotypical youth showed increased NAcc connectivity with frontal brain regions involved in mentalizing. In addition, we found that increased NAcc-frontal cortex connectivity in typically developing youth was related to better scores on a standardized measure of social functioning. Our results indicate that cumulative genetic variation on the OXTR impacts reward system connectivity in both youth with ASD and neurotypical controls. By showing differential genetic effects on neuroendophenotypes, these pathways elucidate mechanisms of vulnerability versus resilience in carriers of disease-associated risk alleles.

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

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.

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.

Disrupted cortical connectivity theory as an explanatory model for autism spectrum disorders

NASA Astrophysics Data System (ADS)

Kana, Rajesh K.; Libero, Lauren E.; Moore, Marie S.

2011-12-01

Recent findings of neurological functioning in autism spectrum disorder (ASD) point to altered brain connectivity as a key feature of its pathophysiology. The cortical underconnectivity theory of ASD (Just et al., 2004) provides an integrated framework for addressing these new findings. This theory suggests that weaker functional connections among brain areas in those with ASD hamper their ability to accomplish complex cognitive and social tasks successfully. We will discuss this theory, but will modify the term underconnectivity to ‘disrupted cortical connectivity’ to capture patterns of both under- and over-connectivity in the brain. In this paper, we will review the existing literature on ASD to marshal supporting evidence for hypotheses formulated on the disrupted cortical connectivity theory. These hypotheses are: 1) underconnectivity in ASD is manifested mainly in long-distance cortical as well as subcortical connections rather than in short-distance cortical connections; 2) underconnectivity in ASD is manifested only in complex cognitive and social functions and not in low-level sensory and perceptual tasks; 3) functional underconnectivity in ASD may be the result of underlying anatomical abnormalities, such as problems in the integrity of white matter; 4) the ASD brain adapts to underconnectivity through compensatory strategies such as overconnectivity mainly in frontal and in posterior brain areas. This may be manifested as deficits in tasks that require frontal-parietal integration. While overconnectivity can be tested by examining the cortical minicolumn organization, long-distance underconnectivity can be tested by cognitively demanding tasks; and 5) functional underconnectivity in brain areas in ASD will be seen not only during complex tasks but also during task-free resting states. We will also discuss some empirical predictions that can be tested in future studies, such as: 1) how disrupted connectivity relates to cognitive impairments in skills such as Theory-of-Mind, cognitive flexibility, and information processing; and 2) how connection abnormalities relate to, and may determine, behavioral symptoms hallmarked by the triad of Impairments in ASD. Furthermore, we will relate the disrupted cortical connectivity model to existing cognitive and neural models of ASD.

Effective connectivity inferred from fMRI transition dynamics during movie viewing points to a balanced reconfiguration of cortical interactions.

PubMed

Gilson, Matthieu; Deco, Gustavo; Friston, Karl J; Hagmann, Patric; Mantini, Dante; Betti, Viviana; Romani, Gian Luca; Corbetta, Maurizio

2017-10-09

Our behavior entails a flexible and context-sensitive interplay between brain areas to integrate information according to goal-directed requirements. However, the neural mechanisms governing the entrainment of functionally specialized brain areas remain poorly understood. In particular, the question arises whether observed changes in the regional activity for different cognitive conditions are explained by modifications of the inputs to the brain or its connectivity? We observe that transitions of fMRI activity between areas convey information about the tasks performed by 19 subjects, watching a movie versus a black screen (rest). We use a model-based framework that explains this spatiotemporal functional connectivity pattern by the local variability for 66 cortical regions and the network effective connectivity between them. We find that, among the estimated model parameters, movie viewing affects to a larger extent the local activity, which we interpret as extrinsic changes related to the increased stimulus load. However, detailed changes in the effective connectivity preserve a balance in the propagating activity and select specific pathways such that high-level brain regions integrate visual and auditory information, in particular boosting the communication between the two brain hemispheres. These findings speak to a dynamic coordination underlying the functional integration in the brain. Copyright © 2017. Published by Elsevier Inc.

Resting-state activity in development and maintenance of normal brain function.

PubMed

Pizoli, Carolyn E; Shah, Manish N; Snyder, Abraham Z; Shimony, Joshua S; Limbrick, David D; Raichle, Marcus E; Schlaggar, Bradley L; Smyth, Matthew D

2011-07-12

One of the most intriguing recent discoveries concerning brain function is that intrinsic neuronal activity manifests as spontaneous fluctuations of the blood oxygen level-dependent (BOLD) functional MRI signal. These BOLD fluctuations exhibit temporal synchrony within widely distributed brain regions known as resting-state networks. Resting-state networks are present in the waking state, during sleep, and under general anesthesia, suggesting that spontaneous neuronal activity plays a fundamental role in brain function. Despite its ubiquitous presence, the physiological role of correlated, spontaneous neuronal activity remains poorly understood. One hypothesis is that this activity is critical for the development of synaptic connections and maintenance of synaptic homeostasis. We had a unique opportunity to test this hypothesis in a 5-y-old boy with severe epileptic encephalopathy. The child developed marked neurologic dysfunction in association with a seizure disorder, resulting in a 1-y period of behavioral regression and progressive loss of developmental milestones. His EEG showed a markedly abnormal pattern of high-amplitude, disorganized slow activity with frequent generalized and multifocal epileptiform discharges. Resting-state functional connectivity MRI showed reduced BOLD fluctuations and a pervasive lack of normal connectivity. The child underwent successful corpus callosotomy surgery for treatment of drop seizures. Postoperatively, the patient's behavior returned to baseline, and he resumed development of new skills. The waking EEG revealed a normal background, and functional connectivity MRI demonstrated restoration of functional connectivity architecture. These results provide evidence that intrinsic, coherent neuronal signaling may be essential to the development and maintenance of the brain's functional organization.

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.

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

Time-dependence of graph theory metrics in functional connectivity analysis

PubMed Central

Chiang, Sharon; Cassese, Alberto; Guindani, Michele; Vannucci, Marina; Yeh, Hsiang J.; Haneef, Zulfi; Stern, John M.

2016-01-01

Brain graphs provide a useful way to computationally model the network structure of the connectome, and this has led to increasing interest in the use of graph theory to quantitate and investigate the topological characteristics of the healthy brain and brain disorders on the network level. The majority of graph theory investigations of functional connectivity have relied on the assumption of temporal stationarity. However, recent evidence increasingly suggests that functional connectivity fluctuates over the length of the scan. In this study, we investigate the stationarity of brain network topology using a Bayesian hidden Markov model (HMM) approach that estimates the dynamic structure of graph theoretical measures of whole-brain functional connectivity. In addition to extracting the stationary distribution and transition probabilities of commonly employed graph theory measures, we propose two estimators of temporal stationarity: the S-index and N-index. These indexes can be used to quantify different aspects of the temporal stationarity of graph theory measures. We apply the method and proposed estimators to resting-state functional MRI data from healthy controls and patients with temporal lobe epilepsy. Our analysis shows that several graph theory measures, including small-world index, global integration measures, and betweenness centrality, may exhibit greater stationarity over time and therefore be more robust. Additionally, we demonstrate that accounting for subject-level differences in the level of temporal stationarity of network topology may increase discriminatory power in discriminating between disease states. Our results confirm and extend findings from other studies regarding the dynamic nature of functional connectivity, and suggest that using statistical models which explicitly account for the dynamic nature of functional connectivity in graph theory analyses may improve the sensitivity of investigations and consistency across investigations. PMID:26518632

Time-dependence of graph theory metrics in functional connectivity analysis.

PubMed

Chiang, Sharon; Cassese, Alberto; Guindani, Michele; Vannucci, Marina; Yeh, Hsiang J; Haneef, Zulfi; Stern, John M

2016-01-15

Brain graphs provide a useful way to computationally model the network structure of the connectome, and this has led to increasing interest in the use of graph theory to quantitate and investigate the topological characteristics of the healthy brain and brain disorders on the network level. The majority of graph theory investigations of functional connectivity have relied on the assumption of temporal stationarity. However, recent evidence increasingly suggests that functional connectivity fluctuates over the length of the scan. In this study, we investigate the stationarity of brain network topology using a Bayesian hidden Markov model (HMM) approach that estimates the dynamic structure of graph theoretical measures of whole-brain functional connectivity. In addition to extracting the stationary distribution and transition probabilities of commonly employed graph theory measures, we propose two estimators of temporal stationarity: the S-index and N-index. These indexes can be used to quantify different aspects of the temporal stationarity of graph theory measures. We apply the method and proposed estimators to resting-state functional MRI data from healthy controls and patients with temporal lobe epilepsy. Our analysis shows that several graph theory measures, including small-world index, global integration measures, and betweenness centrality, may exhibit greater stationarity over time and therefore be more robust. Additionally, we demonstrate that accounting for subject-level differences in the level of temporal stationarity of network topology may increase discriminatory power in discriminating between disease states. Our results confirm and extend findings from other studies regarding the dynamic nature of functional connectivity, and suggest that using statistical models which explicitly account for the dynamic nature of functional connectivity in graph theory analyses may improve the sensitivity of investigations and consistency across investigations. Copyright © 2015 Elsevier Inc. All rights reserved.

Default network connectivity decodes brain states with simulated microgravity.

PubMed

Zeng, Ling-Li; Liao, Yang; Zhou, Zongtan; Shen, Hui; Liu, Yadong; Liu, Xufeng; Hu, Dewen

2016-04-01

With great progress of space navigation technology, it becomes possible to travel beyond Earth's gravity. So far, it remains unclear whether the human brain can function normally within an environment of microgravity and confinement. Particularly, it is a challenge to figure out some neuroimaging-based markers for rapid screening diagnosis of disrupted brain function in microgravity environment. In this study, a 7-day -6° head down tilt bed rest experiment was used to simulate the microgravity, and twenty healthy male participants underwent resting-state functional magnetic resonance imaging scans at baseline and after the simulated microgravity experiment. We used a multivariate pattern analysis approach to distinguish the brain states with simulated microgravity from normal gravity based on the functional connectivity within the default network, resulting in an accuracy of no less than 85 % via cross-validation. Moreover, most discriminative functional connections were mainly located between the limbic system and cortical areas and were enhanced after simulated microgravity, implying a self-adaption or compensatory enhancement to fulfill the need of complex demand in spatial navigation and motor control functions in microgravity environment. Overall, the findings suggest that the brain states in microgravity are likely different from those in normal gravity and that brain connectome could act as a biomarker to indicate the brain state in microgravity.

Functional brain networks in Alzheimer's disease: EEG analysis based on limited penetrable visibility graph and phase space method

NASA Astrophysics Data System (ADS)

Wang, Jiang; Yang, Chen; Wang, Ruofan; Yu, Haitao; Cao, Yibin; Liu, Jing

2016-10-01

In this paper, EEG series are applied to construct functional connections with the correlation between different regions in order to investigate the nonlinear characteristic and the cognitive function of the brain with Alzheimer's disease (AD). First, limited penetrable visibility graph (LPVG) and phase space method map single EEG series into networks, and investigate the underlying chaotic system dynamics of AD brain. Topological properties of the networks are extracted, such as average path length and clustering coefficient. It is found that the network topology of AD in several local brain regions are different from that of the control group with no statistically significant difference existing all over the brain. Furthermore, in order to detect the abnormality of AD brain as a whole, functional connections among different brain regions are reconstructed based on similarity of clustering coefficient sequence (CCSS) of EEG series in the four frequency bands (delta, theta, alpha, and beta), which exhibit obvious small-world properties. Graph analysis demonstrates that for both methodologies, the functional connections between regions of AD brain decrease, particularly in the alpha frequency band. AD causes the graph index complexity of the functional network decreased, the small-world properties weakened, and the vulnerability increased. The obtained results show that the brain functional network constructed by LPVG and phase space method might be more effective to distinguish AD from the normal control than the analysis of single series, which is helpful for revealing the underlying pathological mechanism of the disease.

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

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.

Anterior Temporal Lobe Connectivity Correlates with Functional Outcome after Aphasic Stroke

ERIC Educational Resources Information Center

Warren, Jane E.; Crinion, Jennifer T.; Ralph, Matthew A. Lambon; Wise, Richard J. S.

2009-01-01

Focal brain lesions are assumed to produce language deficits by two basic mechanisms: local cortical dysfunction at the lesion site, and remote cortical dysfunction due to disruption of the transfer and integration of information between connected brain regions. However, functional imaging studies investigating language outcome after aphasic…

Resting-state functional connectivity differentiates anxious apprehension and anxious arousal.

PubMed

Burdwood, Erin N; Infantolino, Zachary P; Crocker, Laura D; Spielberg, Jeffrey M; Banich, Marie T; Miller, Gregory A; Heller, Wendy

2016-10-01

Brain regions in the default mode network (DMN) display greater functional connectivity at rest or during self-referential processing than during goal-directed tasks. The present study assessed resting-state connectivity as a function of anxious apprehension and anxious arousal, independent of depressive symptoms, in order to understand how these dimensions disrupt cognition. Whole-brain, seed-based analyses indicated differences between anxious apprehension and anxious arousal in DMN functional connectivity. Lower connectivity associated with higher anxious apprehension suggests decreased adaptive, inner-focused thought processes, whereas higher connectivity at higher levels of anxious arousal may reflect elevated monitoring of physiological responses to threat. These findings further the conceptualization of anxious apprehension and anxious arousal as distinct psychological dimensions with distinct neural instantiations. © 2016 Society for Psychophysiological Research.

From hippocampus to whole-brain: The role of integrative processing in episodic memory retrieval.

PubMed

Geib, Benjamin R; Stanley, Matthew L; Dennis, Nancy A; Woldorff, Marty G; Cabeza, Roberto

2017-04-01

Multivariate functional connectivity analyses of neuroimaging data have revealed the importance of complex, distributed interactions between disparate yet interdependent brain regions. Recent work has shown that topological properties of functional brain networks are associated with individual and group differences in cognitive performance, including in episodic memory. After constructing functional whole-brain networks derived from an event-related fMRI study of memory retrieval, we examined differences in functional brain network architecture between forgotten and remembered words. This study yielded three main findings. First, graph theory analyses showed that successfully remembering compared to forgetting was associated with significant changes in the connectivity profile of the left hippocampus and a corresponding increase in efficient communication with the rest of the brain. Second, bivariate functional connectivity analyses indicated stronger interactions between the left hippocampus and a retrieval assembly for remembered versus forgotten items. This assembly included the left precuneus, left caudate, bilateral supramarginal gyrus, and the bilateral dorsolateral superior frontal gyrus. Integrative properties of the retrieval assembly were greater for remembered than forgotten items. Third, whole-brain modularity analyses revealed that successful memory retrieval was marginally significantly associated with a less segregated modular architecture in the network. The magnitude of the decreases in modularity between remembered and forgotten conditions was related to memory performance. These findings indicate that increases in integrative properties at the nodal, retrieval assembly, and whole-brain topological levels facilitate memory retrieval, while also underscoring the potential of multivariate brain connectivity approaches for providing valuable new insights into the neural bases of memory processes. Hum Brain Mapp 38:2242-2259, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Differences in hemispherical thalamo-cortical causality analysis during resting-state fMRI.

PubMed

Anwar, Abdul Rauf; Muthalib, Makii; Perrey, Stephane; Wolff, Stephan; Deuschl, Guunther; Heute, Ulrich; Muthuraman, Muthuraman

2014-01-01

Thalamus is a very important part of the human brain. It has been reported to act as a relay for the messaging taking place between the cortical and sub-cortical regions of the brain. In the present study, we analyze the functional network between both hemispheres of the brain with the focus on thalamus. We used conditional Granger causality (CGC) and time-resolved partial directed coherence (tPDC) to investigate the functional connectivity. Results of CGC analysis revealed the asymmetry between connection strengths of the bilateral thalamus. Upon testing the functional connectivity of the default-mode network (DMN) at low-frequency fluctuations (LFF) and comparing coherence vectors using Spearman's rank correlation, we found that thalamus is a better source for the signals directed towards the contralateral regions of the brain, however, when thalamus acts as sink, it is a better sink for signals generated from ipsilateral regions of the brain.

Human brain distinctiveness based on EEG spectral coherence connectivity.

PubMed

Rocca, D La; Campisi, P; Vegso, B; Cserti, P; Kozmann, G; Babiloni, F; Fallani, F De Vico

2014-09-01

The use of EEG biometrics, for the purpose of automatic people recognition, has received increasing attention in the recent years. Most of the current analyses rely on the extraction of features characterizing the activity of single brain regions, like power spectrum estimation, thus neglecting possible temporal dependencies between the generated EEG signals. However, important physiological information can be extracted from the way different brain regions are functionally coupled. In this study, we propose a novel approach that fuses spectral coherence-based connectivity between different brain regions as a possibly viable biometric feature. The proposed approach is tested on a large dataset of subjects (N = 108) during eyes-closed (EC) and eyes-open (EO) resting state conditions. The obtained recognition performance shows that using brain connectivity leads to higher distinctiveness with respect to power-spectrum measurements, in both the experimental conditions. Notably, a 100% recognition accuracy is obtained in EC and EO when integrating functional connectivity between regions in the frontal lobe, while a lower 97.5% is obtained in EC (96.26% in EO) when fusing power spectrum information from parieto-occipital (centro-parietal in EO) regions. Taken together, these results suggest that the functional connectivity patterns represent effective features for improving EEG-based biometric systems.

Higher Dimensional Meta-State Analysis Reveals Reduced Resting fMRI Connectivity Dynamism in Schizophrenia Patients.

PubMed

Miller, Robyn L; Yaesoubi, Maziar; Turner, Jessica A; Mathalon, Daniel; Preda, Adrian; Pearlson, Godfrey; Adali, Tulay; Calhoun, Vince D

2016-01-01

Resting-state functional brain imaging studies of network connectivity have long assumed that functional connections are stationary on the timescale of a typical scan. Interest in moving beyond this simplifying assumption has emerged only recently. The great hope is that training the right lens on time-varying properties of whole-brain network connectivity will shed additional light on previously concealed brain activation patterns characteristic of serious neurological or psychiatric disorders. We present evidence that multiple explicitly dynamical properties of time-varying whole-brain network connectivity are strongly associated with schizophrenia, a complex mental illness whose symptomatic presentation can vary enormously across subjects. As with so much brain-imaging research, a central challenge for dynamic network connectivity lies in determining transformations of the data that both reduce its dimensionality and expose features that are strongly predictive of important population characteristics. Our paper introduces an elegant, simple method of reducing and organizing data around which a large constellation of mutually informative and intuitive dynamical analyses can be performed. This framework combines a discrete multidimensional data-driven representation of connectivity space with four core dynamism measures computed from large-scale properties of each subject's trajectory, ie., properties not identifiable with any specific moment in time and therefore reasonable to employ in settings lacking inter-subject time-alignment, such as resting-state functional imaging studies. Our analysis exposes pronounced differences between schizophrenia patients (Nsz = 151) and healthy controls (Nhc = 163). Time-varying whole-brain network connectivity patterns are found to be markedly less dynamically active in schizophrenia patients, an effect that is even more pronounced in patients with high levels of hallucinatory behavior. To the best of our knowledge this is the first demonstration that high-level dynamic properties of whole-brain connectivity, generic enough to be commensurable under many decompositions of time-varying connectivity data, exhibit robust and systematic differences between schizophrenia patients and healthy controls.

Higher Dimensional Meta-State Analysis Reveals Reduced Resting fMRI Connectivity Dynamism in Schizophrenia Patients

PubMed Central

Miller, Robyn L.; Yaesoubi, Maziar; Turner, Jessica A.; Mathalon, Daniel; Preda, Adrian; Pearlson, Godfrey; Adali, Tulay; Calhoun, Vince D.

2016-01-01

Resting-state functional brain imaging studies of network connectivity have long assumed that functional connections are stationary on the timescale of a typical scan. Interest in moving beyond this simplifying assumption has emerged only recently. The great hope is that training the right lens on time-varying properties of whole-brain network connectivity will shed additional light on previously concealed brain activation patterns characteristic of serious neurological or psychiatric disorders. We present evidence that multiple explicitly dynamical properties of time-varying whole-brain network connectivity are strongly associated with schizophrenia, a complex mental illness whose symptomatic presentation can vary enormously across subjects. As with so much brain-imaging research, a central challenge for dynamic network connectivity lies in determining transformations of the data that both reduce its dimensionality and expose features that are strongly predictive of important population characteristics. Our paper introduces an elegant, simple method of reducing and organizing data around which a large constellation of mutually informative and intuitive dynamical analyses can be performed. This framework combines a discrete multidimensional data-driven representation of connectivity space with four core dynamism measures computed from large-scale properties of each subject’s trajectory, ie., properties not identifiable with any specific moment in time and therefore reasonable to employ in settings lacking inter-subject time-alignment, such as resting-state functional imaging studies. Our analysis exposes pronounced differences between schizophrenia patients (Nsz = 151) and healthy controls (Nhc = 163). Time-varying whole-brain network connectivity patterns are found to be markedly less dynamically active in schizophrenia patients, an effect that is even more pronounced in patients with high levels of hallucinatory behavior. To the best of our knowledge this is the first demonstration that high-level dynamic properties of whole-brain connectivity, generic enough to be commensurable under many decompositions of time-varying connectivity data, exhibit robust and systematic differences between schizophrenia patients and healthy controls. PMID:26981625

On the Application of Quantitative EEG for Characterizing Autistic Brain: A Systematic Review

PubMed Central

Billeci, Lucia; Sicca, Federico; Maharatna, Koushik; Apicella, Fabio; Narzisi, Antonio; Campatelli, Giulia; Calderoni, Sara; Pioggia, Giovanni; Muratori, Filippo

2013-01-01

Autism-Spectrum Disorders (ASD) are thought to be associated with abnormalities in neural connectivity at both the global and local levels. Quantitative electroencephalography (QEEG) is a non-invasive technique that allows a highly precise measurement of brain function and connectivity. This review encompasses the key findings of QEEG application in subjects with ASD, in order to assess the relevance of this approach in characterizing brain function and clustering phenotypes. QEEG studies evaluating both the spontaneous brain activity and brain signals under controlled experimental stimuli were examined. Despite conflicting results, literature analysis suggests that QEEG features are sensitive to modification in neuronal regulation dysfunction which characterize autistic brain. QEEG may therefore help in detecting regions of altered brain function and connectivity abnormalities, in linking behavior with brain activity, and subgrouping affected individuals within the wide heterogeneity of ASD. The use of advanced techniques for the increase of the specificity and of spatial localization could allow finding distinctive patterns of QEEG abnormalities in ASD subjects, paving the way for the development of tailored intervention strategies. PMID:23935579

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.

Two hands, one brain, and aging.

PubMed

Maes, Celine; Gooijers, Jolien; Orban de Xivry, Jean-Jacques; Swinnen, Stephan P; Boisgontier, Matthieu P

2017-04-01

Many activities of daily living require moving both hands in an organized manner in space and time. Therefore, understanding the impact of aging on bimanual coordination is essential for prolonging functional independence and well-being in older adults. Here we investigated the behavioral and neural determinants of bimanual coordination in aging. The studies surveyed in this review reveal that aging is associated with cortical hyper-activity (but also subcortical hypo-activity) during performance of bimanual tasks. In addition to changes in activation in local areas, the interaction between distributed brain areas also exhibits age-related effects, i.e., functional connectivity is increased in the resting brain as well as during task performance. The mechanisms and triggers underlying these functional activation and connectivity changes remain to be investigated. This requires further research investment into the detailed study of interactions between brain structure, function and connectivity. This will also provide the foundation for interventional research programs towards preservation of brain health and behavioral performance by maximizing neuroplasticity potential in older adults. 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

Reduced prefrontal connectivity in psychopathy.

PubMed

Motzkin, Julian C; Newman, Joseph P; Kiehl, Kent A; Koenigs, Michael

2011-11-30

Linking psychopathy to a specific brain abnormality could have significant clinical, legal, and scientific implications. Theories on the neurobiological basis of the disorder typically propose dysfunction in a circuit involving ventromedial prefrontal cortex (vmPFC). However, to date there is limited brain imaging data to directly test whether psychopathy may indeed be associated with any structural or functional abnormality within this brain area. In this study, we employ two complementary imaging techniques to assess the structural and functional connectivity of vmPFC in psychopathic and non-psychopathic criminals. Using diffusion tensor imaging, we show that psychopathy is associated with reduced structural integrity in the right uncinate fasciculus, the primary white matter connection between vmPFC and anterior temporal lobe. Using functional magnetic resonance imaging, we show that psychopathy is associated with reduced functional connectivity between vmPFC and amygdala as well as between vmPFC and medial parietal cortex. Together, these data converge to implicate diminished vmPFC connectivity as a characteristic neurobiological feature of psychopathy.

Reduced Prefrontal Connectivity in Psychopathy

PubMed Central

Motzkin, Julian C.; Newman, Joseph P.; Kiehl, Kent A.; Koenigs, Michael

2012-01-01

Linking psychopathy to a specific brain abnormality could have significant clinical, legal, and scientific implications. Theories on the neurobiological basis of the disorder typically propose dysfunction in a circuit involving ventromedial prefrontal cortex (vmPFC). However, to date there is limited brain imaging data to directly test whether psychopathy may indeed be associated with any structural or functional abnormality within this brain area. In this study, we employ two complementary imaging techniques to assess the structural and functional connectivity of vmPFC in psychopathic and non-psychopathic criminals. Using diffusion tensor imaging, we show that psychopathy is associated with reduced structural integrity in the right uncinate fasciculus, the primary white matter connection between vmPFC and anterior temporal lobe. Using functional magnetic resonance imaging, we show that psychopathy is associated with reduced functional connectivity between vmPFC and amygdala as well as between vmPFC and medial parietal cortex. Together, these data converge to implicate diminished vmPFC connectivity as a characteristic neurobiological feature of psychopathy. PMID:22131397

Dynamics of Intersubject Brain Networks during Anxious Anticipation

PubMed Central

Najafi, Mahshid; Kinnison, Joshua; Pessoa, Luiz

2017-01-01

How do large-scale brain networks reorganize during the waxing and waning of anxious anticipation? Here, threat was dynamically modulated during human functional MRI as two circles slowly meandered on the screen; if they touched, an unpleasant shock was delivered. We employed intersubject correlation analysis, which allowed the investigation of network-level functional connectivity across brains, and sought to determine how network connectivity changed during periods of approach (circles moving closer) and periods of retreat (circles moving apart). Analysis of positive connection weights revealed that dynamic threat altered connectivity within and between the salience, executive, and task-negative networks. For example, dynamic functional connectivity increased within the salience network during approach and decreased during retreat. The opposite pattern was found for the functional connectivity between the salience and task-negative networks: decreases during approach and increases during approach. Functional connections between subcortical regions and the salience network also changed dynamically during approach and retreat periods. Subcortical regions exhibiting such changes included the putative periaqueductal gray, putative habenula, and putative bed nucleus of the stria terminalis. Additional analysis of negative functional connections revealed dynamic changes, too. For example, negative weights within the salience network decreased during approach and increased during retreat, opposite what was found for positive weights. Together, our findings unraveled dynamic features of functional connectivity of large-scale networks and subcortical regions across participants while threat levels varied continuously, and demonstrate the potential of characterizing emotional processing at the level of dynamic networks. PMID:29209184

Advanced Connectivity Analysis (ACA): a Large Scale Functional Connectivity Data Mining Environment.

PubMed

Chen, Rong; Nixon, Erika; Herskovits, Edward

2016-04-01

Using resting-state functional magnetic resonance imaging (rs-fMRI) to study functional connectivity is of great importance to understand normal development and function as well as a host of neurological and psychiatric disorders. Seed-based analysis is one of the most widely used rs-fMRI analysis methods. Here we describe a freely available large scale functional connectivity data mining software package called Advanced Connectivity Analysis (ACA). ACA enables large-scale seed-based analysis and brain-behavior analysis. It can seamlessly examine a large number of seed regions with minimal user input. ACA has a brain-behavior analysis component to delineate associations among imaging biomarkers and one or more behavioral variables. We demonstrate applications of ACA to rs-fMRI data sets from a study of autism.

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.

Effect of brain structure, brain function, and brain connectivity on relapse in alcohol-dependent patients.

PubMed

Beck, Anne; Wüstenberg, Torsten; Genauck, Alexander; Wrase, Jana; Schlagenhauf, Florian; Smolka, Michael N; Mann, Karl; Heinz, Andreas

2012-08-01

In alcohol-dependent patients, brain atrophy and functional brain activation elicited by alcohol-associated stimuli may predict relapse. However, to date, the interaction between both factors has not been studied. To determine whether results from structural and functional magnetic resonance imaging are associated with relapse in detoxified alcohol-dependent patients. A cue-reactivity functional magnetic resonance experiment with alcohol-associated and neutral stimuli. After a follow-up period of 3 months, the group of 46 detoxified alcohol-dependent patients was subdivided into 16 abstainers and 30 relapsers. Faculty for Clinical Medicine Mannheim at the University of Heidelberg, Germany. A total of 46 detoxified alcohol-dependent patients and 46 age- and sex-matched healthy control subjects Local gray matter volume, local stimulus-related functional magnetic resonance imaging activation, joint analyses of structural and functional data with Biological Parametric Mapping, and connectivity analyses adopting the psychophysiological interaction approach. Subsequent relapsers showed pronounced atrophy in the bilateral orbitofrontal cortex and in the right medial prefrontal and anterior cingulate cortex, compared with healthy controls and patients who remained abstinent. The local gray matter volume-corrected brain response elicited by alcohol-associated vs neutral stimuli in the left medial prefrontal cortex was enhanced for subsequent relapsers, whereas abstainers displayed an increased neural response in the midbrain (the ventral tegmental area extending into the subthalamic nucleus) and ventral striatum. For alcohol-associated vs neutral stimuli in abstainers compared with relapsers, the analyses of the psychophysiological interaction showed a stronger functional connectivity between the midbrain and the left amygdala and between the midbrain and the left orbitofrontal cortex. Subsequent relapsers displayed increased brain atrophy in brain areas associated with error monitoring and behavioral control. Correcting for gray matter reductions, we found that, in these patients, alcohol-related cues elicited increased activation in brain areas associated with attentional bias toward these cues and that, in patients who remained abstinent, increased activation and connectivity were observed in brain areas associated with processing of salient or aversive stimuli.

