Altered interhemispheric functional connectivity in patients with anisometropic and strabismic amblyopia: a resting-state fMRI study.

PubMed

Liang, Minglong; Xie, Bing; Yang, Hong; Yin, Xuntao; Wang, Hao; Yu, Longhua; He, Sheng; Wang, Jian

2017-05-01

Altered brain functional connectivity has been reported in patients with amblyopia by recent neuroimaging studies. However, relatively little is known about the alterations in interhemispheric functional connectivity in amblyopia. The present study aimed to investigate the functional connectivity patterns between homotopic regions across hemispheres in patients with anisometropic and strabismic amblyopia under resting state. Nineteen monocular anisometropic amblyopia (AA), 18 strabismic amblyopia (SA), and 20 normal-sight controls (NC) were enrolled in this study. After a comprehensive ophthalmologic examination, resting-state fMRI scanning was performed in all participants. The pattern of the interhemispheric functional connectivity was measured with the voxel-mirrored homotopic connectivity (VMHC) approach. VMHC values differences within and between three groups were compared, and correlations between VMHC values and each the clinical variable were also analyzed. Altered VMHC was observed in AA and SA patients in lingual gyrus and fusiform gyrus compared with NC subjects. The altered VMHC of lingual gyrus showed a pattern of AA > SA > NC, while the altered VMHC of fusiform gyrus showed a pattern of AA > NC > SA. Moreover, the VMHC values of lingual gyrus were positively correlated with the stereoacuity both in AA and SA patients, and the VMHC values of fusiform gyrus were positively correlated with the amount of anisometropia just in AA patients. These findings suggest that interhemispheric functional coordination between several homotopic visual-related brain regions is impaired both in AA and SA patients under resting state and revealed the similarities and differences in interhemispheric functional connectivity between the anisometropic and strabismic amblyopia.

Disrupted functional connectivity patterns of the insula subregions in drug-free major depressive disorder.

PubMed

Wang, Chao; Wu, Huawang; Chen, Fangfang; Xu, Jinping; Li, Hongming; Li, Hong; Wang, Jiaojian

2018-07-01

Major depressive disorder (MDD) is characterized by impairments in emotional and cognitive functions. Emerging studies have shown that cognition and emotion interact by reaching identical brain regions, and the insula is one such region with functional and structural heterogeneity. Although previous literatures have shown the role of insula in MDD，it remains unclear whether the insular subregions show differential change patterns in MDD. Using the resting-state fMRI data in a group of 23 drug-free MDD patients and 34 healthy controls (HCs), we investigated whether the abnormal connectivity patterns of insular sub-regions or any behavioural correlates can be detected in MDD. Further hierarchical cluster analysis was used to identify the functional connectivity-clustering patterns of insular sub-regions. Compared with HCs, the MDD exhibited higher connectivities between dorsal agranular insula and inferior parietal lobule and between ventral dysgranular and granular insula and thalamus/habehula, and lower connectivity of hypergranular insula to subgenual anterior cingulate cortex. Moreover, the three subregions with significant group differences were in three separate functional systems along anterior-to-posteior gradient. The anterior and middle insula showed positive correlation with depressive severity, while the posterior insular was to the contrary. The small and unbalanced sample size, only included moderate and severe depression and the possible inter-individual differences may limit the interpretability. These findings provided evidences for the MDD-related effects in functional connectivity patterns of insular subregions, and revealed that the subregions might be involved in different neural circuits associated with the contrary impacts on the depressive symptoms. Copyright © 2017 Elsevier B.V. All rights reserved.

Functional connectome fingerprinting: identifying individuals using patterns of brain connectivity.

PubMed

Finn, Emily S; Shen, Xilin; Scheinost, Dustin; Rosenberg, Monica D; Huang, Jessica; Chun, Marvin M; Papademetris, Xenophon; Constable, R Todd

2015-11-01

Functional magnetic resonance imaging (fMRI) studies typically collapse data from many subjects, but brain functional organization varies between individuals. Here we establish that this individual variability is both robust and reliable, using data from the Human Connectome Project to demonstrate that functional connectivity profiles act as a 'fingerprint' that can accurately identify subjects from a large group. Identification was successful across scan sessions and even between task and rest conditions, indicating that an individual's connectivity profile is intrinsic, and can be used to distinguish that individual regardless of how the brain is engaged during imaging. Characteristic connectivity patterns were distributed throughout the brain, but the frontoparietal network emerged as most distinctive. Furthermore, we show that connectivity profiles predict levels of fluid intelligence: the same networks that were most discriminating of individuals were also most predictive of cognitive behavior. Results indicate the potential to draw inferences about single subjects on the basis of functional connectivity fMRI.

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.

Different Hippocampus Functional Connectivity Patterns in Healthy Young Adults with Mutations of APP/Presenilin-1/2 and APOEε4.

PubMed

Zheng, Li Juan; Su, Yun Yan; Wang, Yun Fei; Schoepf, U Joseph; Varga-Szemes, Akos; Pannell, Jonathan; Liang, Xue; Zheng, Gang; Lu, Guang Ming; Yang, Gui Fen; Zhang, Long Jiang

2018-04-01

This study aims to explore the hippocampus-based functional connectivity patterns in young, healthy APP and/or presenilin-1/2 mutation carriers and APOE ε4 subjects. Seventy-eight healthy young adults (33 male, mean age 24.0 ± 2.2 years; 18 APP and/or presenilin1/2 mutation carriers [APP/presenilin-1/2 group], 30 APOE ε4 subjects [APOE ε4 group], and 30 subjects without the above-mentioned genes [control group]) underwent resting-state functional MR imaging and neuropsychological assessments. Bilateral hippocampus functional connectivity patterns were compared among three groups. The brain regions with statistical differences were then extracted, and correlation analyses were performed between Z values of the brain regions and neuropsychological results. Compared with control group, both APOE ε4 group and APP/presenilin-1/2 group showed increased functional connectivity in medial prefrontal cortex and precuneus for the seeds of bilateral hippocampi. The APOE ε4 group displayed increased functional connectivity from bilateral hippocampi to the left middle temporal gyrus compared with the control group. Moreover, compared with the APP/presenilin-1/2 group, the APOE ε4 group also had markedly increased functional connectivity in right hippocampus-left middle temporal gyrus. The Z values of right hippocampus-left middle temporal gyrus correlated with various neuropsychological results across all the subjects, as well as in APOE ε4 group. Young healthy adults carrying APOE ε4 and APP/presenilin-1/2 displayed different hippocampus functional connectivity patterns, which may underlie the discrepant mechanisms of gene-modulated cognitive dysfunction in Alzheimer's disease.

Structural and functional connectional fingerprints in mild cognitive impairment and Alzheimer's disease patients.

PubMed

Son, Seong-Jin; Kim, Jonghoon; Park, Hyunjin

2017-01-01

Regional volume atrophy and functional degeneration are key imaging hallmarks of Alzheimer's disease (AD) in structural and functional magnetic resonance imaging (MRI), respectively. We jointly explored regional volume atrophy and functional connectivity to better characterize neuroimaging data of AD and mild cognitive impairment (MCI). All data were obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. We compared regional volume atrophy and functional connectivity in 10 subcortical regions using structural MRI and resting-state functional MRI (rs-fMRI). Neuroimaging data of normal controls (NC) (n = 35), MCI (n = 40), and AD (n = 30) were compared. Significant differences of regional volumes and functional connectivity measures between groups were assessed using permutation tests in 10 regions. The regional volume atrophy and functional connectivity of identified regions were used as features for the random forest classifier to distinguish among three groups. The features of the identified regions were also regarded as connectional fingerprints that could distinctively separate a given group from the others. We identified a few regions with distinctive regional atrophy and functional connectivity patterns for NC, MCI, and AD groups. A three label classifier using the information of regional volume atrophy and functional connectivity of identified regions achieved classification accuracy of 53.33% to distinguish among NC, MCI, and AD. We identified distinctive regional atrophy and functional connectivity patterns that could be regarded as a connectional fingerprint.

Structural and functional connectional fingerprints in mild cognitive impairment and Alzheimer’s disease patients

PubMed Central

Son, Seong-Jin; Kim, Jonghoon

2017-01-01

Regional volume atrophy and functional degeneration are key imaging hallmarks of Alzheimer’s disease (AD) in structural and functional magnetic resonance imaging (MRI), respectively. We jointly explored regional volume atrophy and functional connectivity to better characterize neuroimaging data of AD and mild cognitive impairment (MCI). All data were obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. We compared regional volume atrophy and functional connectivity in 10 subcortical regions using structural MRI and resting-state functional MRI (rs-fMRI). Neuroimaging data of normal controls (NC) (n = 35), MCI (n = 40), and AD (n = 30) were compared. Significant differences of regional volumes and functional connectivity measures between groups were assessed using permutation tests in 10 regions. The regional volume atrophy and functional connectivity of identified regions were used as features for the random forest classifier to distinguish among three groups. The features of the identified regions were also regarded as connectional fingerprints that could distinctively separate a given group from the others. We identified a few regions with distinctive regional atrophy and functional connectivity patterns for NC, MCI, and AD groups. A three label classifier using the information of regional volume atrophy and functional connectivity of identified regions achieved classification accuracy of 53.33% to distinguish among NC, MCI, and AD. We identified distinctive regional atrophy and functional connectivity patterns that could be regarded as a connectional fingerprint. PMID:28333946

Linking DMN connectivity to episodic memory capacity: What can we learn from patients with medial temporal lobe damage?

PubMed Central

McCormick, Cornelia; Protzner, Andrea B.; Barnett, Alexander J.; Cohn, Melanie; Valiante, Taufik A.; McAndrews, Mary Pat

2014-01-01

Computational models predict that focal damage to the Default Mode Network (DMN) causes widespread decreases and increases of functional DMN connectivity. How such alterations impact functioning in a specific cognitive domain such as episodic memory remains relatively unexplored. Here, we show in patients with unilateral medial temporal lobe epilepsy (mTLE) that focal structural damage leads indeed to specific patterns of DMN functional connectivity alterations, specifically decreased connectivity between both medial temporal lobes (MTLs) and the posterior part of the DMN and increased intrahemispheric anterior–posterior connectivity. Importantly, these patterns were associated with better and worse episodic memory capacity, respectively. These distinct patterns, shown here for the first time, suggest that a close dialogue between both MTLs and the posterior components of the DMN is required to fully express the extensive repertoire of episodic memory abilities. PMID:25068108

Default mode network connectivity distinguishes chemotherapy-treated breast cancer survivors from controls

PubMed Central

Kesler, Shelli R.; Wefel, Jeffrey S.; Hosseini, S. M. Hadi; Cheung, Maria; Watson, Christa L.; Hoeft, Fumiko

2013-01-01

Breast cancer (BC) chemotherapy is associated with cognitive changes including persistent deficits in some individuals. We tested the accuracy of default mode network (DMN) resting state functional connectivity patterns in discriminating chemotherapy treated (C+) from non–chemotherapy (C−) treated BC survivors and healthy controls (HC). We also examined the relationship between DMN connectivity patterns and cognitive function. Multivariate pattern analysis was used to classify 30 C+, 27 C−, and 24 HC, which showed significant accuracy for discriminating C+ from C− (91.23%, P < 0.0001) and C+ from HC (90.74%, P < 0.0001). The C− group did not differ significantly from HC (47.06%, P = 0.60). Lower subjective memory function was correlated (P < 0.002) with greater hyperplane distance (distance from the linear decision function that optimally separates the groups). Disrupted DMN connectivity may help explain long-term cognitive difficulties following BC chemotherapy. PMID:23798392

Linked Sex Differences in Cognition and Functional Connectivity in Youth.

PubMed

Satterthwaite, Theodore D; Wolf, Daniel H; Roalf, David R; Ruparel, Kosha; Erus, Guray; Vandekar, Simon; Gennatas, Efstathios D; Elliott, Mark A; Smith, Alex; Hakonarson, Hakon; Verma, Ragini; Davatzikos, Christos; Gur, Raquel E; Gur, Ruben C

2015-09-01

Sex differences in human cognition are marked, but little is known regarding their neural origins. Here, in a sample of 674 human participants ages 9-22, we demonstrate that sex differences in cognitive profiles are related to multivariate patterns of resting-state functional connectivity MRI (rsfc-MRI). Males outperformed females on motor and spatial cognitive tasks; females were faster in tasks of emotion identification and nonverbal reasoning. Sex differences were also prominent in the rsfc-MRI data at multiple scales of analysis, with males displaying more between-module connectivity, while females demonstrated more within-module connectivity. Multivariate pattern analysis using support vector machines classified subject sex on the basis of their cognitive profile with 63% accuracy (P < 0.001), but was more accurate using functional connectivity data (71% accuracy; P < 0.001). Moreover, the degree to which a given participant's cognitive profile was "male" or "female" was significantly related to the masculinity or femininity of their pattern of brain connectivity (P = 2.3 × 10(-7)). This relationship was present even when considering males and female separately. Taken together, these results demonstrate for the first time that sex differences in patterns of cognition are in part represented on a neural level through divergent patterns of brain connectivity. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

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.

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.

Convergent functional architecture of the superior parietal lobule unraveled with multimodal neuroimaging approaches.

PubMed

Wang, Jiaojian; Yang, Yong; Fan, Lingzhong; Xu, Jinping; Li, Changhai; Liu, Yong; Fox, Peter T; Eickhoff, Simon B; Yu, Chunshui; Jiang, Tianzi

2015-01-01

The superior parietal lobule (SPL) plays a pivotal role in many cognitive, perceptive, and motor-related processes. This implies that a mosaic of distinct functional and structural subregions may exist in this area. Recent studies have demonstrated that the ongoing spontaneous fluctuations in the brain at rest are highly structured and, like coactivation patterns, reflect the integration of cortical locations into long-distance networks. This suggests that the internal differentiation of a complex brain region may be revealed by interaction patterns that are reflected in different neuroimaging modalities. On the basis of this perspective, we aimed to identify a convergent functional organization of the SPL using multimodal neuroimaging approaches. The SPL was first parcellated based on its structural connections as well as on its resting-state connectivity and coactivation patterns. Then, post hoc functional characterizations and connectivity analyses were performed for each subregion. The three types of connectivity-based parcellations consistently identified five subregions in the SPL of each hemisphere. The two anterior subregions were found to be primarily involved in action processes and in visually guided visuomotor functions, whereas the three posterior subregions were primarily associated with visual perception, spatial cognition, reasoning, working memory, and attention. This parcellation scheme for the SPL was further supported by revealing distinct connectivity patterns for each subregion in all the used modalities. These results thus indicate a convergent functional architecture of the SPL that can be revealed based on different types of connectivity and is reflected by different functions and interactions. © 2014 Wiley Periodicals, Inc.

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

Function in the Human Connectome: Task-fMRI and Individual Differences in Behavior

PubMed Central

Barch, Deanna M.; Burgess, Gregory C.; Harms, Michael P.; Petersen, Steven E.; Schlaggar, Bradley L.; Corbetta, Maurizio; Glasser, Matthew F.; Curtiss, Sandra; Dixit, Sachin; Feldt, Cindy; Nolan, Dan; Bryant, Edward; Hartley, Tucker; Footer, Owen; Bjork, James M.; Poldrack, Russ; Smith, Steve; Johansen-Berg, Heidi; Snyder, Abraham Z.; Van Essen, David C.

2014-01-01

The primary goal of the Human Connectome Project (HCP) is to delineate the typical patterns of structural and functional connectivity in the healthy adult human brain. However, we know that there are important individual differences in such patterns of connectivity, with evidence that this variability is associated with alterations in important cognitive and behavioral variables that affect real world function. The HCP data will be a critical stepping-off point for future studies that will examine how variation in human structural and functional connectivity play a role in adult and pediatric neurological and psychiatric disorders that account for a huge amount of public health resources. Thus, the HCP is collecting behavioral measures of a range of motor, sensory, cognitive and emotional processes that will delineate a core set of functions relevant to understanding the relationship between brain connectivity and human behavior. In addition, the HCP is using task-fMRI (tfMRI) to help delineate the relationships between individual differences in the neurobiological substrates of mental processing and both functional and structural connectivity, as well as to help characterize and validate the connectivity analyses to be conducted on the structural and functional connectivity data. This paper describes the logic and rationale behind the development of the behavioral, individual difference, and tfMRI batteries and provides preliminary data on the patterns of activation associated with each of the fMRI tasks, at both a group and individual level. PMID:23684877

Potential risk for healthy siblings to develop schizophrenia: evidence from pattern classification with whole-brain connectivity.

PubMed

Liu, Meijie; Zeng, Ling-Li; Shen, Hui; Liu, Zhening; Hu, Dewen

2012-03-28

Recent resting-state functional connectivity MRI studies using group-level statistical analysis have demonstrated the inheritable characters of schizophrenia. The objective of the present study was to use pattern classification as a means to investigate schizophrenia inheritance based on the whole-brain resting-state functional connectivity at the individual subject level. One-against-one pattern classifications were made amongst three groups (i.e. patients diagnosed with schizophrenia, healthy siblings, and healthy controls after preprocessing), resulting in an 80.4% separation between patients with schizophrenia and healthy controls, a 77.6% separation between schizophrenia patients and their healthy siblings, and a 78.7% separation between healthy siblings and healthy controls, respectively. These results suggest that the healthy siblings of schizophrenia patients have an altered resting-state functional connectivity pattern compared with healthy controls. Thus, healthy siblings may have a potential higher risk for developing schizophrenia compared with the general population. Moreover, this pattern differed from that of schizophrenia patients and may contribute to the normal behavior exhibition of healthy siblings in daily life.

DIFFUSION-WEIGHTED IMAGING TRACTOGRAPHY-BASED PARCELLATION OF THE HUMAN PARIETAL CORTEX AND COMPARISON WITH HUMAN AND MACAQUE RESTING STATE FUNCTIONAL CONNECTIVITY

PubMed Central

Mars, Rogier B.; Jbabdi, Saad; Sallet, Jérôme; O’Reilly, Jill X.; Croxson, Paula L.; Olivier, Etienne; Noonan, MaryAnn P.; Bergmann, Caroline; Mitchell, Anna S.; Baxter, Mark G.; Behrens, Timothy E.J.; Johansen-Berg, Heidi; Tomassini, Valentina; Miller, Karla L.; Rushworth, Matthew F.S.

2011-01-01

Despite the prominence of parietal activity in human neuromaging investigations of sensorimotor and cognitive processes there remains uncertainty about basic aspects of parietal cortical anatomical organization. Descriptions of human parietal cortex draw heavily on anatomical schemes developed in other primate species but the validity of such comparisons has been questioned by claims that there are fundamental differences between the parietal cortex in humans and other primates. A scheme is presented for parcellation of human lateral parietal cortex into component regions on the basis of anatomical connectivity and the functional interactions of the resulting clusters with other brain regions. Anatomical connectivity was estimated using diffusion-weighted magnetic resonance image (MRI) based tractography and functional interactions were assessed by correlations in activity measured with functional MRI (fMRI) at rest. Resting state functional connectivity was also assessed directly in the rhesus macaque lateral parietal cortex in an additional experiment and the patterns found reflected known neuroanatomical connections. Cross-correlation in the tractography-based connectivity patterns of parietal voxels reliably parcellated human lateral parietal cortex into ten component clusters. The resting state functional connectivity of human superior parietal and intraparietal clusters with frontal and extrastriate cortex suggested correspondences with areas in macaque superior and intraparietal sulcus. Functional connectivity patterns with parahippocampal cortex and premotor cortex again suggested fundamental correspondences between inferior parietal cortex in humans and macaques. In contrast, the human parietal cortex differs in the strength of its interactions between the central inferior parietal lobule region and the anterior prefrontal cortex. PMID:21411650

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

Functional connectivity and structural covariance between regions of interest can be measured more accurately using multivariate distance correlation.

PubMed

Geerligs, Linda; Cam-Can; Henson, Richard N

2016-07-15

Studies of brain-wide functional connectivity or structural covariance typically use measures like the Pearson correlation coefficient, applied to data that have been averaged across voxels within regions of interest (ROIs). However, averaging across voxels may result in biased connectivity estimates when there is inhomogeneity within those ROIs, e.g., sub-regions that exhibit different patterns of functional connectivity or structural covariance. Here, we propose a new measure based on "distance correlation"; a test of multivariate dependence of high dimensional vectors, which allows for both linear and non-linear dependencies. We used simulations to show how distance correlation out-performs Pearson correlation in the face of inhomogeneous ROIs. To evaluate this new measure on real data, we use resting-state fMRI scans and T1 structural scans from 2 sessions on each of 214 participants from the Cambridge Centre for Ageing & Neuroscience (Cam-CAN) project. Pearson correlation and distance correlation showed similar average connectivity patterns, for both functional connectivity and structural covariance. Nevertheless, distance correlation was shown to be 1) more reliable across sessions, 2) more similar across participants, and 3) more robust to different sets of ROIs. Moreover, we found that the similarity between functional connectivity and structural covariance estimates was higher for distance correlation compared to Pearson correlation. We also explored the relative effects of different preprocessing options and motion artefacts on functional connectivity. Because distance correlation is easy to implement and fast to compute, it is a promising alternative to Pearson correlations for investigating ROI-based brain-wide connectivity patterns, for functional as well as structural data. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

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.

Convergent and divergent functional connectivity patterns in patients with long-term left-sided and right-sided deafness.

PubMed

Zhang, Yanyang; Mao, Zhiqi; Feng, Shiyu; Wang, Wenxin; Zhang, Jun; Yu, Xinguang

2018-02-05

Cortical reorganization may be induced in long-term single-sided deafness (SD); however, the influence of the deafness side on the functional changes remains poorly understood. Here, we investigated whole-brain functional connectivity patterns in long-term SD patients. The normalized voxel-based functional connectivity strength (FCS) was determined using resting-state fMRI (rs-fMRI) in 17 left-sided deafness (LD) patients, 21 right-sided deafness (RD) patients and 21 healthy controls (HCs). Relative to the HCs, both the LD and RD patients exhibited a reduction in the FCS in the ipsilateral visual cortex. However, compared to that in the HCs, a significantly higher FCS was observed in some regions in the salience and default-mode networks in the RD patients, but this FCS alternation pattern was not observed in the LD patients. A direct comparison of the two patient groups revealed a significantly increased FCS in the supplemental motor area in the LD group. Altogether, the long-term SD groups with LD and RD exhibited convergent and divergent functional connectivity patterns in whole-brain networks, providing promising evidence that the functional changes in long-term SD are highly deafness-side-dependent. Copyright © 2017 Elsevier B.V. All rights reserved.

Functional connectivity of task context representations in prefrontal nodes of the multiple demand network.

PubMed

Stiers, Peter; Goulas, Alexandros

2018-06-01

A subset of regions in the lateral and medial prefrontal cortex and the anterior insula increase their activity level whenever a cognitive task becomes more demanding, regardless of the specific nature of this demand. During execution of a task, these areas and the surrounding cortex temporally encode aspects of the task context in spatially distributed patterns of activity. It is not clear whether these patterns reflect underlying anatomical subnetworks that still exist when task execution has finished. We use fMRI in 12 participants performing alternating blocks of three cognitive tasks to address this question. A first data set is used to define multiple demand regions in each participant. A second dataset from the same participants is used to determine multiple demand voxel assemblies with a preference for one task over the others. We then show that these voxels remain functionally coupled during execution of non-preferred tasks and that they exhibit stronger functional connectivity during rest. This indicates that the assemblies of task preference sharing voxels reflect patterns of underlying anatomical connections. Moreover, we show that voxels preferring the same task have more similar whole brain functional connectivity profiles that are consistent across participants. This suggests that voxel assemblies differ in patterns of input-output connections, most likely reflecting task demand-specific information exchange.

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

PubMed

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

2013-01-01

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

Cerebro-cerebellar resting state functional connectivity in children and adolescents with autism spectrum disorder

PubMed Central

Khan, Amanda J.; Nair, Aarti; Keown, Christopher L.; Datko, Michael C.; Lincoln, Alan J.; Müller, Ralph-Axel

2017-01-01

Background The cerebellum plays important roles in both sensorimotor and supramodal cognitive functions. Cellular, volumetric, and functional abnormalities of the cerebellum have been found in autism spectrum disorders (ASD), but no comprehensive investigation of cerebro-cerebellar connectivity in ASD is available. Methods We used resting-state functional connectivity MRI in 56 children and adolescents (28 ASD, 28 typically developing [TD]) aged 8–17 years. Partial and total correlation analyses were performed for unilateral regions of interest (ROIs), distinguished in two broad domains as sensorimotor (premotor/primary motor, somatosensory, superior temporal, occipital) and supramodal (prefrontal, posterior parietal, and inferior and middle temporal). Results There were three main findings: (i) Total correlation analyses showed predominant cerebro-cerebellar functional overconnectivity in the ASD group; (ii) partial correlation analyses that emphasized domain-specificity (sensorimotor vs. supramodal) indicated a pattern of robustly increased connectivity in the ASD group (compared to the TD group) for sensorimotor ROIs, but predominantly reduced connectivity for supramodal ROIs; (iii) this atypical pattern of connectivity was supported by significantly increased non-canonical connections (between sensorimotor cerebral and supramodal cerebellar ROIs, and vice versa) in the ASD group. Conclusions Our findings indicate that sensorimotor intrinsic functional connectivity is atypically increased in ASD, at the expense of connectivity supporting cerebellar participation in supramodal cognition. PMID:25959247

Vegetation Patterns and Degradation Thresholds in the Mulga Landscapes of Australia

NASA Astrophysics Data System (ADS)

Azadi, Samira; Saco, Patricia; Moreno-de las Heras, Mariano; Willgoose, Garry

2017-04-01

Drylands are often characterised by a spatially heterogeneous vegetation cover forming mosaics of patches dense vegetation within bare soil. This 'patterned' or 'patchy' vegetation cover is sensitive to human pressures. Previous work suggests that within these landscapes there is a critical vegetation cover threshold below which the landscape functionality is lost. This threshold behaviour is tightly linked to the overland flow redistribution and an increase in hydrologic connectivity that induces loss of resources (i.e., leakiness). In fact, disturbances (such as wildfire, overgrazing or harvesting activities) can disrupt the spatial structure of vegetation, increase landscape hydrologic connectivity, trigger erosion and produce a substantial loss of water. All these effects affect ecosystem functionality. Here we present the results of exploring the impact of degradation processes induced by vegetation disturbances (mainly grazing) on ecosystem functionality and connectivity in semiarid landscapes with various types of vegetation patterns. The sites are carefully selected in Mulga landscapes bioregion (New South Wales, Queensland) and in sites of Northern Territory in Australia, which display similar vegetation characteristics but with different vegetation patterns and good quality rainfall information. The analysis of vegetation patterns is derived from high resolution remote sensing images (IKONOS, QuickBird, Pleiades). Using MODIS NDVI and local precipitation data, we compute rainfall use efficiency and precipitation marginal response in order to assess the ecosystem functionality. We use vegetation binary maps and digital elevation models to estimate mean Flowlength as an indicator of structural hydrologic connectivity. We compare the trends for several sites with varying vegetation patterns (i.e., banded versus spotted patterns). Our results show that disturbances increase hydrologic connectivity and suggest threshold behaviour that affects landscape functionality. Though this threshold behaviour is found in all sites, the plots in higher rainfall landscapes with banded vegetation patterns show evidence of higher resilience. We will also present some preliminary modelling results that complement this analysis and capture the coevolution of vegetation and landforms (erosion), leading to this type of threshold behaviour.

Altered Functional Connectivity of Insular Subregions in Alzheimer’s Disease

PubMed Central

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

2018-01-01

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

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

PubMed

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

2018-01-01

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

Regional homogeneity and functional connectivity patterns in major depressive disorder, cognitive vulnerability to depression and healthy subjects.

PubMed

Sun, Hui; Luo, Lizhu; Yuan, Xinru; Zhang, Lu; He, Yini; Yao, Shuqiao; Wang, Jiaojian; Xiao, Jing

2018-08-01

Cognitive vulnerability to depression (CVD) is a high risk for depressive disorder. Recent studies focus on individuals with CVD to determine the neural basis of major depressive disorder (MDD) neuropathology. However, whether CVD showed specific or similar brain functional activity and connectivity patterns, compared to MDD, remain largely unknown. Here, using resting-state functional magnetic resonance imaging in subjects with CVD, healthy controls (HC) and MDD, regional homogeneity (ReHo) and resting-state functional connectivity (R-FC) analyses were conducted to assess local synchronization and changes in functional connectivity patterns. Significant ReHo differences were found in right posterior lobe of cerebellum (PLC), left lingual gyrus (LG) and precuneus. Compared to HC, CVD subjects showed increased ReHo in the PLC, which was similar to the difference found between MDD and HC. Compared to MDD patients, CVD subjects showed decreased ReHo in PLC, LG, and precuneus. R-FC analyses found increased functional connections between LG and left inferior parietal lobule, posterior cingulate cortex, and dorsolateral prefrontal cortex in CVD compared to both HC and MDD. Moreover, Regional mean ReHo values were positively correlated with Center for Epidemiologic Studies Depression Scale scores. These analyses revealed that PLC and functional connections between LG and left inferior parietal lobule, posterior cingulate cortex, and dorsolateral prefrontal cortex may be a potential marker for CVD. Copyright © 2018 Elsevier B.V. All rights reserved.

Looking for hotspots of marine metacommunity connectivity: a methodological framework

PubMed Central

Melià, Paco; Schiavina, Marcello; Rossetto, Marisa; Gatto, Marino; Fraschetti, Simonetta; Casagrandi, Renato

2016-01-01

Seascape connectivity critically affects the spatiotemporal dynamics of marine metacommunities. Understanding how connectivity patterns emerge from physically and biologically-mediated interactions is therefore crucial to conserve marine ecosystem functions and biodiversity. Here, we develop a set of biophysical models to explore connectivity in assemblages of species belonging to a typical Mediterranean community (Posidonia oceanica meadows) and characterized by different dispersing traits. We propose a novel methodological framework to synthesize species-specific results into a set of community connectivity metrics and show that spatiotemporal variation in magnitude and direction of the connections, as well as interspecific differences in dispersing traits, are key factors structuring community connectivity. We eventually demonstrate how these metrics can be used to characterize the functional role of each marine area in determining patterns of community connectivity at the basin level and to support marine conservation planning. PMID:27029563

Looking for hotspots of marine metacommunity connectivity: a methodological framework

NASA Astrophysics Data System (ADS)

Melià, Paco; Schiavina, Marcello; Rossetto, Marisa; Gatto, Marino; Fraschetti, Simonetta; Casagrandi, Renato

2016-03-01

Seascape connectivity critically affects the spatiotemporal dynamics of marine metacommunities. Understanding how connectivity patterns emerge from physically and biologically-mediated interactions is therefore crucial to conserve marine ecosystem functions and biodiversity. Here, we develop a set of biophysical models to explore connectivity in assemblages of species belonging to a typical Mediterranean community (Posidonia oceanica meadows) and characterized by different dispersing traits. We propose a novel methodological framework to synthesize species-specific results into a set of community connectivity metrics and show that spatiotemporal variation in magnitude and direction of the connections, as well as interspecific differences in dispersing traits, are key factors structuring community connectivity. We eventually demonstrate how these metrics can be used to characterize the functional role of each marine area in determining patterns of community connectivity at the basin level and to support marine conservation planning.

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.

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…

Domain Selectivity in the Parahippocampal Gyrus Is Predicted by the Same Structural Connectivity Patterns in Blind and Sighted Individuals.

PubMed

Wang, Xiaoying; He, Chenxi; Peelen, Marius V; Zhong, Suyu; Gong, Gaolang; Caramazza, Alfonso; Bi, Yanchao

2017-05-03

Human ventral occipital temporal cortex contains clusters of neurons that show domain-preferring responses during visual perception. Recent studies have reported that some of these clusters show surprisingly similar domain selectivity in congenitally blind participants performing nonvisual tasks. An important open question is whether these functional similarities are driven by similar innate connections in blind and sighted groups. Here we addressed this question focusing on the parahippocampal gyrus (PHG), a region that is selective for large objects and scenes. Based on the assumption that patterns of long-range connectivity shape local computation, we examined whether domain selectivity in PHG is driven by similar structural connectivity patterns in the two populations. Multiple regression models were built to predict the selectivity of PHG voxels for large human-made objects from white matter (WM) connectivity patterns in both groups. These models were then tested using independent data from participants with similar visual experience (two sighted groups) and using data from participants with different visual experience (blind and sighted groups). Strikingly, the WM-based predictions between blind and sighted groups were as successful as predictions between two independent sighted groups. That is, the functional selectivity for large objects of a PHG voxel in a blind participant could be accurately predicted by its WM pattern using the connection-to-function model built from the sighted group data, and vice versa. Regions that significantly predicted PHG selectivity were located in temporal and frontal cortices in both sighted and blind populations. These results show that the large-scale network driving domain selectivity in PHG is independent of vision. SIGNIFICANCE STATEMENT Recent studies have reported intriguingly similar domain selectivity in sighted and congenitally blind individuals in regions within the ventral visual cortex. To examine whether these similarities originate from similar innate connectional roots, we investigated whether the domain selectivity in one population could be predicted by the structural connectivity pattern of the other. We found that the selectivity for large objects of a PHG voxel in a blind participant could be predicted by its structural connectivity pattern using the connection-to-function model built from the sighted group data, and vice versa. These results reveal that the structural connectivity underlying domain selectivity in the PHG is independent of visual experience, providing evidence for nonvisual representations in this region. Copyright © 2017 the authors 0270-6474/17/374706-12$15.00/0.

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.

Sex differences in autism: a resting-state fMRI investigation of functional brain connectivity in males and females

PubMed Central

Swinnen, Stephan P.; Wenderoth, Nicole

2016-01-01

Autism spectrum disorders (ASD) are far more prevalent in males than in females. Little is known however about the differential neural expression of ASD in males and females. We used a resting-state fMRI-dataset comprising 42 males/42 females with ASD and 75 male/75 female typical-controls to examine whether autism-related alterations in intrinsic functional connectivity are similar or different in males and females, and particularly whether alterations reflect ‘neural masculinization’, as predicted by the Extreme Male Brain theory. Males and females showed a differential neural expression of ASD, characterized by highly consistent patterns of hypo-connectivity in males with ASD (compared to typical males), and hyper-connectivity in females with ASD (compared to typical females). Interestingly, patterns of hyper-connectivity in females with ASD reflected a shift towards the (high) connectivity levels seen in typical males (neural masculinization), whereas patterns of hypo-connectivity observed in males with ASD reflected a shift towards the (low) typical feminine connectivity patterns (neural feminization). Our data support the notion that ASD is a disorder of sexual differentiation rather than a disorder characterized by masculinization in both genders. Future work is needed to identify underlying factors such as sex hormonal alterations that drive these sex-specific neural expressions of ASD. PMID:26989195

Cerebro-cerebellar Resting-State Functional Connectivity in Children and Adolescents with Autism Spectrum Disorder.

PubMed

Khan, Amanda J; Nair, Aarti; Keown, Christopher L; Datko, Michael C; Lincoln, Alan J; Müller, Ralph-Axel

2015-11-01

The cerebellum plays important roles in sensori-motor and supramodal cognitive functions. Cellular, volumetric, and functional abnormalities of the cerebellum have been found in autism spectrum disorders (ASD), but no comprehensive investigation of cerebro-cerebellar connectivity in ASD is available. We used resting-state functional connectivity magnetic resonance imaging in 56 children and adolescents (28 subjects with ASD, 28 typically developing subjects) 8-17 years old. Partial and total correlation analyses were performed for unilateral regions of interest (ROIs), distinguished in two broad domains as sensori-motor (premotor/primary motor, somatosensory, superior temporal, and occipital) and supramodal (prefrontal, posterior parietal, and inferior and middle temporal). There were three main findings: 1) Total correlation analyses showed predominant cerebro-cerebellar functional overconnectivity in the ASD group; 2) partial correlation analyses that emphasized domain specificity (sensori-motor vs. supramodal) indicated a pattern of robustly increased connectivity in the ASD group (compared with the typically developing group) for sensori-motor ROIs but predominantly reduced connectivity for supramodal ROIs; and 3) this atypical pattern of connectivity was supported by significantly increased noncanonical connections (between sensori-motor cerebral and supramodal cerebellar ROIs and vice versa) in the ASD group. Our findings indicate that sensori-motor intrinsic functional connectivity is atypically increased in ASD, at the expense of connectivity supporting cerebellar participation in supramodal cognition. Copyright © 2015 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

Estimation of Dynamic Sparse Connectivity Patterns From Resting State fMRI.