Functional connectivity changes in adults with developmental stuttering: a preliminary study using quantitative electro-encephalography

PubMed Central

Joos, Kathleen; De Ridder, Dirk; Boey, Ronny A.; Vanneste, Sven

2014-01-01

Introduction: Stuttering is defined as speech characterized by verbal dysfluencies, but should not be seen as an isolated speech disorder, but as a generalized sensorimotor timing deficit due to impaired communication between speech related brain areas. Therefore we focused on resting state brain activity and functional connectivity. Method: We included 11 patients with developmental stuttering and 11 age matched controls. To objectify stuttering severity and the impact on quality of life (QoL), we used the Dutch validated Test for Stuttering Severity-Readers (TSS-R) and the Overall Assessment of the Speaker’s Experience of Stuttering (OASES), respectively. Furthermore, we used standardized low resolution brain electromagnetic tomography (sLORETA) analyses to look at resting state activity and functional connectivity differences and their correlations with the TSS-R and OASES. Results: No significant results could be obtained when looking at neural activity, however significant alterations in resting state functional connectivity could be demonstrated between persons who stutter (PWS) and fluently speaking controls, predominantly interhemispheric, i.e., a decreased functional connectivity for high frequency oscillations (beta and gamma) between motor speech areas (BA44 and 45) and the contralateral premotor (BA6) and motor (BA4) areas. Moreover, a positive correlation was found between functional connectivity at low frequency oscillations (theta and alpha) and stuttering severity, while a mixed increased and decreased functional connectivity at low and high frequency oscillations correlated with QoL. Discussion: PWS are characterized by decreased high frequency interhemispheric functional connectivity between motor speech, premotor and motor areas in the resting state, while higher functional connectivity in the low frequency bands indicates more severe speech disturbances, suggesting that increased interhemispheric and right sided functional connectivity is maladaptive. PMID:25352797

Neural Signatures of Autism Spectrum Disorders: Insights into Brain Network Dynamics

PubMed Central

Hernandez, Leanna M; Rudie, Jeffrey D; Green, Shulamite A; Bookheimer, Susan; Dapretto, Mirella

2015-01-01

Neuroimaging investigations of autism spectrum disorders (ASDs) have advanced our understanding of atypical brain function and structure, and have recently converged on a model of altered network-level connectivity. Traditional task-based functional magnetic resonance imaging (MRI) and volume-based structural MRI studies have identified widespread atypicalities in brain regions involved in social behavior and other core ASD-related behavioral deficits. More recent advances in MR-neuroimaging methods allow for quantification of brain connectivity using diffusion tensor imaging, functional connectivity, and graph theoretic methods. These newer techniques have moved the field toward a systems-level understanding of ASD etiology, integrating functional and structural measures across distal brain regions. Neuroimaging findings in ASD as a whole have been mixed and at times contradictory, likely due to the vast genetic and phenotypic heterogeneity characteristic of the disorder. Future longitudinal studies of brain development will be crucial to yield insights into mechanisms of disease etiology in ASD sub-populations. Advances in neuroimaging methods and large-scale collaborations will also allow for an integrated approach linking neuroimaging, genetics, and phenotypic data. PMID:25011468

Disconnection of network hubs and cognitive impairment after traumatic brain injury.

PubMed

Fagerholm, Erik D; Hellyer, Peter J; Scott, Gregory; Leech, Robert; Sharp, David J

2015-06-01

Traumatic brain injury affects brain connectivity by producing traumatic axonal injury. This disrupts the function of large-scale networks that support cognition. The best way to describe this relationship is unclear, but one elegant approach is to view networks as graphs. Brain regions become nodes in the graph, and white matter tracts the connections. The overall effect of an injury can then be estimated by calculating graph metrics of network structure and function. Here we test which graph metrics best predict the presence of traumatic axonal injury, as well as which are most highly associated with cognitive impairment. A comprehensive range of graph metrics was calculated from structural connectivity measures for 52 patients with traumatic brain injury, 21 of whom had microbleed evidence of traumatic axonal injury, and 25 age-matched controls. White matter connections between 165 grey matter brain regions were defined using tractography, and structural connectivity matrices calculated from skeletonized diffusion tensor imaging data. This technique estimates injury at the centre of tract, but is insensitive to damage at tract edges. Graph metrics were calculated from the resulting connectivity matrices and machine-learning techniques used to select the metrics that best predicted the presence of traumatic brain injury. In addition, we used regularization and variable selection via the elastic net to predict patient behaviour on tests of information processing speed, executive function and associative memory. Support vector machines trained with graph metrics of white matter connectivity matrices from the microbleed group were able to identify patients with a history of traumatic brain injury with 93.4% accuracy, a result robust to different ways of sampling the data. Graph metrics were significantly associated with cognitive performance: information processing speed (R(2) = 0.64), executive function (R(2) = 0.56) and associative memory (R(2) = 0.25). These results were then replicated in a separate group of patients without microbleeds. The most influential graph metrics were betweenness centrality and eigenvector centrality, which provide measures of the extent to which a given brain region connects other regions in the network. Reductions in betweenness centrality and eigenvector centrality were particularly evident within hub regions including the cingulate cortex and caudate. Our results demonstrate that betweenness centrality and eigenvector centrality are reduced within network hubs, due to the impact of traumatic axonal injury on network connections. The dominance of betweenness centrality and eigenvector centrality suggests that cognitive impairment after traumatic brain injury results from the disconnection of network hubs by traumatic axonal injury. © The Author (2015). Published by Oxford University Press on behalf of the Guarantors of Brain.

Correspondence Between Aberrant Intrinsic Network Connectivity and Gray-Matter Volume in the Ventral Brain of Preterm Born Adults.

PubMed

Bäuml, Josef G; Daamen, Marcel; Meng, Chun; Neitzel, Julia; Scheef, Lukas; Jaekel, Julia; Busch, Barbara; Baumann, Nicole; Bartmann, Peter; Wolke, Dieter; Boecker, Henning; Wohlschläger, Afra M; Sorg, Christian

2015-11-01

Widespread brain changes are present in preterm born infants, adolescents, and even adults. While neurobiological models of prematurity facilitate powerful explanations for the adverse effects of preterm birth on the developing brain at microscale, convincing linking principles at large-scale level to explain the widespread nature of brain changes are still missing. We investigated effects of preterm birth on the brain's large-scale intrinsic networks and their relation to brain structure in preterm born adults. In 95 preterm and 83 full-term born adults, structural and functional magnetic resonance imaging at-rest was used to analyze both voxel-based morphometry and spatial patterns of functional connectivity in ongoing blood oxygenation level-dependent activity. Differences in intrinsic functional connectivity (iFC) were found in cortical and subcortical networks. Structural differences were located in subcortical, temporal, and cingulate areas. Critically, for preterm born adults, iFC-network differences were overlapping and correlating with aberrant regional gray-matter (GM) volume specifically in subcortical and temporal areas. Overlapping changes were predicted by prematurity and in particular by neonatal medical complications. These results provide evidence that preterm birth has long-lasting effects on functional connectivity of intrinsic networks, and these changes are specifically related to structural alterations in ventral brain GM. © The Author 2014. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Brain Connectivity Networks and the Aesthetic Experience of Music.

PubMed

Reybrouck, Mark; Vuust, Peter; Brattico, Elvira

2018-06-12

Listening to music is above all a human experience, which becomes an aesthetic experience when an individual immerses himself/herself in the music, dedicating attention to perceptual-cognitive-affective interpretation and evaluation. The study of these processes where the individual perceives, understands, enjoys and evaluates a set of auditory stimuli has mainly been focused on the effect of music on specific brain structures, as measured with neurophysiology and neuroimaging techniques. The very recent application of network science algorithms to brain research allows an insight into the functional connectivity between brain regions. These studies in network neuroscience have identified distinct circuits that function during goal-directed tasks and resting states. We review recent neuroimaging findings which indicate that music listening is traceable in terms of network connectivity and activations of target regions in the brain, in particular between the auditory cortex, the reward brain system and brain regions active during mind wandering.

Early alterations of social brain networks in young children with autism

PubMed Central

Kojovic, Nada; Rihs, Tonia Anahi; Jan, Reem Kais; Franchini, Martina; Plomp, Gijs; Vulliemoz, Serge; Eliez, Stephan; Michel, Christoph Martin; Schaer, Marie

2018-01-01

Social impairments are a hallmark of Autism Spectrum Disorders (ASD), but empirical evidence for early brain network alterations in response to social stimuli is scant in ASD. We recorded the gaze patterns and brain activity of toddlers with ASD and their typically developing peers while they explored dynamic social scenes. Directed functional connectivity analyses based on electrical source imaging revealed frequency specific network atypicalities in the theta and alpha frequency bands, manifesting as alterations in both the driving and the connections from key nodes of the social brain associated with autism. Analyses of brain-behavioural relationships within the ASD group suggested that compensatory mechanisms from dorsomedial frontal, inferior temporal and insular cortical regions were associated with less atypical gaze patterns and lower clinical impairment. Our results provide strong evidence that directed functional connectivity alterations of social brain networks is a core component of atypical brain development at early stages of ASD. PMID:29482718

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.

Optical Mapping of Brain Activation and Connectivity in Occipitotemporal Cortex During Chinese Character Recognition.

PubMed

Hu, Zhishan; Zhang, Juan; Couto, Tania Alexandra; Xu, Shiyang; Luan, Ping; Yuan, Zhen

2018-06-22

In this study, functional near-infrared spectroscopy (fNIRS) was used to examine the brain activation and connectivity in occipitotemporal cortex during Chinese character recognition (CCR). Eighteen healthy participants were recruited to perform a well-designed task with three categories of stimuli (real characters, pseudo characters, and checkerboards). By inspecting the brain activation difference and its relationship with behavioral data, the left laterality during CCR was clearly identified in the Brodmann area (BA) 18 and 19. In addition, our novel findings also demonstrated that the bilateral superior temporal gyrus (STG), bilateral BA 19, and left fusiform gyrus were also involved in high-level lexical information processing such as semantic and phonological ones. Meanwhile, by examining functional brain networks, we discovered that the right BA 19 exhibited enhanced brain connectivity. In particular, the connectivity in the right fusiform gyrus, right BA 19, and left STG showed significant correlation with the performance of CCR. Consequently, the combination of fNIRS technique with functional network analysis paves a new avenue for improved understanding of the cognitive mechanism underlying CCR.

Altered Odor-Induced Brain Activity as an Early Manifestation of Cognitive Decline in Patients With Type 2 Diabetes.

PubMed

Zhang, Zhou; Zhang, Bing; Wang, Xin; Zhang, Xin; Yang, Qing X; Qing, Zhao; Lu, Jiaming; Bi, Yan; Zhu, Dalong

2018-05-01

Type 2 diabetes is reported to be associated with olfactory dysfunction and cognitive decline. However, whether and how olfactory neural circuit abnormalities involve cognitive impairment in diabetes remains uncovered. This study thus aimed to investigate olfactory network alterations and the associations of odor-induced brain activity with cognitive and metabolic parameters in type 2 diabetes. Participants with normal cognition, including 51 patients with type 2 diabetes and 41 control subjects without diabetes, underwent detailed cognitive assessment, olfactory behavior tests, and odor-induced functional MRI measurements. Olfactory brain regions showing significantly different activation between the two groups were selected for functional connectivity analysis. Compared with the control subjects, patients with diabetes demonstrated significantly lower olfactory threshold score, decreased brain activation, and disrupted functional connectivity in the olfactory network. Positive associations of the disrupted functional connectivity with decreased neuropsychology test scores and reduced pancreatic function were observed in patients with diabetes. Notably, the association between pancreatic function and executive function was mediated by olfactory behavior and olfactory functional connectivity. Our results suggested the alteration of olfactory network is present before clinically measurable cognitive decrements in type 2 diabetes, bridging the gap between the central olfactory system and cognitive decline in diabetes. © 2018 by the American Diabetes Association.

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.

Menthol enhances nicotine-induced locomotor sensitization and in vivo functional connectivity in adolescence.

PubMed

Thompson, Matthew F; Poirier, Guillaume L; Dávila-García, Martha I; Huang, Wei; Tam, Kelly; Robidoux, Maxwell; Dubuke, Michelle L; Shaffer, Scott A; Colon-Perez, Luis; Febo, Marcelo; DiFranza, Joseph R; King, Jean A

2018-03-01

Mentholated cigarettes capture a quarter of the US market, and are disproportionately smoked by adolescents. Menthol allosterically modulates nicotinic acetylcholine receptor function, but its effects on the brain and nicotine addiction are unclear. To determine if menthol is psychoactive, we assessed locomotor sensitization and brain functional connectivity. Adolescent male Sprague Dawley rats were administered nicotine (0.4 mg/kg) daily with or without menthol (0.05 mg/kg or 5.38 mg/kg) for nine days. Following each injection, distance traveled in an open field was recorded. One day after the sensitization experiment, functional connectivity was assessed in awake animals before and after drug administration using magnetic resonance imaging. Menthol (5.38 mg/kg) augmented nicotine-induced locomotor sensitization. Functional connectivity was compared in animals that had received nicotine with or without the 5.38 mg/kg dosage of menthol. Twenty-four hours into withdrawal after the last drug administration, increased functional connectivity was observed for ventral tegmental area and retrosplenial cortex with nicotine+menthol compared to nicotine-only exposure. Upon drug re-administration, the nicotine-only, but not the menthol groups, exhibited altered functional connectivity of the dorsal striatum with the amygdala. Menthol, when administered with nicotine, showed evidence of psychoactive properties by affecting brain activity and behavior compared to nicotine administration alone.

Altered resting brain function and structure in professional badminton players.

PubMed

Di, Xin; Zhu, Senhua; Jin, Hua; Wang, Pin; Ye, Zhuoer; Zhou, Ke; Zhuo, Yan; Rao, Hengyi

2012-01-01

Neuroimaging studies of professional athletic or musical training have demonstrated considerable practice-dependent plasticity in various brain structures, which may reflect distinct training demands. In the present study, structural and functional brain alterations were examined in professional badminton players and compared with healthy controls using magnetic resonance imaging (MRI) and resting-state functional MRI. Gray matter concentration (GMC) was assessed using voxel-based morphometry (VBM), and resting-brain functions were measured by amplitude of low-frequency fluctuation (ALFF) and seed-based functional connectivity. Results showed that the athlete group had greater GMC and ALFF in the right and medial cerebellar regions, respectively. The athlete group also demonstrated smaller ALFF in the left superior parietal lobule and altered functional connectivity between the left superior parietal and frontal regions. These findings indicate that badminton expertise is associated with not only plastic structural changes in terms of enlarged gray matter density in the cerebellum, but also functional alterations in fronto-parietal connectivity. Such structural and functional alterations may reflect specific experiences of badminton training and practice, including high-capacity visuo-spatial processing and hand-eye coordination in addition to refined motor skills.

Association of familial risk for schizophrenia with thalamic and medial prefrontal functional connectivity during attentional control.

PubMed

Antonucci, Linda A; Taurisano, Paolo; Fazio, Leonardo; Gelao, Barbara; Romano, Raffaella; Quarto, Tiziana; Porcelli, Annamaria; Mancini, Marina; Di Giorgio, Annabella; Caforio, Grazia; Pergola, Giulio; Popolizio, Teresa; Bertolino, Alessandro; Blasi, Giuseppe

2016-05-01

Anomalies in behavioral correlates of attentional processing and related brain activity are crucial correlates of schizophrenia and associated with familial risk for this brain disorder. However, it is not clear how brain functional connectivity during attentional processes is key for schizophrenia and linked with trait vs. state related variables. To address this issue, we investigated patterns of functional connections during attentional control in healthy siblings of patients with schizophrenia, who share with probands genetic features but not variables related to the state of the disorder. 356 controls, 55 patients with schizophrenia on stable treatment with antipsychotics and 40 healthy siblings of patients with this brain disorder underwent the Variable Attentional Control (VAC) task during fMRI. Independent Component Analysis (ICA) is allowed to identify independent components (IC) of BOLD signal recorded during task performance. Results indicated reduced connectivity strength in patients with schizophrenia as well as in their healthy siblings in left thalamus within an attentional control component and greater connectivity in right medial prefrontal cortex (PFC) within the so-called Default Mode Network (DMN) compared to healthy individuals. These results suggest a relationship between familial risk for schizophrenia and brain functional networks during attentional control, such that this biological phenotype may be considered a useful intermediate phenotype in order to link genes effects to aspects of the pathophysiology of this brain disorder. Copyright © 2016 Elsevier B.V. All rights reserved.

Lesions causing freezing of gait localize to a cerebellar functional network

PubMed Central

Fasano, Alfonso; Laganiere, Simon E.; Lam, Susy; Fox, Michael D.

2016-01-01

Objective Freezing of gait is a disabling symptom in Parkinson’s disease and related disorders, but the brain regions involved in symptom generation remain unclear. Here we analyze brain lesions causing acute onset freezing of gait to identify regions causally involved in symptom generation. Methods Fourteen cases of lesion-induced freezing of gait were identified from the literature and lesions were mapped to a common brain atlas. Because lesion-induced symptoms can come from sites connected to the lesion location, not just the lesion location itself, we also identified brain regions functionally connected to each lesion location. This technique, termed lesion network mapping, has been recently shown to identify regions involved in symptom generation across a variety of lesion-induced disorders. Results Lesion location was heterogeneous and no single region could be considered necessary for symptom generation. However, over 90% (13/14) of lesions were functionally connected to a focal area in the dorsal medial cerebellum. This cerebellar area overlapped previously recognized regions that are activated by locomotor tasks, termed the cerebellar locomotor region. Connectivity to this region was specific to lesions causing freezing of gait compared to lesions causing other movement disorders (hemichorea or asterixis). Interpretation Lesions causing freezing of gait are located within a common functional network characterized by connectivity to the cerebellar locomotor region. These results based on causal brain lesions complement prior neuroimaging studies in Parkinson’s disease patients, advancing our understanding of the brain regions involved in freezing of gait. PMID:28009063

Hemispheric Asymmetry of Human Brain Anatomical Network Revealed by Diffusion Tensor Tractography

PubMed Central

Liu, Yaou; Duan, Yunyun; Li, Kuncheng

2015-01-01

The topological architecture of the cerebral anatomical network reflects the structural organization of the human brain. Recently, topological measures based on graph theory have provided new approaches for quantifying large-scale anatomical networks. However, few studies have investigated the hemispheric asymmetries of the human brain from the perspective of the network model, and little is known about the asymmetries of the connection patterns of brain regions, which may reflect the functional integration and interaction between different regions. Here, we utilized diffusion tensor imaging to construct binary anatomical networks for 72 right-handed healthy adult subjects. We established the existence of structural connections between any pair of the 90 cortical and subcortical regions using deterministic tractography. To investigate the hemispheric asymmetries of the brain, statistical analyses were performed to reveal the brain regions with significant differences between bilateral topological properties, such as degree of connectivity, characteristic path length, and betweenness centrality. Furthermore, local structural connections were also investigated to examine the local asymmetries of some specific white matter tracts. From the perspective of both the global and local connection patterns, we identified the brain regions with hemispheric asymmetries. Combined with the previous studies, we suggested that the topological asymmetries in the anatomical network may reflect the functional lateralization of the human brain. PMID:26539535

Adverse Effects of Cannabis on Adolescent Brain Development: A Longitudinal Study

PubMed Central

Camchong, Jazmin; Lim, Kelvin O; Kumra, Sanjiv

2017-01-01

Abstract Cannabis is widely perceived as a safe recreational drug and its use is increasing in youth. It is important to understand the implications of cannabis use during childhood and adolescence on brain development. This is the first longitudinal study that compared resting functional connectivity of frontally mediated networks between 43 healthy controls (HCs; 20 females; age M = 16.5 ± 2.7) and 22 treatment-seeking adolescents with cannabis use disorder (CUD; 8 females; age M = 17.6 ± 2.4). Increases in resting functional connectivity between caudal anterior cingulate cortex (ACC) and superior frontal gyrus across time were found in HC, but not in CUD. CUD showed a decrease in functional connectivity between caudal ACC and dorsolateral and orbitofrontal cortices across time. Lower functional connectivity between caudal ACC cortex and orbitofrontal cortex at baseline predicted higher amounts of cannabis use during the following 18 months. Finally, high amounts of cannabis use during the 18-month interval predicted lower intelligence quotient and slower cognitive function measured at follow-up. These data provide compelling longitudinal evidence suggesting that repeated exposure to cannabis during adolescence may have detrimental effects on brain resting functional connectivity, intelligence, and cognitive function. PMID:26912785

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.

Computational modeling of resting-state activity demonstrates markers of normalcy in children with prenatal or perinatal stroke.

PubMed

Adhikari, Mohit H; Raja Beharelle, Anjali; Griffa, Alessandra; Hagmann, Patric; Solodkin, Ana; McIntosh, Anthony R; Small, Steven L; Deco, Gustavo

2015-06-10

Children who sustain a prenatal or perinatal brain injury in the form of a stroke develop remarkably normal cognitive functions in certain areas, with a particular strength in language skills. A dominant explanation for this is that brain regions from the contralesional hemisphere "take over" their functions, whereas the damaged areas and other ipsilesional regions play much less of a role. However, it is difficult to tease apart whether changes in neural activity after early brain injury are due to damage caused by the lesion or by processes related to postinjury reorganization. We sought to differentiate between these two causes by investigating the functional connectivity (FC) of brain areas during the resting state in human children with early brain injury using a computational model. We simulated a large-scale network consisting of realistic models of local brain areas coupled through anatomical connectivity information of healthy and injured participants. We then compared the resulting simulated FC values of healthy and injured participants with the empirical ones. We found that the empirical connectivity values, especially of the damaged areas, correlated better with simulated values of a healthy brain than those of an injured brain. This result indicates that the structural damage caused by an early brain injury is unlikely to have an adverse and sustained impact on the functional connections, albeit during the resting state, of damaged areas. Therefore, these areas could continue to play a role in the development of near-normal function in certain domains such as language in these children. Copyright © 2015 the authors 0270-6474/15/358914-11$15.00/0.

Graph analysis of functional brain networks: practical issues in translational neuroscience

PubMed Central

De Vico Fallani, Fabrizio; Richiardi, Jonas; Chavez, Mario; Achard, Sophie

2014-01-01

The brain can be regarded as a network: a connected system where nodes, or units, represent different specialized regions and links, or connections, represent communication pathways. From a functional perspective, communication is coded by temporal dependence between the activities of different brain areas. In the last decade, the abstract representation of the brain as a graph has allowed to visualize functional brain networks and describe their non-trivial topological properties in a compact and objective way. Nowadays, the use of graph analysis in translational neuroscience has become essential to quantify brain dysfunctions in terms of aberrant reconfiguration of functional brain networks. Despite its evident impact, graph analysis of functional brain networks is not a simple toolbox that can be blindly applied to brain signals. On the one hand, it requires the know-how of all the methodological steps of the pipeline that manipulate the input brain signals and extract the functional network properties. On the other hand, knowledge of the neural phenomenon under study is required to perform physiologically relevant analysis. The aim of this review is to provide practical indications to make sense of brain network analysis and contrast counterproductive attitudes. PMID:25180301

Epicenters of dynamic connectivity in the adaptation of the ventral visual system.

PubMed

Prčkovska, Vesna; Huijbers, Willem; Schultz, Aaron; Ortiz-Teran, Laura; Peña-Gomez, Cleofe; Villoslada, Pablo; Johnson, Keith; Sperling, Reisa; Sepulcre, Jorge

2017-04-01

Neuronal responses adapt to familiar and repeated sensory stimuli. Enhanced synchrony across wide brain systems has been postulated as a potential mechanism for this adaptation phenomenon. Here, we used recently developed graph theory methods to investigate hidden connectivity features of dynamic synchrony changes during a visual repetition paradigm. Particularly, we focused on strength connectivity changes occurring at local and distant brain neighborhoods. We found that connectivity reorganization in visual modal cortex-such as local suppressed connectivity in primary visual areas and distant suppressed connectivity in fusiform areas-is accompanied by enhanced local and distant connectivity in higher cognitive processing areas in multimodal and association cortex. Moreover, we found a shift of the dynamic functional connections from primary-visual-fusiform to primary-multimodal/association cortex. These findings suggest that repetition-suppression is made possible by reorganization of functional connectivity that enables communication between low- and high-order areas. Hum Brain Mapp 38:1965-1976, 2017. © 2017 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Influence of Wiring Cost on the Large-Scale Architecture of Human Cortical Connectivity

PubMed Central

Samu, David; Seth, Anil K.; Nowotny, Thomas

2014-01-01

In the past two decades some fundamental properties of cortical connectivity have been discovered: small-world structure, pronounced hierarchical and modular organisation, and strong core and rich-club structures. A common assumption when interpreting results of this kind is that the observed structural properties are present to enable the brain's function. However, the brain is also embedded into the limited space of the skull and its wiring has associated developmental and metabolic costs. These basic physical and economic aspects place separate, often conflicting, constraints on the brain's connectivity, which must be characterized in order to understand the true relationship between brain structure and function. To address this challenge, here we ask which, and to what extent, aspects of the structural organisation of the brain are conserved if we preserve specific spatial and topological properties of the brain but otherwise randomise its connectivity. We perform a comparative analysis of a connectivity map of the cortical connectome both on high- and low-resolutions utilising three different types of surrogate networks: spatially unconstrained (‘random’), connection length preserving (‘spatial’), and connection length optimised (‘reduced’) surrogates. We find that unconstrained randomisation markedly diminishes all investigated architectural properties of cortical connectivity. By contrast, spatial and reduced surrogates largely preserve most properties and, interestingly, often more so in the reduced surrogates. Specifically, our results suggest that the cortical network is less tightly integrated than its spatial constraints would allow, but more strongly segregated than its spatial constraints would necessitate. We additionally find that hierarchical organisation and rich-club structure of the cortical connectivity are largely preserved in spatial and reduced surrogates and hence may be partially attributable to cortical wiring constraints. In contrast, the high modularity and strong s-core of the high-resolution cortical network are significantly stronger than in the surrogates, underlining their potential functional relevance in the brain. PMID:24699277

Asphyxia-activated corticocardiac signaling accelerates onset of cardiac arrest.

PubMed

Li, Duan; Mabrouk, Omar S; Liu, Tiecheng; Tian, Fangyun; Xu, Gang; Rengifo, Santiago; Choi, Sarah J; Mathur, Abhay; Crooks, Charles P; Kennedy, Robert T; Wang, Michael M; Ghanbari, Hamid; Borjigin, Jimo

2015-04-21

The mechanism by which the healthy heart and brain die rapidly in the absence of oxygen is not well understood. We performed continuous electrocardiography and electroencephalography in rats undergoing experimental asphyxia and analyzed cortical release of core neurotransmitters, changes in brain and heart electrical activity, and brain-heart connectivity. Asphyxia stimulates a robust and sustained increase of functional and effective cortical connectivity, an immediate increase in cortical release of a large set of neurotransmitters, and a delayed activation of corticocardiac functional and effective connectivity that persists until the onset of ventricular fibrillation. Blocking the brain's autonomic outflow significantly delayed terminal ventricular fibrillation and lengthened the duration of detectable cortical activities despite the continued absence of oxygen. These results demonstrate that asphyxia activates a brainstorm, which accelerates premature death of the heart and the brain.

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.

Brain networks governing the golf swing in professional golfers.

PubMed

Kim, Jin Hyun; Han, Joung Kyue; Kim, Bung-Nyun; Han, Doug Hyun

2015-01-01

Golf, as with most complex motor skills, requires multiple different brain functions, including attention, motor planning, coordination, calculation of timing, and emotional control. In this study we assessed the correlation between swing components and brain connectivity from the cerebellum to the cerebrum. Ten female golf players and 10 age-matched female controls were recruited. In order to determine swing consistency among participants, the standard deviation (SD) of the mean swing speed time and the SD of the mean swing angle were assessed over 30 swings. Functional brain connectivity was assessed by resting state functional MRI. Pro-golfers showed greater positive left cerebellum connectivity to the occipital lobe, temporal lobe, parietal lobe and both frontal lobes compared to controls. The SD of play scores was positively correlated with the SD of the impact angle. Constant swing speed and back swing angle in professional golfers were associated with functional connectivity (FC) between the cerebellum and parietal and frontal lobes. In addition, the constant impact angle in professional golfers was associated with improved golf scores and additional FC of the thalamus.

Functional connectivity of the rodent brain using optical imaging

NASA Astrophysics Data System (ADS)

Guevara Codina, Edgar

The aim of this thesis is to apply functional connectivity in a variety of animal models, using several optical imaging modalities. Even at rest, the brain shows high metabolic activity: the correlation in slow spontaneous fluctuations identifies remotely connected areas of the brain; hence the term "functional connectivity". Ongoing changes in spontaneous activity may provide insight into the neural processing that takes most of the brain metabolic activity, and so may provide a vast source of disease related changes. Brain hemodynamics may be modified during disease and affect resting-state activity. The thesis aims to better understand these changes in functional connectivity due to disease, using functional optical imaging. The optical imaging techniques explored in the first two contributions of this thesis are Optical Imaging of Intrinsic Signals and Laser Speckle Contrast Imaging, together they can estimate the metabolic rate of oxygen consumption, that closely parallels neural activity. They both have adequate spatial and temporal resolution and are well adapted to image the convexity of the mouse cortex. In the last article, a depth-sensitive modality called photoacoustic tomography was used in the newborn rat. Optical coherence tomography and laminar optical tomography were also part of the array of imaging techniques developed and applied in other collaborations. The first article of this work shows the changes in functional connectivity in an acute murine model of epileptiform activity. Homologous correlations are both increased and decreased with a small dependence on seizure duration. These changes suggest a potential decoupling between the hemodynamic parameters in resting-state networks, underlining the importance to investigate epileptic networks with several independent hemodynamic measures. The second study examines a novel murine model of arterial stiffness: the unilateral calcification of the right carotid. Seed-based connectivity analysis showed a decreasing trend of homologous correlation in the motor and cingulate cortices. Graph analyses showed a randomization of the cortex functional networks, suggesting a loss of connectivity, more specifically in the motor cortex ipsilateral to the treated carotid; however these changes are not reflected in differentiated metabolic estimates. Confounds remain due to the fact that carotid rigidification gives rise to neural decline in the hippocampus as well as unilateral alteration of vascular pulsatility; however the results support the need to look at several hemodynamic parameters when imaging the brain after arterial remodeling. The third article of this thesis studies a model of inflammatory injury on the newborn rat. Oxygen saturation and functional connectivity were assessed with photoacoustic tomography. Oxygen saturation was decreased in the site of the lesion and on the cortex ipsilateral to the injury; however this decrease is not fully explained by hypovascularization revealed by histology. Seed-based functional connectivity analysis showed that inter-hemispheric connectivity is not affected by inflammatory injury.