PubMed

Cai, Biao; Zille, Pascal; Stephen, Julia M; Wilson, Tony W; Calhoun, Vince D; Wang, Yu Ping

2018-05-01

Functional connectivity (FC) estimated from functional magnetic resonance imaging (fMRI) time series, especially during resting state periods, provides a powerful tool to assess human brain functional architecture in health, disease, and developmental states. Recently, the focus of connectivity analysis has shifted toward the subnetworks of the brain, which reveals co-activating patterns over time. Most prior works produced a dense set of high-dimensional vectors, which are hard to interpret. In addition, their estimations to a large extent were based on an implicit assumption of spatial and temporal stationarity throughout the fMRI scanning session. In this paper, we propose an approach called dynamic sparse connectivity patterns (dSCPs), which takes advantage of both matrix factorization and time-varying fMRI time series to improve the estimation power of FC. The feasibility of analyzing dynamic FC with our model is first validated through simulated experiments. Then, we use our framework to measure the difference between young adults and children with real fMRI data set from the Philadelphia Neurodevelopmental Cohort (PNC). The results from the PNC data set showed significant FC differences between young adults and children in four different states. For instance, young adults had reduced connectivity between the default mode network and other subnetworks, as well as hyperconnectivity within the visual system in states 1 and 3, and hypoconnectivity in state 2. Meanwhile, they exhibited temporal correlation patterns that changed over time within functional subnetworks. In addition, the dSCPs model indicated that older people tend to spend more time within a relatively connected FC pattern. Overall, the proposed method provides a valid means to assess dynamic FC, which could facilitate the study of brain networks.

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

Comprehending text versus reading words in young readers with varying reading ability: Distinct patterns of functional connectivity from common processing hubs

PubMed Central

Aboud, Katherine S.; Bailey, Stephen K.; Petrill, Stephen A.; Cutting, Laurie E.

2016-01-01

Skilled reading depends on recognizing words efficiently in isolation (word-level processing; WL) and extracting meaning from text (discourse-level processing; DL); deficiencies in either result in poor reading. FMRI has revealed consistent overlapping networks in word and passage reading, as well as unique regions for DL processing, however less is known about how WL and DL processes interact. Here we examined functional connectivity from seed regions derived from where BOLD signal overlapped during word and passage reading in 38 adolescents ranging in reading ability, hypothesizing that even though certain regions support word- and higher-level language, connectivity patterns from overlapping regions would be task modulated. Results indeed revealed that the left-lateralized semantic and working memory (WM) seed regions showed task-dependent functional connectivity patterns: during DL processes, semantic and WM nodes all correlated with the left angular gyrus, a region implicated in semantic memory/coherence building. In contrast, during WL, these nodes coordinated with a traditional WL area (left occipitotemporal region). Additionally, these WL and DL findings were modulated by decoding and comprehension abilities, respectively, with poorer abilities correlating with decreased connectivity. Findings indicate that key regions may uniquely contribute to multiple levels of reading; we speculate that these connectivity patterns may be especially salient for reading outcomes and intervention response. PMID:27147257

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

Sex-related differences in amygdala functional connectivity during resting conditions.

PubMed

Kilpatrick, L A; Zald, D H; Pardo, J V; Cahill, L F

2006-04-01

Recent neuroimaging studies have established a sex-related hemispheric lateralization of amygdala involvement in memory for emotionally arousing material. Here, we examine the possibility that sex-related differences in amygdala involvement in memory for emotional material develop from differential patterns of amygdala functional connectivity evident in the resting brain. Seed voxel partial least square analyses of regional cerebral blood flow data revealed significant sex-related differences in amygdala functional connectivity during resting conditions. The right amygdala was associated with greater functional connectivity in men than in women. In contrast, the left amygdala was associated with greater functional connectivity in women than in men. Furthermore, the regions displaying stronger functional connectivity with the right amygdala in males (sensorimotor cortex, striatum, pulvinar) differed from those displaying stronger functional connectivity with the left amygdala in females (subgenual cortex, hypothalamus). These differences in functional connectivity at rest may link to sex-related differences in medical and psychiatric disorders.

Assemblage patterns of fish functional groups relative to habitat connectivity and conditions in floodplain lakes

USGS Publications Warehouse

Miyazono, S.; Aycock, J.N.; Miranda, L.E.; Tietjen, T.E.

2010-01-01

We evaluated the influences of habitat connectivity and local environmental factors on the distribution and abundance patterns of fish functional groups in 17 floodplain lakes in the Yazoo River Basin, USA. The results of univariate and multivariate analyses showed that species-environmental relationships varied with the functional groups. Species richness and assemblage structure of periodic strategists showed strong and positive correlations with habitat connectivity. Densities of most equilibrium and opportunistic strategists decreased with habitat connectivity. Densities of certain equilibrium and opportunistic strategists increased with turbidity. Forested wetlands around the lakes were positively related to the densities of periodic and equilibrium strategists. These results suggest that decreases in habitat connectivity, forested wetland buffers and water quality resulting from environmental manipulations may cause local extinction of certain fish taxa and accelerate the dominance of tolerant fishes in floodplain lakes. ?? 2010 John Wiley & Sons A/S.

A novel method linking neural connectivity to behavioral fluctuations: Behavior-regressed connectivity.

PubMed

Passaro, Antony D; Vettel, Jean M; McDaniel, Jonathan; Lawhern, Vernon; Franaszczuk, Piotr J; Gordon, Stephen M

2017-03-01

During an experimental session, behavioral performance fluctuates, yet most neuroimaging analyses of functional connectivity derive a single connectivity pattern. These conventional connectivity approaches assume that since the underlying behavior of the task remains constant, the connectivity pattern is also constant. We introduce a novel method, behavior-regressed connectivity (BRC), to directly examine behavioral fluctuations within an experimental session and capture their relationship to changes in functional connectivity. This method employs the weighted phase lag index (WPLI) applied to a window of trials with a weighting function. Using two datasets, the BRC results are compared to conventional connectivity results during two time windows: the one second before stimulus onset to identify predictive relationships, and the one second after onset to capture task-dependent relationships. In both tasks, we replicate the expected results for the conventional connectivity analysis, and extend our understanding of the brain-behavior relationship using the BRC analysis, demonstrating subject-specific BRC maps that correspond to both positive and negative relationships with behavior. Comparison with Existing Method(s): Conventional connectivity analyses assume a consistent relationship between behaviors and functional connectivity, but the BRC method examines performance variability within an experimental session to understand dynamic connectivity and transient behavior. The BRC approach examines connectivity as it covaries with behavior to complement the knowledge of underlying neural activity derived from conventional connectivity analyses. Within this framework, BRC may be implemented for the purpose of understanding performance variability both within and between participants. Published by Elsevier B.V.

Age differences in the intrinsic functional connectivity of default network subsystems

PubMed Central

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

2013-01-01

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

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

PubMed

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

2013-01-01

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

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

PubMed Central

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

2014-01-01

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

Sex differences in autism: a resting-state fMRI investigation of functional brain connectivity in males and females.

PubMed

Alaerts, Kaat; Swinnen, Stephan P; Wenderoth, Nicole

2016-06-01

Autism spectrum disorders (ASD) are far more prevalent in males than in females. Little is known however about the differential neural expression of ASD in males and females. We used a resting-state fMRI-dataset comprising 42 males/42 females with ASD and 75 male/75 female typical-controls to examine whether autism-related alterations in intrinsic functional connectivity are similar or different in males and females, and particularly whether alterations reflect 'neural masculinization', as predicted by the Extreme Male Brain theory. Males and females showed a differential neural expression of ASD, characterized by highly consistent patterns of hypo-connectivity in males with ASD (compared to typical males), and hyper-connectivity in females with ASD (compared to typical females). Interestingly, patterns of hyper-connectivity in females with ASD reflected a shift towards the (high) connectivity levels seen in typical males (neural masculinization), whereas patterns of hypo-connectivity observed in males with ASD reflected a shift towards the (low) typical feminine connectivity patterns (neural feminization). Our data support the notion that ASD is a disorder of sexual differentiation rather than a disorder characterized by masculinization in both genders. Future work is needed to identify underlying factors such as sex hormonal alterations that drive these sex-specific neural expressions of ASD. © The Author (2016). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

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

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

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

Personality Is Reflected in the Brain's Intrinsic Functional Architecture

PubMed Central

Adelstein, Jonathan S.; Shehzad, Zarrar; Mennes, Maarten; DeYoung, Colin G.; Zuo, Xi-Nian; Kelly, Clare; Margulies, Daniel S.; Bloomfield, Aaron; Gray, Jeremy R.; Castellanos, F. Xavier; Milham, Michael P.

2011-01-01

Personality describes persistent human behavioral responses to broad classes of environmental stimuli. Investigating how personality traits are reflected in the brain's functional architecture is challenging, in part due to the difficulty of designing appropriate task probes. Resting-state functional connectivity (RSFC) can detect intrinsic activation patterns without relying on any specific task. Here we use RSFC to investigate the neural correlates of the five-factor personality domains. Based on seed regions placed within two cognitive and affective ‘hubs’ in the brain—the anterior cingulate and precuneus—each domain of personality predicted RSFC with a unique pattern of brain regions. These patterns corresponded with functional subdivisions responsible for cognitive and affective processing such as motivation, empathy and future-oriented thinking. Neuroticism and Extraversion, the two most widely studied of the five constructs, predicted connectivity between seed regions and the dorsomedial prefrontal cortex and lateral paralimbic regions, respectively. These areas are associated with emotional regulation, self-evaluation and reward, consistent with the trait qualities. Personality traits were mostly associated with functional connections that were inconsistently present across participants. This suggests that although a fundamental, core functional architecture is preserved across individuals, variable connections outside of that core encompass the inter-individual differences in personality that motivate diverse responses. PMID:22140453

Pattern Genes Suggest Functional Connectivity of Organs

NASA Astrophysics Data System (ADS)

Qin, Yangmei; Pan, Jianbo; Cai, Meichun; Yao, Lixia; Ji, Zhiliang

2016-05-01

Human organ, as the basic structural and functional unit in human body, is made of a large community of different cell types that organically bound together. Each organ usually exerts highly specified physiological function; while several related organs work smartly together to perform complicated body functions. In this study, we present a computational effort to understand the roles of genes in building functional connection between organs. More specifically, we mined multiple transcriptome datasets sampled from 36 human organs and tissues, and quantitatively identified 3,149 genes whose expressions showed consensus modularly patterns: specific to one organ/tissue, selectively expressed in several functionally related tissues and ubiquitously expressed. These pattern genes imply intrinsic connections between organs. According to the expression abundance of the 766 selective genes, we consistently cluster the 36 human organs/tissues into seven functional groups: adipose & gland, brain, muscle, immune, metabolism, mucoid and nerve conduction. The organs and tissues in each group either work together to form organ systems or coordinate to perform particular body functions. The particular roles of specific genes and selective genes suggest that they could not only be used to mechanistically explore organ functions, but also be designed for selective biomarkers and therapeutic targets.

Resting-state fMRI in sleeping infants more closely resembles adult sleep than adult wakefulness

PubMed Central

Snyder, Abraham Z.; Tagliazucchi, Enzo; Laufs, Helmut; Elison, Jed; Emerson, Robert W.; Shen, Mark D.; Wolff, Jason J.; Botteron, Kelly N.; Dager, Stephen; Estes, Annette M.; Evans, Alan; Gerig, Guido; Hazlett, Heather C.; Paterson, Sarah J.; Schultz, Robert T.; Styner, Martin A.; Zwaigenbaum, Lonnie; Schlaggar, Bradley L.

2017-01-01

Resting state functional magnetic resonance imaging (rs-fMRI) in infants enables important studies of functional brain organization early in human development. However, rs-fMRI in infants has universally been obtained during sleep to reduce participant motion artifact, raising the question of whether differences in functional organization between awake adults and sleeping infants that are commonly attributed to development may instead derive, at least in part, from sleep. This question is especially important as rs-fMRI differences in adult wake vs. sleep are well documented. To investigate this question, we compared functional connectivity and BOLD signal propagation patterns in 6, 12, and 24 month old sleeping infants with patterns in adult wakefulness and non-REM sleep. We find that important functional connectivity features seen during infant sleep closely resemble those seen during adult sleep, including reduced default mode network functional connectivity. However, we also find differences between infant and adult sleep, especially in thalamic BOLD signal propagation patterns. These findings highlight the importance of considering sleep state when drawing developmental inferences in infant rs-fMRI. PMID:29149191

Resting-state fMRI in sleeping infants more closely resembles adult sleep than adult wakefulness.

PubMed

Mitra, Anish; Snyder, Abraham Z; Tagliazucchi, Enzo; Laufs, Helmut; Elison, Jed; Emerson, Robert W; Shen, Mark D; Wolff, Jason J; Botteron, Kelly N; Dager, Stephen; Estes, Annette M; Evans, Alan; Gerig, Guido; Hazlett, Heather C; Paterson, Sarah J; Schultz, Robert T; Styner, Martin A; Zwaigenbaum, Lonnie; Schlaggar, Bradley L; Piven, Joseph; Pruett, John R; Raichle, Marcus

2017-01-01

Resting state functional magnetic resonance imaging (rs-fMRI) in infants enables important studies of functional brain organization early in human development. However, rs-fMRI in infants has universally been obtained during sleep to reduce participant motion artifact, raising the question of whether differences in functional organization between awake adults and sleeping infants that are commonly attributed to development may instead derive, at least in part, from sleep. This question is especially important as rs-fMRI differences in adult wake vs. sleep are well documented. To investigate this question, we compared functional connectivity and BOLD signal propagation patterns in 6, 12, and 24 month old sleeping infants with patterns in adult wakefulness and non-REM sleep. We find that important functional connectivity features seen during infant sleep closely resemble those seen during adult sleep, including reduced default mode network functional connectivity. However, we also find differences between infant and adult sleep, especially in thalamic BOLD signal propagation patterns. These findings highlight the importance of considering sleep state when drawing developmental inferences in infant rs-fMRI.

Cross-cultural consistency and diversity in intrinsic functional organization of Broca's Region.

PubMed

Zhang, Yu; Fan, Lingzhong; Caspers, Svenja; Heim, Stefan; Song, Ming; Liu, Cirong; Mo, Yin; Eickhoff, Simon B; Amunts, Katrin; Jiang, Tianzi

2017-04-15

As a core language area, Broca's region was consistently activated in a variety of language studies even across different language systems. Moreover, a high degree of structural and functional heterogeneity in Broca's region has been reported in many studies. This raised the issue of how the intrinsic organization of Broca's region effects by different language experiences in light of its subdivisions. To address this question, we used multi-center resting-state fMRI data to explore the cross-cultural consistency and diversity of Broca's region in terms of its subdivisions, connectivity patterns and modularity organization in Chinese and German speakers. A consistent topological organization of the 13 subdivisions within the extended Broca's region was revealed on the basis of a new in-vivo parcellation map, which corresponded well to the previously reported receptorarchitectonic map. Based on this parcellation map, consistent functional connectivity patterns and modularity organization of these subdivisions were found. Some cultural difference in the functional connectivity patterns was also found, for instance stronger connectivity in Chinese subjects between area 6v2 and the motor hand area, as well as higher correlations between area 45p and middle frontal gyrus. Our study suggests that a generally invariant organization of Broca's region, together with certain regulations of different language experiences on functional connectivity, might exists to support language processing in human brain. Copyright © 2017 Elsevier Inc. All rights reserved.

Development and Plasticity of Cortical Processing Architectures

NASA Astrophysics Data System (ADS)

Singer, Wolf

1995-11-01

One of the basic functions of the cerebral cortex is the analysis and representation of relations among the components of sensory and motor patterns. It is proposed that the cortex applies two complementary strategies to cope with the combinatorial problem posed by the astronomical number of possible relations: (i) the analysis and representation of frequently occurring, behaviorally relevant relations by groups of cells with fixed but broadly tuned response properties; and (ii) the dynamic association of these cells into functionally coherent assemblies. Feedforward connections and reciprocal associative connections, respectively, are thought to underlie these two operations. The architectures of both types of connections are susceptible to experience-dependent modifications during development, but they become fixed in the adult. As development proceeds, feedforward connections also appear to lose much of their functional plasticity, whereas the synapses of the associative connections retain a high susceptibility to use-dependent modifications. The reduced plasticity of feedforward connections is probably responsible for the invariance of cognitive categories acquired early in development. The persistent adaptivity of reciprocal connections is a likely substrate for the ability to generate representations for new perceptual objects and motor patterns throughout life.

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.

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.

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.

Functional connectivity pattern during rest within the episodic memory network in association with episodic memory performance in bipolar disorder.

PubMed

Oertel-Knöchel, Viola; Reinke, Britta; Matura, Silke; Prvulovic, David; Linden, David E J; van de Ven, Vincent

2015-02-28

In this study, we sought to examine the intrinsic functional organization of the episodic memory network during rest in bipolar disorder (BD). The previous work suggests that deficits in intrinsic functional connectivity may account for impaired memory performance. We hypothesized that regions involved in episodic memory processing would reveal aberrant functional connectivity in patients with bipolar disorder. We examined 21 patients with BD and 21 healthy matched controls who underwent functional magnetic resonance imaging (fMRI) during a resting condition. We did a seed-based functional connectivity analysis (SBA), using the regions of the episodic memory network that showed a significantly different activation pattern during task-related fMRI as seeds. The functional connectivity scores (FC) were further correlated with episodic memory task performance. Our results revealed decreased FC scores within frontal areas and between frontal and temporal/hippocampal/limbic regions in BD patients in comparison with controls. We observed higher FC in BD patients compared with controls between frontal and limbic regions. The decrease in fronto-frontal functional connectivity in BD patients showed a significant positive association with episodic memory performance. The association between task-independent dysfunctional frontal-limbic FC and episodic memory performance may be relevant for current pathophysiological models of the disease. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

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

Analyzing functional brain connectivity by means of commute times: a new approach and its application to track event-related dynamics.

PubMed

Dimitriadis, S I; Laskaris, N A; Tzelepi, A; Economou, G

2012-05-01

There is growing interest in studying the association of functional connectivity patterns with particular cognitive tasks. The ability of graphs to encapsulate relational data has been exploited in many related studies, where functional networks (sketched by different neural synchrony estimators) are characterized by a rich repertoire of graph-related metrics. We introduce commute times (CTs) as an alternative way to capture the true interplay between the nodes of a functional connectivity graph (FCG). CT is a measure of the time taken for a random walk to setout and return between a pair of nodes on a graph. Its computation is considered here as a robust and accurate integration, over the FCG, of the individual pairwise measurements of functional coupling. To demonstrate the benefits from our approach, we attempted the characterization of time evolving connectivity patterns derived from EEG signals recorded while the subject was engaged in an eye-movement task. With respect to standard ways, which are currently employed to characterize connectivity, an improved detection of event-related dynamical changes is noticeable. CTs appear to be a promising technique for deriving temporal fingerprints of the brain's dynamic functional organization.

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

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

Breaking Functional Connectivity into Components: A Novel Approach Using an Individual-Based Model, and First Outcomes

PubMed Central

Pe'er, Guy; Henle, Klaus; Dislich, Claudia; Frank, Karin

2011-01-01

Landscape connectivity is a key factor determining the viability of populations in fragmented landscapes. Predicting ‘functional connectivity’, namely whether a patch or a landscape functions as connected from the perspective of a focal species, poses various challenges. First, empirical data on the movement behaviour of species is often scarce. Second, animal-landscape interactions are bound to yield complex patterns. Lastly, functional connectivity involves various components that are rarely assessed separately. We introduce the spatially explicit, individual-based model FunCon as means to distinguish between components of functional connectivity and to assess how each of them affects the sensitivity of species and communities to landscape structures. We then present the results of exploratory simulations over six landscapes of different fragmentation levels and across a range of hypothetical bird species that differ in their response to habitat edges. i) Our results demonstrate that estimations of functional connectivity depend not only on the response of species to edges (avoidance versus penetration into the matrix), the movement mode investigated (home range movements versus dispersal), and the way in which the matrix is being crossed (random walk versus gap crossing), but also on the choice of connectivity measure (in this case, the model output examined). ii) We further show a strong effect of the mortality scenario applied, indicating that movement decisions that do not fully match the mortality risks are likely to reduce connectivity and enhance sensitivity to fragmentation. iii) Despite these complexities, some consistent patterns emerged. For instance, the ranking order of landscapes in terms of functional connectivity was mostly consistent across the entire range of hypothetical species, indicating that simple landscape indices can potentially serve as valuable surrogates for functional connectivity. Yet such simplifications must be carefully evaluated in terms of the components of functional connectivity they actually predict. PMID:21829617

Dopamine-Related Disruption of Functional Topography of Striatal Connections in Unmedicated Patients With Schizophrenia.

PubMed

Horga, Guillermo; Cassidy, Clifford M; Xu, Xiaoyan; Moore, Holly; Slifstein, Mark; Van Snellenberg, Jared X; Abi-Dargham, Anissa

2016-08-01

Despite the well-established role of striatal dopamine in psychosis, current views generally agree that cortical dysfunction is likely necessary for the emergence of psychotic symptoms. The topographic organization of striatal-cortical connections is central to gating and integration of higher-order information, so a disruption of such topography via dysregulated dopamine could lead to cortical dysfunction in schizophrenia. However, this hypothesis remains to be tested using multivariate methods ascertaining the global pattern of striatal connectivity and without the confounding effects of antidopaminergic medication. To examine whether the pattern of brain connectivity across striatal subregions is abnormal in unmedicated patients with schizophrenia and whether this abnormality relates to psychotic symptoms and extrastriatal dopaminergic transmission. In this multimodal, case-control study, we obtained resting-state functional magnetic resonance imaging data from 18 unmedicated patients with schizophrenia and 24 matched healthy controls from the New York State Psychiatric Institute. A subset of these (12 and 17, respectively) underwent positron emission tomography with the dopamine D2 receptor radiotracer carbon 11-labeled FLB457 before and after amphetamine administration. Data were acquired between June 16, 2011, and February 25, 2014. Data analysis was performed from September 1, 2014, to January 11, 2016. Group differences in the striatal connectivity pattern (assessed via multivariable logistic regression) across striatal subregions, the association between the multivariate striatal connectivity pattern and extrastriatal baseline D2 receptor binding potential and its change after amphetamine administration, and the association between the multivariate connectivity pattern and the severity of positive symptoms evaluated with the Positive and Negative Syndrome Scale. Of the patients with schizophrenia (mean [SEM] age, 35.6 [11.8] years), 9 (50%) were male and 9 (50%) were female. Of the controls (mean [SEM] age, 33.7 [8.8] years), 10 (42%) were male and 14 (58%) were female. Patients had an abnormal pattern of striatal connectivity, which included abnormal caudate connections with a distributed set of associative cortex regions (χ229 = 53.55, P = .004). In patients, more deviation from the multivariate pattern of striatal connectivity found in controls correlated specifically with more severe positive symptoms (ρ = -0.77, P = .002). Striatal connectivity also correlated with baseline binding potential across cortical and extrastriatal subcortical regions (t25 = 3.01, P = .01, Bonferroni corrected) but not with its change after amphetamine administration. Using a multimodal, circuit-level interrogation of striatal-cortical connections, it was demonstrated that the functional topography of these connections is globally disrupted in unmedicated patients with schizophrenia. These findings suggest that striatal-cortical dysconnectivity may underlie the effects of dopamine dysregulation on the pathophysiologic mechanism of psychotic symptoms.

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.

Core networks and their reconfiguration patterns across cognitive loads.

PubMed

Zuo, Nianming; Yang, Zhengyi; Liu, Yong; Li, Jin; Jiang, Tianzi

2018-04-20

Different cognitively demanding tasks recruit globally distributed but functionally specific networks. However, the configuration of core networks and their reconfiguration patterns across cognitive loads remain unclear, as does whether these patterns are indicators for the performance of cognitive tasks. In this study, we analyzed functional magnetic resonance imaging data of a large cohort of 448 subjects, acquired with the brain at resting state and executing N-back working memory (WM) tasks. We discriminated core networks by functional interaction strength and connection flexibility. Results demonstrated that the frontoparietal network (FPN) and default mode network (DMN) were core networks, but each exhibited different patterns across cognitive loads. The FPN and DMN both showed strengthened internal connections at the low demand state (0-back) compared with the resting state (control level); whereas, from the low (0-back) to high demand state (2-back), some connections to the FPN weakened and were rewired to the DMN (whose connections all remained strong). Of note, more intensive reconfiguration of both the whole brain and core networks (but no other networks) across load levels indicated relatively poor cognitive performance. Collectively these findings indicate that the FPN and DMN have distinct roles and reconfiguration patterns across cognitively demanding loads. This study advances our understanding of the core networks and their reconfiguration patterns across cognitive loads and provides a new feature to evaluate and predict cognitive capability (e.g., WM performance) based on brain networks. © 2018 Wiley Periodicals, Inc.

Altered Functional Connectivity of the Primary Visual Cortex in Subjects with Amblyopia

PubMed Central

Ding, Kun; Liu, Yong; Yan, Xiaohe; Lin, Xiaoming; Jiang, Tianzi

2013-01-01

Amblyopia, which usually occurs during early childhood and results in poor or blurred vision, is a disorder of the visual system that is characterized by a deficiency in an otherwise physically normal eye or by a deficiency that is out of proportion with the structural or functional abnormalities of the eye. Our previous study demonstrated alterations in the spontaneous activity patterns of some brain regions in individuals with anisometropic amblyopia compared to subjects with normal vision. To date, it remains unknown whether patients with amblyopia show characteristic alterations in the functional connectivity patterns in the visual areas of the brain, particularly the primary visual area. In the present study, we investigated the differences in the functional connectivity of the primary visual area between individuals with amblyopia and normal-sighted subjects using resting functional magnetic resonance imaging. Our findings demonstrated that the cerebellum and the inferior parietal lobule showed altered functional connectivity with the primary visual area in individuals with amblyopia, and this finding provides further evidence for the disruption of the dorsal visual pathway in amblyopic subjects. PMID:23844297

Widespread temporo-occipital lobe dysfunction in amyotrophic lateral sclerosis

NASA Astrophysics Data System (ADS)

Loewe, Kristian; Machts, Judith; Kaufmann, Jörn; Petri, Susanne; Heinze, Hans-Jochen; Borgelt, Christian; Harris, Joseph Allen; Vielhaber, Stefan; Schoenfeld, Mircea Ariel

2017-01-01

Recent studies suggest that amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD) lie on a single clinical continuum. However, previous neuroimaging studies have found only limited involvement of temporal lobe regions in ALS. To better delineate possible temporal lobe involvement in ALS, the present study aimed to examine changes in functional connectivity across the whole brain, particularly with regard to extra-motor regions, in a group of 64 non-demented ALS patients and 38 healthy controls. To assess between-group differences in connectivity, we computed edge-level statistics across subject-specific graphs derived from resting-state functional MRI data. In addition to expected ALS-related decreases in functional connectivity in motor-related areas, we observed extensive changes in connectivity across the temporo-occipital cortex. Although ALS patients with comorbid FTD were deliberately excluded from this study, the pattern of connectivity alterations closely resembles patterns of cerebral degeneration typically seen in FTD. This evidence for subclinical temporal dysfunction supports the idea of a common pathology in ALS and FTD.

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

PubMed

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

2018-05-01

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

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

Correlations and Functional Connections in a Population of Grid Cells

PubMed Central

Roudi, Yasser

2015-01-01

We study the statistics of spike trains of simultaneously recorded grid cells in freely behaving rats. We evaluate pairwise correlations between these cells and, using a maximum entropy kinetic pairwise model (kinetic Ising model), study their functional connectivity. Even when we account for the covariations in firing rates due to overlapping fields, both the pairwise correlations and functional connections decay as a function of the shortest distance between the vertices of the spatial firing pattern of pairs of grid cells, i.e. their phase difference. They take positive values between cells with nearby phases and approach zero or negative values for larger phase differences. We find similar results also when, in addition to correlations due to overlapping fields, we account for correlations due to theta oscillations and head directional inputs. The inferred connections between neurons in the same module and those from different modules can be both negative and positive, with a mean close to zero, but with the strongest inferred connections found between cells of the same module. Taken together, our results suggest that grid cells in the same module do indeed form a local network of interconnected neurons with a functional connectivity that supports a role for attractor dynamics in the generation of grid pattern. PMID:25714908

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.

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.

Mapping functional connectivity

Treesearch

Peter Vogt; Joseph R. Ferrari; Todd R. Lookingbill; Robert H. Gardner; Kurt H. Riitters; Katarzyna Ostapowicz

2009-01-01

An objective and reliable assessment of wildlife movement is important in theoretical and applied ecology. The identification and mapping of landscape elements that may enhance functional connectivity is usually a subjective process based on visual interpretations of species movement patterns. New methods based on mathematical morphology provide a generic, flexible,...

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.

A Flexible Approach for Assessing Functional Landscape Connectivity, with Application to Greater Sage-Grouse (Centrocercus urophasianus)

PubMed Central

Harju, Seth M.; Olson, Chad V.; Dzialak, Matthew R.; Mudd, James P.; Winstead, Jeff B.

2013-01-01

Connectivity of animal populations is an increasingly prominent concern in fragmented landscapes, yet existing methodological and conceptual approaches implicitly assume the presence of, or need for, discrete corridors. We tested this assumption by developing a flexible conceptual approach that does not assume, but allows for, the presence of discrete movement corridors. We quantified functional connectivity habitat for greater sage-grouse (Centrocercus urophasianus) across a large landscape in central western North America. We assigned sample locations to a movement state (encamped, traveling and relocating), and used Global Positioning System (GPS) location data and conditional logistic regression to estimate state-specific resource selection functions. Patterns of resource selection during different movement states reflected selection for sagebrush and general avoidance of rough topography and anthropogenic features. Distinct connectivity corridors were not common in the 5,625 km2 study area. Rather, broad areas functioned as generally high or low quality connectivity habitat. A comprehensive map predicting the quality of connectivity habitat across the study area validated well based on a set of GPS locations from independent greater sage-grouse. The functional relationship between greater sage-grouse and the landscape did not always conform to the idea of a discrete corridor. A more flexible consideration of landscape connectivity may improve the efficacy of management actions by aligning those actions with the spatial patterns by which animals interact with the landscape. PMID:24349241

A flexible approach for assessing functional landscape connectivity, with application to greater sage-grouse (Centrocercus urophasianus).

PubMed

Harju, Seth M; Olson, Chad V; Dzialak, Matthew R; Mudd, James P; Winstead, Jeff B

2013-01-01

Connectivity of animal populations is an increasingly prominent concern in fragmented landscapes, yet existing methodological and conceptual approaches implicitly assume the presence of, or need for, discrete corridors. We tested this assumption by developing a flexible conceptual approach that does not assume, but allows for, the presence of discrete movement corridors. We quantified functional connectivity habitat for greater sage-grouse (Centrocercus urophasianus) across a large landscape in central western North America. We assigned sample locations to a movement state (encamped, traveling and relocating), and used Global Positioning System (GPS) location data and conditional logistic regression to estimate state-specific resource selection functions. Patterns of resource selection during different movement states reflected selection for sagebrush and general avoidance of rough topography and anthropogenic features. Distinct connectivity corridors were not common in the 5,625 km(2) study area. Rather, broad areas functioned as generally high or low quality connectivity habitat. A comprehensive map predicting the quality of connectivity habitat across the study area validated well based on a set of GPS locations from independent greater sage-grouse. The functional relationship between greater sage-grouse and the landscape did not always conform to the idea of a discrete corridor. A more flexible consideration of landscape connectivity may improve the efficacy of management actions by aligning those actions with the spatial patterns by which animals interact with the landscape.

Differential Motor and Prefrontal Cerebello-Cortical Network Development: Evidence from Multimodal Neuroimaging

PubMed Central

Bernard, Jessica A.; Orr, Joseph M.; Mittal, Vijay A.

2015-01-01

While our understanding of cerebellar structural development through adolescence and young adulthood has expanded, we still lack knowledge of the developmental patterns of cerebellar networks during this critical portion of the lifespan. Volume in lateral posterior cerebellar regions associated with cognition and the prefrontal cortex develops more slowly, reaching their peak volume in adulthood, particularly as compared to motor Lobule V. We predicted that resting state functional connectivity of the lateral posterior regions would show a similar pattern of development during adolescence and young adulthood. That is, we expected to see changes over time in Crus I and Crus II connectivity with the cortex, but no changes in Lobule V connectivity. Additionally, we were interested in how structural connectivity changes in cerebello-thalamo-cortical white matter are related to changes in functional connectivity. A sample of 23 individuals between 12 and 21 years old underwent neuroimaging scans at baseline and 12-months later. Functional networks of Crus I and Crus II showed significant connectivity decreases over 12-months, though there were no differences in Lobule V. Furthermore, these functional connectivity changes were correlated with increases in white matter structural integrity in the corresponding cerebello-thalamo-cortical white matter tract. We suggest that these functional network changes are due to both later pruning in the prefrontal cortex as well as further development of the white matter tracts linking these brain regions. PMID:26391125

Convergent and divergent intranetwork and internetwork connectivity patterns in patients with remitted late-life depression and amnestic mild cognitive impairment.

PubMed

Chen, Jiu; Shu, Hao; Wang, Zan; Zhan, Yafeng; Liu, Duan; Liao, Wenxiang; Xu, Lin; Liu, Yong; Zhang, Zhijun

2016-10-01

Both remitted late-life depression (rLLD) and amnesiac mild cognitive impairment (aMCI) alter brain functions in specific regions of the brain. They are also disconnection syndromes that are associated with a high risk of developing Alzheimer's disease (AD). Resting-state functional connectivity magnetic resonance imaging (rs-fcMRI) was performed to define the shared and distinct aberrant patterns in intranetwork and internetwork connectivity between rLLD and aMCI and to determine how knowledge of these differences might contribute to our essential understanding of the altered sequences involved in functional systems both inside and outside of resting-state networks. We used rs-fcMRI to investigate in five functionally well-defined brain networks in two large cohorts of subjects at high risk for AD (55 rLLD and 87 aMCI) and 114 healthy controls (HC). A reduced degree of functional connectivity was observed in the bilateral inferior temporal cortex and supplemental motor area, and reduced correlations were observed within the sensory-motor network (SMN) and in the default mode network (DMN)-control network (CON) pair in the rLLD group than the HC group. The aMCI group showed only focal functional changes in regions of interest pairs, a trend toward increased correlations within the salience network and SMN, and a trend toward a reduced correlation in the DMN-CON pair. Furthermore, the rLLD group exhibited more severely altered functional connectivity than the aMCI group. Interestingly, these altered connectivities were associated with specific multi-domain cognitive and behavioral functions in both rLLD and aMCI. The degree of functional connectivity in the right primary auditory areas was negatively correlated with Hamilton Depression Scale scores in rLLD. Notably, altered connectivity between the right middle temporal cortex and the posterior cerebellum was negatively correlated with Mattis Dementia Rating Scale scores in both rLLD and aMCI. These results demonstrate that rLLD and aMCI may share convergent and divergent aberrant intranetwork and internetwork connectivity patterns as a potential continuous spectrum of the same disease. They further suggest that dysfunctions in the right specific temporal-cerebellum neural circuit may contribute to the similarities observed in rLLD and aMCI conversion to AD. Copyright © 2016 Elsevier Ltd. All rights reserved.