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.

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.

Electro-acupuncture at different acupoints modulating the relative specific brain functional network

NASA Astrophysics Data System (ADS)

Fang, Jiliang; Wang, Xiaoling; Wang, Yin; Liu, Hesheng; Hong, Yang; Liu, Jun; Zhou, Kehua; Wang, Lei; Xue, Chao; Song, Ming; Liu, Baoyan; Zhu, Bing

2010-11-01

Objective: The specific brain effects of acupoint are important scientific concern in acupuncture. However, previous acupuncture fMRI studies focused on acupoints in muscle layer on the limb. Therefore, researches on acupoints within connective tissue at trunk are warranted. Material and Methods: Brain effects of acupuncture on abdomen at acupoints Guanyuan (CV4) and Zhongwan (CV12) were tested using fMRI on 21 healthy volunteers. The data acquisition was performed at resting state, during needle retention, electroacupuncture (EA) and post-EA resting state. Needling sensations were rated after every electroacupuncture (EA) procedure. The needling sensations and the brain functional activity and connectivity were compared between CV4 and CV12 using SPSS, SPM2 and the local and remote connectivity maps. Results and conclusion: EA at CV4 and CV12 induced apparent deactivation effects in the limbic-paralimbic-neocortical network. The default mode of the brain was modified by needle retention and EA, respectively. The functional brain network was significantly changed post EA. However, the minor differences existed between these two acupoints. The results demonstrated similarity between functional brain network mode of acupuncture modulation and functional circuits of emotional and cognitive regulation. Acupuncture may produce analgesia, anti-anxiety and anti-depression via the limbic-paralimbic-neocortical network (LPNN).

Cell type-specific long-range connections of basal forebrain circuit.

PubMed

Do, Johnny Phong; Xu, Min; Lee, Seung-Hee; Chang, Wei-Cheng; Zhang, Siyu; Chung, Shinjae; Yung, Tyler J; Fan, Jiang Lan; Miyamichi, Kazunari; Luo, Liqun; Dan, Yang

2016-09-19

The basal forebrain (BF) plays key roles in multiple brain functions, including sleep-wake regulation, attention, and learning/memory, but the long-range connections mediating these functions remain poorly characterized. Here we performed whole-brain mapping of both inputs and outputs of four BF cell types - cholinergic, glutamatergic, and parvalbumin-positive (PV+) and somatostatin-positive (SOM+) GABAergic neurons - in the mouse brain. Using rabies virus -mediated monosynaptic retrograde tracing to label the inputs and adeno-associated virus to trace axonal projections, we identified numerous brain areas connected to the BF. The inputs to different cell types were qualitatively similar, but the output projections showed marked differences. The connections to glutamatergic and SOM+ neurons were strongly reciprocal, while those to cholinergic and PV+ neurons were more unidirectional. These results reveal the long-range wiring diagram of the BF circuit with highly convergent inputs and divergent outputs and point to both functional commonality and specialization of different BF cell types.

Growth-related neural reorganization and the autism phenotype: a test of the hypothesis that altered brain growth leads to altered connectivity

PubMed Central

Lewis, John D.; Elman, Jeffrey L.

2009-01-01

Theoretical considerations, and findings from computational modeling, comparative neuroanatomy and developmental neuroscience, motivate the hypothesis that a deviant brain growth trajectory will lead to deviant patterns of change in cortico-cortical connectivity. Differences in brain size during development will alter the relative cost and effectiveness of short- and long-distance connections, and should thus impact the growth and retention of connections. Reduced brain size should favor long-distance connectivity; brain overgrowth should favor short-distance connectivity; and inconsistent deviations from the normal growth trajectory – as occurs in autism – should result in potentially disruptive changes to established patterns of functional and physical connectivity during development. To explore this hypothesis, neural networks which modeled inter-hemispheric interaction were grown at the rate of either typically developing children or children with autism. The influence of the length of the inter-hemispheric connections was analyzed at multiple developmental time-points. The networks that modeled autistic growth were less affected by removal of the inter-hemispheric connections than those that modeled normal growth – indicating a reduced reliance on long-distance connections – for short response times, and this difference increased substantially at approximately 24 simulated months of age. The performance of the networks showed a corresponding decline during development. And direct analysis of the connection weights showed a parallel reduction in connectivity. These modeling results support the hypothesis that the deviant growth trajectory in autism spectrum disorders may lead to a disruption of established patterns of functional connectivity during development, with potentially negative behavioral consequences, and a subsequent reduction in physical connectivity. The results are discussed in relation to the growing body of evidence of reduced functional and structural connectivity in autism, and in relation to the behavioral phenotype, particularly the developmental aspects. PMID:18171375

Longitudinal variations of brain functional connectivity: A case report study based on a mouse model of epilepsy.

PubMed

Erramuzpe, A; Encinas, J M; Sierra, A; Maletic-Savatic, M; Brewster, A L; Anderson, Anne E; Stramaglia, S; Cortes, Jesus M

2015-01-01

Brain Functional Connectivity (FC) quantifies statistical dependencies between areas of the brain. FC has been widely used to address altered function of brain circuits in control conditions compared to different pathological states, including epilepsy, a major neurological disorder. However, FC also has the as yet unexplored potential to help us understand the pathological transformation of the brain circuitry. Our hypothesis is that FC can differentiate global brain interactions across a time-scale of days. To this end, we present a case report study based on a mouse model for epilepsy and analyze longitudinal intracranial electroencephalography data of epilepsy to calculate FC changes from the initial insult (status epilepticus) and over the latent period, when epileptogenic networks emerge, and at chronic epilepsy, when unprovoked seizures occur as spontaneous events. We found that the overall network FC at low frequency bands decreased immediately after status epilepticus was provoked, and increased monotonously later on during the latent period. Overall, our results demonstrate the capacity of FC to address longitudinal variations of brain connectivity across the establishment of pathological states.

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.

Sedation of Patients With Disorders of Consciousness During Neuroimaging: Effects on Resting State Functional Brain Connectivity.

PubMed

Kirsch, Muriëlle; Guldenmund, Pieter; Ali Bahri, Mohamed; Demertzi, Athena; Baquero, Katherine; Heine, Lizette; Charland-Verville, Vanessa; Vanhaudenhuyse, Audrey; Bruno, Marie-Aurélie; Gosseries, Olivia; Di Perri, Carol; Ziegler, Erik; Brichant, Jean-François; Soddu, Andrea; Bonhomme, Vincent; Laureys, Steven

2017-02-01

To reduce head movement during resting state functional magnetic resonance imaging, post-coma patients with disorders of consciousness (DOC) are frequently sedated with propofol. However, little is known about the effects of this sedation on the brain connectivity patterns in the damaged brain essential for differential diagnosis. In this study, we aimed to assess these effects. Using resting state functional magnetic resonance imaging 3T data obtained over several years of scanning patients for diagnostic and research purposes, we employed a seed-based approach to examine resting state connectivity in higher-order (default mode, bilateral external control, and salience) and lower-order (auditory, sensorimotor, and visual) resting state networks and connectivity with the thalamus, in 20 healthy unsedated controls, 8 unsedated patients with DOC, and 8 patients with DOC sedated with propofol. The DOC groups were matched for age at onset, etiology, time spent in DOC, diagnosis, standardized behavioral assessment scores, movement intensities, and pattern of structural brain injury (as assessed with T1-based voxel-based morphometry). DOC were associated with severely impaired resting state network connectivity in all but the visual network. Thalamic connectivity to higher-order network regions was also reduced. Propofol administration to patients was associated with minor further decreases in thalamic and insular connectivity. Our findings indicate that connectivity decreases associated with propofol sedation, involving the thalamus and insula, are relatively small compared with those already caused by DOC-associated structural brain injury. Nonetheless, given the known importance of the thalamus in brain arousal, its disruption could well reflect the diminished movement obtained in these patients. However, more research is needed on this topic to fully address the research question.

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.

The modulation of brain functional connectivity with manual acupuncture in healthy subjects: An electroencephalograph case study

NASA Astrophysics Data System (ADS)

Yi, Guo-Sheng; Wang, Jiang; Han, Chun-Xiao; Deng, Bin; Wei, Xi-Le; Li, Nuo

2013-02-01

Manual acupuncture is widely used for pain relief and stress control. Previous studies on acupuncture have shown its modulatory effects on the functional connectivity associated with one or a few preselected brain regions. To investigate how manual acupuncture modulates the organization of functional networks at a whole-brain level, we acupuncture at ST36 of a right leg to obtain electroencephalograph (EEG) signals. By coherence estimation, we determine the synchronizations between all pairwise combinations of EEG channels in three acupuncture states. The resulting synchronization matrices are converted into functional networks by applying a threshold, and the clustering coefficients and path lengths are computed as a function of threshold. The results show that acupuncture can increase functional connections and synchronizations between different brain areas. For a wide range of thresholds, the clustering coefficient during acupuncture and post-acupuncture period is higher than that during the pre-acupuncture control period, whereas the characteristic path length is shorter. We provide further support for the presence of “small-world" network characteristics in functional networks by using acupuncture. These preliminary results highlight the beneficial modulations of functional connectivity by manual acupuncture, which could contribute to the understanding of the effects of acupuncture on the entire brain, as well as the neurophysiological mechanisms underlying acupuncture. Moreover, the proposed method may be a useful approach to the further investigation of the complexity of patterns of interrelations between EEG channels.

When brain neuroscience meets hydrology: timeseries analysis methods for capturing structural and functional aspects of hydrologic connectivity

NASA Astrophysics Data System (ADS)

Ali, G.; Rinderer, M.

2016-12-01

In hydrology, several connectivity definitions exist that hinder intercomparison between different studies. Yet, consensus exists on the distinction between structural connectivity (i.e., physical adjacency of landscape elements that is thought to influence material transfer) and functional or effective connectivity (i.e., interaction or causality between spatial adjacency characteristics and temporally varying factors, leading to the connected flow of material). While hydrologists have succeeded in deriving measures of structural connectivity (SC), the quantification of functional (FC) or effective connectivity (EC) is elusive. Here we borrowed timeseries analysis methods from brain neuroscience to quantify EC and FC among groundwater (n = 34) and stream discharge (n = 1) monitoring sites in a 20-ha Swiss catchment where topography is assumed to be a major driver of connectivity. Influence maps created from elevation data were used to assess SC. FC was assessed by cross-correlation, total and partial mutual information and EC quantified via total and partial entropy, Granger causality and a phase slope index. Results show that generally, a fair percentage of structural connections were also expressed as functional or effective connections. Some FC and EC measures had clear advantages over others, for instance in terms of making a distinction between Darcian fluxes of water and pressure wave-driven processes. False-positive estimations, i.e., the detection of FC and EC despite the absence of SC, were also encountered and used to invalidate the applicability of some brain-connectivity measures in a hydrological context. While our goal was not to identify the best measure of FC or EC, our study showed that the application of brain neuroscience methods for assessing FC and EC in hydrology was possible as long as SC measures were used as constraints for (or prior beliefs about) the establishment of FC and EC.

Testing a dual-systems model of adolescent brain development using resting-state connectivity analyses.

PubMed

van Duijvenvoorde, A C K; Achterberg, M; Braams, B R; Peters, S; Crone, E A

2016-01-01

The current study aimed to test a dual-systems model of adolescent brain development by studying changes in intrinsic functional connectivity within and across networks typically associated with cognitive-control and affective-motivational processes. To this end, resting-state and task-related fMRI data were collected of 269 participants (ages 8-25). Resting-state analyses focused on seeds derived from task-related neural activation in the same participants: the dorsal lateral prefrontal cortex (dlPFC) from a cognitive rule-learning paradigm and the nucleus accumbens (NAcc) from a reward-paradigm. Whole-brain seed-based resting-state analyses showed an age-related increase in dlPFC connectivity with the caudate and thalamus, and an age-related decrease in connectivity with the (pre)motor cortex. nAcc connectivity showed a strengthening of connectivity with the dorsal anterior cingulate cortex (ACC) and subcortical structures such as the hippocampus, and a specific age-related decrease in connectivity with the ventral medial PFC (vmPFC). Behavioral measures from both functional paradigms correlated with resting-state connectivity strength with their respective seed. That is, age-related change in learning performance was mediated by connectivity between the dlPFC and thalamus, and age-related change in winning pleasure was mediated by connectivity between the nAcc and vmPFC. These patterns indicate (i) strengthening of connectivity between regions that support control and learning, (ii) more independent functioning of regions that support motor and control networks, and (iii) more independent functioning of regions that support motivation and valuation networks with age. These results are interpreted vis-à-vis a dual-systems model of adolescent brain development. Copyright © 2015. Published by Elsevier Inc.

Visual Learning Alters the Spontaneous Activity of the Resting Human Brain: An fNIRS Study

PubMed Central

Niu, Haijing; Li, Hao; Sun, Li; Su, Yongming; Huang, Jing; Song, Yan

2014-01-01

Resting-state functional connectivity (RSFC) has been widely used to investigate spontaneous brain activity that exhibits correlated fluctuations. RSFC has been found to be changed along the developmental course and after learning. Here, we investigated whether and how visual learning modified the resting oxygenated hemoglobin (HbO) functional brain connectivity by using functional near-infrared spectroscopy (fNIRS). We demonstrate that after five days of training on an orientation discrimination task constrained to the right visual field, resting HbO functional connectivity and directed mutual interaction between high-level visual cortex and frontal/central areas involved in the top-down control were significantly modified. Moreover, these changes, which correlated with the degree of perceptual learning, were not limited to the trained left visual cortex. We conclude that the resting oxygenated hemoglobin functional connectivity could be used as a predictor of visual learning, supporting the involvement of high-level visual cortex and the involvement of frontal/central cortex during visual perceptual learning. PMID:25243168

Visual learning alters the spontaneous activity of the resting human brain: an fNIRS study.

PubMed

Niu, Haijing; Li, Hao; Sun, Li; Su, Yongming; Huang, Jing; Song, Yan

2014-01-01

Resting-state functional connectivity (RSFC) has been widely used to investigate spontaneous brain activity that exhibits correlated fluctuations. RSFC has been found to be changed along the developmental course and after learning. Here, we investigated whether and how visual learning modified the resting oxygenated hemoglobin (HbO) functional brain connectivity by using functional near-infrared spectroscopy (fNIRS). We demonstrate that after five days of training on an orientation discrimination task constrained to the right visual field, resting HbO functional connectivity and directed mutual interaction between high-level visual cortex and frontal/central areas involved in the top-down control were significantly modified. Moreover, these changes, which correlated with the degree of perceptual learning, were not limited to the trained left visual cortex. We conclude that the resting oxygenated hemoglobin functional connectivity could be used as a predictor of visual learning, supporting the involvement of high-level visual cortex and the involvement of frontal/central cortex during visual perceptual learning.

Towards mapping the brain connectome in depression: functional connectivity by perfusion SPECT.

PubMed

Gardner, Ann; Åstrand, Disa; Öberg, Johanna; Jacobsson, Hans; Jonsson, Cathrine; Larsson, Stig; Pagani, Marco

2014-08-30

Several studies have demonstrated altered brain functional connectivity in the resting state in depression. However, no study has investigated interregional networking in patients with persistent depressive disorder (PDD). The aim of this study was to assess differences in brain perfusion distribution and connectivity between large groups of patients and healthy controls. Participants comprised 91 patients with PDD and 65 age- and sex-matched healthy controls. Resting state perfusion was investigated by single photon emission computed tomography, and group differences were assessed by Statistical Parametric Mapping. Brain connectivity was explored through a voxel-wise interregional correlation analysis using as covariate of interest the normalized values of clusters of voxels in which perfusion differences were found in group analysis. Significantly increased regional brain perfusion distribution covering a large part of the cerebellum was observed in patients as compared with controls. Patients showed a significant negative functional connectivity between the cerebellar cluster and caudate, bilaterally. This study demonstrated inverse relative perfusion between the cerebellum and the caudate in PDD. Functional uncoupling may be associated with a dysregulation between the role of the cerebellum in action control and of the caudate in action selection, initiation and decision making in the patients. The potential impact of the resting state condition and the possibility of mitochondrial impairment are discussed. Copyright © 2014 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

An Evaluation of the Left-Brain vs. Right-Brain Hypothesis with Resting State Functional Connectivity Magnetic Resonance Imaging

PubMed Central

Nielsen, Jared A.; Zielinski, Brandon A.; Ferguson, Michael A.; Lainhart, Janet E.; Anderson, Jeffrey S.

2013-01-01

Lateralized brain regions subserve functions such as language and visuospatial processing. It has been conjectured that individuals may be left-brain dominant or right-brain dominant based on personality and cognitive style, but neuroimaging data has not provided clear evidence whether such phenotypic differences in the strength of left-dominant or right-dominant networks exist. We evaluated whether strongly lateralized connections covaried within the same individuals. Data were analyzed from publicly available resting state scans for 1011 individuals between the ages of 7 and 29. For each subject, functional lateralization was measured for each pair of 7266 regions covering the gray matter at 5-mm resolution as a difference in correlation before and after inverting images across the midsagittal plane. The difference in gray matter density between homotopic coordinates was used as a regressor to reduce the effect of structural asymmetries on functional lateralization. Nine left- and 11 right-lateralized hubs were identified as peaks in the degree map from the graph of significantly lateralized connections. The left-lateralized hubs included regions from the default mode network (medial prefrontal cortex, posterior cingulate cortex, and temporoparietal junction) and language regions (e.g., Broca Area and Wernicke Area), whereas the right-lateralized hubs included regions from the attention control network (e.g., lateral intraparietal sulcus, anterior insula, area MT, and frontal eye fields). Left- and right-lateralized hubs formed two separable networks of mutually lateralized regions. Connections involving only left- or only right-lateralized hubs showed positive correlation across subjects, but only for connections sharing a node. Lateralization of brain connections appears to be a local rather than global property of brain networks, and our data are not consistent with a whole-brain phenotype of greater “left-brained” or greater “right-brained” network strength across individuals. Small increases in lateralization with age were seen, but no differences in gender were observed. PMID:23967180

Structural connectome topology relates to regional BOLD signal dynamics in the mouse brain

NASA Astrophysics Data System (ADS)

Sethi, Sarab S.; Zerbi, Valerio; Wenderoth, Nicole; Fornito, Alex; Fulcher, Ben D.

2017-04-01

Brain dynamics are thought to unfold on a network determined by the pattern of axonal connections linking pairs of neuronal elements; the so-called connectome. Prior work has indicated that structural brain connectivity constrains pairwise correlations of brain dynamics ("functional connectivity"), but it is not known whether inter-regional axonal connectivity is related to the intrinsic dynamics of individual brain areas. Here we investigate this relationship using a weighted, directed mesoscale mouse connectome from the Allen Mouse Brain Connectivity Atlas and resting state functional MRI (rs-fMRI) time-series data measured in 184 brain regions in eighteen anesthetized mice. For each brain region, we measured degree, betweenness, and clustering coefficient from weighted and unweighted, and directed and undirected versions of the connectome. We then characterized the univariate rs-fMRI dynamics in each brain region by computing 6930 time-series properties using the time-series analysis toolbox, hctsa. After correcting for regional volume variations, strong and robust correlations between structural connectivity properties and rs-fMRI dynamics were found only when edge weights were accounted for, and were associated with variations in the autocorrelation properties of the rs-fMRI signal. The strongest relationships were found for weighted in-degree, which was positively correlated to the autocorrelation of fMRI time series at time lag τ = 34 s (partial Spearman correlation ρ = 0.58 ), as well as a range of related measures such as relative high frequency power (f > 0.4 Hz: ρ = - 0.43 ). Our results indicate that the topology of inter-regional axonal connections of the mouse brain is closely related to intrinsic, spontaneous dynamics such that regions with a greater aggregate strength of incoming projections display longer timescales of activity fluctuations.

Structural connectivity in schizophrenia and its impact on the dynamics of spontaneous functional networks

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

Cabral, Joana; Department of Psychiatry, University of Oxford, Oxford OX3 7JX; Fernandes, Henrique M.

The neuropathology of schizophrenia remains unclear. Some insight has come from modern neuroimaging techniques, which offer an unparalleled opportunity to explore in vivo the structure and function of the brain. Using functional magnetic resonance imaging, it has been found that the large-scale resting-state functional connectivity (rsFC) in schizophrenia — measured as the temporal correlations of the blood-oxygen-level-dependent (BOLD) signal — exhibit altered network topology, with lower small-world index. The origin of these rsFC alterations and link with the underlying structural connectivity remain unclear. In this work, we used a computational model of spontaneous large-scale brain activity to explore the rolemore » of the structural connectivity in the large-scale dynamics of the brain in health and schizophrenia. The structural connectomes from 15 adolescent patients with early-onset schizophrenia and 15 age- and gender-matched controls were built from diffusion tensor imaging data to detect the white matter tracts between 90 brain areas. Brain areas, simulated using a reduced dynamic mean-field model, receive excitatory input from other areas in proportion to the number of fibre tracts between them. The simulated mean field activity was transformed into BOLD signal, and the properties of the simulated functional networks were analyzed. Our results suggest that the functional alterations observed in schizophrenia are not directly linked to alterations in the structural topology. Instead, subtly randomized and less small-world functional networks appear when the brain operates with lower global coupling, which shifts the dynamics from the optimal healthy regime.« less

Structural connectivity in schizophrenia and its impact on the dynamics of spontaneous functional networks

NASA Astrophysics Data System (ADS)

Cabral, Joana; Fernandes, Henrique M.; Van Hartevelt, Tim J.; James, Anthony C.; Kringelbach, Morten L.; Deco, Gustavo

2013-12-01

The neuropathology of schizophrenia remains unclear. Some insight has come from modern neuroimaging techniques, which offer an unparalleled opportunity to explore in vivo the structure and function of the brain. Using functional magnetic resonance imaging, it has been found that the large-scale resting-state functional connectivity (rsFC) in schizophrenia — measured as the temporal correlations of the blood-oxygen-level-dependent (BOLD) signal — exhibit altered network topology, with lower small-world index. The origin of these rsFC alterations and link with the underlying structural connectivity remain unclear. In this work, we used a computational model of spontaneous large-scale brain activity to explore the role of the structural connectivity in the large-scale dynamics of the brain in health and schizophrenia. The structural connectomes from 15 adolescent patients with early-onset schizophrenia and 15 age- and gender-matched controls were built from diffusion tensor imaging data to detect the white matter tracts between 90 brain areas. Brain areas, simulated using a reduced dynamic mean-field model, receive excitatory input from other areas in proportion to the number of fibre tracts between them. The simulated mean field activity was transformed into BOLD signal, and the properties of the simulated functional networks were analyzed. Our results suggest that the functional alterations observed in schizophrenia are not directly linked to alterations in the structural topology. Instead, subtly randomized and less small-world functional networks appear when the brain operates with lower global coupling, which shifts the dynamics from the optimal healthy regime.

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.

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.

AICHA: An atlas of intrinsic connectivity of homotopic areas.

PubMed

Joliot, Marc; Jobard, Gaël; Naveau, Mikaël; Delcroix, Nicolas; Petit, Laurent; Zago, Laure; Crivello, Fabrice; Mellet, Emmanuel; Mazoyer, Bernard; Tzourio-Mazoyer, Nathalie

2015-10-30

Atlases of brain anatomical ROIs are widely used for functional MRI data analysis. Recently, it was proposed that an atlas of ROIs derived from a functional brain parcellation could be advantageous, in particular for understanding how different regions share information. However, functional atlases so far proposed do not account for a crucial aspect of cerebral organization, namely homotopy, i.e. that each region in one hemisphere has a homologue in the other hemisphere. We present AICHA (for Atlas of Intrinsic Connectivity of Homotopic Areas), a functional brain ROIs atlas based on resting-state fMRI data acquired in 281 individuals. AICHA ROIs cover the whole cerebrum, each having 1-homogeneity of its constituting voxels intrinsic activity, and 2-a unique homotopic contralateral counterpart with which it has maximal intrinsic connectivity. AICHA was built in 4 steps: (1) estimation of resting-state networks (RSNs) using individual resting-state fMRI independent components, (2) k-means clustering of voxel-wise group level profiles of connectivity, (3) homotopic regional grouping based on maximal inter-hemispheric functional correlation, and (4) ROI labeling. AICHA includes 192 homotopic region pairs (122 gyral, 50 sulcal, and 20 gray nuclei). As an application, we report inter-hemispheric (homotopic and heterotopic) and intra-hemispheric connectivity patterns at different sparsities. ROI functional homogeneity was higher for AICHA than for anatomical ROI atlases, but slightly lower than for another functional ROI atlas not accounting for homotopy. AICHA is ideally suited for intrinsic/effective connectivity analyses, as well as for investigating brain hemispheric specialization. Copyright © 2015 Elsevier B.V. All rights reserved.

Disrupted functional brain connectivity in partial epilepsy: a resting-state fMRI study.

PubMed

Luo, Cheng; Qiu, Chuan; Guo, Zhiwei; Fang, Jiajia; Li, Qifu; Lei, Xu; Xia, Yang; Lai, Yongxiu; Gong, Qiyong; Zhou, Dong; Yao, Dezhong

2011-01-01

Examining the spontaneous activity to understand the neural mechanism of brain disorder is a focus in recent resting-state fMRI. In the current study, to investigate the alteration of brain functional connectivity in partial epilepsy in a systematical way, two levels of analyses (functional connectivity analysis within resting state networks (RSNs) and functional network connectivity (FNC) analysis) were carried out on resting-state fMRI data acquired from the 30 participants including 14 healthy controls(HC) and 16 partial epilepsy patients. According to the etiology, all patients are subdivided into temporal lobe epilepsy group (TLE, included 7 patients) and mixed partial epilepsy group (MPE, 9 patients). Using group independent component analysis, eight RSNs were identified, and selected to evaluate functional connectivity and FNC between groups. Compared with the controls, decreased functional connectivity within all RSNs was found in both TLE and MPE. However, dissociating patterns were observed within the 8 RSNs between two patient groups, i.e, compared with TLE, we found decreased functional connectivity in 5 RSNs increased functional connectivity in 1 RSN, and no difference in the other 2 RSNs in MPE. Furthermore, the hierarchical disconnections of FNC was found in two patient groups, in which the intra-system connections were preserved for all three subsystems while the lost connections were confined to intersystem connections in patients with partial epilepsy. These findings may suggest that decreased resting state functional connectivity and disconnection of FNC are two remarkable characteristics of partial epilepsy. The selective impairment of FNC implicated that it is unsuitable to understand the partial epilepsy only from global or local perspective. We presumed that studying epilepsy in the multi-perspective based on RSNs may be a valuable means to assess the functional changes corresponding to specific RSN and may contribute to the understanding of the neuro-pathophysiological mechanism of epilepsy.

Changes in functional connectivity within the fronto-temporal brain network induced by regular and irregular Russian verb production

PubMed Central

Kireev, Maxim; Slioussar, Natalia; Korotkov, Alexander D.; Chernigovskaya, Tatiana V.; Medvedev, Svyatoslav V.

2015-01-01

Functional connectivity between brain areas involved in the processing of complex language forms remains largely unexplored. Contributing to the debate about neural mechanisms underlying regular and irregular inflectional morphology processing in the mental lexicon, we conducted an fMRI experiment in which participants generated forms from different types of Russian verbs and nouns as well as from nonce stimuli. The data were subjected to a whole brain voxel-wise analysis of context dependent changes in functional connectivity [the so-called psychophysiological interaction (PPI) analysis]. Unlike previously reported subtractive results that reveal functional segregation between brain areas, PPI provides complementary information showing how these areas are functionally integrated in a particular task. To date, PPI evidence on inflectional morphology has been scarce and only available for inflectionally impoverished English verbs in a same-different judgment task. Using PPI here in conjunction with a production task in an inflectionally rich language, we found that functional connectivity between the left inferior frontal gyrus (LIFG) and bilateral superior temporal gyri (STG) was significantly greater for regular real verbs than for irregular ones. Furthermore, we observed a significant positive covariance between the number of mistakes in irregular real verb trials and the increase in functional connectivity between the LIFG and the right anterior cingulate cortex in these trails, as compared to regular ones. Our results therefore allow for dissociation between regularity and processing difficulty effects. These results, on the one hand, shed new light on the functional interplay within the LIFG-bilateral STG language-related network and, on the other hand, call for partial reconsideration of some of the previous findings while stressing the role of functional temporo-frontal connectivity in complex morphological processes. PMID:25741262

Connectivity Neurofeedback Training Can Differentially Change Functional Connectivity and Cognitive Performance.

PubMed

Yamashita, Ayumu; Hayasaka, Shunsuke; Kawato, Mitsuo; Imamizu, Hiroshi

2017-10-01

Advances in functional magnetic resonance imaging have made it possible to provide real-time feedback on brain activity. Neurofeedback has been applied to therapeutic interventions for psychiatric disorders. Since many studies have shown that most psychiatric disorders exhibit abnormal brain networks, a novel experimental paradigm named connectivity neurofeedback, which can directly modulate a brain network, has emerged as a promising approach to treat psychiatric disorders. Here, we investigated the hypothesis that connectivity neurofeedback can induce the aimed direction of change in functional connectivity, and the differential change in cognitive performance according to the direction of change in connectivity. We selected the connectivity between the left primary motor cortex and the left lateral parietal cortex as the target. Subjects were divided into 2 groups, in which only the direction of change (an increase or a decrease in correlation) in the experimentally manipulated connectivity differed between the groups. As a result, subjects successfully induced the expected connectivity changes in either of the 2 directions. Furthermore, cognitive performance significantly and differentially changed from preneurofeedback to postneurofeedback training between the 2 groups. These findings indicate that connectivity neurofeedback can induce the aimed direction of change in connectivity and also a differential change in cognitive performance. © The Author 2017. Published by Oxford University Press.

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

Human brain mapping: A systematic comparison of parcellation methods for the human cerebral cortex.

PubMed

Arslan, Salim; Ktena, Sofia Ira; Makropoulos, Antonios; Robinson, Emma C; Rueckert, Daniel; Parisot, Sarah

2018-04-15

The macro-connectome elucidates the pathways through which brain regions are structurally connected or functionally coupled to perform a specific cognitive task. It embodies the notion of representing and understanding all connections within the brain as a network, while the subdivision of the brain into interacting functional units is inherent in its architecture. As a result, the definition of network nodes is one of the most critical steps in connectivity network analysis. Although brain atlases obtained from cytoarchitecture or anatomy have long been used for this task, connectivity-driven methods have arisen only recently, aiming to delineate more homogeneous and functionally coherent regions. This study provides a systematic comparison between anatomical, connectivity-driven and random parcellation methods proposed in the thriving field of brain parcellation. Using resting-state functional MRI data from the Human Connectome Project and a plethora of quantitative evaluation techniques investigated in the literature, we evaluate 10 subject-level and 24 groupwise parcellation methods at different resolutions. We assess the accuracy of parcellations from four different aspects: (1) reproducibility across different acquisitions and groups, (2) fidelity to the underlying connectivity data, (3) agreement with fMRI task activation, myelin maps, and cytoarchitectural areas, and (4) network analysis. This extensive evaluation of different parcellations generated at the subject and group level highlights the strengths and shortcomings of the various methods and aims to provide a guideline for the choice of parcellation technique and resolution according to the task at hand. The results obtained in this study suggest that there is no optimal method able to address all the challenges faced in this endeavour simultaneously. Copyright © 2017 Elsevier Inc. All rights reserved.

Association Between Brain Activation and Functional Connectivity.

PubMed

Tomasi, Dardo; Volkow, Nora D

2018-04-13

The origin of the "resting-state" brain activity recorded with functional magnetic resonance imaging (fMRI) is still uncertain. Here we provide evidence for the neurovascular origins of the amplitude of the low-frequency fluctuations (ALFF) and the local functional connectivity density (lFCD) by comparing them with task-induced blood-oxygen level dependent (BOLD) responses, which are considered a proxy for neuronal activation. Using fMRI data for 2 different tasks (Relational and Social) collected by the Human Connectome Project in 426 healthy adults, we show that ALFF and lFCD have linear associations with the BOLD response. This association was significantly attenuated by a novel task signal regression (TSR) procedure, indicating that task performance enhances lFCD and ALFF in activated regions. We also show that lFCD predicts BOLD activation patterns, as was recently shown for other functional connectivity metrics, which corroborates that resting functional connectivity architecture impacts brain activation responses. Thus, our findings indicate a common source for BOLD responses, ALFF and lFCD, which is consistent with the neurovascular origin of local hemodynamic synchrony presumably reflecting coordinated fluctuations in neuronal activity. This study also supports the development of task-evoked functional connectivity density mapping.

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.

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.

Normalization of aberrant resting state functional connectivity in fibromyalgia patients following a three month physical exercise therapy

PubMed Central

Flodin, P.; Martinsen, S.; Mannerkorpi, K.; Löfgren, M.; Bileviciute-Ljungar, I.; Kosek, E.; Fransson, P.

2015-01-01

Physical exercise is one of the most efficient interventions to mitigate chronic pain symptoms in fibromyalgia (FM). However, little is known about the neurophysiological mechanisms mediating these effects. In this study we investigated resting-state connectivity using functional magnetic resonance imaging (fMRI) before and after a 15 week standardized exercise program supervised by physical therapists. Our aim was to gain an understanding of how physical exercise influences previously shown aberrant patterns of intrinsic brain activity in FM. Fourteen FM patients and eleven healthy controls successfully completed the physical exercise treatment. We investigated post- versus pre-treatment changes of brain connectivity, as well as changes in clinical symptoms in the patient group. FM patients reported improvements in symptom severity. Although several brain regions showed a treatment-related change in connectivity, only the connectivity between the right anterior insula and the left primary sensorimotor area was significantly more affected by the physical exercise among the fibromyalgia patients compared to healthy controls. Our results suggest that previously observed aberrant intrinsic brain connectivity patterns in FM are partly normalized by the physical exercise therapy. However, none of the observed normalizations in intrinsic brain connectivity were significantly correlated with symptom changes. Further studies conducted in larger cohorts are warranted to investigate the precise relationship between improvements in fibromyalgia symptoms and changes in intrinsic brain activity. PMID:26413476

Normalization of aberrant resting state functional connectivity in fibromyalgia patients following a three month physical exercise therapy.

PubMed

Flodin, P; Martinsen, S; Mannerkorpi, K; Löfgren, M; Bileviciute-Ljungar, I; Kosek, E; Fransson, P

2015-01-01

Physical exercise is one of the most efficient interventions to mitigate chronic pain symptoms in fibromyalgia (FM). However, little is known about the neurophysiological mechanisms mediating these effects. In this study we investigated resting-state connectivity using functional magnetic resonance imaging (fMRI) before and after a 15 week standardized exercise program supervised by physical therapists. Our aim was to gain an understanding of how physical exercise influences previously shown aberrant patterns of intrinsic brain activity in FM. Fourteen FM patients and eleven healthy controls successfully completed the physical exercise treatment. We investigated post- versus pre-treatment changes of brain connectivity, as well as changes in clinical symptoms in the patient group. FM patients reported improvements in symptom severity. Although several brain regions showed a treatment-related change in connectivity, only the connectivity between the right anterior insula and the left primary sensorimotor area was significantly more affected by the physical exercise among the fibromyalgia patients compared to healthy controls. Our results suggest that previously observed aberrant intrinsic brain connectivity patterns in FM are partly normalized by the physical exercise therapy. However, none of the observed normalizations in intrinsic brain connectivity were significantly correlated with symptom changes. Further studies conducted in larger cohorts are warranted to investigate the precise relationship between improvements in fibromyalgia symptoms and changes in intrinsic brain activity.

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

Functional Connectivity of Multiple Brain Regions Required for the Consolidation of Social Recognition Memory.

PubMed

Tanimizu, Toshiyuki; Kenney, Justin W; Okano, Emiko; Kadoma, Kazune; Frankland, Paul W; Kida, Satoshi

2017-04-12

Social recognition memory is an essential and basic component of social behavior that is used to discriminate familiar and novel animals/humans. Previous studies have shown the importance of several brain regions for social recognition memories; however, the mechanisms underlying the consolidation of social recognition memory at the molecular and anatomic levels remain unknown. Here, we show a brain network necessary for the generation of social recognition memory in mice. A mouse genetic study showed that cAMP-responsive element-binding protein (CREB)-mediated transcription is required for the formation of social recognition memory. Importantly, significant inductions of the CREB target immediate-early genes c-fos and Arc were observed in the hippocampus (CA1 and CA3 regions), medial prefrontal cortex (mPFC), anterior cingulate cortex (ACC), and amygdala (basolateral region) when social recognition memory was generated. Pharmacological experiments using a microinfusion of the protein synthesis inhibitor anisomycin showed that protein synthesis in these brain regions is required for the consolidation of social recognition memory. These findings suggested that social recognition memory is consolidated through the activation of CREB-mediated gene expression in the hippocampus/mPFC/ACC/amygdala. Network analyses suggested that these four brain regions show functional connectivity with other brain regions and, more importantly, that the hippocampus functions as a hub to integrate brain networks and generate social recognition memory, whereas the ACC and amygdala are important for coordinating brain activity when social interaction is initiated by connecting with other brain regions. We have found that a brain network composed of the hippocampus/mPFC/ACC/amygdala is required for the consolidation of social recognition memory. SIGNIFICANCE STATEMENT Here, we identify brain networks composed of multiple brain regions for the consolidation of social recognition memory. We found that social recognition memory is consolidated through CREB-meditated gene expression in the hippocampus, medial prefrontal cortex, anterior cingulate cortex (ACC), and amygdala. Importantly, network analyses based on c-fos expression suggest that functional connectivity of these four brain regions with other brain regions is increased with time spent in social investigation toward the generation of brain networks to consolidate social recognition memory. Furthermore, our findings suggest that hippocampus functions as a hub to integrate brain networks and generate social recognition memory, whereas ACC and amygdala are important for coordinating brain activity when social interaction is initiated by connecting with other brain regions. Copyright © 2017 the authors 0270-6474/17/374103-14$15.00/0.

Extraversion modulates functional connectivity hubs of resting-state brain networks.

PubMed

Pang, Yajing; Cui, Qian; Duan, Xujun; Chen, Heng; Zeng, Ling; Zhang, Zhiqiang; Lu, Guangming; Chen, Huafu

2017-09-01

Personality dimension extraversion describes individual differences in social behaviour and socio-emotional functioning. The intrinsic functional connectivity patterns of the brain are reportedly associated with extraversion. However, whether or not extraversion is associated with functional hubs warrants clarification. Functional hubs are involved in the rapid integration of neural processing, and their dysfunction contributes to the development of neuropsychiatric disorders. In this study, we employed the functional connectivity density (FCD) method for the first time to distinguish the energy-efficient hubs associated with extraversion. The resting-state functional magnetic resonance imaging data of 71 healthy subjects were used in the analysis. Short-range FCD was positively correlated with extraversion in the left cuneus, revealing a link between the local functional activity of this region and extraversion in risk-taking. Long-range FCD was negatively correlated with extraversion in the right superior frontal gyrus and the inferior frontal gyrus. Seed-based resting-state functional connectivity (RSFC) analyses revealed that a decreased long-range FCD in individuals with high extraversion scores showed a low long-range functional connectivity pattern between the medial and dorsolateral prefrontal cortex, middle temporal gyrus, and anterior cingulate cortex. This result suggests that decreased RSFC patterns are responsible for self-esteem, self-evaluation, and inhibitory behaviour system that account for the modulation and shaping of extraversion. Overall, our results emphasize specific brain hubs, and reveal long-range functional connections in relation to extraversion, thereby providing a neurobiological basis of extraversion. © 2015 The British Psychological Society.

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.

Functional connectivity decreases in autism in emotion, self, and face circuits identified by Knowledge-based Enrichment Analysis.

PubMed

Cheng, Wei; Rolls, Edmund T; Zhang, Jie; Sheng, Wenbo; Ma, Liang; Wan, Lin; Luo, Qiang; Feng, Jianfeng

2017-03-01

A powerful new method is described called Knowledge based functional connectivity Enrichment Analysis (KEA) for interpreting resting state functional connectivity, using circuits that are functionally identified using search terms with the Neurosynth database. The method derives its power by focusing on neural circuits, sets of brain regions that share a common biological function, instead of trying to interpret single functional connectivity links. This provides a novel way of investigating how task- or function-related networks have resting state functional connectivity differences in different psychiatric states, provides a new way to bridge the gap between task and resting-state functional networks, and potentially helps to identify brain networks that might be treated. The method was applied to interpreting functional connectivity differences in autism. Functional connectivity decreases at the network circuit level in 394 patients with autism compared with 473 controls were found in networks involving the orbitofrontal cortex, anterior cingulate cortex, middle temporal gyrus cortex, and the precuneus, in networks that are implicated in the sense of self, face processing, and theory of mind. The decreases were correlated with symptom severity. Copyright © 2017. Published by Elsevier Inc.

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.

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.

Testosterone affects language areas of the adult human brain.

PubMed

Hahn, Andreas; Kranz, Georg S; Sladky, Ronald; Kaufmann, Ulrike; Ganger, Sebastian; Hummer, Allan; Seiger, Rene; Spies, Marie; Vanicek, Thomas; Winkler, Dietmar; Kasper, Siegfried; Windischberger, Christian; Swaab, Dick F; Lanzenberger, Rupert

2016-05-01

Although the sex steroid hormone testosterone is integrally involved in the development of language processing, ethical considerations mostly limit investigations to single hormone administrations. To circumvent this issue we assessed the influence of continuous high-dose hormone application in adult female-to-male transsexuals. Subjects underwent magnetic resonance imaging before and after 4 weeks of testosterone treatment, with each scan including structural, diffusion weighted and functional imaging. Voxel-based morphometry analysis showed decreased gray matter volume with increasing levels of bioavailable testosterone exclusively in Broca's and Wernicke's areas. Particularly, this may link known sex differences in language performance to the influence of testosterone on relevant brain regions. Using probabilistic tractography, we further observed that longitudinal changes in testosterone negatively predicted changes in mean diffusivity of the corresponding structural connection passing through the extreme capsule. Considering a related increase in myelin staining in rodents, this potentially reflects a strengthening of the fiber tract particularly involved in language comprehension. Finally, functional images at resting-state were evaluated, showing increased functional connectivity between the two brain regions with increasing testosterone levels. These findings suggest testosterone-dependent neuroplastic adaptations in adulthood within language-specific brain regions and connections. Importantly, deteriorations in gray matter volume seem to be compensated by enhancement of corresponding structural and functional connectivity. Hum Brain Mapp 37:1738-1748, 2016. © 2016 Wiley Periodicals, Inc. © 2016 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

Resting-state networks link invasive and noninvasive brain stimulation across diverse psychiatric and neurological diseases

PubMed Central

Fox, Michael D.; Buckner, Randy L.; Liu, Hesheng; Chakravarty, M. Mallar; Lozano, Andres M.; Pascual-Leone, Alvaro

2014-01-01

Brain stimulation, a therapy increasingly used for neurological and psychiatric disease, traditionally is divided into invasive approaches, such as deep brain stimulation (DBS), and noninvasive approaches, such as transcranial magnetic stimulation. The relationship between these approaches is unknown, therapeutic mechanisms remain unclear, and the ideal stimulation site for a given technique is often ambiguous, limiting optimization of the stimulation and its application in further disorders. In this article, we identify diseases treated with both types of stimulation, list the stimulation sites thought to be most effective in each disease, and test the hypothesis that these sites are different nodes within the same brain network as defined by resting-state functional-connectivity MRI. Sites where DBS was effective were functionally connected to sites where noninvasive brain stimulation was effective across diseases including depression, Parkinson's disease, obsessive-compulsive disorder, essential tremor, addiction, pain, minimally conscious states, and Alzheimer’s disease. A lack of functional connectivity identified sites where stimulation was ineffective, and the sign of the correlation related to whether excitatory or inhibitory noninvasive stimulation was found clinically effective. These results suggest that resting-state functional connectivity may be useful for translating therapy between stimulation modalities, optimizing treatment, and identifying new stimulation targets. More broadly, this work supports a network perspective toward understanding and treating neuropsychiatric disease, highlighting the therapeutic potential of targeted brain network modulation. PMID:25267639

Quantifying hydrologic connectivity with measures from the brain neurosciences - a feasibility study

NASA Astrophysics Data System (ADS)

Rinderer, Michael; Ali, Genevieve; Larsen, Laurel

2017-04-01

While the concept of connectivity is increasingly applied in hydrology and ecology, little agreement exists on its definition and quantification approaches. In contrast, the neurosciences have developed a systematic conceptualization of connectivity and methods to quantify it. In particular, neuroscientists make a clear distinction between: 1) structural connectivity, which is determined by the anatomy of the brain neural network, 2) functional connectivity, that is based on statistical dependencies between neural signals, and 3) effective connectivity, that allows to infer causal relations based on the assumption that "true" interactions occur with a certain time delay. In a similar vein, in hydrology, structural connectivity can be defined as the physical adjacency of landscape elements that are seen as a prerequisite of material transfer, while functional or process connectivity would rather describe interactions or causal relations between spatial adjacency characteristics and temporally varying factors. While hydrologists have suggested methods to derive structural connectivity (SC), the quantification of functional (FC) or effective connectivity (EC) has remained elusive. The goal of the current study was therefore to apply timeseries analysis methods from brain neuroscience to quantify EC and FC among groundwater (n = 34) and stream discharge (n = 1) monitoring sites in a 20-ha Swiss catchment where topography is assumed to be a major driver of connectivity. SC was assessed through influence maps that quantify the percentage of flow from an upslope site to a downslope site by applying a multiple flow direction algorithm. FC was assessed by cross-correlation, total and partial mutual information while EC was quantified via total and partial entropy, Granger causality and a phase slope index. Our results showed that many structural connections were also expressed as functional or effective connections, which is reasonable in a catchment with shallow perched groundwater tables. The differentiation between FC and EC measures allowed us to distinguish between hydrological connectivity (i.e., Darcian fluxes of water) and hydraulic connectivity (i.e. pressure wave-driven processes). However, some FC and EC measures also detected the presence of connectivity despite the absence of SC, which highlights the limits of applying brain connectivity measures to hydrology. We therefore conclude that brain neuroscience methods for assessing FC and EC can be powerful tools in assessing hydrological connectivity as long as they are constrained by SC measures.

Brain Functional Connectivity Is Modified by a Hypocaloric Mediterranean Diet and Physical Activity in Obese Women.

PubMed

García-Casares, Natalia; Bernal-López, María R; Roé-Vellvé, Nuria; Gutiérrez-Bedmar, Mario; Fernández-García, Jose C; García-Arnés, Juan A; Ramos-Rodriguez, José R; Alfaro, Francisco; Santamaria-Fernández, Sonia; Steward, Trevor; Jiménez-Murcia, Susana; Garcia-Garcia, Isabel; Valdivielso, Pedro; Fernández-Aranda, Fernando; Tinahones, Francisco J; Gómez-Huelgas, Ricardo

2017-07-01

Functional magnetic resonance imaging (fMRI) in the resting state has shown altered brain connectivity networks in obese individuals. However, the impact of a Mediterranean diet on cerebral connectivity in obese patients when losing weight has not been previously explored. The aim of this study was to examine the connectivity between brain structures before and six months after following a hypocaloric Mediterranean diet and physical activity program in a group of sixteen obese women aged 46.31 ± 4.07 years. Before and after the intervention program, the body mass index (BMI) (kg/m²) was 38.15 ± 4.7 vs. 34.18 ± 4.5 ( p < 0.02), and body weight (kg) was 98.5 ± 13.1 vs. 88.28 ± 12.2 ( p < 0.03). All subjects underwent a pre- and post-intervention fMRI under fasting conditions. Functional connectivity was assessed using seed-based correlations. After the intervention, we found decreased connectivity between the left inferior parietal cortex and the right temporal cortex ( p < 0.001), left posterior cingulate ( p < 0.001), and right posterior cingulate ( p < 0.03); decreased connectivity between the left superior frontal gyrus and the right temporal cortex ( p < 0.01); decreased connectivity between the prefrontal cortex and the somatosensory cortex ( p < 0.025); and decreased connectivity between the left and right posterior cingulate ( p < 0.04). Results were considered significant at a voxel-wise threshold of p ≤ 0.05, and a cluster-level family-wise error correction for multiple comparisons of p ≤ 0.05. In conclusion, functional connectivity between brain structures involved in the pathophysiology of obesity (the inferior parietal lobe, posterior cingulate, temporo-insular cortex, prefrontal cortex) may be modified by a weight loss program including a Mediterranean diet and physical exercise.

Changes in Gait Balance and Brain Connectivity in Response to Equine-Assisted Activity and Training in Children with Attention Deficit Hyperactivity Disorder.

PubMed

Hyun, Gi Jung; Jung, Tae-Woon; Park, Jeong Ha; Kang, Kyoung Doo; Kim, Sun Mi; Son, Young Don; Cheong, Jae Hoon; Kim, Bung-Nyun; Han, Doug Hyun

2016-04-01

Equine-assisted activity and training (EAAT) is thought to improve body balance and clinical symptoms in children with attention deficit hyperactivity disorder (ADHD). The study hypostheses were that EAAT would improve the clinical symptoms and gait balance in children with ADHD and that these improvements would be associated with increased brain connectivity within the balance circuit. A total of 12 children with ADHD and 12 age- and sex-matched healthy control children were recruited. EAAT consisted of three training sessions, each 70 minutes long, once a week for 4 weeks. Brain functional connectivity was assessed by using functional magnetic resonance imaging. After 4 weeks of EAAT, children with ADHD showed improved scores on the Korean ADHD scale (K-ARS), while the K-ARS scores of healthy children did not change. During the 4 weeks, the plantar pressure difference between the left foot and right foot decreased in both the healthy control group and the ADHD group. After 4 weeks of EAAT, healthy controls showed increased brain connectivity from the cerebellum to the left occipital lingual gyrus, fusiform gyrus, right and left thalami, right caudate, right precentral gyrus, and right superior frontal gyrus. However, children with ADHD showed increased brain connectivity from the cerebellum to the right insular cortex, right middle temporal gyrus, left superior temporal gyrus, and right precentral gyrus. In contrast, children with ADHD exhibited decreased brain connectivity from the cerebellum to the left inferior frontal gyrus. EAAT may improve clinical symptoms, gait balance, and brain connectivity, the last of which controls gait balance, in children with ADHD. However, children with ADHD who have deficits in the fronto-cerebellar tract did not exhibit changes in brain connectivity as extensive as those in healthy children in response to EAAT.

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

Individual differences in intrinsic brain connectivity predict decision strategy.

PubMed

Barnes, Kelly Anne; Anderson, Kevin M; Plitt, Mark; Martin, Alex

2014-10-15

When humans are provided with ample time to make a decision, individual differences in strategy emerge. Using an adaptation of a well-studied decision making paradigm, motion direction discrimination, we probed the neural basis of individual differences in strategy. We tested whether strategies emerged from moment-to-moment reconfiguration of functional brain networks involved in decision making with task-evoked functional MRI (fMRI) and whether intrinsic properties of functional brain networks, measured at rest with functional connectivity MRI (fcMRI), were associated with strategy use. We found that human participants reliably selected one of two strategies across 2 days of task performance, either continuously accumulating evidence or waiting for task difficulty to decrease. Individual differences in decision strategy were predicted both by the degree of task-evoked activation of decision-related brain regions and by the strength of pretask correlated spontaneous brain activity. These results suggest that spontaneous brain activity constrains strategy selection on perceptual decisions.

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.

Altered resting state neuromotor connectivity in men with chronic prostatitis/chronic pelvic pain syndrome: A MAPP

PubMed Central

Kutch, Jason J.; Yani, Moheb S.; Asavasopon, Skulpan; Kirages, Daniel J.; Rana, Manku; Cosand, Louise; Labus, Jennifer S.; Kilpatrick, Lisa A.; Ashe-McNalley, Cody; Farmer, Melissa A.; Johnson, Kevin A.; Ness, Timothy J.; Deutsch, Georg; Harris, Richard E.; Apkarian, A. Vania; Clauw, Daniel J.; Mackey, Sean C.; Mullins, Chris; Mayer, Emeran A.

2015-01-01

Brain network activity associated with altered motor control in individuals with chronic pain is not well understood. Chronic Prostatitis/Chronic Pelvic Pain Syndrome (CP/CPPS) is a debilitating condition in which previous studies have revealed altered resting pelvic floor muscle activity in men with CP/CPPS compared to healthy controls. We hypothesized that the brain networks controlling pelvic floor muscles would also show altered resting state function in men with CP/CPPS. Here we describe the results of the first test of this hypothesis focusing on the motor cortical regions, termed pelvic-motor, that can directly activate pelvic floor muscles. A group of men with CP/CPPS (N = 28), as well as group of age-matched healthy male controls (N = 27), had resting state functional magnetic resonance imaging scans as part of the Multidisciplinary Approach to the Study of Chronic Pelvic Pain (MAPP) Research Network study. Brain maps of the functional connectivity of pelvic-motor were compared between groups. A significant group difference was observed in the functional connectivity between pelvic-motor and the right posterior insula. The effect size of this group difference was among the largest effect sizes in functional connectivity between all pairs of 165 anatomically-defined subregions of the brain. Interestingly, many of the atlas region pairs with large effect sizes also involved other subregions of the insular cortices. We conclude that functional connectivity between motor cortex and the posterior insula may be among the most important markers of altered brain function in men with CP/CPPS, and may represent changes in the integration of viscerosensory and motor processing. PMID:26106574

Neuroticism modulates brain visuo-vestibular and anxiety systems during a virtual rollercoaster task.

PubMed

Riccelli, Roberta; Indovina, Iole; Staab, Jeffrey P; Nigro, Salvatore; Augimeri, Antonio; Lacquaniti, Francesco; Passamonti, Luca

2017-02-01

Different lines of research suggest that anxiety-related personality traits may influence the visual and vestibular control of balance, although the brain mechanisms underlying this effect remain unclear. To our knowledge, this is the first functional magnetic resonance imaging (fMRI) study that investigates how individual differences in neuroticism and introversion, two key personality traits linked to anxiety, modulate brain regional responses and functional connectivity patterns during a fMRI task simulating self-motion. Twenty-four healthy individuals with variable levels of neuroticism and introversion underwent fMRI while performing a virtual reality rollercoaster task that included two main types of trials: (1) trials simulating downward or upward self-motion (vertical motion), and (2) trials simulating self-motion in horizontal planes (horizontal motion). Regional brain activity and functional connectivity patterns when comparing vertical versus horizontal motion trials were correlated with personality traits of the Five Factor Model (i.e., neuroticism, extraversion-introversion, openness, agreeableness, and conscientiousness). When comparing vertical to horizontal motion trials, we found a positive correlation between neuroticism scores and regional activity in the left parieto-insular vestibular cortex (PIVC). For the same contrast, increased functional connectivity between the left PIVC and right amygdala was also detected as a function of higher neuroticism scores. Together, these findings provide new evidence that individual differences in personality traits linked to anxiety are significantly associated with changes in the activity and functional connectivity patterns within visuo-vestibular and anxiety-related systems during simulated vertical self-motion. Hum Brain Mapp 38:715-726, 2017. © 2016 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc. © 2016 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

Functional neuroanatomy of disorders of consciousness.

PubMed

Di Perri, Carol; Stender, Johan; Laureys, Steven; Gosseries, Olivia

2014-01-01

Our understanding of the mechanisms of loss and recovery of consciousness, following severe brain injury or during anesthesia, is changing rapidly. Recent neuroimaging studies have shown that patients with chronic disorders of consciousness and subjects undergoing general anesthesia present a complex dysfunctionality in the architecture of brain connectivity. At present, the global hallmark of impaired consciousness appears to be a multifaceted dysfunctional connectivity pattern with both within-network loss of connectivity in a widespread frontoparietal network and between-network hyperconnectivity involving other regions such as the insula and ventral tegmental area. Despite ongoing efforts, the mechanisms underlying the emergence of consciousness after severe brain injury are not thoroughly understood. Important questions remain unanswered: What triggers the connectivity impairment leading to disorders of consciousness? Why do some patients recover from coma, while others with apparently similar brain injuries do not? Understanding these mechanisms could lead to a better comprehension of brain function and, hopefully, lead to new therapeutic strategies in this challenging patient population. © 2013.

Robust prediction of individual creative ability from brain functional connectivity.

PubMed

Beaty, Roger E; Kenett, Yoed N; Christensen, Alexander P; Rosenberg, Monica D; Benedek, Mathias; Chen, Qunlin; Fink, Andreas; Qiu, Jiang; Kwapil, Thomas R; Kane, Michael J; Silvia, Paul J

2018-01-30

People's ability to think creatively is a primary means of technological and cultural progress, yet the neural architecture of the highly creative brain remains largely undefined. Here, we employed a recently developed method in functional brain imaging analysis-connectome-based predictive modeling-to identify a brain network associated with high-creative ability, using functional magnetic resonance imaging (fMRI) data acquired from 163 participants engaged in a classic divergent thinking task. At the behavioral level, we found a strong correlation between creative thinking ability and self-reported creative behavior and accomplishment in the arts and sciences ( r = 0.54). At the neural level, we found a pattern of functional brain connectivity related to high-creative thinking ability consisting of frontal and parietal regions within default, salience, and executive brain systems. In a leave-one-out cross-validation analysis, we show that this neural model can reliably predict the creative quality of ideas generated by novel participants within the sample. Furthermore, in a series of external validation analyses using data from two independent task fMRI samples and a large task-free resting-state fMRI sample, we demonstrate robust prediction of individual creative thinking ability from the same pattern of brain connectivity. The findings thus reveal a whole-brain network associated with high-creative ability comprised of cortical hubs within default, salience, and executive systems-intrinsic functional networks that tend to work in opposition-suggesting that highly creative people are characterized by the ability to simultaneously engage these large-scale brain networks.

[Clinical interest of fMRI and functional exploration methods of brain activity and interactivity: physical and neurophysiological considerations].

PubMed

de Marco, G; Menuel, C; Guillevin, R; Vallée, J-N; Lehmann, P; Fall, S; Quaglino, V; Bourdin, B; Devauchelle, B; Chiras, J

2008-07-01

After having provided a brief reminder of the principle of the blood oxygen level-dependent (BOLD) contrast effect, the physiological bases of brain activity and the concepts of functional integration and effective connectivity, we describe the most recent approaches, which permit to explore brain activity and putative networks of interconnected active areas in order to examine the normal brain physiology and its dysfunctions. We present various methods and studies of brain activity analysis clinically applicable, and we detail the concepts of functional and effective connectivity, which allow to study the cerebral plasticity which occurs at the child's during the maturation (e.g., dyslexia), at the adult during the ageing (e.g., Alzheimer disease), or still in schizophrenia or Parkinson disease. The study of specific circuits in networks has to allow defining in a more realistic way the dynamic of the central nervous system, which underlies various cerebral functions, both in physiological and pathological conditions. This connectivity approach should improve the diagnostic and facilitate the development of new therapeutic strategies.

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.

The association between resting functional connectivity and dispositional optimism.