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

PubMed

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

2018-06-01

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

The relationship between spatial configuration and functional connectivity of brain regions

PubMed Central

Woolrich, Mark W; Glasser, Matthew F; Robinson, Emma C; Beckmann, Christian F; Van Essen, David C

2018-01-01

Brain connectivity is often considered in terms of the communication between functionally distinct brain regions. Many studies have investigated the extent to which patterns of coupling strength between multiple neural populations relates to behaviour. For example, studies have used ‘functional connectivity fingerprints’ to characterise individuals' brain activity. Here, we investigate the extent to which the exact spatial arrangement of cortical regions interacts with measures of brain connectivity. We find that the shape and exact location of brain regions interact strongly with the modelling of brain connectivity, and present evidence that the spatial arrangement of functional regions is strongly predictive of non-imaging measures of behaviour and lifestyle. We believe that, in many cases, cross-subject variations in the spatial configuration of functional brain regions are being interpreted as changes in functional connectivity. Therefore, a better understanding of these effects is important when interpreting the relationship between functional imaging data and cognitive traits. PMID:29451491

Evidence of a dissociation pattern in resting-state default mode network connectivity in first-episode, treatment-naive major depression patients.

PubMed

Zhu, Xueling; Wang, Xiang; Xiao, Jin; Liao, Jian; Zhong, Mingtian; Wang, Wei; Yao, Shuqiao

2012-04-01

Imaging studies have shown that major depressive disorder (MDD) is associated with altered activity patterns of the default mode network (DMN). However, the neural correlates of the resting-state DMN and MDD-related pathopsychological characteristics, such as depressive rumination and overgeneral autobiographical memory (OGM) phenomena, still remain unclear. Using independent component analysis, we analyzed resting-state functional magnetic resonance imaging data obtained from 35 first-episode, treatment-naive young adults with MDD and from 35 matched healthy control subjects. Patients with MDD exhibited higher levels of rumination and OGM than did the control subjects. We observed increased functional connectivity in the anterior medial cortex regions (especially the medial prefrontal cortex and anterior cingulate cortex) and decreased functional connectivity in the posterior medial cortex regions (especially the posterior cingulate cortex/precuneus) in MDD patients compared with control subjects. In the depressed group, the increased functional connectivity in the anterior medial cortex correlated positively with rumination score, while the decreased functional connectivity in the posterior medial cortex correlated negatively with OGM score. We report dissociation between anterior and posterior functional connectivity in resting-state DMNs of first-episode, treatment-naive young adults with MDD. Increased functional connectivity in anterior medial regions of the resting-state DMN was associated with rumination, whereas decreased functional connectivity in posterior medial regions was associated with OGM. These results provide new evidence for the importance of the DMN in the pathophysiology of MDD and suggest that abnormal DMN activity may be an MDD trait. Copyright © 2012 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

Multimodal analysis of cortical chemoarchitecture and macroscale fMRI resting‐state functional connectivity

PubMed Central

Scholtens, Lianne H.; Turk, Elise; Mantini, Dante; Vanduffel, Wim; Feldman Barrett, Lisa

2016-01-01

Abstract The cerebral cortex is well known to display a large variation in excitatory and inhibitory chemoarchitecture, but the effect of this variation on global scale functional neural communication and synchronization patterns remains less well understood. Here, we provide evidence of the chemoarchitecture of cortical regions to be associated with large‐scale region‐to‐region resting‐state functional connectivity. We assessed the excitatory versus inhibitory chemoarchitecture of cortical areas as an ExIn ratio between receptor density mappings of excitatory (AMPA, M1) and inhibitory (GABAA, M2) receptors, computed on the basis of data collated from pioneering studies of autoradiography mappings as present in literature of the human (2 datasets) and macaque (1 dataset) cortex. Cortical variation in ExIn ratio significantly correlated with total level of functional connectivity as derived from resting‐state functional connectivity recordings of cortical areas across all three datasets (human I: P = 0.0004; human II: P = 0.0008; macaque: P = 0.0007), suggesting cortical areas with an overall more excitatory character to show higher levels of intrinsic functional connectivity during resting‐state. Our findings are indicative of the microscale chemoarchitecture of cortical regions to be related to resting‐state fMRI connectivity patterns at the global system's level of connectome organization. Hum Brain Mapp 37:3103–3113, 2016. © 2016 Wiley Periodicals, Inc. PMID:27207489

Transdiagnostic differences in the resting-state functional connectivity of the prefrontal cortex in depression and schizophrenia.

PubMed

Chen, Xi; Liu, Chang; He, Hui; Chang, Xin; Jiang, Yuchao; Li, Yingjia; Duan, Mingjun; Li, Jianfu; Luo, Cheng; Yao, Dezhong

2017-08-01

Depression and schizophrenia are two of the most serious psychiatric disorders. They share similar symptoms but the pathology-specific commonalities and differences remain unknown. This study was conducted to acquire a full picture of the functional alterations in schizophrenia and depression patients. The resting-state fMRI data from 20 patients with schizophrenia, 20 patients with depression and 20 healthy control subjects were collected. A data-driven approach that included local functional connectivity density (FCD) analysis combined with multivariate pattern analysis (MVPA) was used to compare the three groups. Based on the results of the MVPA, the local FCD value in the orbitofrontal cortex (OFC) can differentiate depression patients from schizophrenia patients. The patients with depression had a higher local FCD value in the medial and anterior parts of the OFC than the subjects in the other two groups, which suggested altered abstract and reward reinforces processing in depression patients. Subsequent functional connectivity analysis indicated that the connection in the prefrontal cortex was significantly lower in people with schizophrenia compared to people with depression and healthy controls. The systematically different medications for schizophrenia and depression may have different effects on functional connectivity. These results suggested that the resting-state functional connectivity pattern in the prefrontal cortex may be a transdiagnostic difference between depression and schizophrenia patients. Copyright © 2017 Elsevier B.V. All rights reserved.

Investigating the Temporal Patterns within and between Intrinsic Connectivity Networks under Eyes-Open and Eyes-Closed Resting States: A Dynamical Functional Connectivity Study Based on Phase Synchronization

PubMed Central

Wang, Xun-Heng; Li, Lihua; Xu, Tao; Ding, Zhongxiang

2015-01-01

The brain active patterns were organized differently under resting states of eyes open (EO) and eyes closed (EC). The altered voxel-wise and regional-wise resting state active patterns under EO/EC were found by static analysis. More importantly, dynamical spontaneous functional connectivity has been observed in the resting brain. To the best of our knowledge, the dynamical mechanisms of intrinsic connectivity networks (ICNs) under EO/EC remain largely unexplored. The goals of this paper were twofold: 1) investigating the dynamical intra-ICN and inter-ICN temporal patterns during resting state; 2) analyzing the altered dynamical temporal patterns of ICNs under EO/EC. To this end, a cohort of healthy subjects with scan conditions of EO/EC were recruited from 1000 Functional Connectomes Project. Through Hilbert transform, time-varying phase synchronization (PS) was applied to evaluate the inter-ICN synchrony. Meanwhile, time-varying amplitude was analyzed as dynamical intra-ICN temporal patterns. The results found six micro-states of inter-ICN synchrony. The medial visual network (MVN) showed decreased intra-ICN amplitude during EC relative to EO. The sensory-motor network (SMN) and auditory network (AN) exhibited enhanced intra-ICN amplitude during EC relative to EO. Altered inter-ICN PS was found between certain ICNs. Particularly, the SMN and AN exhibited enhanced PS to other ICNs during EC relative to EO. In addition, the intra-ICN amplitude might influence the inter-ICN synchrony. Moreover, default mode network (DMN) might play an important role in information processing during EO/EC. Together, the dynamical temporal patterns within and between ICNs were altered during different scan conditions of EO/EC. Overall, the dynamical intra-ICN and inter-ICN temporal patterns could benefit resting state fMRI-related research, and could be potential biomarkers for human functional connectome. PMID:26469182

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.

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.

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.

Imbalanced pattern completion vs. separation in cognitive disease: network simulations of synaptic pathologies predict a personalized therapeutics strategy.

PubMed

Hanson, Jesse E; Madison, Daniel V

2010-08-13

Diverse Mouse genetic models of neurodevelopmental, neuropsychiatric, and neurodegenerative causes of impaired cognition exhibit at least four convergent points of synaptic malfunction: 1) Strength of long-term potentiation (LTP), 2) Strength of long-term depression (LTD), 3) Relative inhibition levels (Inhibition), and 4) Excitatory connectivity levels (Connectivity). To test the hypothesis that pathological increases or decreases in these synaptic properties could underlie imbalances at the level of basic neural network function, we explored each type of malfunction in a simulation of autoassociative memory. These network simulations revealed that one impact of impairments or excesses in each of these synaptic properties is to shift the trade-off between pattern separation and pattern completion performance during memory storage and recall. Each type of synaptic pathology either pushed the network balance towards intolerable error in pattern separation or intolerable error in pattern completion. Imbalances caused by pathological impairments or excesses in LTP, LTD, inhibition, or connectivity, could all be exacerbated, or rescued, by the simultaneous modulation of any of the other three synaptic properties. Because appropriate modulation of any of the synaptic properties could help re-balance network function, regardless of the origins of the imbalance, we propose a new strategy of personalized cognitive therapeutics guided by assay of pattern completion vs. pattern separation function. Simulated examples and testable predictions of this theorized approach to cognitive therapeutics are presented.

Connectivity patterns in cognitive control networks predict naturalistic multitasking ability.

PubMed

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

2018-06-01

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

Task-specific activity and connectivity within the mentalizing network during emotion and intention mentalizing.

PubMed

Atique, Bijoy; Erb, Michael; Gharabaghi, Alireza; Grodd, Wolfgang; Anders, Silke

2011-04-15

Mentalizing, i.e. the process of inferring another person's mental state, is thought to be primarily subserved by three brain regions, the VMPFC (ventromedial prefrontal cortex), precuneus and TPJ (temporo-parietal junction). However, it is still unclear what the exact roles of these regions in mentalizing are. Here, we compare activity within, and functional connectivity between, the VMPFC, precuneus and TPJ during two different mentalizing tasks. Specifically, we examine whether inferring another person's emotion ("emotion mentalizing") and inferring another person's intention ("intention mentalizing") activate similar or distinct subregions within the VMPFC, precuneus and TPJ, and whether these different kinds of mentalizing are associated with different patterns of functional connectivity between these regions. Our results indicate that emotion mentalizing and intention mentalizing activate partly distinct subregions of the right and left TPJ that can be spatially separated across participants. These subregions also showed different patterns of functional connectivity with the VMPFC: a more anterior region of the right and left TPJ, which was more strongly activated during emotion mentalizing, showed stronger functional connectivity with the VMPFC, particularly during emotion mentalizing, than a more posterior region that was more strongly activated during intention mentalizing. Critically, this double dissociation became evident only when the fine-scale distribution of activity within activated regions was analysed, and despite the fact that there was also a significant overlap of activity during the two tasks. Our findings provide first evidence that different neural modules might have evolved within the TPJ that show distinct patterns of functional connectivity and might subserve slightly different subfunctions of mentalizing. Copyright © 2010 Elsevier Inc. All rights reserved.

Amygdala subnuclei connectivity in response to violence reveals unique influences of individual differences in psychopathic traits in a non-forensic sample

PubMed Central

Yoder, Keith J.; Porges, Eric C.; Decety, Jean

2016-01-01

Atypical amygdala function and connectivity have reliably been associated with psychopathy. However, the amygdala is not a unitary structure. To examine how psychopathic traits in a non-forensic sample are linked to amygdala response to violence, the current study used probabilistic tractography to classify amygdala subnuclei based on anatomical projections to and from amygdala subnuclei in a group of 43 male participants. The segmentation identified the basolateral complex (BLA; lateral, basal, and accessory basal subnuclei) and the central subnucleus (CE), which were used as seeds in a functional connectivity analysis to identify differences in neuronal coupling specific to observed violence. While a full amygdala seed showed significant connectivity only to right middle occipital gyrus, subnuclei seeds revealed unique connectivity patterns. BLA showed enhanced coupling with anterior cingulate and prefrontal regions, while CE showed increased connectivity with the brainstem, but reduced connectivity with superior parietal and precentral gyrus. Further, psychopathic personality factors were related to specific patterns of connectivity. Fearless Dominance scores on the psychopathic personality inventory predicted increased coupling between the BLA seed and sensory integration cortices, and increased connectivity between the CE seed and posterior insula. Conversely, Self-Centered Impulsivity scores were negatively correlated with coupling between BLA and ventrolateral prefrontal cortex, and Coldheartedness scores predicted increased functional connectivity between BLA and dorsal anterior cingulate cortex. Taken together, these findings demonstrate how subnuclei segmentations reveal important functional connectivity differences that are otherwise inaccessible. Such an approach yields a better understanding of amygdala dysfunction in psychopathy. PMID:25557777

Amygdala subnuclei connectivity in response to violence reveals unique influences of individual differences in psychopathic traits in a nonforensic sample.

PubMed

Yoder, Keith J; Porges, Eric C; Decety, Jean

2015-04-01

Atypical amygdala function and connectivity have reliably been associated with psychopathy. However, the amygdala is not a unitary structure. To examine how psychopathic traits in a nonforensic sample are linked to amygdala response to violence, this study used probabilistic tractography to classify amygdala subnuclei based on anatomical projections to and from amygdala subnuclei in a group of 43 male participants. The segmentation identified the basolateral complex (BLA; lateral, basal, and accessory basal subnuclei) and the central subnucleus (CE), which were used as seeds in a functional connectivity analysis to identify differences in neuronal coupling specific to observed violence. While a full amygdala seed showed significant connectivity only to right middle occipital gyrus, subnuclei seeds revealed unique connectivity patterns. BLA showed enhanced coupling with anterior cingulate and prefrontal regions, while CE showed increased connectivity with the brainstem, but reduced connectivity with superior parietal and precentral gyrus. Further, psychopathic personality factors were related to specific patterns of connectivity. Fearless Dominance scores on the psychopathic personality inventory predicted increased coupling between the BLA seed and sensory integration cortices, and increased connectivity between the CE seed and posterior insula. Conversely, Self-Centered Impulsivity scores were negatively correlated with coupling between BLA and ventrolateral prefrontal cortex, and Coldheartedness scores predicted increased functional connectivity between BLA and dorsal anterior cingulate cortex. Taken together, these findings demonstrate how subnuclei segmentations reveal important functional connectivity differences that are otherwise inaccessible. Such an approach yields a better understanding of amygdala dysfunction in psychopathy. © 2014 Wiley Periodicals, Inc.

Conflict-related anterior cingulate functional connectivity is associated with past suicidal ideation and behavior in recent-onset schizophrenia.

PubMed

Minzenberg, Michael J; Lesh, Tyler; Niendam, Tara; Yoon, Jong H; Cheng, Yaoan; Rhoades, Remy; Carter, Cameron S

2015-06-01

Suicide is highly prevalent in schizophrenia (SZ), yet it remains unclear how suicide risk factors such as past suicidal ideation or behavior relate to brain function. Circuits modulated by the prefrontal cortex (PFC) are altered in SZ, including in dorsal anterior cingulate cortex (dACC) during conflict-monitoring (an important component of cognitive control), and dACC changes are observed in post-mortem studies of heterogeneous suicide victims. We tested whether conflict-related dACC functional connectivity is associated with past suicidal ideation and behavior in SZ. 32 patients with recent-onset of DSM-IV-TR-defined SZ were evaluated with the Columbia Suicide Severity Rating Scale and functional MRI during cognitive control (AX-CPT) task performance. Group-level regression models relating past history of suicidal ideation or behavior to dACC-seeded functional connectivity during conflict-monitoring controlled for severity of depression, psychosis and impulsivity. Past suicidal ideation was associated with relatively higher functional connectivity of the dACC with the precuneus during conflict-monitoring. Intensity of worst-point past suicidal ideation was associated with relatively higher dACC functional connectivity in medial parietal lobe and striato-thalamic nuclei. In contrast, among those with past suicidal ideation (n = 17), past suicidal behavior was associated with lower conflict-related dACC connectivity with multiple lateral and medial PFC regions, parietal and temporal cortical regions. This study provides unique evidence that recent-onset schizophrenia patients with past suicidal ideation or behavior show altered dACC-based circuit function during conflict-monitoring. Suicidal ideation and suicidal behavior have divergent patterns of associated dACC functional connectivity, suggesting a differing pattern of conflict-related brain dysfunction with these two distinct features of suicide phenomenology. Published by Elsevier Ltd.

Temporal and spectral characteristics of dynamic functional connectivity between resting-state networks reveal information beyond static connectivity

PubMed Central

Yeh, Hsiang J.; Guindani, Michele; Vannucci, Marina; Haneef, Zulfi; Stern, John M.

2018-01-01

Estimation of functional connectivity (FC) has become an increasingly powerful tool for investigating healthy and abnormal brain function. Static connectivity, in particular, has played a large part in guiding conclusions from the majority of resting-state functional MRI studies. However, accumulating evidence points to the presence of temporal fluctuations in FC, leading to increasing interest in estimating FC as a dynamic quantity. One central issue that has arisen in this new view of connectivity is the dramatic increase in complexity caused by dynamic functional connectivity (dFC) estimation. To computationally handle this increased complexity, a limited set of dFC properties, primarily the mean and variance, have generally been considered. Additionally, it remains unclear how to integrate the increased information from dFC into pattern recognition techniques for subject-level prediction. In this study, we propose an approach to address these two issues based on a large number of previously unexplored temporal and spectral features of dynamic functional connectivity. A Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model is used to estimate time-varying patterns of functional connectivity between resting-state networks. Time-frequency analysis is then performed on dFC estimates, and a large number of previously unexplored temporal and spectral features drawn from signal processing literature are extracted for dFC estimates. We apply the investigated features to two neurologic populations of interest, healthy controls and patients with temporal lobe epilepsy, and show that the proposed approach leads to substantial increases in predictive performance compared to both traditional estimates of static connectivity as well as current approaches to dFC. Variable importance is assessed and shows that there are several quantities that can be extracted from dFC signal which are more informative than the traditional mean or variance of dFC. This work illuminates many previously unexplored facets of the dynamic properties of functional connectivity between resting-state networks, and provides a platform for dynamic functional connectivity analysis that facilitates its usage as an investigative measure for healthy as well as abnormal brain function. PMID:29320526

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

PubMed

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

2015-06-01

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

Cocaine dependence and thalamic functional connectivity: a multivariate pattern analysis.

PubMed

Zhang, Sheng; Hu, Sien; Sinha, Rajita; Potenza, Marc N; Malison, Robert T; Li, Chiang-Shan R

2016-01-01

Cocaine dependence is associated with deficits in cognitive control. Previous studies demonstrated that chronic cocaine use affects the activity and functional connectivity of the thalamus, a subcortical structure critical for cognitive functioning. However, the thalamus contains nuclei heterogeneous in functions, and it is not known how thalamic subregions contribute to cognitive dysfunctions in cocaine dependence. To address this issue, we used multivariate pattern analysis (MVPA) to examine how functional connectivity of the thalamus distinguishes 100 cocaine-dependent participants (CD) from 100 demographically matched healthy control individuals (HC). We characterized six task-related networks with independent component analysis of fMRI data of a stop signal task and employed MVPA to distinguish CD from HC on the basis of voxel-wise thalamic connectivity to the six independent components. In an unbiased model of distinct training and testing data, the analysis correctly classified 72% of subjects with leave-one-out cross-validation (p < 0.001), superior to comparison brain regions with similar voxel counts (p < 0.004, two-sample t test). Thalamic voxels that form the basis of classification aggregate in distinct subclusters, suggesting that connectivities of thalamic subnuclei distinguish CD from HC. Further, linear regressions provided suggestive evidence for a correlation of the thalamic connectivities with clinical variables and performance measures on the stop signal task. Together, these findings support thalamic circuit dysfunction in cognitive control as an important neural marker of cocaine dependence.

Cross-modal integration of polyphonic characters in Chinese audio-visual sentences: a MVPA study based on functional connectivity.

PubMed

Zhang, Zhengyi; Zhang, Gaoyan; Zhang, Yuanyuan; Liu, Hong; Xu, Junhai; Liu, Baolin

2017-12-01

This study aimed to investigate the functional connectivity in the brain during the cross-modal integration of polyphonic characters in Chinese audio-visual sentences. The visual sentences were all semantically reasonable and the audible pronunciations of the polyphonic characters in corresponding sentences contexts varied in four conditions. To measure the functional connectivity, correlation, coherence and phase synchronization index (PSI) were used, and then multivariate pattern analysis was performed to detect the consensus functional connectivity patterns. These analyses were confined in the time windows of three event-related potential components of P200, N400 and late positive shift (LPS) to investigate the dynamic changes of the connectivity patterns at different cognitive stages. We found that when differentiating the polyphonic characters with abnormal pronunciations from that with the appreciate ones in audio-visual sentences, significant classification results were obtained based on the coherence in the time window of the P200 component, the correlation in the time window of the N400 component and the coherence and PSI in the time window the LPS component. Moreover, the spatial distributions in these time windows were also different, with the recruitment of frontal sites in the time window of the P200 component, the frontal-central-parietal regions in the time window of the N400 component and the central-parietal sites in the time window of the LPS component. These findings demonstrate that the functional interaction mechanisms are different at different stages of audio-visual integration of polyphonic characters.

Frontal dysconnectivity in 22q11.2 deletion syndrome: an atlas-based functional connectivity analysis.

PubMed

Mattiaccio, Leah M; Coman, Ioana L; Thompson, Carlie A; Fremont, Wanda P; Antshel, Kevin M; Kates, Wendy R

2018-01-20

22q11.2 deletion syndrome (22q11DS) is a neurodevelopmental syndrome associated with deficits in cognitive and emotional processing. This syndrome represents one of the highest risk factors for the development of schizophrenia. Previous studies of functional connectivity (FC) in 22q11DS report aberrant connectivity patterns in large-scale networks that are associated with the development of psychotic symptoms. In this study, we performed a functional connectivity analysis using the CONN toolbox to test for differential connectivity patterns between 54 individuals with 22q11DS and 30 healthy controls, between the ages of 17-25 years old. We mapped resting-state fMRI data onto 68 atlas-based regions of interest (ROIs) generated by the Desikan-Killany atlas in FreeSurfer, resulting in 2278 ROI-to-ROI connections for which we determined total linear temporal associations between each. Within the group with 22q11DS only, we further tested the association between prodromal symptoms of psychosis and FC. We observed that relative to controls, individuals with 22q11DS displayed increased FC in lobar networks involving the frontal-frontal, frontal-parietal, and frontal-occipital ROIs. In contrast, FC between ROIs in the parietal-temporal and occipital lobes was reduced in the 22q11DS group relative to healthy controls. Moreover, positive psychotic symptoms were positively associated with increased functional connections between the left precuneus and right superior frontal gyrus, as well as reduced functional connectivity between the bilateral pericalcarine. Positive symptoms were negatively associated with increased functional connectivity between the right pericalcarine and right postcentral gyrus. Our results suggest that functional organization may be altered in 22q11DS, leading to disruption in connectivity between frontal and other lobar substructures, and potentially increasing risk for prodromal psychosis.

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.

[Seeking the aetiology of autistic spectrum disorder. Part 2: Functional neuroimaging].

PubMed

Bryńska, Anita

2012-01-01

Multiple functional imaging techniques help to a better understanding of the neurobiological basis of autism-spectrum disorders (ASD). The early functional imaging studies on ASD focused on task-specific methods related to core symptom domains and explored patterns of activation in response to face processing, theory of mind tasks, language processing and executive function tasks. On the other hand, fMRI research in ASD focused on the development of functional connectivity methods and has provided evidence of alterations in cortical connectivity in ASD and establish autism as a disorder of under-connectivity among the brain regions participating in cortical networks. This atypical functional connectivity in ASD results in inefficiency and poor integration of processing in network connections to achieve task performance. The goal of this review is to summarise the actual neuroimaging functional data and examine their implication for understanding of the neurobiology of ASD.

Distinct hippocampal functional networks revealed by tractography-based parcellation.

PubMed

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

2016-07-01

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

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

PubMed Central

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

2015-01-01

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

Structural connectivity patterns associated with the putative visual word form area and children's reading ability.

PubMed

Fan, Qiuyun; Anderson, Adam W; Davis, Nicole; Cutting, Laurie E

2014-10-24

With the advent of neuroimaging techniques, especially functional MRI (fMRI), studies have mapped brain regions that are associated with good and poor reading, most centrally a region within the left occipito-temporal/fusiform region (L-OT/F) often referred to as the visual word form area (VWFA). Despite an abundance of fMRI studies of the putative VWFA, research about its structural connectivity has just started. Provided that the putative VWFA may be connected to distributed regions in the brain, it remains unclear how this network is engaged in constituting a well-tuned reading circuitry in the brain. Here we used diffusion MRI to study the structural connectivity patterns of the putative VWFA and surrounding areas within the L-OT/F in children with typically developing (TD) reading ability and with word recognition deficits (WRD; sometimes referred to as dyslexia). We found that L-OT/F connectivity varied along a posterior-anterior gradient, with specific structural connectivity patterns related to reading ability in the ROIs centered upon the putative VWFA. Findings suggest that the architecture of the putative VWFA connectivity is fundamentally different between TD and WRD, with TD showing greater connectivity to linguistic regions than WRD, and WRD showing greater connectivity to visual and parahippocampal regions than TD. Findings thus reveal clear structural abnormalities underlying the functional abnormalities in the putative VWFA in WRD. Copyright © 2014 Elsevier B.V. All rights reserved.

Three dysconnectivity patterns in treatment-resistant schizophrenia patients and their unaffected siblings.

PubMed

Wang, Jicai; Cao, Hongbao; Liao, Yanhui; Liu, Weiqing; Tan, Liwen; Tang, Yanqing; Chen, Jindong; Xu, Xiufeng; Li, Haijun; Luo, Chunrong; Liu, Chunyu; Ries Merikangas, Kathleen; Calhoun, Vince; Tang, Jinsong; Shugart, Yin Yao; Chen, Xiaogang

2015-01-01

Among individuals diagnosed with schizophrenia, approximately 20%-33% are recognized as treatment-resistant schizophrenia (TRS) patients. These TRS patients suffer more severely from the disease but struggle to benefit from existing antipsychotic treatments. A few recent studies suggested that schizophrenia may be caused by impaired synaptic plasticity that manifests as functional dysconnectivity in the brain, however, few of those studies focused on the functional connectivity changes in the brains of TRS groups. In this study, we compared the whole brain connectivity variations in TRS patients, their unaffected siblings, and healthy controls. Connectivity network features between and within the 116 automated anatomical labeling (AAL) brain regions were calculated and compared using maps created with three contrasts: patient vs. control, patient vs. sibling, and sibling vs. To evaluate the predictive power of the selected features, we performed a multivariate classification approach. We also evaluated the influence of six important clinical measures (e.g. age, education level) on the connectivity features. This study identified abnormal significant connectivity changes of three patterns in TRS patients and their unaffected siblings: 1) 69 patient-specific connectivity (PCN); 2) 102 shared connectivity (SCN); and 3) 457 unshared connectivity (UCN). While the first two patterns were widely reported by previous non-TRS specific studies, we were among the first to report widespread significant connectivity differences between TRS patient groups and their healthy sibling groups. Observations of this study may provide new insights for the understanding of the neurophysiological mechanisms of TRS.

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.

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

PubMed Central

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

2016-01-01

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

New whole-body sensory-motor gradients revealed using phase-locked analysis and verified using multivoxel pattern analysis and functional connectivity.

PubMed

Zeharia, Noa; Hertz, Uri; Flash, Tamar; Amedi, Amir

2015-02-18

Topographic organization is one of the main principles of organization in the human brain. Specifically, whole-brain topographic mapping using spectral analysis is responsible for one of the greatest advances in vision research. Thus, it is intriguing that although topography is a key feature also in the motor system, whole-body somatosensory-motor mapping using spectral analysis has not been conducted in humans outside M1/SMA. Here, using this method, we were able to map a homunculus in the globus pallidus, a key target area for deep brain stimulation, which has not been mapped noninvasively or in healthy subjects. The analysis clarifies contradictory and partial results regarding somatotopy in the caudal-cingulate zone and rostral-cingulate zone in the medial wall and in the putamen. Most of the results were confirmed at the single-subject level and were found to be compatible with results from animal studies. Using multivoxel pattern analysis, we could predict movements of individual body parts in these homunculi, thus confirming that they contain somatotopic information. Using functional connectivity, we demonstrate interhemispheric functional somatotopic connectivity of these homunculi, such that the somatotopy in one hemisphere could have been found given the connectivity pattern of the corresponding regions of interest in the other hemisphere. When inspecting the somatotopic and nonsomatotopic connectivity patterns, a similarity index indicated that the pattern of connected and nonconnected regions of interest across different homunculi is similar for different body parts and hemispheres. The results show that topographical gradients are even more widespread than previously assumed in the somatosensory-motor system. Spectral analysis can thus potentially serve as a gold standard for defining somatosensory-motor system areas for basic research and clinical applications. Copyright © 2015 the authors 0270-6474/15/352845-15$15.00/0.

Control Networks in Paediatric Tourette Syndrome Show Immature and Anomalous Patterns of Functional Connectivity

ERIC Educational Resources Information Center

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

2009-01-01

Tourette syndrome (TS) is a developmental disorder characterized by unwanted, repetitive behaviours that manifest as stereotyped movements and vocalizations called "tics". Operating under the hypothesis that the brain's control systems may be impaired in TS, we measured resting-state functional connectivity MRI (rs-fcMRI) between 39 previously…

Altered Connectivity and Action Model Formation in Autism Is Autism

PubMed Central

Mostofsky, Stewart H.; Ewen, Joshua B.

2014-01-01

Internal action models refer to sensory-motor programs that form the brain basis for a wide range of skilled behavior and for understanding others’ actions. Development of these action models, particularly those reliant on visual cues from the external world, depends on connectivity between distant brain regions. Studies of children with autism reveal anomalous patterns of motor learning and impaired execution of skilled motor gestures. These findings robustly correlate with measures of social and communicative function, suggesting that anomalous action model formation may contribute to impaired development of social and communicative (as well as motor) capacity in autism. Examination of the pattern of behavioral findings, as well as convergent data from neuroimaging techniques, further suggests that autism-associated action model formation may be related to abnormalities in neural connectivity, particularly decreased function of long-range connections. This line of study can lead to important advances in understanding the neural basis of autism and, more critically, can be used to guide effective therapies targeted at improving social, communicative, and motor function. PMID:21467306

Aberrant Neural Connectivity during Emotional Processing Associated with Posttraumatic Stress

PubMed Central

Sadeh, Naomi; Spielberg, Jeffrey M.; Warren, Stacie L.; Miller, Gregory A.; Heller, Wendy

2014-01-01

Given the complexity of the brain, characterizing relations among distributed brain regions is likely essential to describing the neural instantiation of posttraumatic stress symptoms. This study examined patterns of functional connectivity among key brain regions implicated in the pathophysiology of posttraumatic stress disorder (PTSD) in 35 trauma-exposed adults using an emotion-word Stroop task. PTSD symptom severity (particularly hyperarousal symptoms) moderated amygdala-mPFC coupling during the processing of unpleasant words, and this moderation correlated positively with reported real-world impairment and amygdala reactivity. Reexperiencing severity moderated hippocampus-insula coupling during pleasant and unpleasant words. Results provide evidence that PTSD symptoms differentially moderate functional coupling during emotional interference and underscore the importance of examining network connectivity in research on PTSD. They suggest that hyperarousal is associated with negative mPFC-amygdala coupling and that reexperiencing is associated with altered insula-hippocampus function, patterns of connectivity that may represent separable indicators of dysfunctional inhibitory control during affective processing. PMID:25419500

Aberrant Neural Connectivity during Emotional Processing Associated with Posttraumatic Stress.

PubMed

Sadeh, Naomi; Spielberg, Jeffrey M; Warren, Stacie L; Miller, Gregory A; Heller, Wendy

2014-11-01

Given the complexity of the brain, characterizing relations among distributed brain regions is likely essential to describing the neural instantiation of posttraumatic stress symptoms. This study examined patterns of functional connectivity among key brain regions implicated in the pathophysiology of posttraumatic stress disorder (PTSD) in 35 trauma-exposed adults using an emotion-word Stroop task. PTSD symptom severity (particularly hyperarousal symptoms) moderated amygdala-mPFC coupling during the processing of unpleasant words, and this moderation correlated positively with reported real-world impairment and amygdala reactivity. Reexperiencing severity moderated hippocampus-insula coupling during pleasant and unpleasant words. Results provide evidence that PTSD symptoms differentially moderate functional coupling during emotional interference and underscore the importance of examining network connectivity in research on PTSD. They suggest that hyperarousal is associated with negative mPFC-amygdala coupling and that reexperiencing is associated with altered insula-hippocampus function, patterns of connectivity that may represent separable indicators of dysfunctional inhibitory control during affective processing.

The relationship between spatial configuration and functional connectivity of brain regions.

PubMed

Bijsterbosch, Janine Diane; Woolrich, Mark W; Glasser, Matthew F; Robinson, Emma C; Beckmann, Christian F; Van Essen, David C; Harrison, Samuel J; Smith, Stephen M

2018-02-16

Brain connectivity is often considered in terms of the communication between functionally distinct brain regions. Many studies have investigated the extent to which patterns of coupling strength between multiple neural populations relates to behaviour. For example, studies have used 'functional connectivity fingerprints' to characterise individuals' brain activity. Here, we investigate the extent to which the exact spatial arrangement of cortical regions interacts with measures of brain connectivity. We find that the shape and exact location of brain regions interact strongly with the modelling of brain connectivity, and present evidence that the spatial arrangement of functional regions is strongly predictive of non-imaging measures of behaviour and lifestyle. We believe that, in many cases, cross-subject variations in the spatial configuration of functional brain regions are being interpreted as changes in functional connectivity. Therefore, a better understanding of these effects is important when interpreting the relationship between functional imaging data and cognitive traits. © 2018, Bijsterbosch et al.

Multivariate Pattern Classification of Facial Expressions Based on Large-Scale Functional Connectivity.

PubMed

Liang, Yin; Liu, Baolin; Li, Xianglin; Wang, Peiyuan

2018-01-01

It is an important question how human beings achieve efficient recognition of others' facial expressions in cognitive neuroscience, and it has been identified that specific cortical regions show preferential activation to facial expressions in previous studies. However, the potential contributions of the connectivity patterns in the processing of facial expressions remained unclear. The present functional magnetic resonance imaging (fMRI) study explored whether facial expressions could be decoded from the functional connectivity (FC) patterns using multivariate pattern analysis combined with machine learning algorithms (fcMVPA). We employed a block design experiment and collected neural activities while participants viewed facial expressions of six basic emotions (anger, disgust, fear, joy, sadness, and surprise). Both static and dynamic expression stimuli were included in our study. A behavioral experiment after scanning confirmed the validity of the facial stimuli presented during the fMRI experiment with classification accuracies and emotional intensities. We obtained whole-brain FC patterns for each facial expression and found that both static and dynamic facial expressions could be successfully decoded from the FC patterns. Moreover, we identified the expression-discriminative networks for the static and dynamic facial expressions, which span beyond the conventional face-selective areas. Overall, these results reveal that large-scale FC patterns may also contain rich expression information to accurately decode facial expressions, suggesting a novel mechanism, which includes general interactions between distributed brain regions, and that contributes to the human facial expression recognition.

Multivariate Pattern Classification of Facial Expressions Based on Large-Scale Functional Connectivity

PubMed Central

Liang, Yin; Liu, Baolin; Li, Xianglin; Wang, Peiyuan

2018-01-01

It is an important question how human beings achieve efficient recognition of others’ facial expressions in cognitive neuroscience, and it has been identified that specific cortical regions show preferential activation to facial expressions in previous studies. However, the potential contributions of the connectivity patterns in the processing of facial expressions remained unclear. The present functional magnetic resonance imaging (fMRI) study explored whether facial expressions could be decoded from the functional connectivity (FC) patterns using multivariate pattern analysis combined with machine learning algorithms (fcMVPA). We employed a block design experiment and collected neural activities while participants viewed facial expressions of six basic emotions (anger, disgust, fear, joy, sadness, and surprise). Both static and dynamic expression stimuli were included in our study. A behavioral experiment after scanning confirmed the validity of the facial stimuli presented during the fMRI experiment with classification accuracies and emotional intensities. We obtained whole-brain FC patterns for each facial expression and found that both static and dynamic facial expressions could be successfully decoded from the FC patterns. Moreover, we identified the expression-discriminative networks for the static and dynamic facial expressions, which span beyond the conventional face-selective areas. Overall, these results reveal that large-scale FC patterns may also contain rich expression information to accurately decode facial expressions, suggesting a novel mechanism, which includes general interactions between distributed brain regions, and that contributes to the human facial expression recognition. PMID:29615882

Differential Resting-State Connectivity Patterns of the Right Anterior and Posterior Dorsolateral Prefrontal Cortices (DLPFC) in Schizophrenia.