PubMed

Ran, Qian; Yang, Junyi; Yang, Wenjing; Wei, Dongtao; Qiu, Jiang; Zhang, Dong

2017-01-01

Dispositional optimism is an individual characteristic that plays an important role in human experience. Optimists are people who tend to hold positive expectations for their future. Previous studies have focused on the neural basis of optimism, such as task response neural activity and brain structure volume. However, the functional connectivity between brain regions of the dispositional optimists are poorly understood. Previous study suggested that the ventromedial prefrontal cortex (vmPFC) are associated with individual differences in dispositional optimism, but it is unclear whether there are other brain regions that combine with the vmPFC to contribute to dispositional optimism. Thus, the present study used the resting-state functional connectivity (RSFC) approach and set the vmPFC as the seed region to examine if differences in functional brain connectivity between the vmPFC and other brain regions would be associated with individual differences in dispositional optimism. The results found that dispositional optimism was significantly positively correlated with the strength of the RSFC between vmPFC and middle temporal gyrus (mTG) and negativly correlated with RSFC between vmPFC and inferior frontal gyrus (IFG). These findings may be suggested that mTG and IFG which associated with emotion processes and emotion regulation also play an important role in the dispositional optimism.

The association between resting functional connectivity and dispositional optimism

PubMed Central

Yang, Wenjing; Wei, Dongtao; Qiu, Jiang; Zhang, Dong

2017-01-01

Dispositional optimism is an individual characteristic that plays an important role in human experience. Optimists are people who tend to hold positive expectations for their future. Previous studies have focused on the neural basis of optimism, such as task response neural activity and brain structure volume. However, the functional connectivity between brain regions of the dispositional optimists are poorly understood. Previous study suggested that the ventromedial prefrontal cortex (vmPFC) are associated with individual differences in dispositional optimism, but it is unclear whether there are other brain regions that combine with the vmPFC to contribute to dispositional optimism. Thus, the present study used the resting-state functional connectivity (RSFC) approach and set the vmPFC as the seed region to examine if differences in functional brain connectivity between the vmPFC and other brain regions would be associated with individual differences in dispositional optimism. The results found that dispositional optimism was significantly positively correlated with the strength of the RSFC between vmPFC and middle temporal gyrus (mTG) and negativly correlated with RSFC between vmPFC and inferior frontal gyrus (IFG). These findings may be suggested that mTG and IFG which associated with emotion processes and emotion regulation also play an important role in the dispositional optimism. PMID:28700613

Voxel-wise motion artifacts in population-level whole-brain connectivity analysis of resting-state FMRI.

PubMed

Spisák, Tamás; Jakab, András; Kis, Sándor A; Opposits, Gábor; Aranyi, Csaba; Berényi, Ervin; Emri, Miklós

2014-01-01

Functional Magnetic Resonance Imaging (fMRI) based brain connectivity analysis maps the functional networks of the brain by estimating the degree of synchronous neuronal activity between brain regions. Recent studies have demonstrated that "resting-state" fMRI-based brain connectivity conclusions may be erroneous when motion artifacts have a differential effect on fMRI BOLD signals for between group comparisons. A potential explanation could be that in-scanner displacement, due to rotational components, is not spatially constant in the whole brain. However, this localized nature of motion artifacts is poorly understood and is rarely considered in brain connectivity studies. In this study, we initially demonstrate the local correspondence between head displacement and the changes in the resting-state fMRI BOLD signal. Than, we investigate how connectivity strength is affected by the population-level variation in the spatial pattern of regional displacement. We introduce Regional Displacement Interaction (RDI), a new covariate parameter set for second-level connectivity analysis and demonstrate its effectiveness in reducing motion related confounds in comparisons of groups with different voxel-vise displacement pattern and preprocessed using various nuisance regression methods. The effect of using RDI as second-level covariate is than demonstrated in autism-related group comparisons. The relationship between the proposed method and some of the prevailing subject-level nuisance regression techniques is evaluated. Our results show that, depending on experimental design, treating in-scanner head motion as a global confound may not be appropriate. The degree of displacement is highly variable among various brain regions, both within and between subjects. These regional differences bias correlation-based measures of brain connectivity. The inclusion of the proposed second-level covariate into the analysis successfully reduces artifactual motion-related group differences and preserves real neuronal differences, as demonstrated by the autism-related comparisons.

Differential Hemispheric Predilection of Microstructural White Matter and Functional Connectivity Abnormalities between Respectively Semantic and Behavioral Variant Frontotemporal Dementia.

PubMed

Meijboom, Rozanna; Steketee, Rebecca M E; Ham, Leontine S; van der Lugt, Aad; van Swieten, John C; Smits, Marion

2017-01-01

Semantic dementia (SD) and behavioral variant frontotemporal dementia (bvFTD), subtypes of frontotemporal dementia, are characterized by distinct clinical symptoms and neuroimaging features, with predominant left temporal grey matter (GM) atrophy in SD and bilateral or right frontal GM atrophy in bvFTD. Such differential hemispheric predilection may also be reflected by other neuroimaging features, such as brain connectivity. This study investigated white matter (WM) microstructure and functional connectivity differences between SD and bvFTD, focusing on the hemispheric predilection of these differences. Eight SD and 12 bvFTD patients, and 17 controls underwent diffusion tensor imaging and resting state functional MRI at 3T. Whole-brain WM microstructure was assessed to determine distinct WM tracts affected in SD and bvFTD. For these tracts, diffusivity measures and lateralization indices were calculated. Functional connectivity was established for GM regions affected in early stage SD or bvFTD. Results of a direct comparison between SD and bvFTD are reported. Whole-brain WM microstructure abnormalities were more pronounced in the left hemisphere in SD and bilaterally- with a slight predilection for the right- in bvFTD. Lateralization of tract-specific abnormalities was seen in SD only, toward the left hemisphere. Functional connectivity of disease-specific regions was mainly decreased bilaterally in SD and in the right hemisphere in bvFTD. SD and bvFTD show WM microstructure and functional connectivity abnormalities in different regions, that are respectively more pronounced in the left hemisphere in SD and in the right hemisphere in bvFTD. This indicates differential hemispheric predilection of brain connectivity abnormalities between SD and bvFTD.

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.

Structural connectivity of right frontal hyperactive areas scales with stuttering severity.

PubMed

Neef, Nicole E; Anwander, Alfred; Bütfering, Christoph; Schmidt-Samoa, Carsten; Friederici, Angela D; Paulus, Walter; Sommer, Martin

2018-01-01

A neuronal sign of persistent developmental stuttering is the magnified coactivation of right frontal brain regions during speech production. Whether and how stuttering severity relates to the connection strength of these hyperactive right frontal areas to other brain areas is an open question. Scrutinizing such brain-behaviour and structure-function relationships aims at disentangling suspected underlying neuronal mechanisms of stuttering. Here, we acquired diffusion-weighted and functional images from 31 adults who stutter and 34 matched control participants. Using a newly developed structural connectivity measure, we calculated voxel-wise correlations between connection strength and stuttering severity within tract volumes that originated from functionally hyperactive right frontal regions. Correlation analyses revealed that with increasing speech motor deficits the connection strength increased in the right frontal aslant tract, the right anterior thalamic radiation, and in U-shaped projections underneath the right precentral sulcus. In contrast, with decreasing speech motor deficits connection strength increased in the right uncinate fasciculus. Additional group comparisons of whole-brain white matter skeletons replicated the previously reported reduction of fractional anisotropy in the left and right superior longitudinal fasciculus as well as at the junction of right frontal aslant tract and right superior longitudinal fasciculus in adults who stutter compared to control participants. Overall, our investigation suggests that right fronto-temporal networks play a compensatory role as a fluency enhancing mechanism. In contrast, the increased connection strength within subcortical-cortical pathways may be implied in an overly active global response suppression mechanism in stuttering. Altogether, this combined functional MRI-diffusion tensor imaging study disentangles different networks involved in the neuronal underpinnings of the speech motor deficit in persistent developmental stuttering. © The Author (2017). Published by Oxford University Press on behalf of the Guarantors of Brain.

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).

Functional hypergraph uncovers novel covariant structures over neurodevelopment.

PubMed

Gu, Shi; Yang, Muzhi; Medaglia, John D; Gur, Ruben C; Gur, Raquel E; Satterthwaite, Theodore D; Bassett, Danielle S

2017-08-01

Brain development during adolescence is marked by substantial changes in brain structure and function, leading to a stable network topology in adulthood. However, most prior work has examined the data through the lens of brain areas connected to one another in large-scale functional networks. Here, we apply a recently developed hypergraph approach that treats network connections (edges) rather than brain regions as the unit of interest, allowing us to describe functional network topology from a fundamentally different perspective. Capitalizing on a sample of 780 youth imaged as part of the Philadelphia Neurodevelopmental Cohort, this hypergraph representation of resting-state functional MRI data reveals three distinct classes of subnetworks (hyperedges): clusters, bridges, and stars, which respectively represent homogeneously connected, bipartite, and focal architectures. Cluster hyperedges show a strong resemblance to previously-described functional modules of the brain including somatomotor, visual, default mode, and salience systems. In contrast, star hyperedges represent highly localized subnetworks centered on a small set of regions, and are distributed across the entire cortex. Finally, bridge hyperedges link clusters and stars in a core-periphery organization. Notably, developmental changes within hyperedges are ordered in a similar core-periphery fashion, with the greatest developmental effects occurring in networked hyperedges within the functional core. Taken together, these results reveal a novel decomposition of the network organization of human brain, and further provide a new perspective on the role of local structures that emerge across neurodevelopment. Hum Brain Mapp 38:3823-3835, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Reorganization of Functional Connectivity as a Correlate of Cognitive Recovery in Acquired Brain Injury

ERIC Educational Resources Information Center

Castellanos, Nazareth P.; Paul, Nuria; Ordonez, Victoria E.; Demuynck, Olivier; Bajo, Ricardo; Campo, Pablo; Bilbao, Alvaro; Ortiz, Tomas; del-Pozo, Francisco; Maestu, Fernando

2010-01-01

Cognitive processes require a functional interaction between specialized multiple, local and remote brain regions. Although these interactions can be strongly altered by an acquired brain injury, brain plasticity allows network reorganization to be principally responsible for recovery. The present work evaluates the impact of brain injury on…

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.

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.

Motor Sequence Learning-Induced Neural Efficiency in Functional Brain Connectivity

PubMed Central

Karim, Helmet T; Huppert, Theodore J; Erickson, Kirk I; Wollam, Mariegold E; Sparto, Patrick J; Sejdić, Ervin; VanSwearingen, Jessie M

2016-01-01

Previous studies have shown the functional neural circuitry differences before and after an explicitly learned motor sequence task, but have not assessed these changes during the process of motor skill learning. Functional magnetic resonance imaging activity was measured while participants (n=13) were asked to tap their fingers to visually presented sequences in blocks that were either the same sequence repeated (learning block) or random sequences (control block). Motor learning was associated with a decrease in brain activity during learning compared to control. Lower brain activation was noted in the posterior parietal association area and bilateral thalamus during the later periods of learning (not during the control). Compared to the control condition, we found the task-related motor learning was associated with decreased connectivity between the putamen and left inferior frontal gyrus and left middle cingulate brain regions. Motor learning was associated with changes in network activity, spatial extent, and connectivity. PMID:27845228

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.

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

PubMed

Guo, Hao; 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%.

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

Differential structural and resting state connectivity between insular subdivisions and other pain-related brain regions.

PubMed

Wiech, K; Jbabdi, S; Lin, C S; Andersson, J; Tracey, I

2014-10-01

Functional neuroimaging studies suggest that the anterior, mid, and posterior division of the insula subserve different functions in the perception of pain. The anterior insula (AI) has predominantly been associated with cognitive-affective aspects of pain, while the mid and posterior divisions have been implicated in sensory-discriminative processing. We examined whether this functional segregation is paralleled by differences in (1) structural and (2) resting state connectivity and (3) in correlations with pain-relevant psychological traits. Analyses were restricted to the 3 insular subdivisions and other pain-related brain regions. Both type of analyses revealed largely overlapping results. The AI division was predominantly connected to the ventrolateral prefrontal cortex (structural and resting state connectivity) and orbitofrontal cortex (structural connectivity). In contrast, the posterior insula showed strong connections to the primary somatosensory cortex (SI; structural connectivity) and secondary somatosensory cortex (SII; structural and resting state connectivity). The mid insula displayed a hybrid connectivity pattern with strong connections with the ventrolateral prefrontal cortex, SII (structural and resting state connectivity) and SI (structural connectivity). Moreover, resting state connectivity revealed strong connectivity of all 3 subdivisions with the thalamus. On the behavioural level, AI structural connectivity was related to the individual degree of pain vigilance and awareness that showed a positive correlation with AI-amygdala connectivity and a negative correlation with AI-rostral anterior cingulate cortex connectivity. In sum, our findings show a differential structural and resting state connectivity for the anterior, mid, and posterior insula with other pain-relevant brain regions, which might at least partly explain their different functional profiles in pain processing. Copyright © 2014 The Authors. Published by Elsevier B.V. All rights reserved.

Predicting individual brain functional connectivity using a Bayesian hierarchical model.

PubMed

Dai, Tian; Guo, Ying

2017-02-15

Network-oriented analysis of functional magnetic resonance imaging (fMRI), especially resting-state fMRI, has revealed important association between abnormal connectivity and brain disorders such as schizophrenia, major depression and Alzheimer's disease. Imaging-based brain connectivity measures have become a useful tool for investigating the pathophysiology, progression and treatment response of psychiatric disorders and neurodegenerative diseases. Recent studies have started to explore the possibility of using functional neuroimaging to help predict disease progression and guide treatment selection for individual patients. These studies provide the impetus to develop statistical methodology that would help provide predictive information on disease progression-related or treatment-related changes in neural connectivity. To this end, we propose a prediction method based on Bayesian hierarchical model that uses individual's baseline fMRI scans, coupled with relevant subject characteristics, to predict the individual's future functional connectivity. A key advantage of the proposed method is that it can improve the accuracy of individualized prediction of connectivity by combining information from both group-level connectivity patterns that are common to subjects with similar characteristics as well as individual-level connectivity features that are particular to the specific subject. Furthermore, our method also offers statistical inference tools such as predictive intervals that help quantify the uncertainty or variability of the predicted outcomes. The proposed prediction method could be a useful approach to predict the changes in individual patient's brain connectivity with the progression of a disease. It can also be used to predict a patient's post-treatment brain connectivity after a specified treatment regimen. Another utility of the proposed method is that it can be applied to test-retest imaging data to develop a more reliable estimator for individual functional connectivity. We show there exists a nice connection between our proposed estimator and a recently developed shrinkage estimator of connectivity measures in the neuroimaging community. We develop an expectation-maximization (EM) algorithm for estimation of the proposed Bayesian hierarchical model. Simulations studies are performed to evaluate the accuracy of our proposed prediction methods. We illustrate the application of the methods with two data examples: the longitudinal resting-state fMRI from ADNI2 study and the test-retest fMRI data from Kirby21 study. In both the simulation studies and the fMRI data applications, we demonstrate that the proposed methods provide more accurate prediction and more reliable estimation of individual functional connectivity as compared with alternative methods. Copyright © 2017 Elsevier Inc. All rights reserved.

Early Environmental Enrichment Enhances Abnormal Brain Connectivity in a Rabbit Model of Intrauterine Growth Restriction.

PubMed

Illa, Miriam; Brito, Verónica; Pla, Laura; Eixarch, Elisenda; Arbat-Plana, Ariadna; Batallé, Dafnis; Muñoz-Moreno, Emma; Crispi, Fatima; Udina, Esther; Figueras, Francesc; Ginés, Silvia; Gratacós, Eduard

2017-10-12

The structural correspondence of neurodevelopmental impairments related to intrauterine growth restriction (IUGR) that persists later in life remains elusive. Moreover, early postnatal stimulation strategies have been proposed to mitigate these effects. Long-term brain connectivity abnormalities in an IUGR rabbit model and the effects of early postnatal environmental enrichment (EE) were explored. IUGR was surgically induced in one horn, whereas the contralateral one produced the controls. Postnatally, a subgroup of IUGR animals was housed in an enriched environment. Functional assessment was performed at the neonatal and long-term periods. At the long-term period, structural brain connectivity was evaluated by means of diffusion-weighted brain magnetic resonance imaging and by histological assessment focused on the hippocampus. IUGR animals displayed poorer functional results and presented altered whole-brain networks and decreased median fractional anisotropy in the hippocampus. Reduced density of dendritic spines and perineuronal nets from hippocampal neurons were also observed. Of note, IUGR animals exposed to enriched environment presented an improvement in terms of both function and structure. IUGR is associated with altered brain connectivity at the global and cellular level. A strategy based on early EE has the potential to restore the neurodevelopmental consequences of IUGR. © 2017 S. Karger AG, Basel.

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.

From structure to function, via dynamics

NASA Astrophysics Data System (ADS)

Stetter, O.; Soriano, J.; Geisel, T.; Battaglia, D.

2013-01-01

Neurons in the brain are wired into a synaptic network that spans multiple scales, from local circuits within cortical columns to fiber tracts interconnecting distant areas. However, brain function require the dynamic control of inter-circuit interactions on time-scales faster than synaptic changes. In particular, strength and direction of causal influences between neural populations (described by the so-called directed functional connectivity) must be reconfigurable even when the underlying structural connectivity is fixed. Such directed functional influences can be quantified resorting to causal analysis of time-series based on tools like Granger Causality or Transfer Entropy. The ability to quickly reorganize inter-areal interactions is a chief requirement for performance in a changing natural environment. But how can manifold functional networks stem "on demand" from an essentially fixed structure? We explore the hypothesis that the self-organization of neuronal synchronous activity underlies the control of brain functional connectivity. Based on simulated and real recordings of critical neuronal cultures in vitro, as well as on mean-field and spiking network models of interacting brain areas, we have found that "function follows dynamics", rather than structure. Different dynamic states of a same structural network, characterized by different synchronization properties, are indeed associated to different functional digraphs (functional multiplicity). We also highlight the crucial role of dynamics in establishing a structure-to-function link, by showing that whenever different structural topologies lead to similar dynamical states, than the associated functional connectivities are also very similar (structural degeneracy).

Extreme brain events: Higher-order statistics of brain resting activity and its relation with structural connectivity

NASA Astrophysics Data System (ADS)

Amor, T. A.; Russo, R.; Diez, I.; Bharath, P.; Zirovich, M.; Stramaglia, S.; Cortes, J. M.; de Arcangelis, L.; Chialvo, D. R.

2015-09-01

The brain exhibits a wide variety of spatiotemporal patterns of neuronal activity recorded using functional magnetic resonance imaging as the so-called blood-oxygenated-level-dependent (BOLD) signal. An active area of work includes efforts to best describe the plethora of these patterns evolving continuously in the brain. Here we explore the third-moment statistics of the brain BOLD signals in the resting state as a proxy to capture extreme BOLD events. We find that the brain signal exhibits typically nonzero skewness, with positive values for cortical regions and negative values for subcortical regions. Furthermore, the combined analysis of structural and functional connectivity demonstrates that relatively more connected regions exhibit activity with high negative skewness. Overall, these results highlight the relevance of recent results emphasizing that the spatiotemporal location of the relatively large-amplitude events in the BOLD time series contains relevant information to reproduce a number of features of the brain dynamics during resting state in health and disease.

Increased sensitivity to age-related differences in brain functional connectivity during continuous multiple object tracking compared to resting-state.

PubMed

Dørum, Erlend S; Kaufmann, Tobias; Alnæs, Dag; Andreassen, Ole A; Richard, Geneviève; Kolskår, Knut K; Nordvik, Jan Egil; Westlye, Lars T

2017-03-01

Age-related differences in cognitive agility vary greatly between individuals and cognitive functions. This heterogeneity is partly mirrored in individual differences in brain network connectivity as revealed using resting-state functional magnetic resonance imaging (fMRI), suggesting potential imaging biomarkers for age-related cognitive decline. However, although convenient in its simplicity, the resting state is essentially an unconstrained paradigm with minimal experimental control. Here, based on the conception that the magnitude and characteristics of age-related differences in brain connectivity is dependent on cognitive context and effort, we tested the hypothesis that experimentally increasing cognitive load boosts the sensitivity to age and changes the discriminative network configurations. To this end, we obtained fMRI data from younger (n=25, mean age 24.16±5.11) and older (n=22, mean age 65.09±7.53) healthy adults during rest and two load levels of continuous multiple object tracking (MOT). Brain network nodes and their time-series were estimated using independent component analysis (ICA) and dual regression, and the edges in the brain networks were defined as the regularized partial temporal correlations between each of the node pairs at the individual level. Using machine learning based on a cross-validated regularized linear discriminant analysis (rLDA) we attempted to classify groups and cognitive load from the full set of edge-wise functional connectivity indices. While group classification using resting-state data was highly above chance (approx. 70% accuracy), functional connectivity (FC) obtained during MOT strongly increased classification performance, with 82% accuracy for the young and 95% accuracy for the old group at the highest load level. Further, machine learning revealed stronger differentiation between rest and task in young compared to older individuals, supporting the notion of network dedifferentiation in cognitive aging. Task-modulation in edgewise FC was primarily observed between attention- and sensorimotor networks; with decreased negative correlations between attention- and default mode networks in older adults. These results demonstrate that the magnitude and configuration of age-related differences in brain functional connectivity are partly dependent on cognitive context and load, which emphasizes the importance of assessing brain connectivity differences across a range of cognitive contexts beyond the resting-state. Copyright © 2017 Elsevier Inc. All rights reserved.

Regional expression of the MAPT gene is associated with loss of hubs in brain networks and cognitive impairment in Parkinson disease and progressive supranuclear palsy.

PubMed

Rittman, Timothy; Rubinov, Mikail; Vértes, Petra E; Patel, Ameera X; Ginestet, Cedric E; Ghosh, Boyd C P; Barker, Roger A; Spillantini, Maria Grazia; Bullmore, Edward T; Rowe, James B

2016-12-01

Abnormalities of tau protein are central to the pathogenesis of progressive supranuclear palsy, whereas haplotype variation of the tau gene MAPT influences the risk of Parkinson disease and Parkinson's disease dementia. We assessed whether regional MAPT expression might be associated with selective vulnerability of global brain networks to neurodegenerative pathology. Using task-free functional magnetic resonance imaging in progressive supranuclear palsy, Parkinson disease, and healthy subjects (n = 128), we examined functional brain networks and measured the connection strength between 471 gray matter regions. We obtained MAPT and SNCA microarray expression data in healthy subjects from the Allen brain atlas. Regional connectivity varied according to the normal expression of MAPT. The regional expression of MAPT correlated with the proportionate loss of regional connectivity in Parkinson's disease. Executive cognition was impaired in proportion to the loss of hub connectivity. These effects were not seen with SNCA, suggesting that alpha-synuclein pathology is not mediated through global network properties. The results establish a link between regional MAPT expression and selective vulnerability of functional brain networks to neurodegeneration. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Disrupted global metastability and static and dynamic brain connectivity across individuals in the Alzheimer’s disease continuum

NASA Astrophysics Data System (ADS)

Córdova-Palomera, Aldo; Kaufmann, Tobias; Persson, Karin; Alnæs, Dag; Doan, Nhat Trung; Moberget, Torgeir; Lund, Martina Jonette; Barca, Maria Lage; Engvig, Andreas; Brækhus, Anne; Engedal, Knut; Andreassen, Ole A.; Selbæk, Geir; Westlye, Lars T.

2017-01-01

As findings on the neuropathological and behavioral components of Alzheimer’s disease (AD) continue to accrue, converging evidence suggests that macroscale brain functional disruptions may mediate their association. Recent developments on theoretical neuroscience indicate that instantaneous patterns of brain connectivity and metastability may be a key mechanism in neural communication underlying cognitive performance. However, the potential significance of these patterns across the AD spectrum remains virtually unexplored. We assessed the clinical sensitivity of static and dynamic functional brain disruptions across the AD spectrum using resting-state fMRI in a sample consisting of AD patients (n = 80) and subjects with either mild (n = 44) or subjective (n = 26) cognitive impairment (MCI, SCI). Spatial maps constituting the nodes in the functional brain network and their associated time-series were estimated using spatial group independent component analysis and dual regression, and whole-brain oscillatory activity was analyzed both globally (metastability) and locally (static and dynamic connectivity). Instantaneous phase metrics showed functional coupling alterations in AD compared to MCI and SCI, both static (putamen, dorsal and default-mode) and dynamic (temporal, frontal-superior and default-mode), along with decreased global metastability. The results suggest that brains of AD patients display altered oscillatory patterns, in agreement with theoretical premises on cognitive dynamics.

Adaptation of brain functional and structural networks in aging.

PubMed

Lee, Annie; Ratnarajah, Nagulan; Tuan, Ta Anh; Chen, Shen-Hsing Annabel; Qiu, Anqi

2015-01-01

The human brain, especially the prefrontal cortex (PFC), is functionally and anatomically reorganized in order to adapt to neuronal challenges in aging. This study employed structural MRI, resting-state fMRI (rs-fMRI), and high angular resolution diffusion imaging (HARDI), and examined the functional and structural reorganization of the PFC in aging using a Chinese sample of 173 subjects aged from 21 years and above. We found age-related increases in the structural connectivity between the PFC and posterior brain regions. Such findings were partially mediated by age-related increases in the structural connectivity of the occipital lobe within the posterior brain. Based on our findings, it is thought that the PFC reorganization in aging could be partly due to the adaptation to age-related changes in the structural reorganization of the posterior brain. This thus supports the idea derived from task-based fMRI that the PFC reorganization in aging may be adapted to the need of compensation for resolving less distinctive stimulus information from the posterior brain regions. In addition, we found that the structural connectivity of the PFC with the temporal lobe was fully mediated by the temporal cortical thickness, suggesting that the brain morphology plays an important role in the functional and structural reorganization with aging.

Chronnectome fingerprinting: Identifying individuals and predicting higher cognitive functions using dynamic brain connectivity patterns.

PubMed

Liu, Jin; Liao, Xuhong; Xia, Mingrui; He, Yong

2018-02-01

The human brain is a large, interacting dynamic network, and its architecture of coupling among brain regions varies across time (termed the "chronnectome"). However, very little is known about whether and how the dynamic properties of the chronnectome can characterize individual uniqueness, such as identifying individuals as a "fingerprint" of the brain. Here, we employed multiband resting-state functional magnetic resonance imaging data from the Human Connectome Project (N = 105) and a sliding time-window dynamic network analysis approach to systematically examine individual time-varying properties of the chronnectome. We revealed stable and remarkable individual variability in three dynamic characteristics of brain connectivity (i.e., strength, stability, and variability), which was mainly distributed in three higher order cognitive systems (i.e., default mode, dorsal attention, and fronto-parietal) and in two primary systems (i.e., visual and sensorimotor). Intriguingly, the spatial patterns of these dynamic characteristics of brain connectivity could successfully identify individuals with high accuracy and could further significantly predict individual higher cognitive performance (e.g., fluid intelligence and executive function), which was primarily contributed by the higher order cognitive systems. Together, our findings highlight that the chronnectome captures inherent functional dynamics of individual brain networks and provides implications for individualized characterization of health and disease. © 2017 Wiley Periodicals, Inc.

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.

EEG functional connectivity, axon delays and white matter disease.

PubMed

Nunez, Paul L; Srinivasan, Ramesh; Fields, R Douglas

2015-01-01

Both structural and functional brain connectivities are closely linked to white matter disease. We discuss several such links of potential interest to neurologists, neurosurgeons, radiologists, and non-clinical neuroscientists. Treatment of brains as genuine complex systems suggests major emphasis on the multi-scale nature of brain connectivity and dynamic behavior. Cross-scale interactions of local, regional, and global networks are apparently responsible for much of EEG's oscillatory behaviors. Finite axon propagation speed, often assumed to be infinite in local network models, is central to our conceptual framework. Myelin controls axon speed, and the synchrony of impulse traffic between distant cortical regions appears to be critical for optimal mental performance and learning. Several experiments suggest that axon conduction speed is plastic, thereby altering the regional and global white matter connections that facilitate binding of remote local networks. Combined EEG and high resolution EEG can provide distinct multi-scale estimates of functional connectivity in both healthy and diseased brains with measures like frequency and phase spectra, covariance, and coherence. White matter disease may profoundly disrupt normal EEG coherence patterns, but currently these kinds of studies are rare in scientific labs and essentially missing from clinical environments. Copyright © 2014 International Federation of Clinical Neurophysiology. All rights reserved.

The usefulness of sLORETA in evaluating the effect of high-dose ARA-C on brain connectivity in patients with acute myeloid leukemia: an exploratory study

PubMed Central

Zarabla, Alessia; Ungania, Sara; Cacciatore, Alessandra; Maialetti, Andrea; Petreri, Gianluca; Mengarelli, Andrea; Spadea, Antonio; Marchesi, Francesco; Renzi, Daniela; Gumenyuk, Svitlana; Strigari, Lidia; Maschio, Marta

2017-01-01

Summary Cytosine arabinoside (Ara-C) is one of the key drugs for treating acute myeloid leukemia (AML). High intravenous doses may produce a number of central nervous system (CNS) toxicities and contribute to modifications in brain functional connectivity. sLORETA is a software used for localizing brain electrical activity and functional connectivity. The aim of this study was to apply sLORETA in the evaluation of possible effects of Ara-C on brain connectivity in patients with AML without CNS involvement. We studied eight patients with AML; four were administered standard doses of Ara-C while the other four received high doses. sLORETA was computed from computerized EEG data before treatment and after six months of treatment. Three regions of interest, corresponding to specific combinations of Brodmann areas, were defined. In the patients receiving high-dose Ara-C, a statistically significant reduction in functional connectivity was observed in the frontoparietal network, which literature data suggest is involved in attentional processes. Our data highlight the possibility of using novel techniques to study potential CNS toxicity of cancer therapy.

Mapping the functional connectome in traumatic brain injury: What can graph metrics tell us?

PubMed

Caeyenberghs, Karen; Verhelst, Helena; Clemente, Adam; Wilson, Peter H

2017-10-15

Traumatic brain injury (TBI) is associated with cognitive and motor deficits, and poses a significant personal, societal, and economic burden. One mechanism by which TBI is thought to affect cognition and behavior is through changes in functional connectivity. Graph theory is a powerful framework for quantifying topological features of neuroimaging-derived functional networks. The objective of this paper is to review studies examining functional connectivity in TBI with an emphasis on graph theoretical analysis that is proving to be valuable in uncovering network abnormalities in this condition. We review studies that have examined TBI-related alterations in different properties of the functional brain network, including global integration, segregation, centrality and resilience. We focus on functional data using task-related fMRI or resting-state fMRI in patients with TBI of different severity and recovery phase, and consider how graph metrics may inform rehabilitation and enhance efficacy. Moreover, we outline some methodological challenges associated with the examination of functional connectivity in patients with brain injury, including the sample size, parcellation scheme used, node definition and subgroup analyses. The findings suggest that TBI is associated with hyperconnectivity and a suboptimal global integration, characterized by increased connectivity degree and strength and reduced efficiency of functional networks. This altered functional connectivity, also evident in other clinical populations, is attributable to diffuse white matter pathology and reductions in gray and white matter volume. These functional alterations are implicated in post-concussional symptoms, posttraumatic stress and neurocognitive dysfunction after TBI. Finally, the effects of focal lesions have been found to depend critically on topological position and their role in the network. Graph theory is a unique and powerful tool for exploring functional connectivity in brain-injured patients. One limitation is that its results do not provide specific measures about the biophysical mechanism underlying TBI. Continued work in this field will hopefully see graph metrics used as biomarkers to provide more accurate diagnosis and help guide treatment at the individual patient level. Copyright © 2016. Published by Elsevier Inc.

Alzheimer Classification Using a Minimum Spanning Tree of High-Order Functional Network on fMRI Dataset

PubMed Central

Guo, Hao; Liu, Lei; Chen, Junjie; Xu, Yong; Jie, Xiang

2017-01-01

Functional magnetic resonance imaging (fMRI) is one of the most useful methods to generate functional connectivity networks of the brain. However, conventional network generation methods ignore dynamic changes of functional connectivity between brain regions. Previous studies proposed constructing high-order functional connectivity networks that consider the time-varying characteristics of functional connectivity, and a clustering method was performed to decrease computational cost. However, random selection of the initial clustering centers and the number of clusters negatively affected classification accuracy, and the network lost neurological interpretability. Here we propose a novel method that introduces the minimum spanning tree method to high-order functional connectivity networks. As an unbiased method, the minimum spanning tree simplifies high-order network structure while preserving its core framework. The dynamic characteristics of time series are not lost with this approach, and the neurological interpretation of the network is guaranteed. Simultaneously, we propose a multi-parameter optimization framework that involves extracting discriminative features from the minimum spanning tree high-order functional connectivity networks. Compared with the conventional methods, our resting-state fMRI classification method based on minimum spanning tree high-order functional connectivity networks greatly improved the diagnostic accuracy for Alzheimer's disease. PMID:29249926

Structural and functional connectivity of the subthalamic nucleus during vocal emotion decoding

PubMed Central

Frühholz, Sascha; Ceravolo, Leonardo; Grandjean, Didier

2016-01-01

Our understanding of the role played by the subthalamic nucleus (STN) in human emotion has recently advanced with STN deep brain stimulation, a neurosurgical treatment for Parkinson’s disease and obsessive-compulsive disorder. However, the potential presence of several confounds related to pathological models raises the question of how much they affect the relevance of observations regarding the physiological function of the STN itself. This underscores the crucial importance of obtaining evidence from healthy participants. In this study, we tested the structural and functional connectivity between the STN and other brain regions related to vocal emotion in a healthy population by combining diffusion tensor imaging and psychophysiological interaction analysis from a high-resolution functional magnetic resonance imaging study. As expected, we showed that the STN is functionally connected to the structures involved in emotional prosody decoding, notably the orbitofrontal cortex, inferior frontal gyrus, auditory cortex, pallidum and amygdala. These functional results were corroborated by probabilistic fiber tracking, which revealed that the left STN is structurally connected to the amygdala and the orbitofrontal cortex. These results confirm, in healthy participants, the role played by the STN in human emotion and its structural and functional connectivity with the brain network involved in vocal emotions. PMID:26400857

Adverse Effects of Cannabis on Adolescent Brain Development: A Longitudinal Study.

PubMed

Camchong, Jazmin; Lim, Kelvin O; Kumra, Sanjiv

2017-03-01

Cannabis is widely perceived as a safe recreational drug and its use is increasing in youth. It is important to understand the implications of cannabis use during childhood and adolescence on brain development. This is the first longitudinal study that compared resting functional connectivity of frontally mediated networks between 43 healthy controls (HCs; 20 females; age M = 16.5 ± 2.7) and 22 treatment-seeking adolescents with cannabis use disorder (CUD; 8 females; age M = 17.6 ± 2.4). Increases in resting functional connectivity between caudal anterior cingulate cortex (ACC) and superior frontal gyrus across time were found in HC, but not in CUD. CUD showed a decrease in functional connectivity between caudal ACC and dorsolateral and orbitofrontal cortices across time. Lower functional connectivity between caudal ACC cortex and orbitofrontal cortex at baseline predicted higher amounts of cannabis use during the following 18 months. Finally, high amounts of cannabis use during the 18-month interval predicted lower intelligence quotient and slower cognitive function measured at follow-up. These data provide compelling longitudinal evidence suggesting that repeated exposure to cannabis during adolescence may have detrimental effects on brain resting functional connectivity, intelligence, and cognitive function. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Altered Resting Brain Function and Structure in Professional Badminton Players

PubMed Central

Di, Xin; Zhu, Senhua; Wang, Pin; Ye, Zhuoer; Zhou, Ke; Zhuo, Yan

2012-01-01

Abstract Neuroimaging studies of professional athletic or musical training have demonstrated considerable practice-dependent plasticity in various brain structures, which may reflect distinct training demands. In the present study, structural and functional brain alterations were examined in professional badminton players and compared with healthy controls using magnetic resonance imaging (MRI) and resting-state functional MRI. Gray matter concentration (GMC) was assessed using voxel-based morphometry (VBM), and resting-brain functions were measured by amplitude of low-frequency fluctuation (ALFF) and seed-based functional connectivity. Results showed that the athlete group had greater GMC and ALFF in the right and medial cerebellar regions, respectively. The athlete group also demonstrated smaller ALFF in the left superior parietal lobule and altered functional connectivity between the left superior parietal and frontal regions. These findings indicate that badminton expertise is associated with not only plastic structural changes in terms of enlarged gray matter density in the cerebellum, but also functional alterations in fronto-parietal connectivity. Such structural and functional alterations may reflect specific experiences of badminton training and practice, including high-capacity visuo-spatial processing and hand-eye coordination in addition to refined motor skills. PMID:22840241

Fine-Granularity Functional Interaction Signatures for Characterization of Brain Conditions

PubMed Central

Hu, Xintao; Zhu, Dajiang; Lv, Peili; Li, Kaiming; Han, Junwei; Wang, Lihong; Shen, Dinggang; Guo, Lei; Liu, Tianming

2014-01-01

In the human brain, functional activity occurs at multiple spatial scales. Current studies on functional brain networks and their alterations in brain diseases via resting-state functional magnetic resonance imaging (rs-fMRI) are generally either at local scale (regionally confined analysis and inter-regional functional connectivity analysis) or at global scale (graph theoretic analysis). In contrast, inferring functional interaction at fine-granularity sub-network scale has not been adequately explored yet. Here our hypothesis is that functional interaction measured at fine-granularity subnetwork scale can provide new insight into the neural mechanisms of neurological and psychological conditions, thus offering complementary information for healthy and diseased population classification. In this paper, we derived fine-granularity functional interaction (FGFI) signatures in subjects with Mild Cognitive Impairment (MCI) and Schizophrenia by diffusion tensor imaging (DTI) and rsfMRI, and used patient-control classification experiments to evaluate the distinctiveness of the derived FGFI features. Our experimental results have shown that the FGFI features alone can achieve comparable classification performance compared with the commonly used inter-regional connectivity features. However, the classification performance can be substantially improved when FGFI features and inter-regional connectivity features are integrated, suggesting the complementary information achieved from the FGFI signatures. PMID:23319242

Stable functional networks exhibit consistent timing in the human brain.

PubMed

Chapeton, Julio I; Inati, Sara K; Zaghloul, Kareem A

2017-03-01

Despite many advances in the study of large-scale human functional networks, the question of timing, stability, and direction of communication between cortical regions has not been fully addressed. At the cellular level, neuronal communication occurs through axons and dendrites, and the time required for such communication is well defined and preserved. At larger spatial scales, however, the relationship between timing, direction, and communication between brain regions is less clear. Here, we use a measure of effective connectivity to identify connections between brain regions that exhibit communication with consistent timing. We hypothesized that if two brain regions are communicating, then knowledge of the activity in one region should allow an external observer to better predict activity in the other region, and that such communication involves a consistent time delay. We examine this question using intracranial electroencephalography captured from nine human participants with medically refractory epilepsy. We use a coupling measure based on time-lagged mutual information to identify effective connections between brain regions that exhibit a statistically significant increase in average mutual information at a consistent time delay. These identified connections result in sparse, directed functional networks that are stable over minutes, hours, and days. Notably, the time delays associated with these connections are also highly preserved over multiple time scales. We characterize the anatomic locations of these connections, and find that the propagation of activity exhibits a preferred posterior to anterior temporal lobe direction, consistent across participants. Moreover, networks constructed from connections that reliably exhibit consistent timing between anatomic regions demonstrate features of a small-world architecture, with many reliable connections between anatomically neighbouring regions and few long range connections. Together, our results demonstrate that cortical regions exhibit functional relationships with well-defined and consistent timing, and the stability of these relationships over multiple time scales suggests that these stable pathways may be reliably and repeatedly used for large-scale cortical communication. Published by Oxford University Press on behalf of the Guarantors of Brain 2017. This work is written by US Government employees and is in the public domain in the United States.

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.

A selective involvement of putamen functional connectivity in youth with internet gaming disorder.

PubMed

Hong, Soon-Beom; Harrison, Ben J; Dandash, Orwa; Choi, Eun-Jung; Kim, Seong-Chan; Kim, Ho-Hyun; Shim, Do-Hyun; Kim, Chang-Dai; Kim, Jae-Won; Yi, Soon-Hyung

2015-03-30

Brain cortico-striatal circuits have consistently been implicated in the pathology of addiction related disorders. We applied a reliable seed-based analysis of the resting-state brain activity to comprehensively delineate the subdivisions of striatal functional connectivity implicated in internet gaming disorder. Among twelve right-handed male adolescents with internet gaming disorder and 11 right-handed and gender-matched healthy controls, we examined group differences in the functional connectivity of dorsal and ventral subdivisions of the caudate nucleus and putamen, as well as the association of these connectivity indices with behavioral measures of internet use. Adolescents with internet gaming disorder showed significantly reduced dorsal putamen functional connectivity with the posterior insula-parietal operculum. More time spent playing online games predicted significantly greater functional connectivity between the dorsal putamen and bilateral primary somatosensory cortices in adolescents with internet gaming disorder, and significantly lower functional connectivity between the dorsal putamen and bilateral sensorimotor cortices in healthy controls. The dorsal putamen functional connectivity was significantly and specifically different in adolescents with internet gaming disorder. The findings suggest a possible biomarker of internet gaming disorder. Copyright © 2015. Published by Elsevier B.V.

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

Cannabinoid Modulation of Functional Connectivity within Regions Processing Attentional Salience

PubMed Central

Bhattacharyya, Sagnik; Falkenberg, Irina; Martin-Santos, Rocio; Atakan, Zerrin; Crippa, Jose A; Giampietro, Vincent; Brammer, Mick; McGuire, Philip

2015-01-01

There is now considerable evidence to support the hypothesis that psychotic symptoms are the result of abnormal salience attribution, and that the attribution of salience is largely mediated through the prefrontal cortex, the striatum, and the hippocampus. Although these areas show differential activation under the influence of delta-9-tetrahydrocannabinol (delta-9-THC) and cannabidiol (CBD), the two major derivatives of cannabis sativa, little is known about the effects of these cannabinoids on the functional connectivity between these regions. We investigated this in healthy occasional cannabis users by employing event-related functional magnetic resonance imaging (fMRI) following oral administration of delta-9-THC, CBD, or a placebo capsule. Employing a seed cluster-based functional connectivity analysis that involved using the average time series from each seed cluster for a whole-brain correlational analysis, we investigated the effect of drug condition on functional connectivity between the seed clusters and the rest of the brain during an oddball salience processing task. Relative to the placebo condition, delta-9-THC and CBD had opposite effects on the functional connectivity between the dorsal striatum, the prefrontal cortex, and the hippocampus. Delta-9-THC reduced fronto-striatal connectivity, which was related to its effect on task performance, whereas this connection was enhanced by CBD. Conversely, mediotemporal-prefrontal connectivity was enhanced by delta-9-THC and reduced by CBD. Our results suggest that the functional integration of brain regions involved in salience processing is differentially modulated by single doses of delta-9-THC and CBD and that this relates to the processing of salient stimuli. PMID:25249057

Discriminative analysis of non-linear brain connectivity for leukoaraiosis with resting-state fMRI

NASA Astrophysics Data System (ADS)

Lai, Youzhi; Xu, Lele; Yao, Li; Wu, Xia

2015-03-01

Leukoaraiosis (LA) describes diffuse white matter abnormalities on CT or MR brain scans, often seen in the normal elderly and in association with vascular risk factors such as hypertension, or in the context of cognitive impairment. The mechanism of cognitive dysfunction is still unclear. The recent clinical studies have revealed that the severity of LA was not corresponding to the cognitive level, and functional connectivity analysis is an appropriate method to detect the relation between LA and cognitive decline. However, existing functional connectivity analyses of LA have been mostly limited to linear associations. In this investigation, a novel measure utilizing the extended maximal information coefficient (eMIC) was applied to construct non-linear functional connectivity in 44 LA subjects (9 dementia, 25 mild cognitive impairment (MCI) and 10 cognitively normal (CN)). The strength of non-linear functional connections for the first 1% of discriminative power increased in MCI compared with CN and dementia, which was opposed to its linear counterpart. Further functional network analysis revealed that the changes of the non-linear and linear connectivity have similar but not completely the same spatial distribution in human brain. In the multivariate pattern analysis with multiple classifiers, the non-linear functional connectivity mostly identified dementia, MCI and CN from LA with a relatively higher accuracy rate than the linear measure. Our findings revealed the non-linear functional connectivity provided useful discriminative power in classification of LA, and the spatial distributed changes between the non-linear and linear measure may indicate the underlying mechanism of cognitive dysfunction in LA.

Cannabinoid modulation of functional connectivity within regions processing attentional salience.

PubMed

Bhattacharyya, Sagnik; Falkenberg, Irina; Martin-Santos, Rocio; Atakan, Zerrin; Crippa, Jose A; Giampietro, Vincent; Brammer, Mick; McGuire, Philip

2015-05-01

There is now considerable evidence to support the hypothesis that psychotic symptoms are the result of abnormal salience attribution, and that the attribution of salience is largely mediated through the prefrontal cortex, the striatum, and the hippocampus. Although these areas show differential activation under the influence of delta-9-tetrahydrocannabinol (delta-9-THC) and cannabidiol (CBD), the two major derivatives of cannabis sativa, little is known about the effects of these cannabinoids on the functional connectivity between these regions. We investigated this in healthy occasional cannabis users by employing event-related functional magnetic resonance imaging (fMRI) following oral administration of delta-9-THC, CBD, or a placebo capsule. Employing a seed cluster-based functional connectivity analysis that involved using the average time series from each seed cluster for a whole-brain correlational analysis, we investigated the effect of drug condition on functional connectivity between the seed clusters and the rest of the brain during an oddball salience processing task. Relative to the placebo condition, delta-9-THC and CBD had opposite effects on the functional connectivity between the dorsal striatum, the prefrontal cortex, and the hippocampus. Delta-9-THC reduced fronto-striatal connectivity, which was related to its effect on task performance, whereas this connection was enhanced by CBD. Conversely, mediotemporal-prefrontal connectivity was enhanced by delta-9-THC and reduced by CBD. Our results suggest that the functional integration of brain regions involved in salience processing is differentially modulated by single doses of delta-9-THC and CBD and that this relates to the processing of salient stimuli.

Nicotine effects on brain function and functional connectivity in schizophrenia.

PubMed

Jacobsen, Leslie K; D'Souza, D Cyril; Mencl, W Einar; Pugh, Kenneth R; Skudlarski, Pawel; Krystal, John H

2004-04-15

Nicotine in tobacco smoke can improve functioning in multiple cognitive domains. High rates of smoking among schizophrenic patients may reflect an effort to remediate cognitive dysfunction. Our primary aim was to determine whether nicotine improves cognitive function by facilitating activation of brain regions mediating task performance or by facilitating functional connectivity. Thirteen smokers with schizophrenia and 13 smokers with no mental illness were withdrawn from tobacco and underwent functional magnetic resonance imaging (fMRI) scanning twice, once after placement of a placebo patch and once after placement of a nicotine patch. During scanning, subjects performed an n-back task with two levels of working memory load and of selective attention load. During the most difficult (dichotic 2-back) task condition, nicotine improved performance of schizophrenic subjects and worsened performance of control subjects. Nicotine also enhanced activation of a network of regions, including anterior cingulate cortex and bilateral thalamus, and modulated thalamocortical functional connectivity to a greater degree in schizophrenic than in control subjects during dichotic 2-back task performance. In tasks that tax working memory and selective attention, nicotine may improve performance in schizophrenia patients by enhancing activation of and functional connectivity between brain regions that mediate task performance.

Neural basis of exertional fatigue in the heat: A review of magnetic resonance imaging methods.

PubMed

Tan, X R; Low, I C C; Stephenson, M C; Soong, T W; Lee, J K W

2018-03-01

The central nervous system, specifically the brain, is implicated in the development of exertional fatigue under a hot environment. Diverse neuroimaging techniques have been used to visualize the brain activity during or after exercise. Notably, the use of magnetic resonance imaging (MRI) has become prevalent due to its excellent spatial resolution and versatility. This review evaluates the significance and limitations of various brain MRI techniques in exercise studies-brain volumetric analysis, functional MRI, functional connectivity MRI, and arterial spin labeling. The review aims to provide a summary on the neural basis of exertional fatigue and proposes future directions for brain MRI studies. A systematic literature search was performed where a total of thirty-seven brain MRI studies associated with exercise, fatigue, or related physiological factors were reviewed. The findings suggest that with moderate dehydration, there is a decrease in total brain volume accompanied with expansion of ventricular volume. With exercise fatigue, there is increased activation of sensorimotor and cognitive brain areas, increased thalamo-insular activation and decreased interhemispheric connectivity in motor cortex. Under passive hyperthermia, there are regional changes in cerebral perfusion, a reduction in local connectivity in functional brain networks and an impairment to executive function. Current literature suggests that the brain structure and function are influenced by exercise, fatigue, and related physiological perturbations. However, there is still a dearth of knowledge and it is hoped that through understanding of MRI advantages and limitations, future studies will shed light on the central origin of exertional fatigue in the heat. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

A New Approach to Investigate the Association between Brain Functional Connectivity and Disease Characteristics of Attention-Deficit/Hyperactivity Disorder: Topological Neuroimaging Data Analysis.

PubMed

Kyeong, Sunghyon; Park, Seonjeong; Cheon, Keun-Ah; Kim, Jae-Jin; Song, Dong-Ho; Kim, Eunjoo

2015-01-01

Attention-deficit/hyperactivity disorder (ADHD) is currently diagnosed by a diagnostic interview, mainly based on subjective reports from parents or teachers. It is necessary to develop methods that rely on objectively measureable neurobiological data to assess brain-behavior relationship in patients with ADHD. We investigated the application of a topological data analysis tool, Mapper, to analyze the brain functional connectivity data from ADHD patients. To quantify the disease severity using the neuroimaging data, the decomposition of individual functional networks into normal and disease components by the healthy state model (HSM) was performed, and the magnitude of the disease component (MDC) was computed. Topological data analysis using Mapper was performed to distinguish children with ADHD (n = 196) from typically developing controls (TDC) (n = 214). In the topological data analysis, the partial clustering results of patients with ADHD and normal subjects were shown in a chain-like graph. In the correlation analysis, the MDC showed a significant increase with lower intelligence scores in TDC. We also found that the rates of comorbidity in ADHD significantly increased when the deviation of the functional connectivity from HSM was large. In addition, a significant correlation between ADHD symptom severity and MDC was found in part of the dataset. The application of HSM and topological data analysis methods in assessing the brain functional connectivity seem to be promising tools to quantify ADHD symptom severity and to reveal the hidden relationship between clinical phenotypic variables and brain connectivity.

Alterations in Brain Structure and Functional Connectivity in Alcohol Dependent Patients and Possible Association with Impulsivity.

PubMed

Wang, Junkai; Fan, Yunli; Dong, Yue; Ma, Mengying; Ma, Yi; Dong, Yuru; Niu, Yajuan; Jiang, Yin; Wang, Hong; Wang, Zhiyan; Wu, Liuzhen; Sun, Hongqiang; Cui, Cailian

2016-01-01

Previous studies have documented that heightened impulsivity likely contributes to the development and maintenance of alcohol use disorders. However, there is still a lack of studies that comprehensively detected the brain changes associated with abnormal impulsivity in alcohol addicts. This study was designed to investigate the alterations in brain structure and functional connectivity associated with abnormal impulsivity in alcohol dependent patients. Brain structural and functional magnetic resonance imaging data as well as impulsive behavior data were collected from 20 alcohol dependent patients and 20 age- and sex-matched healthy controls respectively. Voxel-based morphometry was used to investigate the differences of grey matter volume, and tract-based spatial statistics was used to detect abnormal white matter regions between alcohol dependent patients and healthy controls. The alterations in resting-state functional connectivity in alcohol dependent patients were examined using selected brain areas with gray matter deficits as seed regions. Compared with healthy controls, alcohol dependent patients had significantly reduced gray matter volume in the mesocorticolimbic system including the dorsal posterior cingulate cortex, the dorsal anterior cingulate cortex, the medial prefrontal cortex, the orbitofrontal cortex and the putamen, decreased fractional anisotropy in the regions connecting the damaged grey matter areas driven by higher radial diffusivity value in the same areas and decreased resting-state functional connectivity within the reward network. Moreover, the gray matter volume of the left medial prefrontal cortex exhibited negative correlations with various impulse indices. These findings suggest that chronic alcohol dependence could cause a complex neural changes linked to abnormal impulsivity.

Greater widespread functional connectivity of the caudate in older adults who practice kripalu yoga and vipassana meditation than in controls

PubMed Central

Gard, Tim; Taquet, Maxime; Dixit, Rohan; Hölzel, Britta K.; Dickerson, Bradford C.; Lazar, Sara W.

2015-01-01

There has been a growing interest in understanding how contemplative practices affect brain functional organization. However, most studies have restricted their exploration to predefined networks. Furthermore, scientific comparisons of different contemplative traditions are largely lacking. Here we explored differences in whole brain resting state functional connectivity between experienced yoga practitioners, experienced meditators, and matched controls. Analyses were repeated in an independent sample of experienced meditators and matched controls. Analyses utilizing Network-Based Statistics (Zalesky et al., 2010) revealed difference components for yoga practitioners > controls and meditators > controls in which the right caudate was a central node. Follow up analyses revealed that yoga practitioners and meditators had significantly greater degree centrality in the caudate than controls. This greater degree centrality was not driven by single connections but by greater connectivity between the caudate and numerous brain regions. Findings of greater caudate connectivity in meditators than in controls was replicated in an independent dataset. These findings suggest that yoga and meditation practitioners have stronger functional connectivity within basal ganglia cortico-thalamic feedback loops than non-practitioners. Although we could not provide evidence for its mechanistic role, this greater connectivity might be related to the often reported effects of meditation and yoga on behavioral flexibility, mental health, and well-being. PMID:25852521

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.

Distinct phasic and sustained brain responses and connectivity of amygdala and bed nucleus of the stria terminalis during threat anticipation in panic disorder.

PubMed

Brinkmann, L; Buff, C; Feldker, K; Tupak, S V; Becker, M P I; Herrmann, M J; Straube, T

2017-11-01

Panic disorder (PD) patients are constantly concerned about future panic attacks and exhibit general hypersensitivity to unpredictable threat. We aimed to reveal phasic and sustained brain responses and functional connectivity of the amygdala and the bed nucleus of the stria terminalis (BNST) during threat anticipation in PD. Using functional magnetic resonance imaging (fMRI), we investigated 17 PD patients and 19 healthy controls (HC) during anticipation of temporally unpredictable aversive and neutral sounds. We used a phasic and sustained analysis model to disentangle temporally dissociable brain activations. PD patients compared with HC showed phasic amygdala and sustained BNST responses during anticipation of aversive v. neutral stimuli. Furthermore, increased phasic activation was observed in anterior cingulate cortex (ACC), insula and prefrontal cortex (PFC). Insula and PFC also showed sustained activation. Functional connectivity analyses revealed partly distinct phasic and sustained networks. We demonstrate a role for the BNST during unpredictable threat anticipation in PD and provide first evidence for dissociation between phasic amygdala and sustained BNST activation and their functional connectivity. In line with a hypersensitivity to uncertainty in PD, our results suggest time-dependent involvement of brain regions related to fear and anxiety.

Cognitive Enhancement Therapy Improves Resting-State Functional Connectivity in Early Course Schizophrenia

PubMed Central

Eack, Shaun M.; Newhill, Christina E.; Keshavan, Matcheri S.

2016-01-01

Objective Cognitive remediation is emerging as an effective psychosocial intervention for addressing untreated cognitive and functional impairments in persons with schizophrenia, and might achieve its benefits through neuroplastic changes in brain connectivity. This study seeks to examine the effects of cognitive enhancement therapy (CET) on fronto-temporal brain connectivity in a randomized controlled trial with individuals in the early course of schizophrenia. Method Stabilized, early course outpatients with schizophrenia or schizoaffective disorder (N = 41) were randomly assigned to CET (n = 25) or an active enriched supportive therapy (EST) control (n = 16) and treated for 2 years. Functional MRI data were collected annually, and pseudo resting-state functional connectivity analysis was used to examine differential changes in fronto-temporal connectivity between those treated with CET compared with EST. Results Individuals receiving CET evidenced significantly less functional connectivity loss between the resting-state network and the left dorsolateral prefrontal cortex as well as significantly increased connectivity with the right insular cortex compared to EST (all corrected p < .01). These neural networks are involved in emotion processing and problem-solving. Increased connectivity with the right insula significantly mediated CET effects on improved emotion perception (z′ = −1.96, p = .021), and increased connectivity with the left dorsolateral prefrontal cortex mediated CET-related improvements in emotion regulation (z′ = −1.71, p = .052). Conclusions These findings provide preliminary evidence that CET, a psychosocial cognitive remediation intervention, may enhance connectivity between frontal and temporal brain regions implicated in problem-solving and emotion processing in service of cognitive enhancement in schizophrenia. PMID:27713804

Aberrant patterns of local and long-range functional connectivity densities in schizophrenia

PubMed Central

Tian, Hongjun; Li, Jie; Qu, Hongru; Cheng, Langlang; Zhu, Jingjing; Zhuo, Chuanjun

2017-01-01

Schizophrenia is a disorder of brain dysconnectivity, and both the connection strength and connection number are disrupted in patients with schizophrenia. The functional connectivity density (FCD) can reflect alterations in the connection number. Alterations in the global FCD (gFCD) in schizophrenia were previously demonstrated; however, alterations in two other indices of the pathological characteristics of the brain, local FCD (lFCD) and long-range FCD (lrFCD), have not been revealed. To investigate lFCD and lrFCD alterations in patients with schizophrenia, 95 patients and 93 matched healthy controls were examined using structural and resting-state functional magnetic resonance imaging scanning. lFCD and lrFCD were measured using FCD mapping, and differences were identified using a two-sample t-test in a voxel-wise manner, with age and gender considered to increase variability. Multiple comparisons were performed using a false discovery rate method with a corrected threshold of P<0.05. Our analysis showed that lFCD was primarily decreased in the postcentral gyrus, right calcarine sulcus, and inferior occipital gyrus lobule, but increased in the bilateral subcortical regions. The differences in lFCD were more pronounced and complicated than those in lrFCD. In summary, in contrast with previous studies that focused on the connection strength, our findings, from the perspective of connection number, indicate that schizophrenia is a disorder of brain dysconnectivity, particularly affecting the local functional connectivity network, and support the hypothesis that schizophrenia is associated with a widespread cortical functional connectivity/activity deficit, with hyper- and/or hypo-connectivity/activity coexisting in some cortical or subcortical regions. PMID:28654893

Aberrant patterns of local and long-range functional connectivity densities in schizophrenia.

PubMed

Liu, Chuanxin; Zhang, Wei; Chen, Guangdong; Tian, Hongjun; Li, Jie; Qu, Hongru; Cheng, Langlang; Zhu, Jingjing; Zhuo, Chuanjun

2017-07-18

Schizophrenia is a disorder of brain dysconnectivity, and both the connection strength and connection number are disrupted in patients with schizophrenia. The functional connectivity density (FCD) can reflect alterations in the connection number. Alterations in the global FCD (gFCD) in schizophrenia were previously demonstrated; however, alterations in two other indices of the pathological characteristics of the brain, local FCD (lFCD) and long-range FCD (lrFCD), have not been revealed. To investigate lFCD and lrFCD alterations in patients with schizophrenia, 95 patients and 93 matched healthy controls were examined using structural and resting-state functional magnetic resonance imaging scanning. lFCD and lrFCD were measured using FCD mapping, and differences were identified using a two-sample t-test in a voxel-wise manner, with age and gender considered to increase variability. Multiple comparisons were performed using a false discovery rate method with a corrected threshold of P<0.05. Our analysis showed that lFCD was primarily decreased in the postcentral gyrus, right calcarine sulcus, and inferior occipital gyrus lobule, but increased in the bilateral subcortical regions. The differences in lFCD were more pronounced and complicated than those in lrFCD. In summary, in contrast with previous studies that focused on the connection strength, our findings, from the perspective of connection number, indicate that schizophrenia is a disorder of brain dysconnectivity, particularly affecting the local functional connectivity network, and support the hypothesis that schizophrenia is associated with a widespread cortical functional connectivity/activity deficit, with hyper- and/or hypo-connectivity/activity coexisting in some cortical or subcortical regions.

Differences between child and adult large-scale functional brain networks for reading tasks.