PubMed

Chechko, Natalia; Cieslik, Edna C; Müller, Veronika I; Nickl-Jockschat, Thomas; Derntl, Birgit; Kogler, Lydia; Aleman, André; Jardri, Renaud; Sommer, Iris E; Gruber, Oliver; Eickhoff, Simon B

2018-01-01

In schizophrenia (SCZ), dysfunction of the dorsolateral prefrontal cortex (DLPFC) has been linked to the deficits in executive functions and attention. It has been suggested that, instead of considering the right DLPFC as a cohesive functional entity, it can be divided into two parts (anterior and posterior) based on its whole-brain connectivity patterns. Given these two subregions' differential association with cognitive processes, we investigated the functional connectivity (FC) profile of both subregions through resting-state data to determine whether they are differentially affected in SCZ. Resting-state magnetic resonance imaging (MRI) scans were obtained from 120 patients and 172 healthy controls (HC) at 6 different MRI sites. The results showed differential FC patterns for the anterior and posterior parts of the right executive control-related DLPFC in SCZ with the parietal, the temporal and the cerebellar regions, along with a convergent reduction of connectivity with the striatum and the occipital cortex. An increased psychopathology level was linked to a higher difference in posterior vs. anterior FC for the left IFG/anterior insula, regions involved in higher-order cognitive processes. In sum, the current analysis demonstrated that even between two neighboring clusters connectivity could be differentially disrupted in SCZ. Lacking the necessary anatomical specificity, such notions may in fact be detrimental to a proper understanding of SCZ pathophysiology.

Causal manipulation of functional connectivity in a specific neural pathway during behaviour and at rest

PubMed Central

Johnen, Vanessa M; Neubert, Franz-Xaver; Buch, Ethan R; Verhagen, Lennart; O'Reilly, Jill X; Mars, Rogier B; Rushworth, Matthew F S

2015-01-01

Correlations in brain activity between two areas (functional connectivity) have been shown to relate to their underlying structural connections. We examine the possibility that functional connectivity also reflects short-term changes in synaptic efficacy. We demonstrate that paired transcranial magnetic stimulation (TMS) near ventral premotor cortex (PMv) and primary motor cortex (M1) with a short 8-ms inter-pulse interval evoking synchronous pre- and post-synaptic activity and which strengthens interregional connectivity between the two areas in a pattern consistent with Hebbian plasticity, leads to increased functional connectivity between PMv and M1 as measured with functional magnetic resonance imaging (fMRI). Moreover, we show that strengthening connectivity between these nodes has effects on a wider network of areas, such as decreasing coupling in a parallel motor programming stream. A control experiment revealed that identical TMS pulses at identical frequencies caused no change in fMRI-measured functional connectivity when the inter-pulse-interval was too long for Hebbian-like plasticity. DOI: http://dx.doi.org/10.7554/eLife.04585.001 PMID:25664941

Distinct neural signatures detected for ADHD subtypes after controlling for micro-movements in resting state functional connectivity MRI data

PubMed Central

Fair, Damien A.; Nigg, Joel T.; Iyer, Swathi; Bathula, Deepti; Mills, Kathryn L.; Dosenbach, Nico U. F.; Schlaggar, Bradley L.; Mennes, Maarten; Gutman, David; Bangaru, Saroja; Buitelaar, Jan K.; Dickstein, Daniel P.; Di Martino, Adriana; Kennedy, David N.; Kelly, Clare; Luna, Beatriz; Schweitzer, Julie B.; Velanova, Katerina; Wang, Yu-Feng; Mostofsky, Stewart; Castellanos, F. Xavier; Milham, Michael P.

2012-01-01

In recent years, there has been growing enthusiasm that functional magnetic resonance imaging (MRI) could achieve clinical utility for a broad range of neuropsychiatric disorders. However, several barriers remain. For example, the acquisition of large-scale datasets capable of clarifying the marked heterogeneity that exists in psychiatric illnesses will need to be realized. In addition, there continues to be a need for the development of image processing and analysis methods capable of separating signal from artifact. As a prototypical hyperkinetic disorder, and movement-related artifact being a significant confound in functional imaging studies, ADHD offers a unique challenge. As part of the ADHD-200 Global Competition and this special edition of Frontiers, the ADHD-200 Consortium demonstrates the utility of an aggregate dataset pooled across five institutions in addressing these challenges. The work aimed to (1) examine the impact of emerging techniques for controlling for “micro-movements,” and (2) provide novel insights into the neural correlates of ADHD subtypes. Using support vector machine (SVM)-based multivariate pattern analysis (MVPA) we show that functional connectivity patterns in individuals are capable of differentiating the two most prominent ADHD subtypes. The application of graph-theory revealed that the Combined (ADHD-C) and Inattentive (ADHD-I) subtypes demonstrated some overlapping (particularly sensorimotor systems), but unique patterns of atypical connectivity. For ADHD-C, atypical connectivity was prominent in midline default network components, as well as insular cortex; in contrast, the ADHD-I group exhibited atypical patterns within the dlPFC regions and cerebellum. Systematic motion-related artifact was noted, and highlighted the need for stringent motion correction. Findings reported were robust to the specific motion correction strategy employed. These data suggest that resting-state functional connectivity MRI (rs-fcMRI) data can be used to characterize individual patients with ADHD and to identify neural distinctions underlying the clinical heterogeneity of ADHD. PMID:23382713

Fish utilisation of wetland nurseries with complex hydrological connectivity.

PubMed

Davis, Ben; Johnston, Ross; Baker, Ronald; Sheaves, Marcus

2012-01-01

The physical and faunal characteristics of coastal wetlands are driven by dynamics of hydrological connectivity to adjacent habitats. Wetlands on estuary floodplains are particularly dynamic, driven by a complex interplay of tidal marine connections and seasonal freshwater flooding, often with unknown consequences for fish using these habitats. To understand the patterns and subsequent processes driving fish assemblage structure in such wetlands, we examined the nature and diversity of temporal utilisation patterns at a species or genus level over three annual cycles in a tropical Australian estuarine wetland system. Four general patterns of utilisation were apparent based on CPUE and size-structure dynamics: (i) classic nursery utlisation (use by recently settled recruits for their first year) (ii) interrupted peristence (iii) delayed recruitment (iv) facultative wetland residence. Despite the small self-recruiting 'facultative wetland resident' group, wetland occupancy seems largely driven by connectivity to the subtidal estuary channel. Variable connection regimes (i.e. frequency and timing of connections) within and between different wetland units (e.g. individual pools, lagoons, swamps) will therefore interact with the diversity of species recruitment schedules to generate variable wetland assemblages in time and space. In addition, the assemblage structure is heavily modified by freshwater flow, through simultaneously curtailing persistence of the 'interrupted persistence' group, establishing connectivity for freshwater spawned members of both the 'facultative wetland resident' and 'delayed recruitment group', and apparently mediating use of intermediate nursery habitats for marine-spawned members of the 'delayed recruitment' group. The diversity of utilisation pattern and the complexity of associated drivers means assemblage compositions, and therefore ecosystem functioning, is likely to vary among years depending on variations in hydrological connectivity. Consequently, there is a need to incorporate this diversity into understandings of habitat function, conservation and management.

Fish Utilisation of Wetland Nurseries with Complex Hydrological Connectivity

PubMed Central

Davis, Ben; Johnston, Ross; Baker, Ronald; Sheaves, Marcus

2012-01-01

The physical and faunal characteristics of coastal wetlands are driven by dynamics of hydrological connectivity to adjacent habitats. Wetlands on estuary floodplains are particularly dynamic, driven by a complex interplay of tidal marine connections and seasonal freshwater flooding, often with unknown consequences for fish using these habitats. To understand the patterns and subsequent processes driving fish assemblage structure in such wetlands, we examined the nature and diversity of temporal utilisation patterns at a species or genus level over three annual cycles in a tropical Australian estuarine wetland system. Four general patterns of utilisation were apparent based on CPUE and size-structure dynamics: (i) classic nursery utlisation (use by recently settled recruits for their first year) (ii) interrupted peristence (iii) delayed recruitment (iv) facultative wetland residence. Despite the small self-recruiting ‘facultative wetland resident’ group, wetland occupancy seems largely driven by connectivity to the subtidal estuary channel. Variable connection regimes (i.e. frequency and timing of connections) within and between different wetland units (e.g. individual pools, lagoons, swamps) will therefore interact with the diversity of species recruitment schedules to generate variable wetland assemblages in time and space. In addition, the assemblage structure is heavily modified by freshwater flow, through simultaneously curtailing persistence of the ’interrupted persistence’ group, establishing connectivity for freshwater spawned members of both the ‘facultative wetland resident’ and ‘delayed recruitment group’, and apparently mediating use of intermediate nursery habitats for marine-spawned members of the ‘delayed recruitment’ group. The diversity of utilisation pattern and the complexity of associated drivers means assemblage compositions, and therefore ecosystem functioning, is likely to vary among years depending on variations in hydrological connectivity. Consequently, there is a need to incorporate this diversity into understandings of habitat function, conservation and management. PMID:23152857

Exploratory graphical models of functional and structural connectivity patterns for Alzheimer's Disease diagnosis.

PubMed

Ortiz, Andrés; Munilla, Jorge; Álvarez-Illán, Ignacio; Górriz, Juan M; Ramírez, Javier

2015-01-01

Alzheimer's Disease (AD) is the most common neurodegenerative disease in elderly people. Its development has been shown to be closely related to changes in the brain connectivity network and in the brain activation patterns along with structural changes caused by the neurodegenerative process. Methods to infer dependence between brain regions are usually derived from the analysis of covariance between activation levels in the different areas. However, these covariance-based methods are not able to estimate conditional independence between variables to factor out the influence of other regions. Conversely, models based on the inverse covariance, or precision matrix, such as Sparse Gaussian Graphical Models allow revealing conditional independence between regions by estimating the covariance between two variables given the rest as constant. This paper uses Sparse Inverse Covariance Estimation (SICE) methods to learn undirected graphs in order to derive functional and structural connectivity patterns from Fludeoxyglucose (18F-FDG) Position Emission Tomography (PET) data and segmented Magnetic Resonance images (MRI), drawn from the ADNI database, for Control, MCI (Mild Cognitive Impairment Subjects), and AD subjects. Sparse computation fits perfectly here as brain regions usually only interact with a few other areas. The models clearly show different metabolic covariation patters between subject groups, revealing the loss of strong connections in AD and MCI subjects when compared to Controls. Similarly, the variance between GM (Gray Matter) densities of different regions reveals different structural covariation patterns between the different groups. Thus, the different connectivity patterns for controls and AD are used in this paper to select regions of interest in PET and GM images with discriminative power for early AD diagnosis. Finally, functional an structural models are combined to leverage the classification accuracy. The results obtained in this work show the usefulness of the Sparse Gaussian Graphical models to reveal functional and structural connectivity patterns. This information provided by the sparse inverse covariance matrices is not only used in an exploratory way but we also propose a method to use it in a discriminative way. Regression coefficients are used to compute reconstruction errors for the different classes that are then introduced in a SVM for classification. Classification experiments performed using 68 Controls, 70 AD, and 111 MCI images and assessed by cross-validation show the effectiveness of the proposed method.

Differential Patterns of Abnormal Activity and Connectivity in the Amygdala-Prefrontal Circuitry in Bipolar-I and Bipolar-NOS Youth

ERIC Educational Resources Information Center

Ladouceur, Cecile D.; Farchione, Tiffany; Diwadkar, Vaibhav; Pruitt, Patrick; Radwan, Jacqueline; Axelson, David A.; Birmaher, Boris; Phillips, Mary L.

2011-01-01

Objective: The functioning of neural systems supporting emotion processing and regulation in youth with bipolar disorder not otherwise specified (BP-NOS) remains poorly understood. We sought to examine patterns of activity and connectivity in youth with BP-NOS relative to youth with bipolar disorder type I (BP-I) and healthy controls (HC). Method:…

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

Functional subregions of the human entorhinal cortex

PubMed Central

Maass, Anne; Berron, David; Libby, Laura A; Ranganath, Charan; Düzel, Emrah

2015-01-01

The entorhinal cortex (EC) is the primary site of interactions between the neocortex and hippocampus. Studies in rodents and nonhuman primates suggest that EC can be divided into subregions that connect differentially with perirhinal cortex (PRC) vs parahippocampal cortex (PHC) and with hippocampal subfields along the proximo-distal axis. Here, we used high-resolution functional magnetic resonance imaging at 7 Tesla to identify functional subdivisions of the human EC. In two independent datasets, PRC showed preferential intrinsic functional connectivity with anterior-lateral EC and PHC with posterior-medial EC. These EC subregions, in turn, exhibited differential connectivity with proximal and distal subiculum. In contrast, connectivity of PRC and PHC with subiculum followed not only a proximal-distal but also an anterior-posterior gradient. Our data provide the first evidence that the human EC can be divided into functional subdivisions whose functional connectivity closely parallels the known anatomical connectivity patterns of the rodent and nonhuman primate EC. DOI: http://dx.doi.org/10.7554/eLife.06426.001 PMID:26052749

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.

Characterizing Variability of Modular Brain Connectivity with Constrained Principal Component Analysis

PubMed Central

Hirayama, Jun-ichiro; Hyvärinen, Aapo; Kiviniemi, Vesa; Kawanabe, Motoaki; Yamashita, Okito

2016-01-01

Characterizing the variability of resting-state functional brain connectivity across subjects and/or over time has recently attracted much attention. Principal component analysis (PCA) serves as a fundamental statistical technique for such analyses. However, performing PCA on high-dimensional connectivity matrices yields complicated “eigenconnectivity” patterns, for which systematic interpretation is a challenging issue. Here, we overcome this issue with a novel constrained PCA method for connectivity matrices by extending the idea of the previously proposed orthogonal connectivity factorization method. Our new method, modular connectivity factorization (MCF), explicitly introduces the modularity of brain networks as a parametric constraint on eigenconnectivity matrices. In particular, MCF analyzes the variability in both intra- and inter-module connectivities, simultaneously finding network modules in a principled, data-driven manner. The parametric constraint provides a compact module-based visualization scheme with which the result can be intuitively interpreted. We develop an optimization algorithm to solve the constrained PCA problem and validate our method in simulation studies and with a resting-state functional connectivity MRI dataset of 986 subjects. The results show that the proposed MCF method successfully reveals the underlying modular eigenconnectivity patterns in more general situations and is a promising alternative to existing methods. PMID:28002474

Multimodal MR-imaging reveals large-scale structural and functional connectivity changes in profound early blindness

PubMed Central

Bauer, Corinna M.; Hirsch, Gabriella V.; Zajac, Lauren; Koo, Bang-Bon; Collignon, Olivier

2017-01-01

In the setting of profound ocular blindness, numerous lines of evidence demonstrate the existence of dramatic anatomical and functional changes within the brain. However, previous studies based on a variety of distinct measures have often provided inconsistent findings. To help reconcile this issue, we used a multimodal magnetic resonance (MR)-based imaging approach to provide complementary structural and functional information regarding this neuroplastic reorganization. This included gray matter structural morphometry, high angular resolution diffusion imaging (HARDI) of white matter connectivity and integrity, and resting state functional connectivity MRI (rsfcMRI) analysis. When comparing the brains of early blind individuals to sighted controls, we found evidence of co-occurring decreases in cortical volume and cortical thickness within visual processing areas of the occipital and temporal cortices respectively. Increases in cortical volume in the early blind were evident within regions of parietal cortex. Investigating white matter connections using HARDI revealed patterns of increased and decreased connectivity when comparing both groups. In the blind, increased white matter connectivity (indexed by increased fiber number) was predominantly left-lateralized, including between frontal and temporal areas implicated with language processing. Decreases in structural connectivity were evident involving frontal and somatosensory regions as well as between occipital and cingulate cortices. Differences in white matter integrity (as indexed by quantitative anisotropy, or QA) were also in general agreement with observed pattern changes in the number of white matter fibers. Analysis of resting state sequences showed evidence of both increased and decreased functional connectivity in the blind compared to sighted controls. Specifically, increased connectivity was evident between temporal and inferior frontal areas. Decreases in functional connectivity were observed between occipital and frontal and somatosensory-motor areas and between temporal (mainly fusiform and parahippocampus) and parietal, frontal, and other temporal areas. Correlations in white matter connectivity and functional connectivity observed between early blind and sighted controls showed an overall high degree of association. However, comparing the relative changes in white matter and functional connectivity between early blind and sighted controls did not show a significant correlation. In summary, these findings provide complimentary evidence, as well as highlight potential contradictions, regarding the nature of regional and large scale neuroplastic reorganization resulting from early onset blindness. PMID:28328939

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.

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.

Differences on Brain Connectivity in Adulthood Are Present in Subjects with Iron Deficiency Anemia in Infancy

PubMed Central

Algarin, Cecilia; Karunakaran, Keerthana Deepti; Reyes, Sussanne; Morales, Cristian; Lozoff, Betsy; Peirano, Patricio; Biswal, Bharat

2017-01-01

Iron deficiency continues to be the most prevalent micronutrient deficit worldwide. Since iron is involved in several processes including myelination, dopamine neurotransmission and neuronal metabolism, the presence of iron deficiency anemia (IDA) in infancy relates to long-lasting neurofunctional effects. There is scarce data regarding whether these effects would extend to former iron deficient anemic human adults. Resting state functional magnetic resonance imaging (fMRI) is a novel technique to explore patterns of functional connectivity. Default Mode Network (DMN), one of the resting state networks, is deeply involved in memory, social cognition and self-referential processes. The four core regions consistently identified in the DMN are the medial prefrontal cortex, posterior cingulate/retrosplenial cortex and left and right inferior parietal cortex. Therefore to investigate the DMN in former iron deficient anemic adults is a particularly useful approach to elucidate de long term effects on functional brain. We conducted this research to explore the connection between IDA in infancy and altered patterns of resting state brain functional networks in young adults. Resting-state fMRI studies were performed to 31 participants that belong to a follow-up study since infancy. Of them, 14 participants were former iron deficient anemic in infancy and 17 were controls, with mean age of 21.5 years (±1.5) and 54.8% were males. Resting-state fMRI protocol was used and the data was analyzed using the seed based connectivity statistical analysis to assess the DMN. We found that compared to controls, former iron deficient anemic subjects showed posterior DMN decreased connectivity to the left posterior cingulate cortex (PCC), whereas they exhibited increased anterior DMN connectivity to the right PCC. Differences between groups were also apparent in the left medial frontal gyrus, with former iron deficient anemic participants having increased connectivity with areas included in DMN and dorsal attention networks. These preliminary results suggest different patterns of functional connectivity between former iron deficient anemic and control young adults. Indeed, IDA in infancy, a common nutritional problem among human infants, may turn out to be important for understanding the mechanisms of cognitive alterations, common in adulthood. PMID:28326037

Contrasting brain patterns of writing-related DTI parameters, fMRI connectivity, and DTI-fMRI connectivity correlations in children with and without dysgraphia or dyslexia.

PubMed

Richards, T L; Grabowski, T J; Boord, P; Yagle, K; Askren, M; Mestre, Z; Robinson, P; Welker, O; Gulliford, D; Nagy, W; Berninger, V

2015-01-01

Based on comprehensive testing and educational history, children in grades 4-9 (on average 12 years) were diagnosed with dysgraphia (persisting handwriting impairment) or dyslexia (persisting word spelling/reading impairment) or as typical writers and readers (controls). The dysgraphia group (n = 14) and dyslexia group (n = 17) were each compared to the control group (n = 9) and to each other in separate analyses. Four brain region seed points (left occipital temporal gyrus, supramarginal gyrus, precuneus, and inferior frontal gyrus) were used in these analyses which were shown in a metaanalysis to be related to written word production on four indicators of white matter integrity and fMRI functional connectivity for four tasks (self-guided mind wandering during resting state, writing letter that follows a visually displayed letter in alphabet, writing missing letter to create a correctly spelled real word, and planning for composing after scanning on topic specified by researcher). For those DTI indicators on which the dysgraphic group or dyslexic group differed from the control group (fractional anisotropy, relative anisotropy, axial diffusivity but not radial diffusivity), correlations were computed between the DTI parameter and fMRI functional connectivity for the two writing tasks (alphabet and spelling) by seed points. Analyses, controlled for multiple comparisons, showed that (a) the control group exhibited more white matter integrity than either the dysgraphic or dyslexic group; (b) the dysgraphic and dyslexic groups showed more functional connectivity than the control group but differed in patterns of functional connectivity for task and seed point; and (c) the dysgraphic and dyslexic groups showed different patterns of significant DTI-fMRI connectivity correlations for specific seed points and written language tasks. Thus, dysgraphia and dyslexia differ in white matter integrity, fMRI functional connectivity, and white matter-gray matter correlations. Of clinical relevance, brain differences were observed in dysgraphia and dyslexia on written language tasks yoked to their defining behavioral impairments in handwriting and/or in word spelling and on the cognitive mind wandering rest condition and composition planning.

Contrasting brain patterns of writing-related DTI parameters, fMRI connectivity, and DTI–fMRI connectivity correlations in children with and without dysgraphia or dyslexia

PubMed Central

Richards, T.L.; Grabowski, T.J.; Boord, P.; Yagle, K.; Askren, M.; Mestre, Z.; Robinson, P.; Welker, O.; Gulliford, D.; Nagy, W.; Berninger, V.

2015-01-01

Based on comprehensive testing and educational history, children in grades 4–9 (on average 12 years) were diagnosed with dysgraphia (persisting handwriting impairment) or dyslexia (persisting word spelling/reading impairment) or as typical writers and readers (controls). The dysgraphia group (n = 14) and dyslexia group (n = 17) were each compared to the control group (n = 9) and to each other in separate analyses. Four brain region seed points (left occipital temporal gyrus, supramarginal gyrus, precuneus, and inferior frontal gyrus) were used in these analyses which were shown in a metaanalysis to be related to written word production on four indicators of white matter integrity and fMRI functional connectivity for four tasks (self-guided mind wandering during resting state, writing letter that follows a visually displayed letter in alphabet, writing missing letter to create a correctly spelled real word, and planning for composing after scanning on topic specified by researcher). For those DTI indicators on which the dysgraphic group or dyslexic group differed from the control group (fractional anisotropy, relative anisotropy, axial diffusivity but not radial diffusivity), correlations were computed between the DTI parameter and fMRI functional connectivity for the two writing tasks (alphabet and spelling) by seed points. Analyses, controlled for multiple comparisons, showed that (a) the control group exhibited more white matter integrity than either the dysgraphic or dyslexic group; (b) the dysgraphic and dyslexic groups showed more functional connectivity than the control group but differed in patterns of functional connectivity for task and seed point; and (c) the dysgraphic and dyslexic groups showed different patterns of significant DTI–fMRI connectivity correlations for specific seed points and written language tasks. Thus, dysgraphia and dyslexia differ in white matter integrity, fMRI functional connectivity, and white matter–gray matter correlations. Of clinical relevance, brain differences were observed in dysgraphia and dyslexia on written language tasks yoked to their defining behavioral impairments in handwriting and/or in word spelling and on the cognitive mind wandering rest condition and composition planning. PMID:26106566

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.

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.

Intrinsic Resting-State Functional Connectivity in the Human Spinal Cord at 3.0 T.

PubMed

San Emeterio Nateras, Oscar; Yu, Fang; Muir, Eric R; Bazan, Carlos; Franklin, Crystal G; Li, Wei; Li, Jinqi; Lancaster, Jack L; Duong, Timothy Q

2016-04-01

To apply resting-state functional magnetic resonance (MR) imaging to map functional connectivity of the human spinal cord. Studies were performed in nine self-declared healthy volunteers with informed consent and institutional review board approval. Resting-state functional MR imaging was performed to map functional connectivity of the human cervical spinal cord from C1 to C4 at 1 × 1 × 3-mm resolution with a 3.0-T clinical MR imaging unit. Independent component analysis (ICA) was performed to derive resting-state functional MR imaging z-score maps rendered on two-dimensional and three-dimensional images. Seed-based analysis was performed for cross validation with ICA networks by using Pearson correlation. Reproducibility analysis of resting-state functional MR imaging maps from four repeated trials in a single participant yielded a mean z score of 6 ± 1 (P < .0001). The centroid coordinates across the four trials deviated by 2 in-plane voxels ± 2 mm (standard deviation) and up to one adjacent image section ± 3 mm. ICA of group resting-state functional MR imaging data revealed prominent functional connectivity patterns within the spinal cord gray matter. There were statistically significant (z score > 3, P < .001) bilateral, unilateral, and intersegmental correlations in the ventral horns, dorsal horns, and central spinal cord gray matter. Three-dimensional surface rendering provided visualization of these components along the length of the spinal cord. Seed-based analysis showed that many ICA components exhibited strong and significant (P < .05) correlations, corroborating the ICA results. Resting-state functional MR imaging connectivity networks are qualitatively consistent with known neuroanatomic and functional structures in the spinal cord. Resting-state functional MR imaging of the human cervical spinal cord with a 3.0-T clinical MR imaging unit and standard MR imaging protocols and hardware reveals prominent functional connectivity patterns within the spinal cord gray matter, consistent with known functional and anatomic layouts of the spinal cord.

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.

Aberrant coupling within and across the default mode, task-positive, and salience network in subjects at risk for psychosis.

PubMed

Wotruba, Diana; Michels, Lars; Buechler, Roman; Metzler, Sibylle; Theodoridou, Anastasia; Gerstenberg, Miriam; Walitza, Susanne; Kollias, Spyros; Rössler, Wulf; Heekeren, Karsten

2014-09-01

The task-positive network (TPN) is anticorrelated with activity in the default mode network (DMN), and possibly reflects competition between the processing of external and internal information, while the salience network (SN) is pivotal in regulating TPN and DMN activity. Because abnormal functional connectivity in these networks has been related to schizophrenia, we tested whether alterations are also evident in subjects at risk for psychosis. Resting-state functional magnetic resonance imaging was tested in 28 subjects with basic symptoms reporting subjective cognitive-perceptive symptoms; 19 with attenuated or brief, limited psychotic symptoms; and 29 matched healthy controls. We characterized spatial differences in connectivity patterns, as well as internetwork connectivity. Right anterior insula (rAI) was selected as seed region for identifying the SN; medioprefrontal cortex (MPFC) for the DMN and TPN. The 3 groups differed in connectivity patterns between the MPFC and right dorsolateral prefrontal cortex (rDLPFC), and between the rAI and posterior cingulate cortex (PCC). In particular, the typically observed antagonistic relationship in MPFC-rDLPFC, rAI-PCC, and internetwork connectivity of DMN-TPN was absent in both at-risk groups. Notably, those connectivity patterns were associated with symptoms related to reality distortions, whereas enhanced connectivity strengths of MPFC-rDLPFC and TPN-DMN were related to poor performance in cognitive functions. We propose that the loss of a TPN-DMN anticorrelation, accompanied by an aberrant spatial extent in the DMN, TPN, and SN in the psychosis risk state, reflects the confusion of internally and externally focused states and disturbance of cognition, as seen in psychotic disorders. © The Author 2013. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Dynamic reorganization of human resting-state networks during visuospatial attention.

PubMed

Spadone, Sara; Della Penna, Stefania; Sestieri, Carlo; Betti, Viviana; Tosoni, Annalisa; Perrucci, Mauro Gianni; Romani, Gian Luca; Corbetta, Maurizio

2015-06-30

Fundamental problems in neuroscience today are understanding how patterns of ongoing spontaneous activity are modified by task performance and whether/how these intrinsic patterns influence task-evoked activation and behavior. We examined these questions by comparing instantaneous functional connectivity (IFC) and directed functional connectivity (DFC) changes in two networks that are strongly correlated and segregated at rest: the visual (VIS) network and the dorsal attention network (DAN). We measured how IFC and DFC during a visuospatial attention task, which requires dynamic selective rerouting of visual information across hemispheres, changed with respect to rest. During the attention task, the two networks remained relatively segregated, and their general pattern of within-network correlation was maintained. However, attention induced a decrease of correlation in the VIS network and an increase of the DAN→VIS IFC and DFC, especially in a top-down direction. In contrast, within the DAN, IFC was not modified by attention, whereas DFC was enhanced. Importantly, IFC modulations were behaviorally relevant. We conclude that a stable backbone of within-network functional connectivity topography remains in place when transitioning between resting wakefulness and attention selection. However, relative decrease of correlation of ongoing "idling" activity in visual cortex and synchronization between frontoparietal and visual cortex were behaviorally relevant, indicating that modulations of resting activity patterns are important for task performance. Higher order resting connectivity in the DAN was relatively unaffected during attention, potentially indicating a role for simultaneous ongoing activity as a "prior" for attention selection.

Multimodal approaches to functional connectivity in autism spectrum disorders: An integrative perspective.

PubMed

Mash, Lisa E; Reiter, Maya A; Linke, Annika C; Townsend, Jeanne; Müller, Ralph-Axel

2018-05-01

Atypical functional connectivity has been implicated in autism spectrum disorders (ASDs). However, the literature to date has been largely inconsistent, with mixed and conflicting reports of hypo- and hyper-connectivity. These discrepancies are partly due to differences between various neuroimaging modalities. Functional magnetic resonance imaging (fMRI), electroencephalography (EEG), and magnetoencephalography (MEG) measure distinct indices of functional connectivity (e.g., blood-oxygenation level-dependent [BOLD] signal vs. electrical activity). Furthermore, each method has unique benefits and disadvantages with respect to spatial and temporal resolution, vulnerability to specific artifacts, and practical implementation. Thus far, functional connectivity research on ASDs has remained almost exclusively unimodal; therefore, interpreting findings across modalities remains a challenge. Multimodal integration of fMRI, EEG, and MEG data is critical in resolving discrepancies in the literature, and working toward a unifying framework for interpreting past and future findings. This review aims to provide a theoretical foundation for future multimodal research on ASDs. First, we will discuss the merits and shortcomings of several popular theories in ASD functional connectivity research, using examples from the literature to date. Next, the neurophysiological relationships between imaging modalities, including their relationship with invasive neural recordings, will be reviewed. Finally, methodological approaches to multimodal data integration will be presented, and their future application to ASDs will be discussed. Analyses relating transient patterns of neural activity ("states") are particularly promising. This strategy provides a comparable measure across modalities, captures complex spatiotemporal patterns, and is a natural extension of recent dynamic fMRI research in ASDs. © 2017 Wiley Periodicals, Inc. Develop Neurobiol 78: 456-473, 2018. © 2017 Wiley Periodicals, Inc.

Distinctive neural processes during learning in autism.

PubMed

Schipul, Sarah E; Williams, Diane L; Keller, Timothy A; Minshew, Nancy J; Just, Marcel Adam

2012-04-01

This functional magnetic resonance imaging study compared the neural activation patterns of 18 high-functioning individuals with autism and 18 IQ-matched neurotypical control participants as they learned to perform a social judgment task. Participants learned to identify liars among pairs of computer-animated avatars uttering the same sentence but with different facial and vocal expressions, namely those that have previously been associated with lying versus truth-telling. Despite showing a behavioral learning effect similar to the control group, the autism group did not show the same pattern of decreased activation in cortical association areas as they learned the task. Furthermore, the autism group showed a significantly smaller increase in interregion synchronization of activation (functional connectivity) with learning than did the control group. Finally, the autism group had decreased structural connectivity as measured by corpus callosum size, and this measure was reliably related to functional connectivity measures. The findings suggest that cortical underconnectivity in autism may constrain the ability of the brain to rapidly adapt during learning.

Functional hierarchy underlies preferential connectivity disturbances in schizophrenia.

PubMed

Yang, Genevieve J; Murray, John D; Wang, Xiao-Jing; Glahn, David C; Pearlson, Godfrey D; Repovs, Grega; Krystal, John H; Anticevic, Alan

2016-01-12

Schizophrenia may involve an elevated excitation/inhibition (E/I) ratio in cortical microcircuits. It remains unknown how this regulatory disturbance maps onto neuroimaging findings. To address this issue, we implemented E/I perturbations within a neural model of large-scale functional connectivity, which predicted hyperconnectivity following E/I elevation. To test predictions, we examined resting-state functional MRI in 161 schizophrenia patients and 164 healthy subjects. As predicted, patients exhibited elevated functional connectivity that correlated with symptom levels, and was most prominent in association cortices, such as the fronto-parietal control network. This pattern was absent in patients with bipolar disorder (n = 73). To account for the pattern observed in schizophrenia, we integrated neurobiologically plausible, hierarchical differences in association vs. sensory recurrent neuronal dynamics into our model. This in silico architecture revealed preferential vulnerability of association networks to E/I imbalance, which we verified empirically. Reported effects implicate widespread microcircuit E/I imbalance as a parsimonious mechanism for emergent inhomogeneous dysconnectivity in schizophrenia.

Functional hierarchy underlies preferential connectivity disturbances in schizophrenia

PubMed Central

Yang, Genevieve J.; Murray, John D.; Wang, Xiao-Jing; Glahn, David C.; Pearlson, Godfrey D.; Repovs, Grega; Krystal, John H.; Anticevic, Alan

2016-01-01

Schizophrenia may involve an elevated excitation/inhibition (E/I) ratio in cortical microcircuits. It remains unknown how this regulatory disturbance maps onto neuroimaging findings. To address this issue, we implemented E/I perturbations within a neural model of large-scale functional connectivity, which predicted hyperconnectivity following E/I elevation. To test predictions, we examined resting-state functional MRI in 161 schizophrenia patients and 164 healthy subjects. As predicted, patients exhibited elevated functional connectivity that correlated with symptom levels, and was most prominent in association cortices, such as the fronto-parietal control network. This pattern was absent in patients with bipolar disorder (n = 73). To account for the pattern observed in schizophrenia, we integrated neurobiologically plausible, hierarchical differences in association vs. sensory recurrent neuronal dynamics into our model. This in silico architecture revealed preferential vulnerability of association networks to E/I imbalance, which we verified empirically. Reported effects implicate widespread microcircuit E/I imbalance as a parsimonious mechanism for emergent inhomogeneous dysconnectivity in schizophrenia. PMID:26699491

Altered resting-state amygdala functional connectivity in men with posttraumatic stress disorder

PubMed Central

Sripada, Rebecca K.; King, Anthony P.; Garfinkel, Sarah N.; Wang, Xin; Sripada, Chandra S.; Welsh, Robert C.; Liberzon, Israel

2012-01-01

Background Converging neuroimaging research suggests altered emotion neurocircuitry in individuals with posttraumatic stress disorder (PTSD). Emotion activation studies in these individuals have shown hyperactivation in emotion-related regions, including the amygdala and insula, and hypoactivation in emotion-regulation regions, including the medial prefrontal cortex (mPFC) and anterior cingulate cortex (ACC). However, few studies have examined patterns of connectivity at rest in individuals with PTSD, a potentially powerful method for illuminating brain network structure. Methods Using the amygdala as a seed region, we measured resting-state brain connectivity using 3 T functional magnetic resonance imaging in returning male veterans with PTSD and combat controls without PTSD. Results Fifteen veterans with PTSD and 14 combat controls enrolled in our study. Compared with controls, veterans with PTSD showed greater positive connectivity between the amygdala and insula, reduced positive connectivity between the amygdala and hippocampus, and reduced anticorrelation between the amygdala and dorsal ACC and rostral ACC. Limitations Only male veterans with combat exposure were tested, thus our findings cannot be generalized to women or to individuals with non–combat related PTSD. Conclusion These results demonstrate that studies of functional connectivity during resting state can discern aberrant patterns of coupling within emotion circuits and suggest a possible brain basis for emotion-processing and emotion-regulation deficits in individuals with PTSD. PMID:22313617

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.

Disrupted resting-state functional connectivity in minimally treated chronic schizophrenia.

PubMed

Wang, Xijin; Xia, Mingrui; Lai, Yunyao; Dai, Zhengjia; Cao, Qingjiu; Cheng, Zhang; Han, Xue; Yang, Lei; Yuan, Yanbo; Zhang, Yong; Li, Keqing; Ma, Hong; Shi, Chuan; Hong, Nan; Szeszko, Philip; Yu, Xin; He, Yong

2014-07-01

The pathophysiology of chronic schizophrenia may reflect long term brain changes related to the disorder. The effect of chronicity on intrinsic functional connectivity patterns in schizophrenia without the potentially confounding effect of antipsychotic medications, however, remains largely unknown. We collected resting-state fMRI data in 21 minimally treated chronic schizophrenia patients and 20 healthy controls. We computed regional functional connectivity strength for each voxel in the brain, and further divided regional functional connectivity strength into short-range regional functional connectivity strength and long-range regional functional connectivity strength. General linear models were used to detect between-group differences in these regional functional connectivity strength metrics and to further systematically investigate the relationship between these differences and clinical/behavioral variables in the patients. Compared to healthy controls, the minimally treated chronic schizophrenia patients showed an overall reduced regional functional connectivity strength especially in bilateral sensorimotor cortex, right lateral prefrontal cortex, left insula and right lingual gyrus, and these regional functional connectivity strength decreases mainly resulted from disruption of short-range regional functional connectivity strength. The minimally treated chronic schizophrenia patients also showed reduced long-range regional functional connectivity strength in the bilateral posterior cingulate cortex/precuneus, and increased long-range regional functional connectivity strength in the right lateral prefrontal cortex and lingual gyrus. Notably, disrupted short-range regional functional connectivity strength mainly correlated with duration of illness and negative symptoms, whereas disrupted long-range regional functional connectivity strength correlated with neurocognitive performance. All of the results were corrected using Monte-Carlo simulation. This exploratory study demonstrates a disruption of intrinsic functional connectivity without long-term exposure to antipsychotic medications in chronic schizophrenia. Furthermore, this disruption was connection-distance dependent, thus raising the possibility for differential neural pathways in neurocognitive impairment and psychiatric symptoms in schizophrenia. Copyright © 2014 Elsevier B.V. All rights reserved.

Non-Inferential Multi-Subject Study of Functional Connectivity during Visual Stimulation.

PubMed

Esposito, F; Cirillo, M; Aragri, A; Caranci, F; Cirillo, L; Di Salle, F; Cirillo, S

2007-01-31

Independent component analysis (ICA) is a powerful technique for the multivariate, non-inferential, data-driven analysis of functional magnetic resonance imaging (fMRI) data-sets. The non-inferential nature of ICA makes this a suitable technique for the study of complex mental states whose temporal evolution would be difficult to describe analytically in terms of classical statistical regressors. Taking advantage of this feature, ICA can extract a number of functional connectivity patterns regardless of the task executed by the subject. The technique is so powerful that functional connectivity patterns can be derived even when the subject is just resting in the scanner, opening the opportunity for functional investigation of the human mind at its basal "default" state, which has been proposed to be altered in several brain disorders. However, one major drawback of ICA consists in the difficulty of managing its results, which are not represented by a single functional image as in inferential studies. This produces the need for a classification of ICA results and exacerbates the difficulty of obtaining group "averaged" functional connectivity patterns, while preserving the interpretation of individual differences. Addressing the subject-level variability in the very same framework of "grouping" appears to be a favourable approach towards the clinical evaluation and application of ICA-based methodologies. Here we present a novel strategy for group-level ICA analyses, namely the self-organizing group-level ICA (sog-ICA), which is used on visual activation fMRI data from a block-design experiment repeated on six subjects. We propose the sog-ICA as a multi-subject analysis tool for grouping ICA data while assessing the similarity and variability of the fMRI results of individual subject decompositions.

Efficiency of weak brain connections support general cognitive functioning.

PubMed

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

2014-09-01

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

Brain regions with abnormal network properties in severe epilepsy of Lennox-Gastaut phenotype: Multivariate analysis of task-free fMRI.

PubMed

Pedersen, Mangor; Curwood, Evan K; Archer, John S; Abbott, David F; Jackson, Graeme D

2015-11-01

Lennox-Gastaut syndrome, and the similar but less tightly defined Lennox-Gastaut phenotype, describe patients with severe epilepsy, generalized epileptic discharges, and variable intellectual disability. Our previous functional neuroimaging studies suggest that abnormal diffuse association network activity underlies the epileptic discharges of this clinical phenotype. Herein we use a data-driven multivariate approach to determine the spatial changes in local and global networks of patients with severe epilepsy of the Lennox-Gastaut phenotype. We studied 9 adult patients and 14 controls. In 20 min of task-free blood oxygen level-dependent functional magnetic resonance imaging data, two metrics of functional connectivity were studied: Regional homogeneity or local connectivity, a measure of concordance between each voxel to a focal cluster of adjacent voxels; and eigenvector centrality, a global connectivity estimate designed to detect important neural hubs. Multivariate pattern analysis of these data in a machine-learning framework was used to identify spatial features that classified disease subjects. Multivariate pattern analysis was 95.7% accurate in classifying subjects for both local and global connectivity measures (22/23 subjects correctly classified). Maximal discriminating features were the following: increased local connectivity in frontoinsular and intraparietal areas; increased global connectivity in posterior association areas; decreased local connectivity in sensory (visual and auditory) and medial frontal cortices; and decreased global connectivity in the cingulate cortex, striatum, hippocampus, and pons. Using a data-driven analysis method in task-free functional magnetic resonance imaging, we show increased connectivity in critical areas of association cortex and decreased connectivity in primary cortex. This supports previous findings of a critical role for these association cortical regions as a final common pathway in generating the Lennox-Gastaut phenotype. Abnormal function of these areas is likely to be important in explaining the intellectual problems characteristic of this disorder. Wiley Periodicals, Inc. © 2015 International League Against Epilepsy.

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.

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.

Schaffer Collateral Inputs to CA1 Excitatory and Inhibitory Neurons Follow Different Connectivity Rules.

PubMed

Kwon, Osung; Feng, Linqing; Druckmann, Shaul; Kim, Jinhyun

2018-05-30

Neural circuits, governed by a complex interplay between excitatory and inhibitory neurons, are the substrate for information processing, and the organization of synaptic connectivity in neural network is an important determinant of circuit function. Here, we analyzed the fine structure of connectivity in hippocampal CA1 excitatory and inhibitory neurons innervated by Schaffer collaterals (SCs) using mGRASP in male mice. Our previous study revealed spatially structured synaptic connectivity between CA3 and CA1 pyramidal cells (PCs). Surprisingly, parvalbumin-positive interneurons (PVs) showed a significantly more random pattern spatial structure. Notably, application of Peters' rule for synapse prediction by random overlap between axons and dendrites enhanced structured connectivity in PCs, but, by contrast, made the connectivity pattern in PVs more random. In addition, PCs in a deep sublayer of striatum pyramidale appeared more highly structured than PCs in superficial layers, and little or no sublayer specificity was found in PVs. Our results show that CA1 excitatory PCs and inhibitory PVs innervated by the same SC inputs follow different connectivity rules. The different organizations of fine scale structured connectivity in hippocampal excitatory and inhibitory neurons provide important insights into the development and functions of neural networks. SIGNIFICANCE STATEMENT Understanding how neural circuits generate behavior is one of the central goals of neuroscience. An important component of this endeavor is the mapping of fine-scale connection patterns that underlie, and help us infer, signal processing in the brain. Here, using our recently developed synapse detection technology (mGRASP and neuTube), we provide detailed profiles of synaptic connectivity in excitatory (CA1 pyramidal) and inhibitory (CA1 parvalbumin-positive) neurons innervated by the same presynaptic inputs (CA3 Schaffer collaterals). Our results reveal that these two types of CA1 neurons follow different connectivity patterns. Our new evidence for differently structured connectivity at a fine scale in hippocampal excitatory and inhibitory neurons provides a better understanding of hippocampal networks and will guide theoretical and experimental studies. Copyright © 2018 the authors 0270-6474/18/385140-13$15.00/0.

Disentangling dynamic networks: Separated and joint expressions of functional connectivity patterns in time.

PubMed

Leonardi, Nora; Shirer, William R; Greicius, Michael D; Van De Ville, Dimitri

2014-12-01

Resting-state functional connectivity (FC) is highly variable across the duration of a scan. Groups of coevolving connections, or reproducible patterns of dynamic FC (dFC), have been revealed in fluctuating FC by applying unsupervised learning techniques. Based on results from k-means clustering and sliding-window correlations, it has recently been hypothesized that dFC may cycle through several discrete FC states. Alternatively, it has been proposed to represent dFC as a linear combination of multiple FC patterns using principal component analysis. As it is unclear whether sparse or nonsparse combinations of FC patterns are most appropriate, and as this affects their interpretation and use as markers of cognitive processing, the goal of our study was to evaluate the impact of sparsity by performing an empirical evaluation of simulated, task-based, and resting-state dFC. To this aim, we applied matrix factorizations subject to variable constraints in the temporal domain and studied both the reproducibility of ensuing representations of dFC and the expression of FC patterns over time. During subject-driven tasks, dFC was well described by alternating FC states in accordance with the nature of the data. The estimated FC patterns showed a rich structure with combinations of known functional networks enabling accurate identification of three different tasks. During rest, dFC was better described by multiple FC patterns that overlap. The executive control networks, which are critical for working memory, appeared grouped alternately with externally or internally oriented networks. These results suggest that combinations of FC patterns can provide a meaningful way to disentangle resting-state dFC. © 2014 The Authors. Human Brain Mapping published by Wiley Periodicals, Inc.

Patterns of thought: Population variation in the associations between large-scale network organisation and self-reported experiences at rest.

PubMed

Wang, Hao-Ting; Bzdok, Danilo; Margulies, Daniel; Craddock, Cameron; Milham, Michael; Jefferies, Elizabeth; Smallwood, Jonathan

2018-08-01

Contemporary cognitive neuroscience recognises unconstrained processing varies across individuals, describing variation in meaningful attributes, such as intelligence. It may also have links to patterns of on-going experience. This study examined whether dimensions of population variation in different modes of unconstrained processing can be described by the associations between patterns of neural activity and self-reports of experience during the same period. We selected 258 individuals from a publicly available data set who had measures of resting-state functional magnetic resonance imaging, and self-reports of experience during the scan. We used machine learning to determine patterns of association between the neural and self-reported data, finding variation along four dimensions. 'Purposeful' experiences were associated with lower connectivity - in particular default mode and limbic networks were less correlated with attention and sensorimotor networks. 'Emotional' experiences were associated with higher connectivity, especially between limbic and ventral attention networks. Experiences focused on themes of 'personal importance' were associated with reduced functional connectivity within attention and control systems. Finally, visual experiences were associated with stronger connectivity between visual and other networks, in particular the limbic system. Some of these patterns had contrasting links with cognitive function as assessed in a separate laboratory session - purposeful thinking was linked to greater intelligence and better abstract reasoning, while a focus on personal importance had the opposite relationship. Together these findings are consistent with an emerging literature on unconstrained states and also underlines that these states are heterogeneous, with distinct modes of population variation reflecting the interplay of different large-scale networks. Copyright © 2018 Elsevier Inc. All rights reserved.

Resting-state hemodynamics are spatiotemporally coupled to synchronized and symmetric neural activity in excitatory neurons.

PubMed

Ma, Ying; Shaik, Mohammed A; Kozberg, Mariel G; Kim, Sharon H; Portes, Jacob P; Timerman, Dmitriy; Hillman, Elizabeth M C

2016-12-27

Brain hemodynamics serve as a proxy for neural activity in a range of noninvasive neuroimaging techniques including functional magnetic resonance imaging (fMRI). In resting-state fMRI, hemodynamic fluctuations have been found to exhibit patterns of bilateral synchrony, with correlated regions inferred to have functional connectivity. However, the relationship between resting-state hemodynamics and underlying neural activity has not been well established, making the neural underpinnings of functional connectivity networks unclear. In this study, neural activity and hemodynamics were recorded simultaneously over the bilateral cortex of awake and anesthetized Thy1-GCaMP mice using wide-field optical mapping. Neural activity was visualized via selective expression of the calcium-sensitive fluorophore GCaMP in layer 2/3 and 5 excitatory neurons. Characteristic patterns of resting-state hemodynamics were accompanied by more rapidly changing bilateral patterns of resting-state neural activity. Spatiotemporal hemodynamics could be modeled by convolving this neural activity with hemodynamic response functions derived through both deconvolution and gamma-variate fitting. Simultaneous imaging and electrophysiology confirmed that Thy1-GCaMP signals are well-predicted by multiunit activity. Neurovascular coupling between resting-state neural activity and hemodynamics was robust and fast in awake animals, whereas coupling in urethane-anesthetized animals was slower, and in some cases included lower-frequency (<0.04 Hz) hemodynamic fluctuations that were not well-predicted by local Thy1-GCaMP recordings. These results support that resting-state hemodynamics in the awake and anesthetized brain are coupled to underlying patterns of excitatory neural activity. The patterns of bilaterally-symmetric spontaneous neural activity revealed by wide-field Thy1-GCaMP imaging may depict the neural foundation of functional connectivity networks detected in resting-state fMRI.

Resting-state hemodynamics are spatiotemporally coupled to synchronized and symmetric neural activity in excitatory neurons

PubMed Central

Ma, Ying; Shaik, Mohammed A.; Kozberg, Mariel G.; Portes, Jacob P.; Timerman, Dmitriy

2016-01-01

Brain hemodynamics serve as a proxy for neural activity in a range of noninvasive neuroimaging techniques including functional magnetic resonance imaging (fMRI). In resting-state fMRI, hemodynamic fluctuations have been found to exhibit patterns of bilateral synchrony, with correlated regions inferred to have functional connectivity. However, the relationship between resting-state hemodynamics and underlying neural activity has not been well established, making the neural underpinnings of functional connectivity networks unclear. In this study, neural activity and hemodynamics were recorded simultaneously over the bilateral cortex of awake and anesthetized Thy1-GCaMP mice using wide-field optical mapping. Neural activity was visualized via selective expression of the calcium-sensitive fluorophore GCaMP in layer 2/3 and 5 excitatory neurons. Characteristic patterns of resting-state hemodynamics were accompanied by more rapidly changing bilateral patterns of resting-state neural activity. Spatiotemporal hemodynamics could be modeled by convolving this neural activity with hemodynamic response functions derived through both deconvolution and gamma-variate fitting. Simultaneous imaging and electrophysiology confirmed that Thy1-GCaMP signals are well-predicted by multiunit activity. Neurovascular coupling between resting-state neural activity and hemodynamics was robust and fast in awake animals, whereas coupling in urethane-anesthetized animals was slower, and in some cases included lower-frequency (<0.04 Hz) hemodynamic fluctuations that were not well-predicted by local Thy1-GCaMP recordings. These results support that resting-state hemodynamics in the awake and anesthetized brain are coupled to underlying patterns of excitatory neural activity. The patterns of bilaterally-symmetric spontaneous neural activity revealed by wide-field Thy1-GCaMP imaging may depict the neural foundation of functional connectivity networks detected in resting-state fMRI. PMID:27974609

Structural connectivity allows for multi-threading during rest: the structure of the cortex leads to efficient alternation between resting state exploratory behavior and default mode processing.

PubMed

Senden, Mario; Goebel, Rainer; Deco, Gustavo

2012-05-01

Despite the absence of stimulation or task conditions the cortex exhibits highly structured spatio-temporal activity patterns. These patterns are known as resting state networks (RSNs) and emerge as low-frequency fluctuations (<0.1 Hz) observed in the fMRI signal of human subjects during rest. We are interested in the relationship between structural connectivity of the cortex and the fluctuations exhibited during resting conditions. We are especially interested in the effect of degree of connectivity on resting state dynamics as the default mode network (DMN) is highly connected. We find in experimental resting fMRI data that the DMN is the functional network that is most frequently active and for the longest time. In large-scale computational simulations of the cortex based on the corresponding underlying DTI/DSI based neuroanatomical connectivity matrix, we additionally find a strong correlation between the mean degree of functional networks and the proportion of time they are active. By artificially modifying different types of neuroanatomical connectivity matrices in the model, we were able to demonstrate that only models based on structural connectivity containing hubs give rise to this relationship. We conclude that, during rest, the cortex alternates efficiently between explorations of its externally oriented functional repertoire and internally oriented processing as a consequence of the DMN's high degree of connectivity. Copyright © 2012 Elsevier Inc. All rights reserved.

Dynamic Resting-State Functional Connectivity in Major Depression.

PubMed

Kaiser, Roselinde H; Whitfield-Gabrieli, Susan; Dillon, Daniel G; Goer, Franziska; Beltzer, Miranda; Minkel, Jared; Smoski, Moria; Dichter, Gabriel; Pizzagalli, Diego A

2016-06-01

Major depressive disorder (MDD) is characterized by abnormal resting-state functional connectivity (RSFC), especially in medial prefrontal cortical (MPFC) regions of the default network. However, prior research in MDD has not examined dynamic changes in functional connectivity as networks form, interact, and dissolve over time. We compared unmedicated individuals with MDD (n=100) to control participants (n=109) on dynamic RSFC (operationalized as SD in RSFC over a series of sliding windows) of an MPFC seed region during a resting-state functional magnetic resonance imaging scan. Among participants with MDD, we also investigated the relationship between symptom severity and RSFC. Secondary analyses probed the association between dynamic RSFC and rumination. Results showed that individuals with MDD were characterized by decreased dynamic (less variable) RSFC between MPFC and regions of parahippocampal gyrus within the default network, a pattern related to sustained positive connectivity between these regions across sliding windows. In contrast, the MDD group exhibited increased dynamic (more variable) RSFC between MPFC and regions of insula, and higher severity of depression was related to increased dynamic RSFC between MPFC and dorsolateral prefrontal cortex. These patterns of highly variable RSFC were related to greater frequency of strong positive and negative correlations in activity across sliding windows. Secondary analyses indicated that increased dynamic RSFC between MPFC and insula was related to higher levels of recent rumination. These findings provide initial evidence that depression, and ruminative thinking in depression, are related to abnormal patterns of fluctuating communication among brain systems involved in regulating attention and self-referential thinking.

Functional Connectivity Mapping in the Animal Model: Principles and Applications of Resting-State fMRI

PubMed Central

Gorges, Martin; Roselli, Francesco; Müller, Hans-Peter; Ludolph, Albert C.; Rasche, Volker; Kassubek, Jan

2017-01-01

“Resting-state” fMRI has substantially contributed to the understanding of human and non-human functional brain organization by the analysis of correlated patterns in spontaneous activity within dedicated brain systems. Spontaneous neural activity is indirectly measured from the blood oxygenation level-dependent signal as acquired by echo planar imaging, when subjects quietly “resting” in the scanner. Animal models including disease or knockout models allow a broad spectrum of experimental manipulations not applicable in humans. The non-invasive fMRI approach provides a promising tool for cross-species comparative investigations. This review focuses on the principles of “resting-state” functional connectivity analysis and its applications to living animals. The translational aspect from in vivo animal models toward clinical applications in humans is emphasized. We introduce the fMRI-based investigation of the non-human brain’s hemodynamics, the methodological issues in the data postprocessing, and the functional data interpretation from different abstraction levels. The longer term goal of integrating fMRI connectivity data with structural connectomes obtained with tracing and optical imaging approaches is presented and will allow the interrogation of fMRI data in terms of directional flow of information and may identify the structural underpinnings of observed functional connectivity patterns. PMID:28539914

The Dissociative Subtype of Posttraumatic Stress Disorder: Unique Resting-State Functional Connectivity of Basolateral and Centromedial Amygdala Complexes

PubMed Central

Nicholson, Andrew A; Densmore, Maria; Frewen, Paul A; Théberge, Jean; Neufeld, Richard WJ; McKinnon, Margaret C; Lanius, Ruth A

2015-01-01

Previous studies point towards differential connectivity patterns among basolateral (BLA) and centromedial (CMA) amygdala regions in patients with posttraumatic stress disorder (PTSD) as compared with controls. Here we describe the first study to compare directly connectivity patterns of the BLA and CMA complexes between PTSD patients with and without the dissociative subtype (PTSD+DS and PTSD−DS, respectively). Amygdala connectivity to regulatory prefrontal regions and parietal regions involved in consciousness and proprioception were expected to differ between these two groups based on differential limbic regulation and behavioral symptoms. PTSD patients (n=49) with (n=13) and without (n=36) the dissociative subtype and age-matched healthy controls (n=40) underwent resting-state fMRI. Bilateral BLA and CMA connectivity patterns were compared using a seed-based approach via SPM Anatomy Toolbox. Among patients with PTSD, the PTSD+DS group exhibited greater amygdala functional connectivity to prefrontal regions involved in emotion regulation (bilateral BLA and left CMA to the middle frontal gyrus and bilateral CMA to the medial frontal gyrus) as compared with the PTSD−DS group. In addition, the PTSD+DS group showed greater amygdala connectivity to regions involved in consciousness, awareness, and proprioception—implicated in depersonalization and derealization (left BLA to superior parietal lobe and cerebellar culmen; left CMA to dorsal posterior cingulate and precuneus). Differences in amygdala complex connectivity to specific brain regions parallel the unique symptom profiles of the PTSD subgroups and point towards unique biological markers of the dissociative subtype of PTSD. PMID:25790021

Network Disruption and Cerebrospinal Fluid Amyloid-Beta and Phospho-Tau Levels in Mild Cognitive Impairment.

PubMed

Canuet, Leonides; Pusil, Sandra; López, María Eugenia; Bajo, Ricardo; Pineda-Pardo, José Ángel; Cuesta, Pablo; Gálvez, Gerardo; Gaztelu, José María; Lourido, Daniel; García-Ribas, Guillermo; Maestú, Fernando

2015-07-15

Synaptic dysfunction is a core deficit in Alzheimer's disease, preceding hallmark pathological abnormalities. Resting-state magnetoencephalography (MEG) was used to assess whether functional connectivity patterns, as an index of synaptic dysfunction, are associated with CSF biomarkers [i.e., phospho-tau (p-tau) and amyloid beta (Aβ42) levels]. We studied 12 human subjects diagnosed with mild cognitive impairment due to Alzheimer's disease, comparing those with normal and abnormal CSF levels of the biomarkers. We also evaluated the association between aberrant functional connections and structural connectivity abnormalities, measured with diffusion tensor imaging, as well as the convergent impact of cognitive deficits and CSF variables on network disorganization. One-third of the patients converted to Alzheimer's disease during a follow-up period of 2.5 years. Patients with abnomal CSF p-tau and Aβ42 levels exhibited both reduced and increased functional connectivity affecting limbic structures such as the anterior/posterior cingulate cortex, orbitofrontal cortex, and medial temporal areas in different frequency bands. A reduction in posterior cingulate functional connectivity mediated by p-tau was associated with impaired axonal integrity of the hippocampal cingulum. We noted that several connectivity abnormalities were predicted by CSF biomarkers and cognitive scores. These preliminary results indicate that CSF markers of amyloid deposition and neuronal injury in early Alzheimer's disease associate with a dual pattern of cortical network disruption, affecting key regions of the default mode network and the temporal cortex. MEG is useful to detect early synaptic dysfunction associated with Alzheimer's disease brain pathology in terms of functional network organization. In this preliminary study, we used magnetoencephalography and an integrative approach to explore the impact of CSF biomarkers, neuropsychological scores, and white matter structural abnormalities on neural function in mild cognitive impairment. Disruption in functional connectivity between several pairs of cortical regions associated with abnormal levels of biomarkers, cognitive deficits, or with impaired axonal integrity of hippocampal tracts. Amyloid deposition and tau protein-related neuronal injury in early Alzheimer's disease are associated with synaptic dysfunction and a dual pattern of cortical network disorganization (i.e., desynchronization and hypersynchronization) that affects key regions of the default mode network and temporal areas. Copyright © 2015 the authors 0270-6474/15/3510326-06$15.00/0.

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.

Neural traces of stress: cortisol related sustained enhancement of amygdala-hippocampal functional connectivity

PubMed Central

Vaisvaser, Sharon; Lin, Tamar; Admon, Roee; Podlipsky, Ilana; Greenman, Yona; Stern, Naftali; Fruchter, Eyal; Wald, Ilan; Pine, Daniel S.; Tarrasch, Ricardo; Bar-Haim, Yair; Hendler, Talma

2013-01-01

Stressful experiences modulate neuro-circuitry function, and the temporal trajectory of these alterations, elapsing from early disturbances to late recovery, heavily influences resilience and vulnerability to stress. Such effects of stress may depend on processes that are engaged during resting-state, through active recollection of past experiences and anticipation of future events, all known to involve the default mode network (DMN). By inducing social stress and acquiring resting-state functional magnetic resonance imaging (fMRI) before stress, immediately following it, and 2 h later, we expanded the time-window for examining the trajectory of the stress response. Throughout the study repeated cortisol samplings and self-reports of stress levels were obtained from 51 healthy young males. Post-stress alterations were investigated by whole brain resting-state functional connectivity (rsFC) of two central hubs of the DMN: the posterior cingulate cortex (PCC) and hippocampus. Results indicate a ’recovery’ pattern of DMN connectivity, in which all alterations, ascribed to the intervening stress, returned to pre-stress levels. The only exception to this pattern was a stress-induced rise in amygdala-hippocampal connectivity, which was sustained for as long as 2 h following stress induction. Furthermore, this sustained enhancement of limbic connectivity was inversely correlated to individual stress-induced cortisol responsiveness (AUCi) and characterized only the group lacking such increased cortisol (i.e., non-responders). Our observations provide evidence of a prolonged post-stress response profile, characterized by both the comprehensive balance of most DMN functional connections and the distinct time and cortisol dependent ascent of intra-limbic connectivity. These novel insights into neuro-endocrine relations are another milestone in the ongoing search for individual markers in stress-related psychopathologies. PMID:23847492

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

PubMed

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

2018-01-01

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

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.

Generation of optimal artificial neural networks using a pattern search algorithm: application to approximation of chemical systems.

PubMed

Ihme, Matthias; Marsden, Alison L; Pitsch, Heinz

2008-02-01

A pattern search optimization method is applied to the generation of optimal artificial neural networks (ANNs). Optimization is performed using a mixed variable extension to the generalized pattern search method. This method offers the advantage that categorical variables, such as neural transfer functions and nodal connectivities, can be used as parameters in optimization. When used together with a surrogate, the resulting algorithm is highly efficient for expensive objective functions. Results demonstrate the effectiveness of this method in optimizing an ANN for the number of neurons, the type of transfer function, and the connectivity among neurons. The optimization method is applied to a chemistry approximation of practical relevance. In this application, temperature and a chemical source term are approximated as functions of two independent parameters using optimal ANNs. Comparison of the performance of optimal ANNs with conventional tabulation methods demonstrates equivalent accuracy by considerable savings in memory storage. The architecture of the optimal ANN for the approximation of the chemical source term consists of a fully connected feedforward network having four nonlinear hidden layers and 117 synaptic weights. An equivalent representation of the chemical source term using tabulation techniques would require a 500 x 500 grid point discretization of the parameter space.

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.

A time-frequency analysis of the dynamics of cortical networks of sleep spindles from MEG-EEG recordings

PubMed Central

Zerouali, Younes; Lina, Jean-Marc; Sekerovic, Zoran; Godbout, Jonathan; Dube, Jonathan; Jolicoeur, Pierre; Carrier, Julie

2014-01-01

Sleep spindles are a hallmark of NREM sleep. They result from a widespread thalamo-cortical loop and involve synchronous cortical networks that are still poorly understood. We investigated whether brain activity during spindles can be characterized by specific patterns of functional connectivity among cortical generators. For that purpose, we developed a wavelet-based approach aimed at imaging the synchronous oscillatory cortical networks from simultaneous MEG-EEG recordings. First, we detected spindles on the EEG and extracted the corresponding frequency-locked MEG activity under the form of an analytic ridge signal in the time-frequency plane (Zerouali et al., 2013). Secondly, we performed source reconstruction of the ridge signal within the Maximum Entropy on the Mean framework (Amblard et al., 2004), yielding a robust estimate of the cortical sources producing observed oscillations. Lastly, we quantified functional connectivity among cortical sources using phase-locking values. The main innovations of this methodology are (1) to reveal the dynamic behavior of functional networks resolved in the time-frequency plane and (2) to characterize functional connectivity among MEG sources through phase interactions. We showed, for the first time, that the switch from fast to slow oscillatory mode during sleep spindles is required for the emergence of specific patterns of connectivity. Moreover, we show that earlier synchrony during spindles was associated with mainly intra-hemispheric connectivity whereas later synchrony was associated with global long-range connectivity. We propose that our methodology can be a valuable tool for studying the connectivity underlying neural processes involving sleep spindles, such as memory, plasticity or aging. PMID:25389381

The neurogenetic frontier--lessons from misbehaving zebrafish.

PubMed

Burgess, Harold A; Granato, Michael

2008-11-01

One of the central questions in neuroscience is how refined patterns of connectivity in the brain generate and monitor behavior. Genetic mutations can influence neural circuits by disrupting differentiation or maintenance of component neuronal cells or by altering functional patterns of nervous system connectivity. Mutagenesis screens therefore have the potential to reveal not only the molecular underpinnings of brain development and function, but to illuminate the cellular basis of behavior. Practical considerations make the zebrafish an organism of choice for undertaking forward genetic analysis of behavior. The powerful array of experimental tools at the disposal of the zebrafish researcher makes it possible to link molecular function to neuronal properties that underlie behavior. This review focuses on specific challenges to isolating and analyzing behavioral mutants in zebrafish.

The neurogenetic frontier—lessons from misbehaving zebrafish

PubMed Central

Granato, Michael

2008-01-01

One of the central questions in neuroscience is how refined patterns of connectivity in the brain generate and monitor behavior. Genetic mutations can influence neural circuits by disrupting differentiation or maintenance of component neuronal cells or by altering functional patterns of nervous system connectivity. Mutagenesis screens therefore have the potential to reveal not only the molecular underpinnings of brain development and function, but to illuminate the cellular basis of behavior. Practical considerations make the zebrafish an organism of choice for undertaking forward genetic analysis of behavior. The powerful array of experimental tools at the disposal of the zebrafish researcher makes it possible to link molecular function to neuronal properties that underlie behavior. This review focuses on specific challenges to isolating and analyzing behavioral mutants in zebrafish. PMID:18836206

A birds-eye view of biological connectivity in mangrove systems

NASA Astrophysics Data System (ADS)

Buelow, Christina; Sheaves, Marcus

2015-01-01

Considerable advances in understanding of biological connectivity have flowed from studies of fish-facilitated connectivity within the coastal ecosystem mosaic. However, there are limits to the information that fish can provide on connectivity. Mangrove-bird communities have the potential to connect coastal habitats in different ways and at different scales than fish, so incorporation of these links into our models of coastal ecosystem mosaics affords the opportunity to greatly increase the breadth of our understanding. We review the habitat and foraging requirements of mangrove-bird functional groups to understand how bird use of mangroves facilitates biological connectivity in coastal ecosystem mosaics, and how that connectivity adds to the diversity and complexity of ecological processes in mangrove ecosystems. Avian biological connectivity is primarily characterized by foraging behavior and habitat/resource requirements. Therefore, the consequence of bird links for coastal ecosystem functioning largely depends on patterns of habitat use and foraging, and potentially influences nutrient cycling, top-down control and genetic information linkage. Habitats that experience concentrated bird guano deposition have high levels of nitrogen and phosphorus, placing particular importance on the consequences of avian nutrient translocation and subsidization for coastal ecosystem functioning. High mobility allows mangrove-bird communities to link mangrove forests to other mangrove, terrestrial and marine-pelagic systems. Therefore, the spatial scale of coastal connectivity facilitated by birds is substantially more extensive than fish-facilitated connectivity. In particular, migratory birds link habitats at regional, continental and inter-continental scales as they travel among seasonally available feeding areas from breeding grounds to non-breeding grounds; scales at which there are few fish equivalents. Knowledge of the nature and patterns of fish connectivity have contributed to shifting the initial, historical perception of mangrove-ecosystem functioning from that of a simple system based on nutrient and energy retention, to a view that includes fish-facilitated energy export. In a similar way, understanding the nature and implications of mangrove connectivity through bird movements and migrations affords new possibilities for revising our view of the extent of functional links between mangroves and other ecosystems.

A supplementary functional connectivity microstate attached to the default mode network in depression revealed by resting-state magnetoencephalography.

PubMed

Zhang, Siqi; Tian, Shui; Chattun, Mohammad Ridwan; Tang, Hao; Yan, Rui; Bi, Kun; Yao, Zhijian; Lu, Qing

2018-04-20

Default mode network (DMN) has discernable involvement in the representation of negative, self-referential information in depression. Both increased and decreased resting-state functional connectivity between the anterior and posterior DMN have been observed in depression. These conflicting connectivity differences necessitated further exploration of the resting-state DMN dysfunction in depression. Hence, we investigated the time-varying dynamic interactions within the DMN via functional connectivity microstates in a sub-second level. 25 patients with depression and 25 matched healthy controls were enrolled in the MEG analysis. Spherical K-means algorithms embedded within an iterative optimization frame were applied to sliding windowed correlation matrices, resulting in sub-second alternations of two functional connectivity microstates for groups and highlighting the presence of functional variability. In the power dominant state, depressed patients showed a transient decreased pattern that reflected inter/intra-subnetwork deregulation. A supplementary negatively correlated state simultaneously presented with increased connectivity between the ventromedial prefrontal cortex (vmPFC) and the posterior cingulate cortex (PCC), two core nodes for the anterior and posterior DMN respectively. Additionally, depressed patients stayed longer in the supplementary microstate compared to healthy controls. During the time spent in the supplementary microstate, an attempt to compensate for the aberrant effect of vmPFC on PCC across DMN subnetworks was possibly made to balance the self-related processes disturbed by the dominant pattern. The functional compensation mechanism of the supplementary microstate attached to the dominant disrupted one provided a possible explanation to the existing inconsistent findings between the anterior and posterior DMN in depression. Copyright © 2018 Elsevier Inc. All rights reserved.