PubMed

Liu, Xin; Gao, Yue; Di, Qiqi; Hu, Jiali; Lu, Chunming; Nan, Yun; Booth, James R; Liu, Li

2018-02-01

Reading is an important high-level cognitive function of the human brain, requiring interaction among multiple brain regions. Revealing differences between children's large-scale functional brain networks for reading tasks and those of adults helps us to understand how the functional network changes over reading development. Here we used functional magnetic resonance imaging data of 17 adults (19-28 years old) and 16 children (11-13 years old), and graph theoretical analyses to investigate age-related changes in large-scale functional networks during rhyming and meaning judgment tasks on pairs of visually presented Chinese characters. We found that: (1) adults had stronger inter-regional connectivity and nodal degree in occipital regions, while children had stronger inter-regional connectivity in temporal regions, suggesting that adults rely more on visual orthographic processing whereas children rely more on auditory phonological processing during reading. (2) Only adults showed between-task differences in inter-regional connectivity and nodal degree, whereas children showed no task differences, suggesting the topological organization of adults' reading network is more specialized. (3) Children showed greater inter-regional connectivity and nodal degree than adults in multiple subcortical regions; the hubs in children were more distributed in subcortical regions while the hubs in adults were more distributed in cortical regions. These findings suggest that reading development is manifested by a shift from reliance on subcortical to cortical regions. Taken together, our study suggests that Chinese reading development is supported by developmental changes in brain connectivity properties, and some of these changes may be domain-general while others may be specific to the reading domain. © 2017 Wiley Periodicals, Inc.

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.

Brain dynamics of post-task resting state are influenced by expertise: Insights from baseball players.

PubMed

Muraskin, Jordan; Dodhia, Sonam; Lieberman, Gregory; Garcia, Javier O; Verstynen, Timothy; Vettel, Jean M; Sherwin, Jason; Sajda, Paul

2016-12-01

Post-task resting state dynamics can be viewed as a task-driven state where behavioral performance is improved through endogenous, non-explicit learning. Tasks that have intrinsic value for individuals are hypothesized to produce post-task resting state dynamics that promote learning. We measured simultaneous fMRI/EEG and DTI in Division-1 collegiate baseball players and compared to a group of controls, examining differences in both functional and structural connectivity. Participants performed a surrogate baseball pitch Go/No-Go task before a resting state scan, and we compared post-task resting state connectivity using a seed-based analysis from the supplementary motor area (SMA), an area whose activity discriminated players and controls in our previous results using this task. Although both groups were equally trained on the task, the experts showed differential activity in their post-task resting state consistent with motor learning. Specifically, we found (1) differences in bilateral SMA-L Insula functional connectivity between experts and controls that may reflect group differences in motor learning, (2) differences in BOLD-alpha oscillation correlations between groups suggests variability in modulatory attention in the post-task state, and (3) group differences between BOLD-beta oscillations that may indicate cognitive processing of motor inhibition. Structural connectivity analysis identified group differences in portions of the functionally derived network, suggesting that functional differences may also partially arise from variability in the underlying white matter pathways. Generally, we find that brain dynamics in the post-task resting state differ as a function of subject expertise and potentially result from differences in both functional and structural connectivity. Hum Brain Mapp 37:4454-4471, 2016. © 2016 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc. © 2016 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

A computational study of whole-brain connectivity in resting state and task fMRI

PubMed Central

Goparaju, Balaji; Rana, Kunjan D.; Calabro, Finnegan J.; Vaina, Lucia Maria

2014-01-01

Background We compared the functional brain connectivity produced during resting-state in which subjects were not actively engaged in a task with that produced while they actively performed a visual motion task (task-state). Material/Methods In this paper we employed graph-theoretical measures and network statistics in novel ways to compare, in the same group of human subjects, functional brain connectivity during resting-state fMRI with brain connectivity during performance of a high level visual task. We performed a whole-brain connectivity analysis to compare network statistics in resting and task states among anatomically defined Brodmann areas to investigate how brain networks spanning the cortex changed when subjects were engaged in task performance. Results In the resting state, we found strong connectivity among the posterior cingulate cortex (PCC), precuneus, medial prefrontal cortex (MPFC), lateral parietal cortex, and hippocampal formation, consistent with previous reports of the default mode network (DMN). The connections among these areas were strengthened while subjects actively performed an event-related visual motion task, indicating a continued and strong engagement of the DMN during task processing. Regional measures such as degree (number of connections) and betweenness centrality (number of shortest paths), showed that task performance induces stronger inter-regional connections, leading to a denser processing network, but that this does not imply a more efficient system as shown by the integration measures such as path length and global efficiency, and from global measures such as small-worldness. Conclusions In spite of the maintenance of connectivity and the “hub-like” behavior of areas, our results suggest that the network paths may be rerouted when performing the task condition. PMID:24947491

Effective brain network analysis with resting-state EEG data: a comparison between heroin abstinent and non-addicted subjects

NASA Astrophysics Data System (ADS)

Hu, Bin; Dong, Qunxi; Hao, Yanrong; Zhao, Qinglin; Shen, Jian; Zheng, Fang

2017-08-01

Objective. Neuro-electrophysiological tools have been widely used in heroin addiction studies. Previous studies indicated that chronic heroin abuse would result in abnormal functional organization of the brain, while few heroin addiction studies have applied the effective connectivity tool to analyze the brain functional system (BFS) alterations induced by heroin abuse. The present study aims to identify the abnormality of resting-state heroin abstinent BFS using source decomposition and effective connectivity tools. Approach. The resting-state electroencephalograph (EEG) signals were acquired from 15 male heroin abstinent (HA) subjects and 14 male non-addicted (NA) controls. Multivariate autoregressive models combined independent component analysis (MVARICA) was applied for blind source decomposition. Generalized partial directed coherence (GPDC) was applied for effective brain connectivity analysis. Effective brain networks of both HA and NA groups were constructed. The two groups of effective cortical networks were compared by the bootstrap method. Abnormal causal interactions between decomposed source regions were estimated in the 1-45 Hz frequency domain. Main results. This work suggested: (a) there were clear effective network alterations in heroin abstinent subject groups; (b) the parietal region was a dominant hub of the abnormally weaker causal pathways, and the left occipital region was a dominant hub of the abnormally stronger causal pathways. Significance. These findings provide direct evidence that chronic heroin abuse induces brain functional abnormalities. The potential value of combining effective connectivity analysis and brain source decomposition methods in exploring brain alterations of heroin addicts is also implied.

Effective brain network analysis with resting-state EEG data: a comparison between heroin abstinent and non-addicted subjects.

PubMed

Hu, Bin; Dong, Qunxi; Hao, Yanrong; Zhao, Qinglin; Shen, Jian; Zheng, Fang

2017-08-01

Neuro-electrophysiological tools have been widely used in heroin addiction studies. Previous studies indicated that chronic heroin abuse would result in abnormal functional organization of the brain, while few heroin addiction studies have applied the effective connectivity tool to analyze the brain functional system (BFS) alterations induced by heroin abuse. The present study aims to identify the abnormality of resting-state heroin abstinent BFS using source decomposition and effective connectivity tools. The resting-state electroencephalograph (EEG) signals were acquired from 15 male heroin abstinent (HA) subjects and 14 male non-addicted (NA) controls. Multivariate autoregressive models combined independent component analysis (MVARICA) was applied for blind source decomposition. Generalized partial directed coherence (GPDC) was applied for effective brain connectivity analysis. Effective brain networks of both HA and NA groups were constructed. The two groups of effective cortical networks were compared by the bootstrap method. Abnormal causal interactions between decomposed source regions were estimated in the 1-45 Hz frequency domain. This work suggested: (a) there were clear effective network alterations in heroin abstinent subject groups; (b) the parietal region was a dominant hub of the abnormally weaker causal pathways, and the left occipital region was a dominant hub of the abnormally stronger causal pathways. These findings provide direct evidence that chronic heroin abuse induces brain functional abnormalities. The potential value of combining effective connectivity analysis and brain source decomposition methods in exploring brain alterations of heroin addicts is also implied.

Statistical inference of dynamic resting-state functional connectivity using hierarchical observation modeling.

PubMed

Sojoudi, Alireza; Goodyear, Bradley G

2016-12-01

Spontaneous fluctuations of blood-oxygenation level-dependent functional magnetic resonance imaging (BOLD fMRI) signals are highly synchronous between brain regions that serve similar functions. This provides a means to investigate functional networks; however, most analysis techniques assume functional connections are constant over time. This may be problematic in the case of neurological disease, where functional connections may be highly variable. Recently, several methods have been proposed to determine moment-to-moment changes in the strength of functional connections over an imaging session (so called dynamic connectivity). Here a novel analysis framework based on a hierarchical observation modeling approach was proposed, to permit statistical inference of the presence of dynamic connectivity. A two-level linear model composed of overlapping sliding windows of fMRI signals, incorporating the fact that overlapping windows are not independent was described. To test this approach, datasets were synthesized whereby functional connectivity was either constant (significant or insignificant) or modulated by an external input. The method successfully determines the statistical significance of a functional connection in phase with the modulation, and it exhibits greater sensitivity and specificity in detecting regions with variable connectivity, when compared with sliding-window correlation analysis. For real data, this technique possesses greater reproducibility and provides a more discriminative estimate of dynamic connectivity than sliding-window correlation analysis. Hum Brain Mapp 37:4566-4580, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Brain Modulyzer: Interactive Visual Analysis of Functional Brain Connectivity

DOE PAGES

Murugesan, Sugeerth; Bouchard, Kristopher; Brown, Jesse A.; ...

2016-05-09

Here, we present Brain Modulyzer, an interactive visual exploration tool for functional magnetic resonance imaging (fMRI) brain scans, aimed at analyzing the correlation between different brain regions when resting or when performing mental tasks. Brain Modulyzer combines multiple coordinated views—such as heat maps, node link diagrams, and anatomical views—using brushing and linking to provide an anatomical context for brain connectivity data. Integrating methods from graph theory and analysis, e.g., community detection and derived graph measures, makes it possible to explore the modular and hierarchical organization of functional brain networks. Providing immediate feedback by displaying analysis results instantaneously while changing parametersmore » gives neuroscientists a powerful means to comprehend complex brain structure more effectively and efficiently and supports forming hypotheses that can then be validated via statistical analysis. In order to demonstrate the utility of our tool, we also present two case studies—exploring progressive supranuclear palsy, as well as memory encoding and retrieval« less

Brain Modulyzer: Interactive Visual Analysis of Functional Brain Connectivity

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

Murugesan, Sugeerth; Bouchard, Kristopher; Brown, Jesse A.

Here, we present Brain Modulyzer, an interactive visual exploration tool for functional magnetic resonance imaging (fMRI) brain scans, aimed at analyzing the correlation between different brain regions when resting or when performing mental tasks. Brain Modulyzer combines multiple coordinated views—such as heat maps, node link diagrams, and anatomical views—using brushing and linking to provide an anatomical context for brain connectivity data. Integrating methods from graph theory and analysis, e.g., community detection and derived graph measures, makes it possible to explore the modular and hierarchical organization of functional brain networks. Providing immediate feedback by displaying analysis results instantaneously while changing parametersmore » gives neuroscientists a powerful means to comprehend complex brain structure more effectively and efficiently and supports forming hypotheses that can then be validated via statistical analysis. In order to demonstrate the utility of our tool, we also present two case studies—exploring progressive supranuclear palsy, as well as memory encoding and retrieval« less

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

Convergent Findings of Altered Functional and Structural Brain Connectivity in Individuals with High Functioning Autism: A Multimodal MRI Study

PubMed Central

Samson, Andrea C.; Kirsch, Valerie; Blautzik, Janusch; Grothe, Michel; Erat, Okan; Hegenloh, Michael; Coates, Ute; Reiser, Maximilian F.; Hennig-Fast, Kristina; Meindl, Thomas

2013-01-01

Brain tissue changes in autism spectrum disorders seem to be rather subtle and widespread than anatomically distinct. Therefore a multimodal, whole brain imaging technique appears to be an appropriate approach to investigate whether alterations in white and gray matter integrity relate to consistent changes in functional resting state connectivity in individuals with high functioning autism (HFA). We applied diffusion tensor imaging (DTI), voxel-based morphometry (VBM) and resting state functional connectivity magnetic resonance imaging (fcMRI) to assess differences in brain structure and function between 12 individuals with HFA (mean age 35.5, SD 11.4, 9 male) and 12 healthy controls (mean age 33.3, SD 9.0, 8 male). Psychological measures of empathy and emotionality were obtained and correlated with the most significant DTI, VBM and fcMRI findings. We found three regions of convergent structural and functional differences between HFA participants and controls. The right temporo-parietal junction area and the left frontal lobe showed decreased fractional anisotropy (FA) values along with decreased functional connectivity and a trend towards decreased gray matter volume. The bilateral superior temporal gyrus displayed significantly decreased functional connectivity that was accompanied by the strongest trend of gray matter volume decrease in the temporal lobe of HFA individuals. FA decrease in the right temporo-parietal region was correlated with psychological measurements of decreased emotionality. In conclusion, our results indicate common sites of structural and functional alterations in higher order association cortex areas and may therefore provide multimodal imaging support to the long-standing hypothesis of autism as a disorder of impaired higher-order multisensory integration. PMID:23825652

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.

Effective connectivity of facial expression network by using Granger causality analysis

NASA Astrophysics Data System (ADS)

Zhang, Hui; Li, Xiaoting

2013-10-01

Functional magnetic resonance imaging (fMRI) is an advanced non-invasive data acquisition technique to investigate the neural activity in human brain. In addition to localize the functional brain regions that is activated by specific cognitive task, fMRI can also be utilized to measure the task-related functional interactions among the active regions of interest (ROI) in the brain. Among the variety of analysis tools proposed for modeling the connectivity of brain regions, Granger causality analysis (GCA) measure the directions of information interactions by looking for the lagged effect among the brain regions. In this study, we use fMRI and Granger Causality analysis to investigate the effective connectivity of brain network induced by viewing several kinds of expressional faces. We focus on four kinds of facial expression stimuli: fearful, angry, happy and neutral faces. Five face selective regions of interest are localized and the effective connectivity within these regions is measured for the expressional faces. Our result based on 8 subjects showed that there is significant effective connectivity from STS to amygdala, from amygdala to OFA, aFFA and pFFA, from STS to aFFA and from pFFA to aFFA. This result suggested that there is an information flow from the STS to the amygdala when perusing expressional faces. This emotional expressional information flow that is conveyed by STS and amygdala, flow back to the face selective regions in occipital-temporal lobes, which constructed a emotional face processing network.

Resting state electrical brain activity and connectivity in fibromyalgia

PubMed Central

Vanneste, Sven; Ost, Jan; Van Havenbergh, Tony; De Ridder, Dirk

2017-01-01

The exact mechanism underlying fibromyalgia is unknown, but increased facilitatory modulation and/or dysfunctional descending inhibitory pathway activity are posited as possible mechanisms contributing to sensitization of the central nervous system. The primary goal of this study is to identify a fibromyalgia neural circuit that can account for these abnormalities in central pain. The second goal is to gain a better understanding of the functional connectivity between the default and the executive attention network (salience network plus dorsal lateral prefrontal cortex) in fibromyalgia. We examine neural activity associated with fibromyalgia (N = 44) and compare these with healthy controls (N = 44) using resting state source localized EEG. Our data support an important role of the pregenual anterior cingulate cortex but also suggest that the degree of activation and the degree of integration between different brain areas is important. The inhibition of the connectivity between the dorsal lateral prefrontal cortex and the posterior cingulate cortex on the pain inhibitory pathway seems to be limited by decreased functional connectivity with the pregenual anterior cingulate cortex. Our data highlight the functional dynamics of brain regions integrated in brain networks in fibromyalgia patients. PMID:28650974

Intrinsic functional connectivity alterations in progressive supranuclear palsy: Differential effects in frontal cortex, motor, and midbrain networks.

PubMed

Rosskopf, Johannes; Gorges, Martin; Müller, Hans-Peter; Lulé, Dorothée; Uttner, Ingo; Ludolph, Albert C; Pinkhardt, Elmar; Juengling, Freimut D; Kassubek, Jan

2017-07-01

The topography of functional network changes in progressive supranuclear palsy can be mapped by intrinsic functional connectivity MRI. The objective of this study was to study functional connectivity and its clinical and behavioral correlates in dedicated networks comprising the cognition-related default mode and the motor and midbrain functional networks in patients with PSP. Whole-brain-based "resting-state" functional MRI and high-resolution T1-weighted magnetic resonance imaging data together with neuropsychological and video-oculographic data from 34 PSP patients (22 with Richardson subtype and 12 with parkinsonian subtype) and 35 matched healthy controls were subjected to network-based functional connectivity and voxel-based morphometry analysis. After correction for global patterns of brain atrophy, the group comparison between PSP patients and controls revealed significantly decreased functional connectivity (P < 0.05, corrected) in the prefrontal cortex, which was significantly correlated with cognitive performance (P = 0.006). Of note, midbrain network connectivity in PSP patients showed increased connectivity with the thalamus, on the one hand, whereas, on the other hand, lower functional connectivity within the midbrain was significantly correlated with vertical gaze impairment, as quantified by video-oculography (P = 0.004). PSP Richardson subtype showed significantly increased functional motor network connectivity with the medial prefrontal gyrus. PSP-associated neurodegeneration was attributed to both decreased and increased functional connectivity. Decreasing functional connectivity was associated with worse behavioral performance (ie, dementia severity and gaze palsy), whereas the pattern of increased functional connectivity may be a potential adaptive mechanism. © 2017 International Parkinson and Movement Disorder Society. © 2017 International Parkinson and Movement Disorder Society.

Examining frontotemporal connectivity and rTMS in healthy controls: implications for auditory hallucinations in schizophrenia.

PubMed

Gromann, Paula M; Tracy, Derek K; Giampietro, Vincent; Brammer, Michael J; Krabbendam, Lydia; Shergill, Sukhwinder S

2012-01-01

Repetitive transcranial magnetic stimulation (rTMS) has been shown to have clinically beneficial effects in altering the perception of auditory hallucinations (AH) in patients with schizophrenia. However, the mode of action is not clear. Recent neuroimaging findings indicate that rTMS has the potential to induce not only local effects but also changes in remote, functionally connected brain regions. Frontotemporal dysconnectivity has been proposed as a mechanism leading to psychotic symptoms in schizophrenia. The current study examines functional connectivity between temporal and frontal brain regions after rTMS and the implications for AH in schizophrenia. A connectivity analysis was conducted on the fMRI data of 11 healthy controls receiving rTMS, compared with 11 matched subjects receiving sham TMS, to the temporoparietal junction, before engaging in a task associated with robust frontotemporal activation. Compared to the control group, the rTMS group showed an altered frontotemporal connectivity with stronger connectivity between the right temporoparietal cortex and the dorsolateral prefrontal cortex and the angular gyrus. This finding provides preliminary evidence for the hypothesis that normalizing the functional connectivity between the temporoparietal and frontal brain regions may underlie the therapeutic effect of rTMS on AH in schizophrenia.

Sex and disease-related alterations of anterior insula functional connectivity in chronic abdominal pain.

PubMed

Hong, Jui-Yang; Kilpatrick, Lisa A; Labus, Jennifer S; Gupta, Arpana; Katibian, David; Ashe-McNalley, Cody; Stains, Jean; Heendeniya, Nuwanthi; Smith, Suzanne R; Tillisch, Kirsten; Naliboff, Bruce; Mayer, Emeran A

2014-10-22

Resting-state functional magnetic resonance imaging has been used to investigate intrinsic brain connectivity in healthy subjects and patients with chronic pain. Sex-related differences in the frequency power distribution within the human insula (INS), a brain region involved in the integration of interoceptive, affective, and cognitive influences, have been reported. Here we aimed to test sex and disease-related alterations in the intrinsic functional connectivity of the dorsal anterior INS. The anterior INS is engaged during goal-directed tasks and modulates the default mode and executive control networks. By comparing functional connectivity of the dorsal anterior INS in age-matched female and male healthy subjects and patients with irritable bowel syndrome (IBS), a common chronic abdominal pain condition, we show evidence for sex and disease-related alterations in the functional connectivity of this region: (1) male patients compared with female patients had increased positive connectivity of the dorsal anterior INS bilaterally with the medial prefrontal cortex (PFC) and dorsal posterior INS; (2) female patients compared with male patients had greater negative connectivity of the left dorsal anterior INS with the left precuneus; (3) disease-related differences in the connectivity between the bilateral dorsal anterior INS and the dorsal medial PFC were observed in female subjects; and (4) clinical characteristics were significantly correlated to the insular connectivity with the dorsal medial PFC in male IBS subjects and with the precuneus in female IBS subjects. These findings are consistent with the INS playing an important role in modulating the intrinsic functional connectivity of major networks in the resting brain and show that this role is influenced by sex and diagnosis. Copyright © 2014 the authors 0270-6474/14/3414252-08$15.00/0.

The Effects of Taekwondo Training on Brain Connectivity and Body Intelligence.

PubMed

Kim, Young Jae; Cha, Eun Joo; Kim, Sun Mi; Kang, Kyung Doo; Han, Doug Hyun

2015-07-01

Many studies have reported that Taekwondo training could improve body perception, control and brain activity, as assessed with an electroencephalogram. This study aimed to assess body intelligence and brain connectivity in children with Taekwondo training as compared to children without Taekwondo training. Fifteen children with Taekwondo training (TKD) and 13 age- and sex-matched children who had no previous experience of Taekwondo training (controls) were recruited. Body intelligence, clinical characteristics and brain connectivity in all children were assessed with the Body Intelligence Scale (BIS), self-report, and resting state functional magnetic resonance imaging. The mean BIS score in the TKD group was higher than that in the control group. The TKD group showed increased low-frequency fluctuations in the right frontal precentral gyrus and the right parietal precuneus, compared to the control group. The TKD group showed positive cerebellum vermis (lobe VII) seed to the right frontal, left frontal, and left parietal lobe. The control group showed positive cerebellum seed to the left frontal, parietal, and occipital cortex. Relative to the control group, the TKD group showed increased functional connectivity from cerebellum seed to the right inferior frontal gyrus. To the best of our knowledge, this is the first study to assess the effect of Taekwondo training on brain connectivity in children. Taekwondo training improved body intelligence and brain connectivity from the cerebellum to the parietal and frontal cortex.

Resolving anatomical and functional structure in human brain organization: identifying mesoscale organization in weighted network representations.

PubMed

Lohse, Christian; Bassett, Danielle S; Lim, Kelvin O; Carlson, Jean M

2014-10-01

Human brain anatomy and function display a combination of modular and hierarchical organization, suggesting the importance of both cohesive structures and variable resolutions in the facilitation of healthy cognitive processes. However, tools to simultaneously probe these features of brain architecture require further development. We propose and apply a set of methods to extract cohesive structures in network representations of brain connectivity using multi-resolution techniques. We employ a combination of soft thresholding, windowed thresholding, and resolution in community detection, that enable us to identify and isolate structures associated with different weights. One such mesoscale structure is bipartivity, which quantifies the extent to which the brain is divided into two partitions with high connectivity between partitions and low connectivity within partitions. A second, complementary mesoscale structure is modularity, which quantifies the extent to which the brain is divided into multiple communities with strong connectivity within each community and weak connectivity between communities. Our methods lead to multi-resolution curves of these network diagnostics over a range of spatial, geometric, and structural scales. For statistical comparison, we contrast our results with those obtained for several benchmark null models. Our work demonstrates that multi-resolution diagnostic curves capture complex organizational profiles in weighted graphs. We apply these methods to the identification of resolution-specific characteristics of healthy weighted graph architecture and altered connectivity profiles in psychiatric disease.

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.

Partial covariance based functional connectivity computation using Ledoit-Wolf covariance regularization.

PubMed

Brier, Matthew R; Mitra, Anish; McCarthy, John E; Ances, Beau M; Snyder, Abraham Z

2015-11-01

Functional connectivity refers to shared signals among brain regions and is typically assessed in a task free state. Functional connectivity commonly is quantified between signal pairs using Pearson correlation. However, resting-state fMRI is a multivariate process exhibiting a complicated covariance structure. Partial covariance assesses the unique variance shared between two brain regions excluding any widely shared variance, hence is appropriate for the analysis of multivariate fMRI datasets. However, calculation of partial covariance requires inversion of the covariance matrix, which, in most functional connectivity studies, is not invertible owing to rank deficiency. Here we apply Ledoit-Wolf shrinkage (L2 regularization) to invert the high dimensional BOLD covariance matrix. We investigate the network organization and brain-state dependence of partial covariance-based functional connectivity. Although RSNs are conventionally defined in terms of shared variance, removal of widely shared variance, surprisingly, improved the separation of RSNs in a spring embedded graphical model. This result suggests that pair-wise unique shared variance plays a heretofore unrecognized role in RSN covariance organization. In addition, application of partial correlation to fMRI data acquired in the eyes open vs. eyes closed states revealed focal changes in uniquely shared variance between the thalamus and visual cortices. This result suggests that partial correlation of resting state BOLD time series reflect functional processes in addition to structural connectivity. Copyright © 2015 Elsevier Inc. All rights reserved.

Partial covariance based functional connectivity computation using Ledoit-Wolf covariance regularization

PubMed Central

Brier, Matthew R.; Mitra, Anish; McCarthy, John E.; Ances, Beau M.; Snyder, Abraham Z.

2015-01-01

Functional connectivity refers to shared signals among brain regions and is typically assessed in a task free state. Functional connectivity commonly is quantified between signal pairs using Pearson correlation. However, resting-state fMRI is a multivariate process exhibiting a complicated covariance structure. Partial covariance assesses the unique variance shared between two brain regions excluding any widely shared variance, hence is appropriate for the analysis of multivariate fMRI datasets. However, calculation of partial covariance requires inversion of the covariance matrix, which, in most functional connectivity studies, is not invertible owing to rank deficiency. Here we apply Ledoit-Wolf shrinkage (L2 regularization) to invert the high dimensional BOLD covariance matrix. We investigate the network organization and brain-state dependence of partial covariance-based functional connectivity. Although RSNs are conventionally defined in terms of shared variance, removal of widely shared variance, surprisingly, improved the separation of RSNs in a spring embedded graphical model. This result suggests that pair-wise unique shared variance plays a heretofore unrecognized role in RSN covariance organization. In addition, application of partial correlation to fMRI data acquired in the eyes open vs. eyes closed states revealed focal changes in uniquely shared variance between the thalamus and visual cortices. This result suggests that partial correlation of resting state BOLD time series reflect functional processes in addition to structural connectivity. PMID:26208872

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

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.

The brain functional connectome is robustly altered by lack of sleep.

PubMed

Kaufmann, Tobias; Elvsåshagen, Torbjørn; Alnæs, Dag; Zak, Nathalia; Pedersen, Per Ø; Norbom, Linn B; Quraishi, Sophia H; Tagliazucchi, Enzo; Laufs, Helmut; Bjørnerud, Atle; Malt, Ulrik F; Andreassen, Ole A; Roussos, Evangelos; Duff, Eugene P; Smith, Stephen M; Groote, Inge R; Westlye, Lars T

2016-02-15

Sleep is a universal phenomenon necessary for maintaining homeostasis and function across a range of organs. Lack of sleep has severe health-related consequences affecting whole-body functioning, yet no other organ is as severely affected as the brain. The neurophysiological mechanisms underlying these deficits are poorly understood. Here, we characterize the dynamic changes in brain connectivity profiles inflicted by sleep deprivation and how they deviate from regular daily variability. To this end, we obtained functional magnetic resonance imaging data from 60 young, adult male participants, scanned in the morning and evening of the same day and again the following morning. 41 participants underwent total sleep deprivation before the third scan, whereas the remainder had another night of regular sleep. Sleep deprivation strongly altered the connectivity of several resting-state networks, including dorsal attention, default mode, and hippocampal networks. Multivariate classification based on connectivity profiles predicted deprivation state with high accuracy, corroborating the robustness of the findings on an individual level. Finally, correlation analysis suggested that morning-to-evening connectivity changes were reverted by sleep (control group)-a pattern which did not occur after deprivation. We conclude that both, a day of waking and a night of sleep deprivation dynamically alter the brain functional connectome. Copyright © 2015 Elsevier Inc. All rights reserved.

Stepwise Connectivity of the Modal Cortex Reveals the Multimodal Organization of the Human Brain

PubMed Central

Sepulcre, Jorge; Sabuncu, Mert R.; Yeo, Thomas B.; Liu, Hesheng; Johnson, Keith A.

2012-01-01

How human beings integrate information from external sources and internal cognition to produce a coherent experience is still not well understood. During the past decades, anatomical, neurophysiological and neuroimaging research in multimodal integration have stood out in the effort to understand the perceptual binding properties of the brain. Areas in the human lateral occipito-temporal, prefrontal and posterior parietal cortices have been associated with sensory multimodal processing. Even though this, rather patchy, organization of brain regions gives us a glimpse of the perceptual convergence, the articulation of the flow of information from modality-related to the more parallel cognitive processing systems remains elusive. Using a method called Stepwise Functional Connectivity analysis, the present study analyzes the functional connectome and transitions from primary sensory cortices to higher-order brain systems. We identify the large-scale multimodal integration network and essential connectivity axes for perceptual integration in the human brain. PMID:22855814

Sharing self-related information is associated with intrinsic functional connectivity of cortical midline brain regions

PubMed Central

Meshi, Dar; Mamerow, Loreen; Kirilina, Evgeniya; Morawetz, Carmen; Margulies, Daniel S.; Heekeren, Hauke R.

2016-01-01

Human beings are social animals and they vary in the degree to which they share information about themselves with others. Although brain networks involved in self-related cognition have been identified, especially via the use of resting-state experiments, the neural circuitry underlying individual differences in the sharing of self-related information is currently unknown. Therefore, we investigated the intrinsic functional organization of the brain with respect to participants’ degree of self-related information sharing using resting state functional magnetic resonance imaging and self-reported social media use. We conducted seed-based correlation analyses in cortical midline regions previously shown in meta-analyses to be involved in self-referential cognition: the medial prefrontal cortex (MPFC), central precuneus (CP), and caudal anterior cingulate cortex (CACC). We examined whether and how functional connectivity between these regions and the rest of the brain was associated with participants’ degree of self-related information sharing. Analyses revealed associations between the MPFC and right dorsolateral prefrontal cortex (DLPFC), as well as the CP with the right DLPFC, the left lateral orbitofrontal cortex and left anterior temporal pole. These findings extend our present knowledge of functional brain connectivity, specifically demonstrating how the brain’s intrinsic functional organization relates to individual differences in the sharing of self-related information. PMID:26948055

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.