Intrinsic Functional Connectivity Patterns Predict Consciousness Level and Recovery Outcome in Acquired Brain Injury

PubMed Central

Wu, Xuehai; Zou, Qihong; Hu, Jin; Tang, Weijun; Mao, Ying; Gao, Liang; Zhu, Jianhong; Jin, Yi; Wu, Xin; Lu, Lu; Zhang, Yaojun; Zhang, Yao; Dai, Zhengjia; Gao, Jia-Hong; Weng, Xuchu; Northoff, Georg; Giacino, Joseph T.; He, Yong

2015-01-01

For accurate diagnosis and prognostic prediction of acquired brain injury (ABI), it is crucial to understand the neurobiological mechanisms underlying loss of consciousness. However, there is no consensus on which regions and networks act as biomarkers for consciousness level and recovery outcome in ABI. Using resting-state fMRI, we assessed intrinsic functional connectivity strength (FCS) of whole-brain networks in a large sample of 99 ABI patients with varying degrees of consciousness loss (including fully preserved consciousness state, minimally conscious state, unresponsive wakefulness syndrome/vegetative state, and coma) and 34 healthy control subjects. Consciousness level was evaluated using the Glasgow Coma Scale and Coma Recovery Scale-Revised on the day of fMRI scanning; recovery outcome was assessed using the Glasgow Outcome Scale 3 months after the fMRI scanning. One-way ANOVA of FCS, Spearman correlation analyses between FCS and the consciousness level and recovery outcome, and FCS-based multivariate pattern analysis were performed. We found decreased FCS with loss of consciousness primarily distributed in the posterior cingulate cortex/precuneus (PCC/PCU), medial prefrontal cortex, and lateral parietal cortex. The FCS values of these regions were significantly correlated with consciousness level and recovery outcome. Multivariate support vector machine discrimination analysis revealed that the FCS patterns predicted whether patients with unresponsive wakefulness syndrome/vegetative state and coma would regain consciousness with an accuracy of 81.25%, and the most discriminative region was the PCC/PCU. These findings suggest that intrinsic functional connectivity patterns of the human posteromedial cortex could serve as a potential indicator for consciousness level and recovery outcome in individuals with ABI. SIGNIFICANCE STATEMENT Varying degrees of consciousness loss and recovery are commonly observed in acquired brain injury patients, yet the underlying neurobiological mechanisms remain elusive. Using a large sample of patients with varying degrees of consciousness loss, we demonstrate that intrinsic functional connectivity strength in many brain regions, especially in the posterior cingulate cortex and precuneus, significantly correlated with consciousness level and recovery outcome. We further demonstrate that the functional connectivity pattern of these regions can predict patients with unresponsive wakefulness syndrome/vegetative state and coma would regain consciousness with an accuracy of 81.25%. Our study thus provides potentially important biomarkers of acquired brain injury in clinical diagnosis, prediction of recovery outcome, and decision making for treatment strategies for patients with severe loss of consciousness. PMID:26377477

Genetic and Diagnostic Biomarker Development in ASD Toddlers Using Resting State Functional MRI

DTIC Science & Technology

2017-11-01

and activation-based fMRI from the Courchesne lab report the presence of structural and functional abnormality in these structures by ages 1 to 2...young ages. With this invaluable resource, we will identify early developmental patterns of intrinsic functional network abnormalities in ASD infants...all infants and toddlers, analyses also investigate whether there may be subtypes of abnormal intrinsic connectivity patterns based on early clinical

Contributions of structural connectivity and cerebrovascular parameters to functional magnetic resonance imaging signals in mice at rest and during sensory paw stimulation.

PubMed

Schroeter, Aileen; Grandjean, Joanes; Schlegel, Felix; Saab, Bechara J; Rudin, Markus

2017-07-01

Previously, we reported widespread bilateral increases in stimulus-evoked functional magnetic resonance imaging signals in mouse brain to unilateral sensory paw stimulation. We attributed the pattern to arousal-related cardiovascular changes overruling cerebral autoregulation thereby masking specific signal changes elicited by local neuronal activity. To rule out the possibility that interhemispheric neuronal communication might contribute to bilateral functional magnetic resonance imaging responses, we compared stimulus-evoked functional magnetic resonance imaging responses to unilateral hindpaw stimulation in acallosal I/LnJ, C57BL/6, and BALB/c mice. We found bilateral blood-oxygenation-level dependent signal changes in all three strains, ruling out a dominant contribution of transcallosal communication as reason for bilaterality. Analysis of functional connectivity derived from resting-state functional magnetic resonance imaging, revealed that bilateral cortical functional connectivity is largely abolished in I/LnJ animals. Cortical functional connectivity in all strains correlated with structural connectivity in corpus callosum as revealed by diffusion tensor imaging. Given the profound influence of systemic hemodynamics on stimulus-evoked functional magnetic resonance imaging outcomes, we evaluated whether functional connectivity data might be affected by cerebrovascular parameters, i.e. baseline cerebral blood volume, vascular reactivity, and reserve. We found that effects of cerebral hemodynamics on functional connectivity are largely outweighed by dominating contributions of structural connectivity. In contrast, contributions of transcallosal interhemispheric communication to the occurrence of ipsilateral functional magnetic resonance imaging response of equal amplitude to unilateral stimuli seem negligible.

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.

Mechanisms of hemispheric specialization: Insights from analyses of connectivity

PubMed Central

Stephan, Klaas Enno; Fink, Gereon R.; Marshall, John C.

2007-01-01

Traditionally, anatomical and physiological descriptions of hemispheric specialization have focused on hemispheric asymmetries of local brain structure or local functional properties, respectively. This article reviews the current state of an alternative approach that aims at unraveling the causes and functional principles of hemispheric specialization in terms of asymmetries in connectivity. Starting with an overview of the historical origins of the concept of lateralization, we briefly review recent evidence from anatomical and developmental studies that asymmetries in structural connectivity may be a critical factor shaping hemispheric specialization. These differences in anatomical connectivity, which are found both at the intra- and inter-regional level, are likely to form the structural substrate of different functional principles of information processing in the two hemispheres. The main goal of this article is to describe how these functional principles can be characterized using functional neuroimaging in combination with models of functional and effective connectivity. We discuss the methodology of established models of connectivity which are applicable to data from positron emission tomography and functional magnetic resonance imaging and review published studies that have applied these approaches to characterize asymmetries of connectivity during lateralized tasks. Adopting a model-based approach enables functional imaging to proceed from mere descriptions of asymmetric activation patterns to mechanistic accounts of how these asymmetries are caused. PMID:16949111

Altered amygdala-prefrontal response to facial emotion in offspring of parents with bipolar disorder.

PubMed

Manelis, Anna; Ladouceur, Cecile D; Graur, Simona; Monk, Kelly; Bonar, Lisa K; Hickey, Mary Beth; Dwojak, Amanda C; Axelson, David; Goldstein, Benjamin I; Goldstein, Tina R; Bebko, Genna; Bertocci, Michele A; Hafeman, Danella M; Gill, Mary Kay; Birmaher, Boris; Phillips, Mary L

2015-09-01

This study aimed to identify neuroimaging measures associated with risk for, or protection against, bipolar disorder by comparing youth offspring of parents with bipolar disorder versus youth offspring of non-bipolar parents versus offspring of healthy parents in (i) the magnitude of activation within emotional face processing circuitry; and (ii) functional connectivity between this circuitry and frontal emotion regulation regions. The study was conducted at the University of Pittsburgh Medical Centre. Participants included 29 offspring of parents with bipolar disorder (mean age = 13.8 years; 14 females), 29 offspring of non-bipolar parents (mean age = 13.8 years; 12 females) and 23 healthy controls (mean age = 13.7 years; 11 females). Participants were scanned during implicit processing of emerging happy, sad, fearful and angry faces and shapes. The activation analyses revealed greater right amygdala activation to emotional faces versus shapes in offspring of parents with bipolar disorder and offspring of non-bipolar parents than healthy controls. Given that abnormally increased amygdala activation during emotion processing characterized offspring of both patient groups, and that abnormally increased amygdala activation has often been reported in individuals with already developed bipolar disorder and those with major depressive disorder, these neuroimaging findings may represent markers of increased risk for affective disorders in general. The analysis of psychophysiological interaction revealed that offspring of parents with bipolar disorder showed significantly more negative right amygdala-anterior cingulate cortex functional connectivity to emotional faces versus shapes, but significantly more positive right amygdala-left ventrolateral prefrontal cortex functional connectivity to happy faces (all P-values corrected for multiple tests) than offspring of non-bipolar parents and healthy controls. Taken together with findings of increased amygdala-ventrolateral prefrontal cortex functional connectivity, and decreased amygdala-anterior cingulate cortex functional connectivity previously shown in individuals with bipolar disorder, these connectivity patterns in offspring of parents with bipolar disorder may be risk markers for, rather than markers conferring protection against, bipolar disorder in youth. The patterns of activation and functional connectivity remained unchanged after removing medicated participants and those with current psychopathology from analyses. This is the first study to demonstrate that abnormal functional connectivity patterns within face emotion processing circuitry distinguish offspring of parents with bipolar disorder from those of non-bipolar parents and healthy controls. © 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.

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.

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

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.

Shared neural circuits for mentalizing about the self and others.

PubMed

Lombardo, Michael V; Chakrabarti, Bhismadev; Bullmore, Edward T; Wheelwright, Sally J; Sadek, Susan A; Suckling, John; Baron-Cohen, Simon

2010-07-01

Although many examples exist for shared neural representations of self and other, it is unknown how such shared representations interact with the rest of the brain. Furthermore, do high-level inference-based shared mentalizing representations interact with lower level embodied/simulation-based shared representations? We used functional neuroimaging (fMRI) and a functional connectivity approach to assess these questions during high-level inference-based mentalizing. Shared mentalizing representations in ventromedial prefrontal cortex, posterior cingulate/precuneus, and temporo-parietal junction (TPJ) all exhibited identical functional connectivity patterns during mentalizing of both self and other. Connectivity patterns were distributed across low-level embodied neural systems such as the frontal operculum/ventral premotor cortex, the anterior insula, the primary sensorimotor cortex, and the presupplementary motor area. These results demonstrate that identical neural circuits are implementing processes involved in mentalizing of both self and other and that the nature of such processes may be the integration of low-level embodied processes within higher level inference-based mentalizing.

Tracking ongoing cognition in individuals using brief, whole-brain functional connectivity patterns

PubMed Central

Gonzalez-Castillo, Javier; Hoy, Colin W.; Handwerker, Daniel A.; Robinson, Meghan E.; Buchanan, Laura C.; Saad, Ziad S.; Bandettini, Peter A.

2015-01-01

Functional connectivity (FC) patterns in functional MRI exhibit dynamic behavior on the scale of seconds, with rich spatiotemporal structure and limited sets of whole-brain, quasi-stable FC configurations (FC states) recurring across time and subjects. Based on previous evidence linking various aspects of cognition to group-level, minute-to-minute FC changes in localized connections, we hypothesized that whole-brain FC states may reflect the global, orchestrated dynamics of cognitive processing on the scale of seconds. To test this hypothesis, subjects were continuously scanned as they engaged in and transitioned between mental states dictated by tasks. FC states computed within windows as short as 22.5 s permitted robust tracking of cognition in single subjects with near perfect accuracy. Accuracy dropped markedly for subjects with the lowest task performance. Spatially restricting FC information decreased accuracy at short time scales, emphasizing the distributed nature of whole-brain FC dynamics, beyond univariate magnitude changes, as valuable markers of cognition. PMID:26124112

Discrete Regularization for Calibration of Geologic Facies Against Dynamic Flow Data

NASA Astrophysics Data System (ADS)

Khaninezhad, Mohammad-Reza; Golmohammadi, Azarang; Jafarpour, Behnam

2018-04-01

Subsurface flow model calibration involves many more unknowns than measurements, leading to ill-posed problems with nonunique solutions. To alleviate nonuniqueness, the problem is regularized by constraining the solution space using prior knowledge. In certain sedimentary environments, such as fluvial systems, the contrast in hydraulic properties of different facies types tends to dominate the flow and transport behavior, making the effect of within facies heterogeneity less significant. Hence, flow model calibration in those formations reduces to delineating the spatial structure and connectivity of different lithofacies types and their boundaries. A major difficulty in calibrating such models is honoring the discrete, or piecewise constant, nature of facies distribution. The problem becomes more challenging when complex spatial connectivity patterns with higher-order statistics are involved. This paper introduces a novel formulation for calibration of complex geologic facies by imposing appropriate constraints to recover plausible solutions that honor the spatial connectivity and discreteness of facies models. To incorporate prior connectivity patterns, plausible geologic features are learned from available training models. This is achieved by learning spatial patterns from training data, e.g., k-SVD sparse learning or the traditional Principal Component Analysis. Discrete regularization is introduced as a penalty functions to impose solution discreteness while minimizing the mismatch between observed and predicted data. An efficient gradient-based alternating directions algorithm is combined with variable splitting to minimize the resulting regularized nonlinear least squares objective function. Numerical results show that imposing learned facies connectivity and discreteness as regularization functions leads to geologically consistent solutions that improve facies calibration quality.

Elucidating the nature and mechanism of tic improvement in tourette syndrome: a pilot study.

PubMed

Shprecher, David R; Gannon, Keenan; Agarwal, Nivedita; Shi, Xianfeng; Anderson, Jeffrey S

2014-01-01

For unclear reasons, many Tourette syndrome (TS) children report near-complete tic remission by young adulthood. Immature maturation of brain networks, observed with resting-state functional MRI (rs-fc-MRI) in adolescents and adults with TS, might evolve to a mature pattern in adults who experience tic improvement or remission. We explored the feasibility of testing this hypothesis in our population of young adult TS males, each with prior clinical assessments completed during childhood as part of a separate TS Association Genetics Consortium study. A total of 10 TS males (off tic suppressing drugs for at least 6 months) aged 19-32 years, mean follow-up interval 7.5 (2 to 13) years, and 11 neurologically normal controls were enrolled and underwent 3-Tesla structural and rs-fc-MRI sequences. The mean change in Yale Global Tic Severity Scale (YGTSS) was -31.5% (total) and -26.6% (YGTSS motor+vocal). Two subjects reported resolution of tic-related disability, with drops from mean 45 to 16.5 (YGTSS-total) and 25 to 11.5 (YGTSS motor+vocal.). Rs-fc-MRI revealed significantly increased connectivity between the ipsilateral anterior and mid cingulate cortex and striatum, increased connectivity between local connections, and decreased connectivity between more distant connections; representing an immature connectivity pattern. Similar to previous reports, we found immature patterns of functional connectivity in adult TS subjects. Despite a lack of complete tic remission, two subjects exhibited dramatic drops in tic severity that correlated with tic-related disability improvement. More work is needed to elucidate the mechanism of such dramatic improvement in TS.

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.

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

Patterns, Functions, and Algebra: Wired for Space. NASA Connect: Program 3 in the 2000-2001 Series.

ERIC Educational Resources Information Center

National Aeronautics and Space Administration, Hampton, VA. Langley Research Center.

This teaching unit is designed to help students in grades 5 to 8 explore the concepts of patterns, functions, and algebra in the context of propelling spacecraft. The units in the series have been developed to enhance and enrich mathematics, science, and technology education and to accommodate different teaching and learning styles. Each unit…

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

PubMed Central

Filbey, Francesca M.; Dunlop, Joseph

2015-01-01

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

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.

Evolving soils and hydrologic connectivity in semiarid hillslopes

NASA Astrophysics Data System (ADS)

Saco, Patricia M.

2015-04-01

Soil moisture availability is essential for the stability and resilience of semiarid ecosystems. In these ecosystems the amount of soil moisture available for vegetation growth and survival is intrinsically related to the way water is redistributed, that is from source to sink areas, and therefore prescribed by the hydrologic connectivity of the landscape. Recent studies have shown that hydrologic connectivity is highly dynamic and linked to the coevolution of geomorphic, soil and vegetation structures at a variety of spatial and temporal scales. This study investigates the effect of evolving soil depths on hydrologic connectivity using a modelling framework. The focus is on Australian semiarid hillslopes with patterned vegetation that result from coevolving landforms, soils, water redistribution, and vegetation patterns. We present and analyse results from simulations using a coupled landform evolution-dynamic vegetation model, which includes a soil depth evolution module and accounts for soil production and sediment erosion and deposition processes. We analyse the effect of soils depths on surface connectivity for a range of biotic (plant functional type strategies) and abiotic (slope and erodibility) conditions. The analysis shows that different plant functional types, through their varying facilitation strategies, have a profound effect on soils depths and therefore affect hydrologic connectivity and soil moisture patterns. This interplay becomes particularly important for systems that coevolve to have very shallow soils. In this case soil depth becomes the key factor prescribing surface connectivity and available soil moisture for plants, which affect the recovery of the system after disturbance. Conditions for the existence of threshold behaviour for which small perturbations can trigger a sudden increase in hydrologic connectivity, reduced soil moisture availability and decrease in productivity leading to degraded states are investigated. Critical implications for effective restoration efforts are discussed.

Age-related individual variability in memory performance is associated with amygdala-hippocampal circuit function and emotional pattern separation.

PubMed

Leal, Stephanie L; Noche, Jessica A; Murray, Elizabeth A; Yassa, Michael A

2017-01-01

While aging is generally associated with episodic memory decline, not all older adults exhibit memory loss. Furthermore, emotional memories are not subject to the same extent of forgetting and appear preserved in aging. We conducted high-resolution fMRI during a task involving pattern separation of emotional information in older adults with and without age-related memory impairment (characterized by performance on a word-list learning task: low performers: LP vs. high performers: HP). We found signals consistent with emotional pattern separation in hippocampal dentate (DG)/CA3 in HP but not in LP individuals, suggesting a deficit in emotional pattern separation. During false recognition, we found increased DG/CA3 activity in LP individuals, suggesting that hyperactivity may be associated with overgeneralization. We additionally observed a selective deficit in basolateral amygdala-lateral entorhinal cortex-DG/CA3 functional connectivity in LP individuals during pattern separation of negative information. During negative false recognition, LP individuals showed increased medial temporal lobe functional connectivity, consistent with overgeneralization. Overall, these results suggest a novel mechanistic account of individual differences in emotional memory alterations exhibited in aging. Copyright © 2016 Elsevier Inc. All rights reserved.

Age-related individual variability in memory performance is associated with amygdala-hippocampal circuit function and emotional pattern separation

PubMed Central

Leal, Stephanie L.; Noche, Jessica A.; Murray, Elizabeth A.; Yassa, Michael A.

2018-01-01

While aging is generally associated with episodic memory decline, not all older adults exhibit memory loss. Furthermore, emotional memories are not subject to the same extent of forgetting and appear preserved in aging. We conducted high-resolution fMRI during a task involving pattern separation of emotional information in older adults with and without age-related memory impairment (characterized by performance on a word-list learning task: low performers: LP vs. high performers: HP). We found signals consistent with emotional pattern separation in hippocampal dentate (DG)/CA3 in HP but not in LP individuals, suggesting a deficit in emotional pattern separation. During false recognition, we found increased DG/CA3 activity in LP individuals, suggesting that hyperactivity may be associated with overgeneralization. We additionally observed a selective deficit in basolateral amygdala—lateral entorhinal cortex—DG/CA3 functional connectivity in LP individuals during pattern separation of negative information. During negative false recognition, LP individuals showed increased medial temporal lobe functional connectivity, consistent with overgeneralization. Overall, these results suggest a novel mechanistic account of individual differences in emotional memory alterations exhibited in aging. PMID:27723500

Individual differences in functional connectivity during naturalistic viewing conditions.

PubMed

Vanderwal, Tamara; Eilbott, Jeffrey; Finn, Emily S; Craddock, R Cameron; Turnbull, Adam; Castellanos, F Xavier

2017-08-15

Naturalistic viewing paradigms such as movies have been shown to reduce participant head motion and improve arousal during fMRI scanning relative to task-free rest, and have been used to study both functional connectivity and stimulus-evoked BOLD-signal changes. These task-based hemodynamic changes are synchronized across subjects and involve large areas of the cortex, and it is unclear whether individual differences in functional connectivity are enhanced or diminished under such naturalistic conditions. This work first aims to characterize variability in BOLD-signal based functional connectivity (FC) across 2 distinct movie conditions and eyes-open rest (n=31 healthy adults, 2 scan sessions each). We found that movies have higher within- and between-subject correlations in cluster-wise FC relative to rest. The anatomical distribution of inter-individual variability was similar across conditions, with higher variability occurring at the lateral prefrontal lobes and temporoparietal junctions. Second, we used an unsupervised test-retest matching algorithm that identifies individual subjects from within a group based on FC patterns, quantifying the accuracy of the algorithm across the three conditions. The movies and resting state all enabled identification of individual subjects based on FC matrices, with accuracies between 61% and 100%. Overall, pairings involving movies outperformed rest, and the social, faster-paced movie attained 100% accuracy. When the parcellation resolution, scan duration, and number of edges used were increased, accuracies improved across conditions, and the pattern of movies>rest was preserved. These results suggest that using dynamic stimuli such as movies enhances the detection of FC patterns that are unique at the individual level. Copyright © 2017 Elsevier Inc. All rights reserved.

Altered Amygdala Resting-State Functional Connectivity in Maintenance Hemodialysis End-Stage Renal Disease Patients with Depressive Mood.

PubMed

Chen, Hui Juan; Wang, Yun Fei; Qi, Rongfeng; Schoepf, U Joseph; Varga-Szemes, Akos; Ball, B Devon; Zhang, Zhe; Kong, Xiang; Wen, Jiqiu; Li, Xue; Lu, Guang Ming; Zhang, Long Jiang

2017-04-01

The purpose of this study was to investigate patterns in the amygdala-based emotional processing circuit of hemodialysis patients using resting-state functional MR imaging (rs-fMRI). Fifty hemodialysis patients (25 with depressed mood and 25 without depressed mood) and 26 healthy controls were included. All subjects underwent neuropsychological tests and rs-fMRI, and patients also underwent laboratory tests. Functional connectivity of the bilateral amygdala was compared among the three groups. The relationship between functional connectivity and clinical markers was investigated. Depressed patients showed increased positive functional connectivity of the left amygdala with the left superior temporal gyrus and right parahippocampal gyrus (PHG) but decreased amygdala functional connectivity with the left precuneus, angular gyrus, posterior cingulate cortex (PCC), and left inferior parietal lobule compared with non-depressed patients (P < 0.05, AlphaSim corrected). Depressed patients had increased positive functional connectivity of the right amygdala with bilateral supplementary motor areas and PHG but decreased amygdala functional connectivity with the right superior frontal gyrus, superior parietal lobule, bilateral precuneus, and PCC (P < 0.05, AlphaSim corrected). After including anxiety as a covariate, we discovered additional decreased functional connectivity with anterior cingulate cortex (ACC) for bilateral amygdala (P < 0.05, AlphaSim corrected). For the depressed, neuropsychological test scores were correlated with functional connectivity of multiple regions (P < 0.05, AlphaSim corrected). In conclusion, functional connectivity in the amygdala-prefrontal-PCC-limbic circuits was impaired in depressive hemodialysis patients, with a gradual decrease in ACC between controls, non-depressed, and depressed patients for the right amygdala. This indicates that ACC plays a role in amygdala-based emotional regulatory circuits in these patients.

Aberrant striatal functional connectivity in children with autism.

PubMed

Di Martino, Adriana; Kelly, Clare; Grzadzinski, Rebecca; Zuo, Xi-Nian; Mennes, Maarten; Mairena, Maria Angeles; Lord, Catherine; Castellanos, F Xavier; Milham, Michael P

2011-05-01

Models of autism spectrum disorders (ASD) as neural disconnection syndromes have been predominantly supported by examinations of abnormalities in corticocortical networks in adults with autism. A broader body of research implicates subcortical structures, particularly the striatum, in the physiopathology of autism. Resting state functional magnetic resonance imaging has revealed detailed maps of striatal circuitry in healthy and psychiatric populations and vividly captured maturational changes in striatal circuitry during typical development. Using resting state functional magnetic resonance imaging, we examined striatal functional connectivity (FC) in 20 children with ASD and 20 typically developing children between the ages of 7.6 and 13.5 years. Whole-brain voxelwise statistical maps quantified within-group striatal FC and between-group differences for three caudate and three putamen seeds for each hemisphere. Children with ASD mostly exhibited prominent patterns of ectopic striatal FC (i.e., functional connectivity present in ASD but not in typically developing children), with increased functional connectivity between nearly all striatal subregions and heteromodal associative and limbic cortex previously implicated in the physiopathology of ASD (e.g., insular and right superior temporal gyrus). Additionally, we found striatal functional hyperconnectivity with the pons, thus expanding the scope of functional alterations implicated in ASD. Secondary analyses revealed ASD-related hyperconnectivity between the pons and insula cortex. Examination of FC of striatal networks in children with ASD revealed abnormalities in circuits involving early developing areas, such as the brainstem and insula, with a pattern of increased FC in ectopic circuits that likely reflects developmental derangement rather than immaturity of functional circuits. Copyright © 2011 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

Auditory Resting-State Network Connectivity in Tinnitus: A Functional MRI Study

PubMed Central

Maudoux, Audrey; Lefebvre, Philippe; Cabay, Jean-Evrard; Demertzi, Athena; Vanhaudenhuyse, Audrey; Laureys, Steven; Soddu, Andrea

2012-01-01

The underlying functional neuroanatomy of tinnitus remains poorly understood. Few studies have focused on functional cerebral connectivity changes in tinnitus patients. The aim of this study was to test if functional MRI “resting-state” connectivity patterns in auditory network differ between tinnitus patients and normal controls. Thirteen chronic tinnitus subjects and fifteen age-matched healthy controls were studied on a 3 tesla MRI. Connectivity was investigated using independent component analysis and an automated component selection approach taking into account the spatial and temporal properties of each component. Connectivity in extra-auditory regions such as brainstem, basal ganglia/NAc, cerebellum, parahippocampal, right prefrontal, parietal, and sensorimotor areas was found to be increased in tinnitus subjects. The right primary auditory cortex, left prefrontal, left fusiform gyrus, and bilateral occipital regions showed a decreased connectivity in tinnitus. These results show that there is a modification of cortical and subcortical functional connectivity in tinnitus encompassing attentional, mnemonic, and emotional networks. Our data corroborate the hypothesized implication of non-auditory regions in tinnitus physiopathology and suggest that various regions of the brain seem involved in the persistent awareness of the phenomenon as well as in the development of the associated distress leading to disabling chronic tinnitus. PMID:22574141

Task-Related Deactivation and Functional Connectivity of the Subgenual Cingulate Cortex in Major Depressive Disorder

PubMed Central

Davey, Christopher G.; Yücel, Murat; Allen, Nicholas B.; Harrison, Ben J.

2012-01-01

Background: Major depressive disorder is associated with functional alterations in activity and resting-state connectivity of the extended medial frontal network. In this study we aimed to examine how task-related medial network activity and connectivity were affected in depression. Methods: 18 patients with major depressive disorder, aged 15- to 24-years-old, were matched with 19 healthy control participants. We characterized task-related activations and deactivations while participants engaged with an executive-control task (the multi-source interference task, MSIT). We used a psycho-physiological interactions approach to examine functional connectivity changes with subgenual anterior cingulate cortex. Voxel-wise statistical maps for each analysis were compared between the patient and control groups. Results: There were no differences between groups in their behavioral performances on the MSIT task, and nor in patterns of activation and deactivation. Assessment of functional connectivity with the subgenual cingulate showed that depressed patients did not demonstrate the same reduction in functional connectivity with the ventral striatum during task performance, but that they showed greater reduction in functional connectivity with adjacent ventromedial frontal cortex. The magnitude of this latter connectivity change predicted the relative activation of task-relevant executive-control regions in depressed patients. Conclusion: The study reinforces the importance of the subgenual cingulate cortex for depression, and demonstrates how dysfunctional connectivity with ventral brain regions might influence executive–attentional processes. PMID:22403553

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.

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.

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

PubMed Central

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

2014-01-01

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

Role of testosterone and Y chromosome genes for the masculinization of the human brain.

PubMed

Savic, Ivanka; Frisen, Louise; Manzouri, Amirhossein; Nordenstrom, Anna; Lindén Hirschberg, Angelica

2017-04-01

Women with complete androgen insensitivity syndrome (CAIS) have a male (46,XY) karyotype but no functional androgen receptors. Their condition, therefore, offers a unique model for studying testosterone effects on cerebral sex dimorphism. We present MRI data from 16 women with CAIS and 32 male (46,XY) and 32 female (46,XX) controls. FreeSurfer software was employed to measure cortical thickness and subcortical structural volumes. Axonal connections, indexed by fractional anisotropy, (FA) were measured with diffusion tensor imaging, and functional connectivity with resting state fMRI. Compared to men, CAIS women displayed a "female" pattern by having thicker parietal and occipital cortices, lower FA values in the right corticospinal, superior and inferior longitudinal tracts, and corpus callosum. Their functional connectivity from the amygdala to the medial prefrontal cortex, was stronger and amygdala-connections to the motor cortex weaker than in control men. CAIS and control women also showed stronger posterior cingulate and precuneus connections in the default mode network. Thickness of the motor cortex, the caudate volume, and the FA in the callosal body followed, however, a "male" pattern. Altogether, these data suggest that testosterone modulates the microstructure of somatosensory and visual cortices and their axonal connections to the frontal cortex. Testosterone also influenced functional connections from the amygdala, whereas the motor cortex could, in agreement with our previous reports, be moderated by processes linked to X-chromosome gene dosage. These data raise the question about other genetic factors masculinizing the human brain than the SRY gene and testosterone. Hum Brain Mapp 38:1801-1814, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Action and semantic tool knowledge - Effective connectivity in the underlying neural networks.

PubMed

Kleineberg, Nina N; Dovern, Anna; Binder, Ellen; Grefkes, Christian; Eickhoff, Simon B; Fink, Gereon R; Weiss, Peter H

2018-04-26

Evidence from neuropsychological and imaging studies indicate that action and semantic knowledge about tools draw upon distinct neural substrates, but little is known about the underlying interregional effective connectivity. With fMRI and dynamic causal modeling (DCM) we investigated effective connectivity in the left-hemisphere (LH) while subjects performed (i) a function knowledge and (ii) a value knowledge task, both addressing semantic tool knowledge, and (iii) a manipulation (action) knowledge task. Overall, the results indicate crosstalk between action nodes and semantic nodes. Interestingly, effective connectivity was weakened between semantic nodes and action nodes during the manipulation task. Furthermore, pronounced modulations of effective connectivity within the fronto-parietal action system of the LH (comprising lateral occipito-temporal cortex, intraparietal sulcus, supramarginal gyrus, inferior frontal gyrus) were observed in a bidirectional manner during the processing of action knowledge. In contrast, the function and value knowledge tasks resulted in a significant strengthening of the effective connectivity between visual cortex and fusiform gyrus. Importantly, this modulation was present in both semantic tasks, indicating that processing different aspects of semantic knowledge about tools evokes similar effective connectivity patterns. Data revealed that interregional effective connectivity during the processing of tool knowledge occurred in a bidirectional manner with a weakening of connectivity between areas engaged in action and semantic knowledge about tools during the processing of action knowledge. Moreover, different semantic tool knowledge tasks elicited similar effective connectivity patterns. © 2018 Wiley Periodicals, Inc.

Social interactions elicit rapid shifts in functional connectivity in the social decision-making network of zebrafish

PubMed Central

Teles, Magda C.; Almeida, Olinda; Lopes, João S.; Oliveira, Rui F.

2015-01-01

According to the social decision-making (SDM) network hypothesis, SDM is encoded in a network of forebrain and midbrain structures in a distributed and dynamic fashion, such that the expression of a given social behaviour is better reflected by the overall profile of activation across the different loci rather than by the activity of a single node. This proposal has the implicit assumption that SDM relies on integration across brain regions, rather than on regional specialization. Here we tested the occurrence of functional localization and of functional connectivity in the SDM network. For this purpose we used zebrafish to map different social behaviour states into patterns of neuronal activity, as indicated by the expression of the immediate early genes c-fos and egr-1, across the SDM network. The results did not support functional localization, as some loci had similar patterns of activity associated with different social behaviour states, and showed socially driven changes in functional connectivity. Thus, this study provides functional support to the SDM network hypothesis and suggests that the neural context in which a given node of the network is operating (i.e. the state of its interconnected areas) is central to its functional relevance. PMID:26423839

Social interactions elicit rapid shifts in functional connectivity in the social decision-making network of zebrafish.

PubMed

Teles, Magda C; Almeida, Olinda; Lopes, João S; Oliveira, Rui F

2015-10-07

According to the social decision-making (SDM) network hypothesis, SDM is encoded in a network of forebrain and midbrain structures in a distributed and dynamic fashion, such that the expression of a given social behaviour is better reflected by the overall profile of activation across the different loci rather than by the activity of a single node. This proposal has the implicit assumption that SDM relies on integration across brain regions, rather than on regional specialization. Here we tested the occurrence of functional localization and of functional connectivity in the SDM network. For this purpose we used zebrafish to map different social behaviour states into patterns of neuronal activity, as indicated by the expression of the immediate early genes c-fos and egr-1, across the SDM network. The results did not support functional localization, as some loci had similar patterns of activity associated with different social behaviour states, and showed socially driven changes in functional connectivity. Thus, this study provides functional support to the SDM network hypothesis and suggests that the neural context in which a given node of the network is operating (i.e. the state of its interconnected areas) is central to its functional relevance. © 2015 The Author(s).

A Coordinate-Based Meta-Analysis of Overlaps in Regional Specialization and Functional Connectivity across Subjective Value and Default Mode Networks.

PubMed

Acikalin, M Yavuz; Gorgolewski, Krzysztof J; Poldrack, Russell A

2017-01-01

Previous research has provided qualitative evidence for overlap in a number of brain regions across the subjective value network (SVN) and the default mode network (DMN). In order to quantitatively assess this overlap, we conducted a series of coordinate-based meta-analyses (CBMA) of results from 466 functional magnetic resonance imaging experiments on task-negative or subjective value-related activations in the human brain. In these analyses, we first identified significant overlaps and dissociations across activation foci related to SVN and DMN. Second, we investigated whether these overlapping subregions also showed similar patterns of functional connectivity, suggesting a shared functional subnetwork. We find considerable overlap between SVN and DMN in subregions of central ventromedial prefrontal cortex (cVMPFC) and dorsal posterior cingulate cortex (dPCC). Further, our findings show that similar patterns of bidirectional functional connectivity between cVMPFC and dPCC are present in both networks. We discuss ways in which our understanding of how subjective value (SV) is computed and represented in the brain can be synthesized with what we know about the DMN, mind-wandering, and self-referential processing in light of our findings.

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.

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

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

PubMed

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

2018-06-01

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

Graph Theoretical Framework of Brain Networks in Multiple Sclerosis: A Review of Concepts.

PubMed

Fleischer, Vinzenz; Radetz, Angela; Ciolac, Dumitru; Muthuraman, Muthuraman; Gonzalez-Escamilla, Gabriel; Zipp, Frauke; Groppa, Sergiu

2017-11-01

Network science provides powerful access to essential organizational principles of the human brain. It has been applied in combination with graph theory to characterize brain connectivity patterns. In multiple sclerosis (MS), analysis of the brain networks derived from either structural or functional imaging provides new insights into pathological processes within the gray and white matter. Beyond focal lesions and diffuse tissue damage, network connectivity patterns could be important for closely tracking and predicting the disease course. In this review, we describe concepts of graph theory, highlight novel issues of tissue reorganization in acute and chronic neuroinflammation and address pitfalls with regard to network analysis in MS patients. We further provide an outline of functional and structural connectivity patterns observed in MS, spanning from disconnection and disruption on one hand to adaptation and compensation on the other. Moreover, we link network changes and their relation to clinical disability based on the current literature. Finally, we discuss the perspective of network science in MS for future research and postulate its role in the clinical framework. Copyright © 2017 IBRO. Published by Elsevier Ltd. All rights reserved.

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).

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

Dominance of the Unaffected Hemisphere Motor Network and Its Role in the Behavior of Chronic Stroke Survivors

PubMed Central

Bajaj, Sahil; Housley, Stephen N.; Wu, David; Dhamala, Mukesh; James, G. A.; Butler, Andrew J.

2016-01-01

Balance of motor network activity between the two brain hemispheres after stroke is crucial for functional recovery. Several studies have extensively studied the role of the affected brain hemisphere to better understand changes in motor network activity following stroke. Very few studies have examined the role of the unaffected brain hemisphere and confirmed the test–retest reliability of connectivity measures on unaffected hemisphere. We recorded blood oxygenation level dependent functional magnetic resonance imaging (fMRI) signals from nine stroke survivors with hemiparesis of the left or right hand. Participants performed a motor execution task with affected hand, unaffected hand, and both hands simultaneously. Participants returned for a repeat fMRI scan 1 week later. Using dynamic causal modeling (DCM), we evaluated effective connectivity among three motor areas: the primary motor area (M1), the premotor cortex (PMC) and the supplementary motor area for the affected and unaffected hemispheres separately. Five participants’ manual motor ability was assessed by Fugl-Meyer Motor Assessment scores and root-mean square error of participants’ tracking ability during a robot-assisted game. We found (i) that the task performance with the affected hand resulted in strengthening of the connectivity pattern for unaffected hemisphere, (ii) an identical network of the unaffected hemisphere when participants performed the task with their unaffected hand, and (iii) the pattern of directional connectivity observed in the affected hemisphere was identical for tasks using the affected hand only or both hands. Furthermore, paired t-test comparison found no significant differences in connectivity strength for any path when compared with one-week follow-up. Brain-behavior linear correlation analysis showed that the connectivity patterns in the unaffected hemisphere more accurately reflected the behavioral conditions than the connectivity patterns in the affected hemisphere. Above findings enrich our knowledge of unaffected brain hemisphere following stroke, which further strengthens our neurobiological understanding of stroke-affected brain and can help to effectively identify and apply stroke-treatments. PMID:28082882

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

Aberrant functional connectivity for diagnosis of major depressive disorder: a discriminant analysis.

PubMed

Cao, Longlong; Guo, Shuixia; Xue, Zhimin; Hu, Yong; Liu, Haihong; Mwansisya, Tumbwene E; Pu, Weidan; Yang, Bo; Liu, Chang; Feng, Jianfeng; Chen, Eric Y H; Liu, Zhening

2014-02-01

Aberrant brain functional connectivity patterns have been reported in major depressive disorder (MDD). It is unknown whether they can be used in discriminant analysis for diagnosis of MDD. In the present study we examined the efficiency of discriminant analysis of MDD by individualized computer-assisted diagnosis. Based on resting-state functional magnetic resonance imaging data, a new approach was adopted to investigate functional connectivity changes in 39 MDD patients and 37 well-matched healthy controls. By using the proposed feature selection method, we identified significant altered functional connections in patients. They were subsequently applied to our analysis as discriminant features using a support vector machine classification method. Furthermore, the relative contribution of functional connectivity was estimated. After subset selection of high-dimension features, the support vector machine classifier reached up to approximately 84% with leave-one-out training during the discrimination process. Through summarizing the classification contribution of functional connectivities, we obtained four obvious contribution modules: inferior orbitofrontal module, supramarginal gyrus module, inferior parietal lobule-posterior cingulated gyrus module and middle temporal gyrus-inferior temporal gyrus module. The experimental results demonstrated that the proposed method is effective in discriminating MDD patients from healthy controls. Functional connectivities might be useful as new biomarkers to assist clinicians in computer auxiliary diagnosis of MDD. © 2013 The Authors. Psychiatry and Clinical Neurosciences © 2013 Japanese Society of Psychiatry and Neurology.

Co-activation patterns in resting-state fMRI signals.

PubMed

Liu, Xiao; Zhang, Nanyin; Chang, Catie; Duyn, Jeff H

2018-02-08

The brain is a complex system that integrates and processes information across multiple time scales by dynamically coordinating activities over brain regions and circuits. Correlations in resting-state functional magnetic resonance imaging (rsfMRI) signals have been widely used to infer functional connectivity of the brain, providing a metric of functional associations that reflects a temporal average over an entire scan (typically several minutes or longer). Not until recently was the study of dynamic brain interactions at much shorter time scales (seconds to minutes) considered for inference of functional connectivity. One method proposed for this objective seeks to identify and extract recurring co-activation patterns (CAPs) that represent instantaneous brain configurations at single time points. Here, we review the development and recent advancement of CAP methodology and other closely related approaches, as well as their applications and associated findings. We also discuss the potential neural origins and behavioral relevance of CAPs, along with methodological issues and future research directions in the analysis of fMRI co-activation patterns. Copyright © 2018 Elsevier Inc. All rights reserved.

Functional Network Disruption in the Degenerative Dementias

PubMed Central

Pievani, Michela; de Haan, Willem; Wu, Tao; Seeley, William W; Frisoni, Giovanni B

2011-01-01

Despite considerable advances toward understanding the molecular pathophysiology of the neurodegenerative dementias, the mechanisms linking molecular changes to neuropathology and the latter to clinical symptoms remain largely obscure. Connectivity is a distinctive feature of the brain and the integrity of functional network dynamics is critical for normal functioning. A better understanding of network disruption in the neurodegenerative dementias may help bridge the gap between molecular changes, pathology and symptoms. Recent findings on functional network disruption as assessed with “resting-state” or intrinsic connectivity fMRI and EEG/MEG have shown distinct patterns of network disruption across the major neurodegenerative diseases. These network abnormalities are relatively specific to the clinical syndromes, and in Alzheimer's disease and frontotemporal dementia network disruption tracks the pattern of pathological changes. These findings may have a practical impact on diagnostic accuracy, allowing earlier detection of neurodegenerative diseases even at the pre-symptomatic stage, and tracking of disease progression. PMID:21778116

Nonmonotonic spatial structure of interneuronal correlations in prefrontal microcircuits

PubMed Central

Safavi, Shervin; Dwarakanath, Abhilash; Kapoor, Vishal; Werner, Joachim; Hatsopoulos, Nicholas G.; Logothetis, Nikos K.; Panagiotaropoulos, Theofanis I.

2018-01-01

Correlated fluctuations of single neuron discharges, on a mesoscopic scale, decrease as a function of lateral distance in early sensory cortices, reflecting a rapid spatial decay of lateral connection probability and excitation. However, spatial periodicities in horizontal connectivity and associational input as well as an enhanced probability of lateral excitatory connections in the association cortex could theoretically result in nonmonotonic correlation structures. Here, we show such a spatially nonmonotonic correlation structure, characterized by significantly positive long-range correlations, in the inferior convexity of the macaque prefrontal cortex. This functional connectivity kernel was more pronounced during wakefulness than anesthesia and could be largely attributed to the spatial pattern of correlated variability between functionally similar neurons during structured visual stimulation. These results suggest that the spatial decay of lateral functional connectivity is not a common organizational principle of neocortical microcircuits. A nonmonotonic correlation structure could reflect a critical topological feature of prefrontal microcircuits, facilitating their role in integrative processes. PMID:29588415

Thalamic amplification of cortical connectivity sustains attentional control

PubMed Central

Schmitt, L. Ian; Wimmer, Ralf D.; Nakajima, Miho; Happ, Michael; Mofakham, Sima; Halassa, Michael M.

2017-01-01

While interactions between the thalamus and cortex are critical for cognitive function1–3, the exact contribution of the thalamus to these interactions is often unclear. Recent studies have shown diverse connectivity patterns across the thalamus 4,5, but whether this diversity translates to thalamic functions beyond relaying information to or between cortical regions6 is unknown. Here, by investigating prefrontal cortical (PFC) representation of two rules used to guide attention, we find that the mediodorsal thalamus (MD) sustains these representations without relaying categorical information. Specifically, MD input amplifies local PFC connectivity, enabling rule-specific neural sequences to emerge and thereby maintain rule representations. Consistent with this notion, broadly enhancing PFC excitability diminishes rule specificity and behavioral performance, while enhancing MD excitability improves both. Overall, our results define a previously unknown principle in neuroscience; thalamic control of functional cortical connectivity. This function indicates that the thalamus plays much more central roles in cognition than previously thought. PMID:28467827

Altered functional connectivity during self- and close other-reflection in patients with bipolar disorder with past psychosis and patients with schizophrenia.

PubMed

Zhang, Liwen; Vander Meer, Lisette; Opmeer, Esther M; Marsman, Jan-Bernard C; Ruhé, Henricus G; Aleman, André

2016-12-01

Disturbances in implicit self-processing have been reported both in psychotic patients with bipolar disorder (BD) and schizophrenia. It remains unclear whether these two psychotic disorders show disturbed functional connectivity during explicit self-reflection, which is associated with social functioning and illness symptoms. Therefore, we investigated functional connectivity during explicit self-reflection in BD with past psychosis and schizophrenia. Twenty-three BD-patients, 17 schizophrenia-patients and 21 health controls (HC) performed a self-reflection task, including the conditions self-reflection, close other-reflection and semantic control. Functional connectivity was investigated with generalized psycho-physiological interaction (gPPI). During self-reflection compared to semantic, BD-patients had decreased connectivity between several cortical-midline structures (CMS) nodes (i.e., anterior cingulate cortex, ventromedial prefrontal cortex), the insula and the head of the caudate while HC showed increased connectivities. Schizophrenia-patients, during close other-reflection compared to semantic, demonstrated reduced ventral-anterior insula-precuneus/posterior cingulate cortex (PCC) functional connectivity, whereas this was increased in HC. There were no differences between BD and schizophrenia during self- and close other-reflection. We propose that decreased functional connectivity between the CMS nodes/insula and head of the caudate in BD-patients may imply a reduced involvement of the motivational system during self-reflection; and the reduced functional connectivity between the ventral-anterior insula and precuneus/PCC during close other-reflection in schizophrenia-patients may subserve difficulties in information integration of autobiographical memory and emotional awareness in relation to close others. These distinctive impaired patterns of functional connectivity in BD and schizophrenia (compared to HC) deserve further investigation to determine their robustness and associations with differences in clinical presentation. Copyright © 2016 Elsevier Ltd. All rights reserved.

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.

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.

Abnormal synchrony and effective connectivity in patients with schizophrenia and auditory hallucinations

PubMed Central

de la Iglesia-Vaya, Maria; Escartí, Maria José; Molina-Mateo, Jose; Martí-Bonmatí, Luis; Gadea, Marien; Castellanos, Francisco Xavier; Aguilar García-Iturrospe, Eduardo J.; Robles, Montserrat; Biswal, Bharat B.; Sanjuan, Julio

2014-01-01

Auditory hallucinations (AH) are the most frequent positive symptoms in patients with schizophrenia. Hallucinations have been related to emotional processing disturbances, altered functional connectivity and effective connectivity deficits. Previously, we observed that, compared to healthy controls, the limbic network responses of patients with auditory hallucinations differed when the subjects were listening to emotionally charged words. We aimed to compare the synchrony patterns and effective connectivity of task-related networks between schizophrenia patients with and without AH and healthy controls. Schizophrenia patients with AH (n = 27) and without AH (n = 14) were compared with healthy participants (n = 31). We examined functional connectivity by analyzing correlations and cross-correlations among previously detected independent component analysis time courses. Granger causality was used to infer the information flow direction in the brain regions. The results demonstrate that the patterns of cortico-cortical functional synchrony differentiated the patients with AH from the patients without AH and from the healthy participants. Additionally, Granger-causal relationships between the networks clearly differentiated the groups. In the patients with AH, the principal causal source was an occipital–cerebellar component, versus a temporal component in the patients without AH and the healthy controls. These data indicate that an anomalous process of neural connectivity exists when patients with AH process emotional auditory stimuli. Additionally, a central role is suggested for the cerebellum in processing emotional stimuli in patients with persistent AH. PMID:25379429

Human brain networks in physiological aging: a graph theoretical analysis of cortical connectivity from EEG data.

PubMed

Vecchio, Fabrizio; Miraglia, Francesca; Bramanti, Placido; Rossini, Paolo Maria

2014-01-01

Modern analysis of electroencephalographic (EEG) rhythms provides information on dynamic brain connectivity. To test the hypothesis that aging processes modulate the brain connectivity network, EEG recording was conducted on 113 healthy volunteers. They were divided into three groups in accordance with their ages: 36 Young (15-45 years), 46 Adult (50-70 years), and 31 Elderly (>70 years). To evaluate the stability of the investigated parameters, a subgroup of 10 subjects underwent a second EEG recording two weeks later. Graph theory functions were applied to the undirected and weighted networks obtained by the lagged linear coherence evaluated by eLORETA on cortical sources. EEG frequency bands of interest were: delta (2-4 Hz), theta (4-8 Hz), alpha1 (8-10.5 Hz), alpha2 (10.5-13 Hz), beta1 (13-20 Hz), beta2 (20-30 Hz), and gamma (30-40 Hz). The spectral connectivity analysis of cortical sources showed that the normalized Characteristic Path Length (λ) presented the pattern Young > Adult>Elderly in the higher alpha band. Elderly also showed a greater increase in delta and theta bands than Young. The correlation between age and λ showed that higher ages corresponded to higher λ in delta and theta and lower in the alpha2 band; this pattern reflects the age-related modulation of higher (alpha) and decreased (delta) connectivity. The Normalized Clustering coefficient (γ) and small-world network modeling (σ) showed non-significant age-modulation. Evidence from the present study suggests that graph theory can aid in the analysis of connectivity patterns estimated from EEG and can facilitate the study of the physiological and pathological brain aging features of functional connectivity networks.

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

PubMed Central

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

2013-01-01

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

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

PubMed

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

2014-01-01

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

The Functional Organization and Cortical Connections of Motor Cortex in Squirrels

PubMed Central

Cooke, Dylan F.; Padberg, Jeffrey; Zahner, Tony

2012-01-01

Despite extraordinary diversity in the rodent order, studies of motor cortex have been limited to only 2 species, rats and mice. Here, we examine the topographic organization of motor cortex in the Eastern gray squirrel (Sciurus carolinensis) and cortical connections of motor cortex in the California ground squirrel (Spermophilus beecheyi). We distinguish a primary motor area, M1, based on intracortical microstimulation (ICMS), myeloarchitecture, and patterns of connectivity. A sensorimotor area between M1 and the primary somatosensory area, S1, was also distinguished based on connections, functional organization, and myeloarchitecture. We term this field 3a based on similarities with area 3a in nonrodent mammals. Movements are evoked with ICMS in both M1 and 3a in a roughly somatotopic pattern. Connections of 3a and M1 are distinct and suggest the presence of a third far rostral field, termed “F,” possibly involved in motor processing based on its connections. We hypothesize that 3a is homologous to the dysgranular zone (DZ) in S1 of rats and mice. Our results demonstrate that squirrels have both similar and unique features of M1 organization compared with those described in rats and mice, and that changes in 3a/DZ borders appear to have occurred in both lineages. PMID:22021916

Towards affordable biomarkers of frontotemporal dementia: A classification study via network's information sharing.

PubMed

Dottori, Martin; Sedeño, Lucas; Martorell Caro, Miguel; Alifano, Florencia; Hesse, Eugenia; Mikulan, Ezequiel; García, Adolfo M; Ruiz-Tagle, Amparo; Lillo, Patricia; Slachevsky, Andrea; Serrano, Cecilia; Fraiman, Daniel; Ibanez, Agustin

2017-06-19

Developing effective and affordable biomarkers for dementias is critical given the difficulty to achieve early diagnosis. In this sense, electroencephalographic (EEG) methods offer promising alternatives due to their low cost, portability, and growing robustness. Here, we relied on EEG signals and a novel information-sharing method to study resting-state connectivity in patients with behavioral variant frontotemporal dementia (bvFTD) and controls. To evaluate the specificity of our results, we also tested Alzheimer's disease (AD) patients. The classification power of the ensuing connectivity patterns was evaluated through a supervised classification algorithm (support vector machine). In addition, we compared the classification power yielded by (i) functional connectivity, (ii) relevant neuropsychological tests, and (iii) a combination of both. BvFTD patients exhibited a specific pattern of hypoconnectivity in mid-range frontotemporal links, which showed no alterations in AD patients. These functional connectivity alterations in bvFTD were replicated with a low-density EEG setting (20 electrodes). Moreover, while neuropsychological tests yielded acceptable discrimination between bvFTD and controls, the addition of connectivity results improved classification power. Finally, classification between bvFTD and AD patients was better when based on connectivity than on neuropsychological measures. Taken together, such findings underscore the relevance of EEG measures as potential biomarker signatures for clinical settings.

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.

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.

Dual-labeling method for electron microscopy to characterize synaptic connectivity using genetically encoded fluorescent reporters in Drosophila

PubMed Central

Tanaka, Nobuaki K.; Dye, Louis; Stopfer, Mark

2010-01-01

Light and electron microscopy (LM and EM) both offer important advantages for characterizing neuronal circuitry in intact brains: LM can reveal the general patterns neurons trace between brain areas, and EM can confirm synaptic connections between identified neurons within a small area. In a few species, genetic labeling with fluorescent proteins has been used with LM to visualize many kinds of neurons and to analyze their morphologies and projection patterns. However, combining these large-scale patterns with the fine detail available in EM analysis has been a technical challenge. To analyze the synaptic connectivity of neurons expressing fluorescent markers with EM, we developed a dual-labeling method for use with pre-embedded brains. In Drosophila expressing genetic labels and also injected with markers we visualized synaptic connections among two populations of neurons in the AL, one of which has been shown to mediate a specific function, odor evoked neural oscillation. PMID:21074556

Curvilinear locus coeruleus functional connectivity trajectories over the adult lifespan: a 7T MRI study.

PubMed

Jacobs, Heidi I L; Müller-Ehrenberg, Lisa; Priovoulos, Nikos; Roebroeck, Alard

2018-05-24

The locus coeruleus (LC) plays a crucial role in modulating several higher order cognitive functions via its widespread projections to the entire brain. We set out to investigate the hypothesis that LC functional connectivity (FC) may fluctuate nonlinearly with age and explored its relation to memory function. To that end, 49 cognitively healthy individuals (19-74 years) underwent ultra high-resolution 7T resting-state functional magnetic resonance imaging and cognitive testing. FC patterns from the LC to regions of the isodendritic core network and cortical regions were examined using region of interest-to-region of interest analyses. Curvilinear patterns with age were observed for FC between the left LC and cortical regions and the nucleus basalis of Meynert. A linear negative association was observed between age and LC-FC and ventral tegmental area. Higher levels of FC between the LC and nucleus basalis of Meynert or ventral tegmental area were associated with lower memory performance from age of 40 years onward. Thus, different LC-FC patterns early in life can signal subtle memory deficits. Furthermore, these results highlight the importance of intact interactions between neurotransmitter systems for optimal cognitive aging. Copyright © 2018 Elsevier Inc. 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.

Intranasal oxytocin modulates neural functional connectivity during human social interaction.

PubMed

Rilling, James K; Chen, Xiangchuan; Chen, Xu; Haroon, Ebrahim

2018-02-10

Oxytocin (OT) modulates social behavior in primates and many other vertebrate species. Studies in non-primate animals have demonstrated that, in addition to influencing activity within individual brain areas, OT influences functional connectivity across networks of areas involved in social behavior. Previously, we used fMRI to image brain function in human subjects during a dyadic social interaction task following administration of either intranasal oxytocin (INOT) or placebo, and analyzed the data with a standard general linear model. Here, we conduct an extensive re-analysis of these data to explore how OT modulates functional connectivity across a neural network that animal studies implicate in social behavior. OT induced widespread increases in functional connectivity in response to positive social interactions among men and widespread decreases in functional connectivity in response to negative social interactions among women. Nucleus basalis of Meynert, an important regulator of selective attention and motivation with a particularly high density of OT receptors, had the largest number of OT-modulated connections. Regions known to receive mesolimbic dopamine projections such as the nucleus accumbens and lateral septum were also hubs for OT effects on functional connectivity. Our results suggest that the neural mechanism by which OT influences primate social cognition may include changes in patterns of activity across neural networks that regulate social behavior in other animals. © 2018 Wiley Periodicals, Inc.

Effective Connectivity within the Default Mode Network: Dynamic Causal Modeling of Resting-State fMRI Data.

PubMed

Sharaev, Maksim G; Zavyalova, Viktoria V; Ushakov, Vadim L; Kartashov, Sergey I; Velichkovsky, Boris M

2016-01-01

The Default Mode Network (DMN) is a brain system that mediates internal modes of cognitive activity, showing higher neural activation when one is at rest. Nowadays, there is a lot of interest in assessing functional interactions between its key regions, but in the majority of studies only association of Blood-oxygen-level dependent (BOLD) activation patterns is measured, so it is impossible to identify causal influences. There are some studies of causal interactions (i.e., effective connectivity), however often with inconsistent results. The aim of the current work is to find a stable pattern of connectivity between four DMN key regions: the medial prefrontal cortex (mPFC), the posterior cingulate cortex (PCC), left and right intraparietal cortex (LIPC and RIPC). For this purpose functional magnetic resonance imaging (fMRI) data from 30 healthy subjects (1000 time points from each one) was acquired and spectral dynamic causal modeling (DCM) on a resting-state fMRI data was performed. The endogenous brain fluctuations were explicitly modeled by Discrete Cosine Set at the low frequency band of 0.0078-0.1 Hz. The best model at the group level is the one where connections from both bilateral IPC to mPFC and PCC are significant and symmetrical in strength (p < 0.05). Connections between mPFC and PCC are bidirectional, significant in the group and weaker than connections originating from bilateral IPC. In general, all connections from LIPC/RIPC to other DMN regions are much stronger. One can assume that these regions have a driving role within the DMN. Our results replicate some data from earlier works on effective connectivity within the DMN as well as provide new insights on internal DMN relationships and brain's functioning at resting state.

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.

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.

Large-scale changes in network interactions as a physiological signature of spatial neglect

PubMed Central

Baldassarre, Antonello; Ramsey, Lenny; Hacker, Carl L.; Callejas, Alicia; Astafiev, Serguei V.; Metcalf, Nicholas V.; Zinn, Kristi; Rengachary, Jennifer; Snyder, Abraham Z.; Carter, Alex R.; Shulman, Gordon L.

2014-01-01

The relationship between spontaneous brain activity and behaviour following focal injury is not well understood. Here, we report a large-scale study of resting state functional connectivity MRI and spatial neglect following stroke in a large (n = 84) heterogeneous sample of first-ever stroke patients (within 1–2 weeks). Spatial neglect, which is typically more severe after right than left hemisphere injury, includes deficits of spatial attention and motor actions contralateral to the lesion, and low general attention due to impaired vigilance/arousal. Patients underwent structural and resting state functional MRI scans, and spatial neglect was measured using the Posner spatial cueing task, and Mesulam and Behavioural Inattention Test cancellation tests. A principal component analysis of the behavioural tests revealed a main factor accounting for 34% of variance that captured three correlated behavioural deficits: visual neglect of the contralesional visual field, visuomotor neglect of the contralesional field, and low overall performance. In an independent sample (21 healthy subjects), we defined 10 resting state networks consisting of 169 brain regions: visual-fovea and visual-periphery, sensory-motor, auditory, dorsal attention, ventral attention, language, fronto-parietal control, cingulo-opercular control, and default mode. We correlated the neglect factor score with the strength of resting state functional connectivity within and across the 10 resting state networks. All damaged brain voxels were removed from the functional connectivity:behaviour correlational analysis. We found that the correlated behavioural deficits summarized by the factor score were associated with correlated multi-network patterns of abnormal functional connectivity involving large swaths of cortex. Specifically, dorsal attention and sensory-motor networks showed: (i) reduced interhemispheric functional connectivity; (ii) reduced anti-correlation with fronto-parietal and default mode networks in the right hemisphere; and (iii) increased intrahemispheric connectivity with the basal ganglia. These patterns of functional connectivity:behaviour correlations were stronger in patients with right- as compared to left-hemisphere damage and were independent of lesion volume. Our findings identify large-scale changes in resting state network interactions that are a physiological signature of spatial neglect and may relate to its right hemisphere lateralization. PMID:25367028

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.

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.

Altered resting-state functional connectivity in post-traumatic stress disorder: a perfusion MRI study

NASA Astrophysics Data System (ADS)

Li, Baojuan; Liu, Jian; Liu, Yang; Lu, Hong-Bing; Yin, Hong

2013-03-01

The majority of studies on posttraumatic stress disorder (PTSD) so far have focused on delineating patterns of activations during cognitive processes. Recently, more and more researches have started to investigate functional connectivity in PTSD subjects using BOLD-fMRI. Functional connectivity analysis has been demonstrated as a powerful approach to identify biomarkers of different brain diseases. This study aimed to detect resting-state functional connectivity abnormities in patients with PTSD using arterial spin labeling (ASL) fMRI. As a completely non-invasive technique, ASL allows quantitative estimates of cerebral blood flow (CBF). Compared with BOLD-fMRI, ASL fMRI has many advantages, including less low-frequency signal drifts, superior functional localization, etc. In the current study, ASL images were collected from 10 survivors in mining disaster with recent onset PTSD and 10 survivors without PTSD. Decreased regional CBF in the right middle temporal gyrus, lingual gyrus, and postcentral gyrus was detected in the PTSD patients. Seed-based resting-state functional connectivity analysis was performed using an area in the right middle temporal gyrus as region of interest. Compared with the non-PTSD group, the PTSD subjects demonstrated increased functional connectivity between the right middle temporal gyrus and the right superior temporal gyrus, the left middle temporal gyrus. Meanwhile, decreased functional connectivity between the right middle temporal gyrus and the right postcentral gyrus, the right superior parietal lobule was also found in the PTSD patients. This is the first study which investigated resting-state functional connectivity in PTSD using ASL images. The results may provide new insight into the neural substrates of PTSD.

Pattern-Based Inverse Modeling for Characterization of Subsurface Flow Models with Complex Geologic Heterogeneity

NASA Astrophysics Data System (ADS)

Golmohammadi, A.; Jafarpour, B.; M Khaninezhad, M. R.

2017-12-01

Calibration of heterogeneous subsurface flow models leads to ill-posed nonlinear inverse problems, where too many unknown parameters are estimated from limited response measurements. When the underlying parameters form complex (non-Gaussian) structured spatial connectivity patterns, classical variogram-based geostatistical techniques cannot describe the underlying connectivity patterns. Modern pattern-based geostatistical methods that incorporate higher-order spatial statistics are more suitable for describing such complex spatial patterns. Moreover, when the underlying unknown parameters are discrete (geologic facies distribution), conventional model calibration techniques that are designed for continuous parameters cannot be applied directly. In this paper, we introduce a novel pattern-based model calibration method to reconstruct discrete and spatially complex facies distributions from dynamic flow response data. To reproduce complex connectivity patterns during model calibration, we impose a feasibility constraint to ensure that the solution follows the expected higher-order spatial statistics. For model calibration, we adopt a regularized least-squares formulation, involving data mismatch, pattern connectivity, and feasibility constraint terms. Using an alternating directions optimization algorithm, the regularized objective function is divided into a continuous model calibration problem, followed by mapping the solution onto the feasible set. The feasibility constraint to honor the expected spatial statistics is implemented using a supervised machine learning algorithm. The two steps of the model calibration formulation are repeated until the convergence criterion is met. Several numerical examples are used to evaluate the performance of the developed method.

Phases of Hyperconnectivity and Hypoconnectivity in the Default Mode and Salience Networks Track with Amyloid and Tau in Clinically Normal Individuals

PubMed Central

Hedden, Trey; Mormino, Elizabeth C.; Huijbers, Willem; LaPoint, Molly; Buckley, Rachel F.

2017-01-01

Alzheimer's disease (AD) is characterized by two hallmark molecular pathologies: amyloid aβ1–42 and Tau neurofibrillary tangles. To date, studies of functional connectivity MRI (fcMRI) in individuals with preclinical AD have relied on associations with in vivo measures of amyloid pathology. With the recent advent of in vivo Tau-PET tracers it is now possible to extend investigations on fcMRI in a sample of cognitively normal elderly humans to regional measures of Tau. We modeled fcMRI measures across four major cortical association networks [default-mode network (DMN), salience network (SAL), dorsal attention network, and frontoparietal control network] as a function of global cortical amyloid [Pittsburgh Compound B (PiB)-PET] and regional Tau (AV1451-PET) in entorhinal, inferior temporal (IT), and inferior parietal cortex. Results showed that the interaction term between PiB and IT AV1451 was significantly associated with connectivity in the DMN and salience. The interaction revealed that amyloid-positive (aβ+) individuals show increased connectivity in the DMN and salience when neocortical Tau levels are low, whereas aβ+ individuals demonstrate decreased connectivity in these networks as a function of elevated Tau-PET signal. This pattern suggests a hyperconnectivity phase followed by a hypoconnectivity phase in the course of preclinical AD. SIGNIFICANCE STATEMENT This article offers a first look at the relationship between Tau-PET imaging with F18-AV1451 and functional connectivity MRI (fcMRI) in the context of amyloid-PET imaging. The results suggest a nonlinear relationship between fcMRI and both Tau-PET and amyloid-PET imaging. The pattern supports recent conjecture that the AD fcMRI trajectory is characterized by periods of both hyperconnectivity and hypoconnectivity. Furthermore, this nonlinear pattern can account for the sometimes conflicting reports of associations between amyloid and fcMRI in individuals with preclinical Alzheimer's disease. PMID:28314821

Phases of Hyperconnectivity and Hypoconnectivity in the Default Mode and Salience Networks Track with Amyloid and Tau in Clinically Normal Individuals.

PubMed

Schultz, Aaron P; Chhatwal, Jasmeer P; Hedden, Trey; Mormino, Elizabeth C; Hanseeuw, Bernard J; Sepulcre, Jorge; Huijbers, Willem; LaPoint, Molly; Buckley, Rachel F; Johnson, Keith A; Sperling, Reisa A

2017-04-19

Alzheimer's disease (AD) is characterized by two hallmark molecular pathologies: amyloid aβ 1-42 and Tau neurofibrillary tangles. To date, studies of functional connectivity MRI (fcMRI) in individuals with preclinical AD have relied on associations with in vivo measures of amyloid pathology. With the recent advent of in vivo Tau-PET tracers it is now possible to extend investigations on fcMRI in a sample of cognitively normal elderly humans to regional measures of Tau. We modeled fcMRI measures across four major cortical association networks [default-mode network (DMN), salience network (SAL), dorsal attention network, and frontoparietal control network] as a function of global cortical amyloid [Pittsburgh Compound B (PiB)-PET] and regional Tau (AV1451-PET) in entorhinal, inferior temporal (IT), and inferior parietal cortex. Results showed that the interaction term between PiB and IT AV1451 was significantly associated with connectivity in the DMN and salience. The interaction revealed that amyloid-positive (aβ + ) individuals show increased connectivity in the DMN and salience when neocortical Tau levels are low, whereas aβ + individuals demonstrate decreased connectivity in these networks as a function of elevated Tau-PET signal. This pattern suggests a hyperconnectivity phase followed by a hypoconnectivity phase in the course of preclinical AD. SIGNIFICANCE STATEMENT This article offers a first look at the relationship between Tau-PET imaging with F 18 -AV1451 and functional connectivity MRI (fcMRI) in the context of amyloid-PET imaging. The results suggest a nonlinear relationship between fcMRI and both Tau-PET and amyloid-PET imaging. The pattern supports recent conjecture that the AD fcMRI trajectory is characterized by periods of both hyperconnectivity and hypoconnectivity. Furthermore, this nonlinear pattern can account for the sometimes conflicting reports of associations between amyloid and fcMRI in individuals with preclinical Alzheimer's disease. Copyright © 2017 the authors 0270-6474/17/374324-09$15.00/0.

Early-Course Unmedicated Schizophrenia Patients Exhibit Elevated Prefrontal Connectivity Associated with Longitudinal Change

PubMed Central

Anticevic, Alan; Hu, Xinyu; Xiao, Yuan; Hu, Junmei; Li, Fei; Bi, Feng; Cole, Michael W.; Savic, Aleksandar; Yang, Genevieve J.; Repovs, Grega; Murray, John D.; Wang, Xiao-Jing; Huang, Xiaoqi; Lui, Su; Krystal, John H.

2015-01-01

Strong evidence implicates prefrontal cortex (PFC) as a major source of functional impairment in severe mental illness such as schizophrenia. Numerous schizophrenia studies report deficits in PFC structure, activation, and functional connectivity in patients with chronic illness, suggesting that deficient PFC functional connectivity occurs in this disorder. However, the PFC functional connectivity patterns during illness onset and its longitudinal progression remain uncharacterized. Emerging evidence suggests that early-course schizophrenia involves increased PFC glutamate, which might elevate PFC functional connectivity. To test this hypothesis, we examined 129 non-medicated, human subjects diagnosed with early-course schizophrenia and 106 matched healthy human subjects using both whole-brain data-driven and hypothesis-driven PFC analyses of resting-state fMRI. We identified increased PFC connectivity in early-course patients, predictive of symptoms and diagnostic classification, but less evidence for “hypoconnectivity.” At the whole-brain level, we observed “hyperconnectivity” around areas centered on the default system, with modest overlap with PFC-specific effects. The PFC hyperconnectivity normalized for a subset of the sample followed longitudinally (n = 25), which also predicted immediate symptom improvement. Biologically informed computational modeling implicates altered overall connection strength in schizophrenia. The initial hyperconnectivity, which may decrease longitudinally, could have prognostic and therapeutic implications. PMID:25568120

Early-course unmedicated schizophrenia patients exhibit elevated prefrontal connectivity associated with longitudinal change.

PubMed

Anticevic, Alan; Hu, Xinyu; Xiao, Yuan; Hu, Junmei; Li, Fei; Bi, Feng; Cole, Michael W; Savic, Aleksandar; Yang, Genevieve J; Repovs, Grega; Murray, John D; Wang, Xiao-Jing; Huang, Xiaoqi; Lui, Su; Krystal, John H; Gong, Qiyong

2015-01-07

Strong evidence implicates prefrontal cortex (PFC) as a major source of functional impairment in severe mental illness such as schizophrenia. Numerous schizophrenia studies report deficits in PFC structure, activation, and functional connectivity in patients with chronic illness, suggesting that deficient PFC functional connectivity occurs in this disorder. However, the PFC functional connectivity patterns during illness onset and its longitudinal progression remain uncharacterized. Emerging evidence suggests that early-course schizophrenia involves increased PFC glutamate, which might elevate PFC functional connectivity. To test this hypothesis, we examined 129 non-medicated, human subjects diagnosed with early-course schizophrenia and 106 matched healthy human subjects using both whole-brain data-driven and hypothesis-driven PFC analyses of resting-state fMRI. We identified increased PFC connectivity in early-course patients, predictive of symptoms and diagnostic classification, but less evidence for "hypoconnectivity." At the whole-brain level, we observed "hyperconnectivity" around areas centered on the default system, with modest overlap with PFC-specific effects. The PFC hyperconnectivity normalized for a subset of the sample followed longitudinally (n = 25), which also predicted immediate symptom improvement. Biologically informed computational modeling implicates altered overall connection strength in schizophrenia. The initial hyperconnectivity, which may decrease longitudinally, could have prognostic and therapeutic implications. Copyright © 2015 the authors 0270-6474/15/350267-20$15.00/0.

Network structure shapes spontaneous functional connectivity dynamics.

PubMed

Shen, Kelly; Hutchison, R Matthew; Bezgin, Gleb; Everling, Stefan; McIntosh, Anthony R

2015-04-08

The structural organization of the brain constrains the range of interactions between different regions and shapes ongoing information processing. Therefore, it is expected that large-scale dynamic functional connectivity (FC) patterns, a surrogate measure of coordination between brain regions, will be closely tied to the fiber pathways that form the underlying structural network. Here, we empirically examined the influence of network structure on FC dynamics by comparing resting-state FC (rsFC) obtained using BOLD-fMRI in macaques (Macaca fascicularis) to structural connectivity derived from macaque axonal tract tracing studies. Consistent with predictions from simulation studies, the correspondence between rsFC and structural connectivity increased as the sample duration increased. Regions with reciprocal structural connections showed the most stable rsFC across time. The data suggest that the transient nature of FC is in part dependent on direct underlying structural connections, but also that dynamic coordination can occur via polysynaptic pathways. Temporal stability was found to be dependent on structural topology, with functional connections within the rich-club core exhibiting the greatest stability over time. We discuss these findings in light of highly variable functional hubs. The results further elucidate how large-scale dynamic functional coordination exists within a fixed structural architecture. Copyright © 2015 the authors 0270-6474/15/355579-10$15.00/0.

Mapping the functional connectome traits of levels of consciousness.

PubMed

Amico, Enrico; Marinazzo, Daniele; Di Perri, Carol; Heine, Lizette; Annen, Jitka; Martial, Charlotte; Dzemidzic, Mario; Kirsch, Murielle; Bonhomme, Vincent; Laureys, Steven; Goñi, Joaquín

2017-03-01

Examining task-free functional connectivity (FC) in the human brain offers insights on how spontaneous integration and segregation of information relate to human cognition, and how this organization may be altered in different conditions, and neurological disorders. This is particularly relevant for patients in disorders of consciousness (DOC) following severe acquired brain damage and coma, one of the most devastating conditions in modern medical care. We present a novel data-driven methodology, connICA, which implements Independent Component Analysis (ICA) for the extraction of robust independent FC patterns (FC-traits) from a set of individual functional connectomes, without imposing any a priori data stratification into groups. We here apply connICA to investigate associations between network traits derived from task-free FC and cognitive/clinical features that define levels of consciousness. Three main independent FC-traits were identified and linked to consciousness-related clinical features. The first one represents the functional configuration of a "resting" human brain, and it is associated to a sedative (sevoflurane), the overall effect of the pathology and the level of arousal. The second FC-trait reflects the disconnection of the visual and sensory-motor connectivity patterns. It also relates to the time since the insult and to the ability of communicating with the external environment. The third FC-trait isolates the connectivity pattern encompassing the fronto-parietal and the default-mode network areas as well as the interaction between left and right hemispheres, which are also associated to the awareness of the self and its surroundings. Each FC-trait represents a distinct functional process with a role in the degradation of conscious states of functional brain networks, shedding further light on the functional sub-circuits that get disrupted in severe brain-damage. Copyright © 2017. Published by Elsevier Inc.