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.

Multimodal mapping of the brain's functional connectivity and the adult outcome of attention deficit hyperactivity disorder.

PubMed

Sudre, Gustavo; Szekely, Eszter; Sharp, Wendy; Kasparek, Steven; Shaw, Philip

2017-10-31

We have a limited understanding of why many children with attention deficit hyperactivity disorder do not outgrow the disorder by adulthood. Around 20-30% retain the full syndrome as young adults, and about 50% show partial, rather than complete, remission. Here, to delineate the neurobiology of this variable outcome, we ask if the persistence of childhood symptoms into adulthood impacts on the brain's functional connectivity. We studied 205 participants followed clinically since childhood. In early adulthood, participants underwent magnetoencephalography (MEG) to measure neuronal activity directly and functional MRI (fMRI) to measure hemodynamic activity during a task-free period (the "resting state"). We found that symptoms of inattention persisting into adulthood were associated with disrupted patterns of typical functional connectivity in both MEG and fMRI. Specifically, those with persistent inattention lost the typical balance of connections within the default mode network (DMN; prominent during introspective thought) and connections between this network and those supporting attention and cognitive control. By contrast, adults whose childhood inattentive symptoms had resolved did not differ significantly from their never-affected peers, both hemodynamically and electrophysiologically. The anomalies in functional connectivity tied to clinically significant inattention centered on midline regions of the DMN in both MEG and fMRI, boosting confidence in a possible pathophysiological role. The findings suggest that the clinical course of this common childhood onset disorder impacts the functional connectivity of the adult brain. Published under the PNAS license.

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

Real-time interactive tractography analysis for multimodal brain visualization tool: MultiXplore

NASA Astrophysics Data System (ADS)

Bakhshmand, Saeed M.; de Ribaupierre, Sandrine; Eagleson, Roy

2017-03-01

Most debilitating neurological disorders can have anatomical origins. Yet unlike other body organs, the anatomy alone cannot easily provide an understanding of brain functionality. In fact, addressing the challenge of linking structural and functional connectivity remains in the frontiers of neuroscience. Aggregating multimodal neuroimaging datasets may be critical for developing theories that span brain functionality, global neuroanatomy and internal microstructures. Functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI) are main such techniques that are employed to investigate the brain under normal and pathological conditions. FMRI records blood oxygenation level of the grey matter (GM), whereas DTI is able to reveal the underlying structure of the white matter (WM). Brain global activity is assumed to be an integration of GM functional hubs and WM neural pathways that serve to connect them. In this study we developed and evaluated a two-phase algorithm. This algorithm is employed in a 3D interactive connectivity visualization framework and helps to accelerate clustering of virtual neural pathways. In this paper, we will detail an algorithm that makes use of an index-based membership array formed for a whole brain tractography file and corresponding parcellated brain atlas. Next, we demonstrate efficiency of the algorithm by measuring required times for extracting a variety of fiber clusters, which are chosen in such a way to resemble all sizes probable output data files that algorithm will generate. The proposed algorithm facilitates real-time visual inspection of neuroimaging data to further the discovery in structure-function relationship of the brain networks.

Lateralized Resting-State Functional Brain Network Organization Changes in Heart Failure

PubMed Central

Park, Bumhee; Roy, Bhaswati; Woo, Mary A.; Palomares, Jose A.; Fonarow, Gregg C.; Harper, Ronald M.; Kumar, Rajesh

2016-01-01

Heart failure (HF) patients show brain injury in autonomic, affective, and cognitive sites, which can change resting-state functional connectivity (FC), potentially altering overall functional brain network organization. However, the status of such connectivity or functional organization is unknown in HF. Determination of that status was the aim here, and we examined region-to-region FC and brain network topological properties across the whole-brain in 27 HF patients compared to 53 controls with resting-state functional MRI procedures. Decreased FC in HF appeared between the caudate and cerebellar regions, olfactory and cerebellar sites, vermis and medial frontal regions, and precentral gyri and cerebellar areas. However, increased FC emerged between the middle frontal gyrus and sensorimotor areas, superior parietal gyrus and orbito/medial frontal regions, inferior temporal gyrus and lingual gyrus/cerebellar lobe/pallidum, fusiform gyrus and superior orbitofrontal gyrus and cerebellar sites, and within vermis and cerebellar areas; these connections were largely in the right hemisphere (p<0.005; 10,000 permutations). The topology of functional integration and specialized characteristics in HF are significantly changed in regions showing altered FC, an outcome which would interfere with brain network organization (p<0.05; 10,000 permutations). Brain dysfunction in HF extends to resting conditions, and autonomic, cognitive, and affective deficits may stem from altered FC and brain network organization that may contribute to higher morbidity and mortality in the condition. Our findings likely result from the prominent axonal and nuclear structural changes reported earlier in HF; protecting neural tissue may improve FC integrity, and thus, increase quality of life and reduce morbidity and mortality. PMID:27203600

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.

Studying hemispheric lateralization during a Stroop task through near-infrared spectroscopy-based connectivity

NASA Astrophysics Data System (ADS)

Zhang, Lei; Sun, Jinyan; Sun, Bailei; Luo, Qingming; Gong, Hui

2014-05-01

Near-infrared spectroscopy (NIRS) is a developing and promising functional brain imaging technology. Developing data analysis methods to effectively extract meaningful information from collected data is the major bottleneck in popularizing this technology. In this study, we measured hemodynamic activity of the prefrontal cortex (PFC) during a color-word matching Stroop task using NIRS. Hemispheric lateralization was examined by employing traditional activation and novel NIRS-based connectivity analyses simultaneously. Wavelet transform coherence was used to assess intrahemispheric functional connectivity. Spearman correlation analysis was used to examine the relationship between behavioral performance and activation/functional connectivity, respectively. In agreement with activation analysis, functional connectivity analysis revealed leftward lateralization for the Stroop effect and correlation with behavioral performance. However, functional connectivity was more sensitive than activation for identifying hemispheric lateralization. Granger causality was used to evaluate the effective connectivity between hemispheres. The results showed increased information flow from the left to the right hemispheres for the incongruent versus the neutral task, indicating a leading role of the left PFC. This study demonstrates that the NIRS-based connectivity can reveal the functional architecture of the brain more comprehensively than traditional activation, helping to better utilize the advantages of NIRS.

Abnormal Neural Connectivity in Schizophrenia and fMRI-Brain-Computer Interface as a Potential Therapeutic Approach

PubMed Central

Ruiz, Sergio; Birbaumer, Niels; Sitaram, Ranganatha

2012-01-01

Considering that single locations of structural and functional abnormalities are insufficient to explain the diverse psychopathology of schizophrenia, new models have postulated that the impairments associated with the disease arise from a failure to integrate the activity of local and distributed neural circuits: the “abnormal neural connectivity hypothesis.” In the last years, new evidence coming from neuroimaging have supported and expanded this theory. However, despite the increasing evidence that schizophrenia is a disorder of neural connectivity, so far there are no treatments that have shown to produce a significant change in brain connectivity, or that have been specifically designed to alleviate this problem. Brain-Computer Interfaces based on real-time functional Magnetic Resonance Imaging (fMRI-BCI) are novel techniques that have allowed subjects to achieve self-regulation of circumscribed brain regions. In recent studies, experiments with this technology have resulted in new findings suggesting that this methodology could be used to train subjects to enhance brain connectivity, and therefore could potentially be used as a therapeutic tool in mental disorders including schizophrenia. The present article summarizes the findings coming from hemodynamics-based neuroimaging that support the abnormal connectivity hypothesis in schizophrenia, and discusses a new approach that could address this problem. PMID:23525496

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

An Update Overview on Brain Imaging Studies of Internet Gaming Disorder

PubMed Central

Weinstein, Aviv M.

2017-01-01

There are a growing number of studies on structural and functional brain mechanisms underlying Internet gaming disorder (IGD). Recent functional magnetic resonance imaging studies showed that IGD adolescents and adults had reduced gray matter volume in regions associated with attention motor coordination executive function and perception. Adolescents with IGD showed lower white matter (WM) integrity measures in several brain regions that are involved in decision-making, behavioral inhibition, and emotional regulation. IGD adolescents had also disruption in the functional connectivity in areas responsible for learning memory and executive function, processing of auditory, visual, and somatosensory stimuli and relay of sensory and motor signals. IGD adolescents also had decreased functional connectivity of PFC-striatal circuits, increased risk-taking choices, and impaired ability to control their impulses similar to other impulse control disorders. Recent studies indicated that altered executive control mechanisms in attention deficit hyperactivity disorder (ADHD) would be a predisposition for developing IGD. Finally, patients with IGD have also shown an increased functional connectivity of several executive control brain regions that may related to comorbidity with ADHD and depression. The behavioral addiction model argues that IGD shows the features of excessive use despite adverse consequences, withdrawal phenomena, and tolerance that characterize substance use disorders. The evidence supports the behavioral addiction model of IGD by showing structural and functional changes in the mechanisms of reward and craving (but not withdrawal) in IGD. Future studies need to investigate WM density and functional connectivity in IGD in order to validate these findings. Furthermore, more research is required about the similarity in neurochemical and neurocognitive brain circuits in IGD and comorbid conditions such as ADHD and depression. PMID:29033857

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.

A brain-region-based meta-analysis method utilizing the Apriori algorithm.

PubMed

Niu, Zhendong; Nie, Yaoxin; Zhou, Qian; Zhu, Linlin; Wei, Jieyao

2016-05-18

Brain network connectivity modeling is a crucial method for studying the brain's cognitive functions. Meta-analyses can unearth reliable results from individual studies. Meta-analytic connectivity modeling is a connectivity analysis method based on regions of interest (ROIs) which showed that meta-analyses could be used to discover brain network connectivity. In this paper, we propose a new meta-analysis method that can be used to find network connectivity models based on the Apriori algorithm, which has the potential to derive brain network connectivity models from activation information in the literature, without requiring ROIs. This method first extracts activation information from experimental studies that use cognitive tasks of the same category, and then maps the activation information to corresponding brain areas by using the automatic anatomical label atlas, after which the activation rate of these brain areas is calculated. Finally, using these brain areas, a potential brain network connectivity model is calculated based on the Apriori algorithm. The present study used this method to conduct a mining analysis on the citations in a language review article by Price (Neuroimage 62(2):816-847, 2012). The results showed that the obtained network connectivity model was consistent with that reported by Price. The proposed method is helpful to find brain network connectivity by mining the co-activation relationships among brain regions. Furthermore, results of the co-activation relationship analysis can be used as a priori knowledge for the corresponding dynamic causal modeling analysis, possibly achieving a significant dimension-reducing effect, thus increasing the efficiency of the dynamic causal modeling analysis.

Changes in brain-behavior relationships following a 3-month pilot cognitive intervention program for adults with traumatic brain injury.

PubMed

Porter, S; Torres, I J; Panenka, W; Rajwani, Z; Fawcett, D; Hyder, A; Virji-Babul, N

2017-08-01

Facilitating functional recovery following brain injury is a key goal of neurorehabilitation. Direct, objective measures of changes in the brain are critical to understanding how and when meaningful changes occur, however, assessing neuroplasticity using brain based results remains a significant challenge. Little is known about the underlying changes in functional brain networks that correlate with cognitive outcomes in traumatic brain injury (TBI). The purpose of this pilot study was to assess the feasibility of an intensive three month cognitive intervention program in individuals with chronic TBI and to evaluate the effects of this intervention on brain-behavioral relationships. We used tools from graph theory to evaluate changes in global and local brain network features prior to and following cognitive intervention. Network metrics were calculated from resting state electroencephalographic (EEG) recordings from 10 adult participants with mild to severe brain injury and 11 age and gender matched healthy controls. Local graph metrics showed hyper-connectivity in the right inferior frontal gyrus and hypo-connectivity in the left inferior frontal gyrus in the TBI group at baseline in comparison with the control group. Following the intervention, there was a statistically significant increase in the composite cognitive score in the TBI participants and a statistically significant decrease in functional connectivity in the right inferior frontal gyrus. In addition, there was evidence of changes in the brain-behavior relationships following intervention. The results from this pilot study provide preliminary evidence for functional network reorganization that parallels cognitive improvements after cognitive rehabilitation in individuals with chronic TBI.

The effect of education on regional brain metabolism and its functional connectivity in an aged population utilizing positron emission tomography.

PubMed

Kim, Jaeik; Chey, Jeanyung; Kim, Sang-Eun; Kim, Hoyoung

2015-05-01

Education involves learning new information and acquiring cognitive skills. These require various cognitive processes including learning, memory, and language. Since cognitive processes activate associated brain areas, we proposed that the brains of elderly people with longer education periods would show traces of repeated activation as increased synaptic connectivity and capillary in brain areas involved in learning, memory, and language. Utilizing positron emission topography (PET), this study examined the effect of education in the human brain utilizing the regional cerebral glucose metabolism rates (rCMRglcs). 26 elderly women with high-level education (HEG) and 26 with low-level education (LEG) were compared with regard to their regional brain activation and association between the regions. Further, graphical theoretical analysis using rCMRglcs was applied to examine differences in the functional network properties of the brain. The results showed that the HEG had higher rCMRglc in the ventral cerebral regions that are mainly involved in memory, language, and neurogenesis, while the LEG had higher rCMRglc in apical areas of the cerebrum mainly involved in motor and somatosensory functions. Functional connectivity investigated with graph theoretical analysis illustrated that the brain of the HEG compared to those of the LEG were overall more efficient, more resilient, and characterized by small-worldness. This may be one of the brain's mechanisms mediating the reserve effects found in people with higher education. Copyright © 2014 Elsevier Ireland Ltd and the Japan Neuroscience Society. All rights reserved.

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.

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.

12-h abstinence-induced functional connectivity density changes and craving in young smokers: a resting-state study.

PubMed

Zhao, Shuzhi; Li, Yangding; Li, Min; Wang, Ruonan; Bi, Yanzhi; Zhang, Yajuan; Lu, Xiaoqi; Yu, Dahua; Yang, Likun; Yuan, Kai

2018-06-20

Studying the neural correlates of craving to smoke is of great importance to improve treatment outcomes in smoking addiction. According to previous studies, the critical roles of striatum and frontal brain regions had been revealed in addiction. However, few studies focused on the hub of brain regions in the 12 h abstinence induced craving in young smokers. Thirty-one young male smokers were enrolled in the present study. A within-subject experiment design was carried out to compare functional connectivity density between 12-h smoking abstinence and smoking satiety conditions during resting state in young adult smokers by using functional connectivity density mapping (FCDM). Then, the functional connectivity density changes during smoking abstinence versus satiety were further used to examine correlations with abstinence-induced changes in subjective craving. We found young adult smokers in abstinence state (vs satiety) had higher local functional connectivity density (lFCD) and global functional connectivity density (gFCD) in brain regions including striatal subregions (i.e., bilateral caudate and putamen), frontal regions (i.e., anterior cingulate cortex (ACC) and orbital frontal cortex (OFC)) and bilateral insula. We also found higher lFCD during smoking abstinence (vs satiety) in bilateral thalamus. Additionally, the lFCD changes of the left ACC, bilateral caudate and right OFC were positively correlated with the changes in craving induced by abstinence (i.e., abstinence minus satiety) in young adult smokers. The present findings improve the understanding of the effects of acute smoking abstinence on the hubs of brain gray matter in the abstinence-induces craving and may contribute new insights into the neural mechanism of abstinence-induced craving in young smokers in smoking addiction.

Introducing graph theory to track for neuroplastic alterations in the resting human brain: a transcranial direct current stimulation study.

PubMed

Polanía, Rafael; Paulus, Walter; Antal, Andrea; Nitsche, Michael A

2011-02-01

Transcranial direct current stimulation (tDCS) is a non-invasive brain stimulation technique that alters cortical excitability and activity in a polarity-dependent way. Stimulation for a few minutes has been shown to induce plastic alterations of cortical excitability and to improve cognitive performance. These effects might be related to stimulation-induced alterations of functional cortical network connectivity. We aimed to investigate the impact of tDCS on cortical network function by functional connectivity and graph theoretical analysis of the BOLD fMRI spontaneous activity. fMRI resting-state datasets were acquired immediately before and after 10-min bipolar tDCS during rest, with the anode placed over the left primary motor cortex (M1) and the cathode over the contralateral frontopolar cortex. For each dataset, grey matter voxel-based synchronization matrices were calculated and thresholded to construct undirected graphs. Nodal connectivity degree and minimum path length maps were calculated and compared before and after tDCS. Nodal minimum path lengths significantly increased in the left somatomotor (SM1) cortex after anodal tDCS, which means that the number of direct functional connections from the left SM1 to topologically distant grey matter voxels significantly decreased. In contrast, functional coupling between premotor and superior parietal areas with the left SM1 significantly increased. Additionally, the nodal connectivity degree in the left posterior cingulate cortex (PCC) area as well as in the right dorsolateral prefrontal cortex (right DLPFC) significantly increased. In summary, we provide initial support that tDCS-induced neuroplastic alterations might be related to functional connectivity changes in the human brain. Additionally, we propose our approach as a powerful method to track for neuroplastic changes in the human brain. Copyright © 2010 Elsevier Inc. All rights reserved.

Investigating the Intersession Reliability of Dynamic Brain-State Properties.

PubMed

Smith, Derek M; Zhao, Yrian; Keilholz, Shella D; Schumacher, Eric H

2018-06-01

Dynamic functional connectivity metrics have much to offer to the neuroscience of individual differences of cognition. Yet, despite the recent expansion in dynamic connectivity research, limited resources have been devoted to the study of the reliability of these connectivity measures. To address this, resting-state functional magnetic resonance imaging data from 100 Human Connectome Project subjects were compared across 2 scan days. Brain states (i.e., patterns of coactivity across regions) were identified by classifying each time frame using k means clustering. This was done with and without global signal regression (GSR). Multiple gauges of reliability indicated consistency in the brain-state properties across days and GSR attenuated the reliability of the brain states. Changes in the brain-state properties across the course of the scan were investigated as well. The results demonstrate that summary metrics describing the clustering of individual time frames have adequate test/retest reliability, and thus, these patterns of brain activation may hold promise for individual-difference research.

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.

Large-scale automated histology in the pursuit of connectomes.

PubMed

Kleinfeld, David; Bharioke, Arjun; Blinder, Pablo; Bock, Davi D; Briggman, Kevin L; Chklovskii, Dmitri B; Denk, Winfried; Helmstaedter, Moritz; Kaufhold, John P; Lee, Wei-Chung Allen; Meyer, Hanno S; Micheva, Kristina D; Oberlaender, Marcel; Prohaska, Steffen; Reid, R Clay; Smith, Stephen J; Takemura, Shinya; Tsai, Philbert S; Sakmann, Bert

2011-11-09

How does the brain compute? Answering this question necessitates neuronal connectomes, annotated graphs of all synaptic connections within defined brain areas. Further, understanding the energetics of the brain's computations requires vascular graphs. The assembly of a connectome requires sensitive hardware tools to measure neuronal and neurovascular features in all three dimensions, as well as software and machine learning for data analysis and visualization. We present the state of the art on the reconstruction of circuits and vasculature that link brain anatomy and function. Analysis at the scale of tens of nanometers yields connections between identified neurons, while analysis at the micrometer scale yields probabilistic rules of connection between neurons and exact vascular connectivity.

Large-Scale Automated Histology in the Pursuit of Connectomes

PubMed Central

Bharioke, Arjun; Blinder, Pablo; Bock, Davi D.; Briggman, Kevin L.; Chklovskii, Dmitri B.; Denk, Winfried; Helmstaedter, Moritz; Kaufhold, John P.; Lee, Wei-Chung Allen; Meyer, Hanno S.; Micheva, Kristina D.; Oberlaender, Marcel; Prohaska, Steffen; Reid, R. Clay; Smith, Stephen J.; Takemura, Shinya; Tsai, Philbert S.; Sakmann, Bert

2011-01-01

How does the brain compute? Answering this question necessitates neuronal connectomes, annotated graphs of all synaptic connections within defined brain areas. Further, understanding the energetics of the brain's computations requires vascular graphs. The assembly of a connectome requires sensitive hardware tools to measure neuronal and neurovascular features in all three dimensions, as well as software and machine learning for data analysis and visualization. We present the state of the art on the reconstruction of circuits and vasculature that link brain anatomy and function. Analysis at the scale of tens of nanometers yields connections between identified neurons, while analysis at the micrometer scale yields probabilistic rules of connection between neurons and exact vascular connectivity. PMID:22072665

Motion sickness increases functional connectivity between visual motion and nausea-associated brain regions.

PubMed

Toschi, Nicola; Kim, Jieun; Sclocco, Roberta; Duggento, Andrea; Barbieri, Riccardo; Kuo, Braden; Napadow, Vitaly

2017-01-01

The brain networks supporting nausea not yet understood. We previously found that while visual stimulation activated primary (V1) and extrastriate visual cortices (MT+/V5, coding for visual motion), increasing nausea was associated with increasing sustained activation in several brain areas, with significant co-activation for anterior insula (aIns) and mid-cingulate (MCC) cortices. Here, we hypothesized that motion sickness also alters functional connectivity between visual motion and previously identified nausea-processing brain regions. Subjects prone to motion sickness and controls completed a motion sickness provocation task during fMRI/ECG acquisition. We studied changes in connectivity between visual processing areas activated by the stimulus (MT+/V5, V1), right aIns and MCC when comparing rest (BASELINE) to peak nausea state (NAUSEA). Compared to BASELINE, NAUSEA reduced connectivity between right and left V1 and increased connectivity between right MT+/V5 and aIns and between left MT+/V5 and MCC. Additionally, the change in MT+/V5 to insula connectivity was significantly associated with a change in sympathovagal balance, assessed by heart rate variability analysis. No state-related connectivity changes were noted for the control group. Increased connectivity between a visual motion processing region and nausea/salience brain regions may reflect increased transfer of visual/vestibular mismatch information to brain regions supporting nausea perception and autonomic processing. We conclude that vection-induced nausea increases connectivity between nausea-processing regions and those activated by the nauseogenic stimulus. This enhanced low-frequency coupling may support continual, slowly evolving nausea perception and shifts toward sympathetic dominance. Disengaging this coupling may be a target for biobehavioral interventions aimed at reducing motion sickness severity. Copyright © 2016 Elsevier B.V. All rights reserved.

Migraine classification using magnetic resonance imaging resting-state functional connectivity data.

PubMed

Chong, Catherine D; Gaw, Nathan; Fu, Yinlin; Li, Jing; Wu, Teresa; Schwedt, Todd J

2017-08-01

Background This study used machine-learning techniques to develop discriminative brain-connectivity biomarkers from resting-state functional magnetic resonance neuroimaging ( rs-fMRI) data that distinguish between individual migraine patients and healthy controls. Methods This study included 58 migraine patients (mean age = 36.3 years; SD = 11.5) and 50 healthy controls (mean age = 35.9 years; SD = 11.0). The functional connections of 33 seeded pain-related regions were used as input for a brain classification algorithm that tested the accuracy of determining whether an individual brain MRI belongs to someone with migraine or to a healthy control. Results The best classification accuracy using a 10-fold cross-validation method was 86.1%. Resting functional connectivity of the right middle temporal, posterior insula, middle cingulate, left ventromedial prefrontal and bilateral amygdala regions best discriminated the migraine brain from that of a healthy control. Migraineurs with longer disease durations were classified more accurately (>14 years; 96.7% accuracy) compared to migraineurs with shorter disease durations (≤14 years; 82.1% accuracy). Conclusions Classification of migraine using rs-fMRI provides insights into pain circuits that are altered in migraine and could potentially contribute to the development of a new, noninvasive migraine biomarker. Migraineurs with longer disease burden were classified more accurately than migraineurs with shorter disease burden, potentially indicating that disease duration leads to reorganization of brain circuitry.

Aging Effects on Whole-Brain Functional Connectivity in Adults Free of Cognitive and Psychiatric Disorders.

PubMed

Ferreira, Luiz Kobuti; Regina, Ana Carolina Brocanello; Kovacevic, Natasa; Martin, Maria da Graça Morais; Santos, Pedro Paim; Carneiro, Camila de Godoi; Kerr, Daniel Shikanai; Amaro, Edson; McIntosh, Anthony Randal; Busatto, Geraldo F

2016-09-01

Aging is associated with decreased resting-state functional connectivity (RSFC) within the default mode network (DMN), but most functional imaging studies have restricted the analysis to specific brain regions or networks, a strategy not appropriate to describe system-wide changes. Moreover, few investigations have employed operational psychiatric interviewing procedures to select participants; this is an important limitation since mental disorders are prevalent and underdiagnosed and can be associated with RSFC abnormalities. In this study, resting-state fMRI was acquired from 59 adults free of cognitive and psychiatric disorders according to standardized criteria and based on extensive neuropsychological and clinical assessments. We tested for associations between age and whole-brain RSFC using Partial Least Squares, a multivariate technique. We found that normal aging is not only characterized by decreased RSFC within the DMN but also by ubiquitous increases in internetwork positive correlations and focal internetwork losses of anticorrelations (involving mainly connections between the DMN and the attentional networks). Our results reinforce the notion that the aging brain undergoes a dedifferentiation processes with loss of functional diversity. These findings advance the characterization of healthy aging effects on RSFC and highlight the importance of adopting a broad, system-wide perspective to analyze brain connectivity. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Testosterone affects language areas of the adult human brain

PubMed Central

Hahn, Andreas; Kranz, Georg S.; Sladky, Ronald; Kaufmann, Ulrike; Ganger, Sebastian; Hummer, Allan; Seiger, Rene; Spies, Marie; Vanicek, Thomas; Winkler, Dietmar; Kasper, Siegfried; Windischberger, Christian; Swaab, Dick F.

2016-01-01

Abstract Although the sex steroid hormone testosterone is integrally involved in the development of language processing, ethical considerations mostly limit investigations to single hormone administrations. To circumvent this issue we assessed the influence of continuous high‐dose hormone application in adult female‐to‐male transsexuals. Subjects underwent magnetic resonance imaging before and after 4 weeks of testosterone treatment, with each scan including structural, diffusion weighted and functional imaging. Voxel‐based morphometry analysis showed decreased gray matter volume with increasing levels of bioavailable testosterone exclusively in Broca's and Wernicke's areas. Particularly, this may link known sex differences in language performance to the influence of testosterone on relevant brain regions. Using probabilistic tractography, we further observed that longitudinal changes in testosterone negatively predicted changes in mean diffusivity of the corresponding structural connection passing through the extreme capsule. Considering a related increase in myelin staining in rodents, this potentially reflects a strengthening of the fiber tract particularly involved in language comprehension. Finally, functional images at resting‐state were evaluated, showing increased functional connectivity between the two brain regions with increasing testosterone levels. These findings suggest testosterone‐dependent neuroplastic adaptations in adulthood within language‐specific brain regions and connections. Importantly, deteriorations in gray matter volume seem to be compensated by enhancement of corresponding structural and functional connectivity. Hum Brain Mapp 37:1738–1748, 2016. © 2016 Wiley Periodicals, Inc. PMID:26876303

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.

Resting-state functional connectivity predicts longitudinal pain symptom change in urologic chronic pelvic pain syndrome: a MAPP network study.

PubMed

Kutch, Jason J; Labus, Jennifer S; Harris, Richard E; Martucci, Katherine T; Farmer, Melissa A; Fenske, Sonja; Fling, Connor; Ichesco, Eric; Peltier, Scott; Petre, Bogdan; Guo, Wensheng; Hou, Xiaoling; Stephens, Alisa J; Mullins, Chris; Clauw, Daniel J; Mackey, Sean C; Apkarian, A Vania; Landis, J Richard; Mayer, Emeran A

2017-06-01

Chronic pain symptoms often change over time, even in individuals who have had symptoms for years. Studying biological factors that predict trends in symptom change in chronic pain may uncover novel pathophysiological mechanisms and potential therapeutic targets. In this study, we investigated whether brain functional connectivity measures obtained from resting-state functional magnetic resonance imaging at baseline can predict longitudinal symptom change (3, 6, and 12 months after scan) in urologic chronic pelvic pain syndrome. We studied 52 individuals with urologic chronic pelvic pain syndrome (34 women, 18 men) who had baseline neuroimaging followed by symptom tracking every 2 weeks for 1 year as part of the Multidisciplinary Approach to the Study of Chronic Pelvic Pain (MAPP) Research Network study. We found that brain functional connectivity can make a significant prediction of short-term (3 month) pain reduction with 73.1% accuracy (69.2% sensitivity and 75.0% precision). In addition, we found that the brain regions with greatest contribution to the classification were preferentially aligned with the left frontoparietal network. Resting-state functional magnetic resonance imaging measures seemed to be less informative about 6- or 12-month symptom change. Our study provides the first evidence that future trends in symptom change in patients in a state of chronic pain may be linked to functional connectivity within specific brain networks.

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.

Electrophysiological Source Imaging: A Noninvasive Window to Brain Dynamics.

PubMed

He, Bin; Sohrabpour, Abbas; Brown, Emery; Liu, Zhongming

2018-06-04

Brain activity and connectivity are distributed in the three-dimensional space and evolve in time. It is important to image brain dynamics with high spatial and temporal resolution. Electroencephalography (EEG) and magnetoencephalography (MEG) are noninvasive measurements associated with complex neural activations and interactions that encode brain functions. Electrophysiological source imaging estimates the underlying brain electrical sources from EEG and MEG measurements. It offers increasingly improved spatial resolution and intrinsically high temporal resolution for imaging large-scale brain activity and connectivity on a wide range of timescales. Integration of electrophysiological source imaging and functional magnetic resonance imaging could further enhance spatiotemporal resolution and specificity to an extent that is not attainable with either technique alone. We review methodological developments in electrophysiological source imaging over the past three decades and envision its future advancement into a powerful functional neuroimaging technology for basic and clinical neuroscience applications.

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.

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