Sparse network-based models for patient classification using fMRI

PubMed Central

Rosa, Maria J.; Portugal, Liana; Hahn, Tim; Fallgatter, Andreas J.; Garrido, Marta I.; Shawe-Taylor, John; Mourao-Miranda, Janaina

2015-01-01

Pattern recognition applied to whole-brain neuroimaging data, such as functional Magnetic Resonance Imaging (fMRI), has proved successful at discriminating psychiatric patients from healthy participants. However, predictive patterns obtained from whole-brain voxel-based features are difficult to interpret in terms of the underlying neurobiology. Many psychiatric disorders, such as depression and schizophrenia, are thought to be brain connectivity disorders. Therefore, pattern recognition based on network models might provide deeper insights and potentially more powerful predictions than whole-brain voxel-based approaches. Here, we build a novel sparse network-based discriminative modeling framework, based on Gaussian graphical models and L1-norm regularized linear Support Vector Machines (SVM). In addition, the proposed framework is optimized in terms of both predictive power and reproducibility/stability of the patterns. Our approach aims to provide better pattern interpretation than voxel-based whole-brain approaches by yielding stable brain connectivity patterns that underlie discriminative changes in brain function between the groups. We illustrate our technique by classifying patients with major depressive disorder (MDD) and healthy participants, in two (event- and block-related) fMRI datasets acquired while participants performed a gender discrimination and emotional task, respectively, during the visualization of emotional valent faces. PMID:25463459

Identification of autism spectrum disorder using deep learning and the ABIDE dataset.

PubMed

Heinsfeld, Anibal Sólon; Franco, Alexandre Rosa; Craddock, R Cameron; Buchweitz, Augusto; Meneguzzi, Felipe

2018-01-01

The goal of the present study was to apply deep learning algorithms to identify autism spectrum disorder (ASD) patients from large brain imaging dataset, based solely on the patients brain activation patterns. We investigated ASD patients brain imaging data from a world-wide multi-site database known as ABIDE (Autism Brain Imaging Data Exchange). ASD is a brain-based disorder characterized by social deficits and repetitive behaviors. According to recent Centers for Disease Control data, ASD affects one in 68 children in the United States. We investigated patterns of functional connectivity that objectively identify ASD participants from functional brain imaging data, and attempted to unveil the neural patterns that emerged from the classification. The results improved the state-of-the-art by achieving 70% accuracy in identification of ASD versus control patients in the dataset. The patterns that emerged from the classification show an anticorrelation of brain function between anterior and posterior areas of the brain; the anticorrelation corroborates current empirical evidence of anterior-posterior disruption in brain connectivity in ASD. We present the results and identify the areas of the brain that contributed most to differentiating ASD from typically developing controls as per our deep learning model.

Synchrony of corticostriatal-midbrain activation enables normal inhibitory control and conflict processing in recovering alcoholic men.

PubMed

Schulte, Tilman; Müller-Oehring, Eva M; Sullivan, Edith V; Pfefferbaum, Adolf

2012-02-01

Alcohol dependence is associated with inhibitory control deficits, possibly related to abnormalities in frontoparietal cortical and midbrain function and connectivity. We examined functional connectivity and microstructural fiber integrity between frontoparietal and midbrain structures using a Stroop Match-to-Sample task with functional magnetic resonance imaging and diffusion tensor imaging in 18 alcoholic and 17 control subjects. Manipulation of color cues and response repetition sequences modulated cognitive demands during Stroop conflict. Despite similar lateral frontoparietal activity and functional connectivity in alcoholic and control subjects when processing conflict, control subjects deactivated the posterior cingulate cortex (PCC), whereas alcoholic subjects did not. Posterior cingulum fiber integrity predicted the degree of PCC deactivation in control but not alcoholic subjects. Also, PCC activity was modulated by executive control demands: activated during response switching and deactivated during response repetition. Alcoholics showed the opposite pattern: activation during repetition and deactivation during switching. Here, in alcoholic subjects, greater deviations from the normal PCC activity correlated with higher amounts of lifetime alcohol consumption. A functional dissociation of brain network connectivity between the groups further showed that control subjects exhibited greater corticocortical connectivity among middle cingulate, posterior cingulate, and medial prefrontal cortices than alcoholic subjects. In contrast, alcoholic subjects exhibited greater midbrain-orbitofrontal cortical network connectivity than control subjects. Degree of microstructural fiber integrity predicted robustness of functional connectivity. Thus, even subtle compromise of microstructural connectivity in alcoholism can influence modulation of functional connectivity and underlie alcohol-related cognitive impairment. Copyright © 2012 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

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.

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

PubMed Central

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

2015-01-01

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

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

PubMed

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

2015-01-01

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

Altered functional connectivity in lesional peduncular hallucinosis with REM sleep behavior disorder.

PubMed

Geddes, Maiya R; Tie, Yanmei; Gabrieli, John D E; McGinnis, Scott M; Golby, Alexandra J; Whitfield-Gabrieli, Susan

2016-01-01

Brainstem lesions causing peduncular hallucinosis (PH) produce vivid visual hallucinations occasionally accompanied by sleep disorders. Overlapping brainstem regions modulate visual pathways and REM sleep functions via gating of thalamocortical networks. A 66-year-old man with paroxysmal atrial fibrillation developed abrupt-onset complex visual hallucinations with preserved insight and violent dream enactment behavior. Brain MRI showed restricted diffusion in the left rostrodorsal pons suggestive of an acute ischemic stroke. REM sleep behavior disorder (RBD) was diagnosed on polysomnography. We investigated the integrity of ponto-geniculate-occipital circuits with seed-based resting-state functional connectivity MRI (rs-fcMRI) in this patient compared to 46 controls. Rs-fcMRI revealed significantly reduced functional connectivity between the lesion and lateral geniculate nuclei (LGN), and between LGN and visual association cortex compared to controls. Conversely, functional connectivity between brainstem and visual association cortex, and between visual association cortex and prefrontal cortex (PFC) was significantly increased in the patient. Focal damage to the rostrodorsal pons is sufficient to cause RBD and PH in humans, suggesting an overlapping mechanism in both syndromes. This lesion produced a pattern of altered functional connectivity consistent with disrupted visual cortex connectivity via de-afferentation of thalamocortical pathways. Crown Copyright © 2015. Published by Elsevier Ltd. All rights reserved.

Amygdala subnuclei resting-state functional connectivity sex and estrogen differences.

PubMed

Engman, Jonas; Linnman, Clas; Van Dijk, Koene R A; Milad, Mohammed R

2016-01-01

The amygdala is a hub in emotional processing, including that of negative affect. Healthy men and women have distinct differences in amygdala responses, potentially setting the stage for the observed sex differences in the prevalence of fear, anxiety, and pain disorders. Here, we examined how amygdala subnuclei resting-state functional connectivity is affected by sex, as well as explored how the functional connectivity is related to estrogen levels. Resting-state functional connectivity was measured using functional magnetic resonance imaging (fMRI) with seeds placed in the left and right laterobasal (LB) and centromedial (CM) amygdala. Sex differences were studied in 48 healthy men and 48 healthy women, matched for age, while the association with estrogen was analyzed in a subsample of 24 women, for whom hormone levels had been assessed. For the hormone analyses, the subsample was further divided into a lower and higher estrogen levels group based on a median split. We found distinct sex differences in the LB and CM amygdala resting-state functional connectivity, as well as preliminary evidence for an association between estrogen levels and connectivity patterns. These results are potentially valuable in explaining why women are more afflicted by conditions of negative affect than are men, and could imply a mechanistic role for estrogen in modulating emotion. Copyright © 2015 Elsevier Ltd. All rights reserved.

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.

Modelling non-Euclidean movement and landscape connectivity in highly structured ecological networks

USGS Publications Warehouse

Sutherland, Christopher; Fuller, Angela K.; Royle, J. Andrew

2015-01-01

The ecological distance SCR model uses spatially indexed capture-recapture data to estimate how activity patterns are influenced by landscape structure. As well as reducing bias in estimates of abundance, this approach provides biologically realistic representations of home range geometry, and direct information about species-landscape interactions. The incorporation of both structural (landscape) and functional (movement) components of connectivity provides a direct measure of species-specific landscape connectivity.

Connectivity of Sleep- and Wake-Promoting Regions of the Human Hypothalamus During Resting Wakefulness.

PubMed

Boes, Aaron D; Fischer, David; Geerling, Joel C; Bruss, Joel; Saper, Clifford B; Fox, Michael D

2018-05-29

The hypothalamus is a central hub for regulating sleep-wake patterns, the circuitry of which has been investigated extensively in experimental animals. This work has identified a wake-promoting region in the posterior hypothalamus, with connections to other wake-promoting regions, and a sleep-promoting region in the anterior hypothalamus, with inhibitory projections to the posterior hypothalamus. It is unclear whether a similar organization exists in humans. Here, we use anatomical landmarks to identify homologous sleep and wake-promoting regions of the human hypothalamus and investigate their functional relationships using resting-state functional connectivity MRI in healthy awake participants. First, we identify a negative correlation (anticorrelation) between the anterior and posterior hypothalamus, two regions with opposing roles in sleep-wake regulation. Next, we show that hypothalamic connectivity predicts a pattern of regional sleep-wake changes previously observed in humans. Specifically, regions that are more positively correlated with the posterior hypothalamus and more negatively correlated with the anterior hypothalamus correspond to regions with the greatest change in cerebral blood flow between sleep-wake states. Taken together, these findings provide preliminary evidence relating a hypothalamic circuit investigated in animals to sleep-wake neuroimaging results in humans, with implications for our understanding of human sleep-wake regulation and the functional significance of anticorrelations.

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.

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

Intelligence-related differences in the asymmetry of spontaneous cerebral activity.

PubMed

Santarnecchi, Emiliano; Tatti, Elisa; Rossi, Simone; Serino, Vinicio; Rossi, Alessandro

2015-09-01

Recent evidence suggests the spontaneous BOLD signal synchronization of corresponding interhemispheric, homotopic regions as a stable trait of human brain physiology, with emerging differences in such organization being also related to some pathological conditions. To understand whether such brain functional symmetries play a role into higher-order cognitive functioning, here we correlated the functional homotopy profiles of 119 healthy subjects with their intelligence level. Counterintuitively, reduced homotopic connectivity in above average-IQ versus average-IQ subjects was observed, with significant reductions in visual and somatosensory cortices, supplementary motor area, rolandic operculum, and middle temporal gyrus, possibly suggesting that a downgrading of interhemispheric talk at rest could be associated with higher cognitive functioning. These regions also showed an increased spontaneous synchrony with medial structures located in ipsi- and contralateral hemispheres, with such pattern being mostly detectable for regions placed in the left hemisphere. The interactions with age and gender have been also tested, with different patterns for subjects above and below 25 years old and less homotopic connectivity in the prefrontal cortex and posterior midline regions in female participants with higher IQ scores. These findings support prior evidence suggesting a functional role for homotopic connectivity in human cognitive expression, promoting the reduction of synchrony between primary sensory regions as a predictor of higher intelligence levels. © 2015 Wiley Periodicals, Inc.

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.

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.

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.

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

Preschool Anxiety Disorders Predict Different Patterns of Amygdala-Prefrontal Connectivity at School-Age

PubMed Central

Carpenter, Kimberly L. H.; Angold, Adrian; Chen, Nan-Kuei; Copeland, William E.; Gaur, Pooja; Pelphrey, Kevin; Song, Allen W.; Egger, Helen L.

2015-01-01

Objective In this prospective, longitudinal study of young children, we examined whether a history of preschool generalized anxiety, separation anxiety, and/or social phobia is associated with amygdala-prefrontal dysregulation at school-age. As an exploratory analysis, we investigated whether distinct anxiety disorders differ in the patterns of this amygdala-prefrontal dysregulation. Methods Participants were children taking part in a 5-year study of early childhood brain development and anxiety disorders. Preschool symptoms of generalized anxiety, separation anxiety, and social phobia were assessed with the Preschool Age Psychiatric Assessment (PAPA) in the first wave of the study when the children were between 2 and 5 years old. The PAPA was repeated at age 6. We conducted functional MRIs when the children were 5.5 to 9.5 year old to assess neural responses to viewing of angry and fearful faces. Results A history of preschool social phobia predicted less school-age functional connectivity between the amygdala and the ventral prefrontal cortices to angry faces. Preschool generalized anxiety predicted less functional connectivity between the amygdala and dorsal prefrontal cortices in response to fearful faces. Finally, a history of preschool separation anxiety predicted less school-age functional connectivity between the amygdala and the ventral prefrontal cortices to angry faces and greater school-age functional connectivity between the amygdala and dorsal prefrontal cortices to angry faces. Conclusions Our results suggest that there are enduring neurobiological effects associated with a history of preschool anxiety, which occur over-and-above the effect of subsequent emotional symptoms. Our results also provide preliminary evidence for the neurobiological differentiation of specific preschool anxiety disorders. PMID:25625285

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

Resting-State Functional Connectivity in Autism Spectrum Disorders: A Review

PubMed Central

Hull, Jocelyn V.; Jacokes, Zachary J.; Torgerson, Carinna M.; Irimia, Andrei; Van Horn, John Darrell

2017-01-01

Ongoing debate exists within the resting-state functional MRI (fMRI) literature over how intrinsic connectivity is altered in the autistic brain, with reports of general over-connectivity, under-connectivity, and/or a combination of both. Classifying autism using brain connectivity is complicated by the heterogeneous nature of the condition, allowing for the possibility of widely variable connectivity patterns among individuals with the disorder. Further differences in reported results may be attributable to the age and sex of participants included, designs of the resting-state scan, and to the analysis technique used to evaluate the data. This review systematically examines the resting-state fMRI autism literature to date and compares studies in an attempt to draw overall conclusions that are presently challenging. We also propose future direction for rs-fMRI use to categorize individuals with autism spectrum disorder, serve as a possible diagnostic tool, and best utilize data-sharing initiatives. PMID:28101064

Voltage-sensitive-dye imaging of microstimulation-evoked neural activity through intracortical horizontal and callosal connections in cat visual cortex.

PubMed

Suzurikawa, Jun; Tani, Toshiki; Nakao, Masayuki; Tanaka, Shigeru; Takahashi, Hirokazu

2009-12-01

Recently, intrinsic signal optical imaging has been widely used as a routine procedure for visualizing cortical functional maps. We do not, however, have a well-established imaging method for visualizing cortical functional connectivity indicating spatio-temporal patterns of activity propagation in the cerebral cortex. In the present study, we developed a novel experimental setup for investigating the propagation of neural activities combining the intracortical microstimulation (ICMS) technique with voltage sensitive dye (VSD) imaging, and demonstrated the feasibility of this setup applying to the measurement of time-dependent intra- and inter-hemispheric spread of ICMS-evoked excitation in the cat visual cortices, areas 17 and 18. A microelectrode array for the ICMS was inserted with a specially designed easy-to-detach electrode holder around the 17/18 transition zones (TZs), where the left and right hemispheres were interconnected via the corpus callosum. The microelectrode array was stably anchored in agarose without any holder, which enabled us to visualize evoked activities even in the vicinity of penetration sites as well as in a wide recording region that covered a part of both hemispheres. The VSD imaging could successfully visualize ICMS-evoked excitation and subsequent propagation in the visual cortices contralateral as well as ipsilateral to the ICMS. Using the orientation maps as positional references, we showed that the activity propagation patterns were consistent with previously reported anatomical patterns of intracortical and interhemispheric connections. This finding indicates that our experimental system can serve for the investigation of cortical functional connectivity.

Human connectome module pattern detection using a new multi-graph MinMax cut model.

PubMed

De, Wang; Wang, Yang; Nie, Feiping; Yan, Jingwen; Cai, Weidong; Saykin, Andrew J; Shen, Li; Huang, Heng

2014-01-01

Many recent scientific efforts have been devoted to constructing the human connectome using Diffusion Tensor Imaging (DTI) data for understanding the large-scale brain networks that underlie higher-level cognition in human. However, suitable computational network analysis tools are still lacking in human connectome research. To address this problem, we propose a novel multi-graph min-max cut model to detect the consistent network modules from the brain connectivity networks of all studied subjects. A new multi-graph MinMax cut model is introduced to solve this challenging computational neuroscience problem and the efficient optimization algorithm is derived. In the identified connectome module patterns, each network module shows similar connectivity patterns in all subjects, which potentially associate to specific brain functions shared by all subjects. We validate our method by analyzing the weighted fiber connectivity networks. The promising empirical results demonstrate the effectiveness of our method.

Structural habitat predicts functional dispersal habitat of a large carnivore: how leopards change spots.

PubMed

Fattebert, Julien; Robinson, Hugh S; Balme, Guy; Slotow, Rob; Hunter, Luke

2015-10-01

Natal dispersal promotes inter-population linkage, and is key to spatial distribution of populations. Degradation of suitable landscape structures beyond the specific threshold of an individual's ability to disperse can therefore lead to disruption of functional landscape connectivity and impact metapopulation function. Because it ignores behavioral responses of individuals, structural connectivity is easier to assess than functional connectivity and is often used as a surrogate for landscape connectivity modeling. However using structural resource selection models as surrogate for modeling functional connectivity through dispersal could be erroneous. We tested how well a second-order resource selection function (RSF) models (structural connectivity), based on GPS telemetry data from resident adult leopard (Panthera pardus L.), could predict subadult habitat use during dispersal (functional connectivity). We created eight non-exclusive subsets of the subadult data based on differing definitions of dispersal to assess the predictive ability of our adult-based RSF model extrapolated over a broader landscape. Dispersing leopards used habitats in accordance with adult selection patterns, regardless of the definition of dispersal considered. We demonstrate that, for a wide-ranging apex carnivore, functional connectivity through natal dispersal corresponds to structural connectivity as modeled by a second-order RSF. Mapping of the adult-based habitat classes provides direct visualization of the potential linkages between populations, without the need to model paths between a priori starting and destination points. The use of such landscape scale RSFs may provide insight into predicting suitable dispersal habitat peninsulas in human-dominated landscapes where mitigation of human-wildlife conflict should be focused. We recommend the use of second-order RSFs for landscape conservation planning and propose a similar approach to the conservation of other wide-ranging large carnivore species where landscape-scale resource selection data already exist.

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.

How Visual Is the Visual Cortex? Comparing Connectional and Functional Fingerprints between Congenitally Blind and Sighted Individuals.

PubMed

Wang, Xiaoying; Peelen, Marius V; Han, Zaizhu; He, Chenxi; Caramazza, Alfonso; Bi, Yanchao

2015-09-09

Classical animal visual deprivation studies and human neuroimaging studies have shown that visual experience plays a critical role in shaping the functionality and connectivity of the visual cortex. Interestingly, recent studies have additionally reported circumscribed regions in the visual cortex in which functional selectivity was remarkably similar in individuals with and without visual experience. Here, by directly comparing resting-state and task-based fMRI data in congenitally blind and sighted human subjects, we obtained large-scale continuous maps of the degree to which connectional and functional "fingerprints" of ventral visual cortex depend on visual experience. We found a close agreement between connectional and functional maps, pointing to a strong interdependence of connectivity and function. Visual experience (or the absence thereof) had a pronounced effect on the resting-state connectivity and functional response profile of occipital cortex and the posterior lateral fusiform gyrus. By contrast, connectional and functional fingerprints in the anterior medial and posterior lateral parts of the ventral visual cortex were statistically indistinguishable between blind and sighted individuals. These results provide a large-scale mapping of the influence of visual experience on the development of both functional and connectivity properties of visual cortex, which serves as a basis for the formulation of new hypotheses regarding the functionality and plasticity of specific subregions. Significance statement: How is the functionality and connectivity of the visual cortex shaped by visual experience? By directly comparing resting-state and task-based fMRI data in congenitally blind and sighted subjects, we obtained large-scale continuous maps of the degree to which connectional and functional "fingerprints" of ventral visual cortex depend on visual experience. In addition to revealing regions that are strongly dependent on visual experience (early visual cortex and posterior fusiform gyrus), our results showed regions in which connectional and functional patterns are highly similar in blind and sighted individuals (anterior medial and posterior lateral ventral occipital temporal cortex). These results serve as a basis for the formulation of new hypotheses regarding the functionality and plasticity of specific subregions of the visual cortex. Copyright © 2015 the authors 0270-6474/15/3512545-15$15.00/0.

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.

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.

Functional Characterization and Differential Coactivation Patterns of Two Cytoarchitectonic Visual Areas on the Human Posterior Fusiform Gyrus

PubMed Central

Caspers, Julian; Zilles, Karl; Amunts, Katrin; Laird, Angela R.; Fox, Peter T.; Eickhoff, Simon B.

2016-01-01

The ventral stream of the human extrastriate visual cortex shows a considerable functional heterogeneity from early visual processing (posterior) to higher, domain-specific processing (anterior). The fusiform gyrus hosts several of those “high-level” functional areas. We recently found a subdivision of the posterior fusiform gyrus on the microstructural level, that is, two distinct cytoarchitectonic areas, FG1 and FG2 (Caspers et al., Brain Structure & Function, 2013). To gain a first insight in the function of these two areas, here we studied their behavioral involvement and coactivation patterns by means of meta-analytic connectivity modeling based on the BrainMap database (www.brainmap.org), using probabilistic maps of these areas as seed regions. The coactivation patterns of the areas support the concept of a common involvement in a core network subserving different cognitive tasks, that is, object recognition, visual language perception, or visual attention. In addition, the analysis supports the previous cytoarchitectonic parcellation, indicating that FG1 appears as a transitional area between early and higher visual cortex and FG2 as a higher-order one. The latter area is furthermore lateralized, as it shows strong relations to the visual language processing system in the left hemisphere, while its right side is stronger associated with face selective regions. These findings indicate that functional lateralization of area FG2 relies on a different pattern of connectivity rather than side-specific cytoarchitectonic features. PMID:24038902

Pattern reverberation in networks of excitable systems with connection delays

NASA Astrophysics Data System (ADS)

Lücken, Leonhard; Rosin, David P.; Worlitzer, Vasco M.; Yanchuk, Serhiy

2017-01-01

We consider the recurrent pulse-coupled networks of excitable elements with delayed connections, which are inspired by the biological neural networks. If the delays are tuned appropriately, the network can either stay in the steady resting state, or alternatively, exhibit a desired spiking pattern. It is shown that such a network can be used as a pattern-recognition system. More specifically, the application of the correct pattern as an external input to the network leads to a self-sustained reverberation of the encoded pattern. In terms of the coupling structure, the tolerance and the refractory time of the individual systems, we determine the conditions for the uniqueness of the sustained activity, i.e., for the functionality of the network as an unambiguous pattern detector. We point out the relation of the considered systems with cyclic polychronous groups and show how the assumed delay configurations may arise in a self-organized manner when a spike-time dependent plasticity of the connection delays is assumed. As excitable elements, we employ the simplistic coincidence detector models as well as the Hodgkin-Huxley neuron models. Moreover, the system is implemented experimentally on a Field-Programmable Gate Array.

Sex differences in orbitofrontal connectivity in male and female veterans with TBI.

PubMed

McGlade, Erin; Rogowska, Jadwiga; Yurgelun-Todd, Deborah

2015-09-01

More female soldiers are now serving in combat theaters than at any other time. However, little is known about possible sex differences underlying the neuropathology and manifestation of one of modern war's signature injuries, traumatic brain injury (TBI). The paucity of information regarding sex differences in TBI is particularly evident when examining changes in executive function and emotion regulation associated with post concussive events. The current study objective was to observe whether patterns of orbitofrontal (OFC) functional connectivity would differ between female veterans with TBI and their male counterparts. The study further sought to determine whether OFC connectivity might be differentially associated with clinical measures of aggression and hostility. Seventeen female veterans and 24 male veterans, age 18 to 25, who met criteria for TBI completed resting state magnetic resonance imaging (MRI) and clinical assessment measures. Imaging data were analyzed using left and right seed regions of the OFC, and regression analyses were conducted to observe the relationship between resting state connectivity and self-reported aggression. Females and males in this study differed in OFC connectivity, with females demonstrating greater connectivity between left and right OFC and parietal and occipital regions and males demonstrating greater connectivity between left and right OFC and frontal and temporal regions. Significant associations between resting state connectivity and clinical measures were found only in male veterans. These findings suggest that TBI may interact with sex-specific patterns of brain connectivity in male and female veterans and exert divergent effects on clinical profiles of aggression post-injury.

Patterns of resting state connectivity in human primary visual cortical areas: a 7T fMRI study.

PubMed

Raemaekers, Mathijs; Schellekens, Wouter; van Wezel, Richard J A; Petridou, Natalia; Kristo, Gert; Ramsey, Nick F

2014-01-01

The nature and origin of fMRI resting state fluctuations and connectivity are still not fully known. More detailed knowledge on the relationship between resting state patterns and brain function may help to elucidate this matter. We therefore performed an in depth study of how resting state fluctuations map to the well known architecture of the visual system. We investigated resting state connectivity at both a fine and large scale within and across visual areas V1, V2 and V3 in ten human subjects using a 7Tesla scanner. We found evidence for several coexisting and overlapping connectivity structures at different spatial scales. At the fine-scale level we found enhanced connectivity between the same topographic locations in the fieldmaps of V1, V2 and V3, enhanced connectivity to the contralateral functional homologue, and to a lesser extent enhanced connectivity between iso-eccentric locations within the same visual area. However, by far the largest proportion of the resting state fluctuations occurred within large-scale bilateral networks. These large-scale networks mapped to some extent onto the architecture of the visual system and could thereby obscure fine-scale connectivity. In fact, most of the fine-scale connectivity only became apparent after the large-scale network fluctuations were filtered from the timeseries. We conclude that fMRI resting state fluctuations in the visual cortex may in fact be a composite signal of different overlapping sources. Isolating the different sources could enhance correlations between BOLD and electrophysiological correlates of resting state activity. © 2013 Elsevier Inc. All rights reserved.

Development and function of human cerebral cortex neural networks from pluripotent stem cells in vitro

PubMed Central

Kirwan, Peter; Turner-Bridger, Benita; Peter, Manuel; Momoh, Ayiba; Arambepola, Devika; Robinson, Hugh P. C.; Livesey, Frederick J.

2015-01-01

A key aspect of nervous system development, including that of the cerebral cortex, is the formation of higher-order neural networks. Developing neural networks undergo several phases with distinct activity patterns in vivo, which are thought to prune and fine-tune network connectivity. We report here that human pluripotent stem cell (hPSC)-derived cerebral cortex neurons form large-scale networks that reflect those found in the developing cerebral cortex in vivo. Synchronised oscillatory networks develop in a highly stereotyped pattern over several weeks in culture. An initial phase of increasing frequency of oscillations is followed by a phase of decreasing frequency, before giving rise to non-synchronous, ordered activity patterns. hPSC-derived cortical neural networks are excitatory, driven by activation of AMPA- and NMDA-type glutamate receptors, and can undergo NMDA-receptor-mediated plasticity. Investigating single neuron connectivity within PSC-derived cultures, using rabies-based trans-synaptic tracing, we found two broad classes of neuronal connectivity: most neurons have small numbers (<10) of presynaptic inputs, whereas a small set of hub-like neurons have large numbers of synaptic connections (>40). These data demonstrate that the formation of hPSC-derived cortical networks mimics in vivo cortical network development and function, demonstrating the utility of in vitro systems for mechanistic studies of human forebrain neural network biology. PMID:26395144

Development and function of human cerebral cortex neural networks from pluripotent stem cells in vitro.

PubMed

Kirwan, Peter; Turner-Bridger, Benita; Peter, Manuel; Momoh, Ayiba; Arambepola, Devika; Robinson, Hugh P C; Livesey, Frederick J

2015-09-15

A key aspect of nervous system development, including that of the cerebral cortex, is the formation of higher-order neural networks. Developing neural networks undergo several phases with distinct activity patterns in vivo, which are thought to prune and fine-tune network connectivity. We report here that human pluripotent stem cell (hPSC)-derived cerebral cortex neurons form large-scale networks that reflect those found in the developing cerebral cortex in vivo. Synchronised oscillatory networks develop in a highly stereotyped pattern over several weeks in culture. An initial phase of increasing frequency of oscillations is followed by a phase of decreasing frequency, before giving rise to non-synchronous, ordered activity patterns. hPSC-derived cortical neural networks are excitatory, driven by activation of AMPA- and NMDA-type glutamate receptors, and can undergo NMDA-receptor-mediated plasticity. Investigating single neuron connectivity within PSC-derived cultures, using rabies-based trans-synaptic tracing, we found two broad classes of neuronal connectivity: most neurons have small numbers (<10) of presynaptic inputs, whereas a small set of hub-like neurons have large numbers of synaptic connections (>40). These data demonstrate that the formation of hPSC-derived cortical networks mimics in vivo cortical network development and function, demonstrating the utility of in vitro systems for mechanistic studies of human forebrain neural network biology. © 2015. Published by The Company of Biologists Ltd.

Neural Connectivity Patterns Underlying Symbolic Number Processing Indicate Mathematical Achievement in Children

ERIC Educational Resources Information Center

Park, Joonkoo; Li, Rosa; Brannon, Elizabeth M.

2014-01-01

In early childhood, humans learn culturally specific symbols for number that allow them entry into the world of complex numerical thinking. Yet little is known about how the brain supports the development of the uniquely human symbolic number system. Here, we use functional magnetic resonance imaging along with an effective connectivity analysis…

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

PubMed Central

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

2009-01-01

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

Cognitive performance in healthy older adults relates to spontaneous switching between states of functional connectivity during rest.

PubMed

Cabral, Joana; Vidaurre, Diego; Marques, Paulo; Magalhães, Ricardo; Silva Moreira, Pedro; Miguel Soares, José; Deco, Gustavo; Sousa, Nuno; Kringelbach, Morten L

2017-07-11

Growing evidence has shown that brain activity at rest slowly wanders through a repertoire of different states, where whole-brain functional connectivity (FC) temporarily settles into distinct FC patterns. Nevertheless, the functional role of resting-state activity remains unclear. Here, we investigate how the switching behavior of resting-state FC relates with cognitive performance in healthy older adults. We analyse resting-state fMRI data from 98 healthy adults previously categorized as being among the best or among the worst performers in a cohort study of >1000 subjects aged 50+ who underwent neuropsychological assessment. We use a novel approach focusing on the dominant FC pattern captured by the leading eigenvector of dynamic FC matrices. Recurrent FC patterns - or states - are detected and characterized in terms of lifetime, probability of occurrence and switching profiles. We find that poorer cognitive performance is associated with weaker FC temporal similarity together with altered switching between FC states. These results provide new evidence linking the switching dynamics of FC during rest with cognitive performance in later life, reinforcing the functional role of resting-state activity for effective cognitive processing.

Multivariate pattern analysis reveals anatomical connectivity differences between the left and right mesial temporal lobe epilepsy.

PubMed

Fang, Peng; An, Jie; Zeng, Ling-Li; Shen, Hui; Chen, Fanglin; Wang, Wensheng; Qiu, Shijun; Hu, Dewen

2015-01-01

Previous studies have demonstrated differences of clinical signs and functional brain network organizations between the left and right mesial temporal lobe epilepsy (mTLE), but the anatomical connectivity differences underlying functional variance between the left and right mTLE remain uncharacterized. We examined 43 (22 left, 21 right) mTLE patients with hippocampal sclerosis and 39 healthy controls using diffusion tensor imaging. After the whole-brain anatomical networks were constructed for each subject, multivariate pattern analysis was applied to classify the left mTLE from the right mTLE and extract the anatomical connectivity differences between the left and right mTLE patients. The classification results reveal 93.0% accuracy for the left mTLE versus the right mTLE, 93.4% accuracy for the left mTLE versus controls and 90.0% accuracy for the right mTLE versus controls. Compared with the right mTLE, the left mTLE exhibited a different connectivity pattern in the cortical-limbic network and cerebellum. The majority of the most discriminating anatomical connections were located within or across the cortical-limbic network and cerebellum, thereby indicating that these disease-related anatomical network alterations may give rise to a portion of the complex of emotional and memory deficit between the left and right mTLE. Moreover, the orbitofrontal gyrus, cingulate cortex, hippocampus and parahippocampal gyrus, which exhibit high discriminative power in classification, may play critical roles in the pathophysiology of mTLE. The current study demonstrated that anatomical connectivity differences between the left mTLE and the right mTLE may have the potential to serve as a neuroimaging biomarker to guide personalized diagnosis of the left and right mTLE.

Multivariate pattern dependence

PubMed Central

Saxe, Rebecca

2017-01-01

When we perform a cognitive task, multiple brain regions are engaged. Understanding how these regions interact is a fundamental step to uncover the neural bases of behavior. Most research on the interactions between brain regions has focused on the univariate responses in the regions. However, fine grained patterns of response encode important information, as shown by multivariate pattern analysis. In the present article, we introduce and apply multivariate pattern dependence (MVPD): a technique to study the statistical dependence between brain regions in humans in terms of the multivariate relations between their patterns of responses. MVPD characterizes the responses in each brain region as trajectories in region-specific multidimensional spaces, and models the multivariate relationship between these trajectories. We applied MVPD to the posterior superior temporal sulcus (pSTS) and to the fusiform face area (FFA), using a searchlight approach to reveal interactions between these seed regions and the rest of the brain. Across two different experiments, MVPD identified significant statistical dependence not detected by standard functional connectivity. Additionally, MVPD outperformed univariate connectivity in its ability to explain independent variance in the responses of individual voxels. In the end, MVPD uncovered different connectivity profiles associated with different representational subspaces of FFA: the first principal component of FFA shows differential connectivity with occipital and parietal regions implicated in the processing of low-level properties of faces, while the second and third components show differential connectivity with anterior temporal regions implicated in the processing of invariant representations of face identity. PMID:29155809

Knowing what from where: Hippocampal connectivity with temporoparietal cortex at rest is linked to individual differences in semantic and topographic memory.

PubMed

Sormaz, Mladen; Jefferies, Elizabeth; Bernhardt, Boris C; Karapanagiotidis, Theodoros; Mollo, Giovanna; Bernasconi, Neda; Bernasconi, Andrea; Hartley, Tom; Smallwood, Jonathan

2017-05-15

The hippocampus contributes to episodic, spatial and semantic aspects of memory, yet individual differences within and between these functions are not well-understood. In 136 healthy individuals, we investigated whether these differences reflect variation in the strength of connections between functionally-specialised segments of the hippocampus and diverse cortical regions that participate in different aspects of memory. Better topographical memory was associated with stronger connectivity between lingual gyrus and left anterior, rather than posterior, hippocampus. Better semantic memory was associated with increased connectivity between the intracalcarine/cuneus and left, rather than right, posterior hippocampus. Notably, we observed a double dissociation between semantic and topographical memory: better semantic memory was associated with stronger connectivity between left temporoparietal cortex and left anterior hippocampus, while better topographic memory was linked to stronger connectivity with right anterior hippocampus. Together these data support a division-of-labour account of hippocampal functioning: at the population level, differences in connectivity across the hippocampus reflect functional specialisation for different facets of memory, while variation in these connectivity patterns across individuals is associated with differences in the capacity to retrieve different types of information. In particular, within-hemisphere connectivity between hippocampus and left temporoparietal cortex supports conceptual processing at the expense of spatial ability. Copyright © 2017. Published by Elsevier Inc.

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.

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.

Reconfiguration of Intrinsic Functional Coupling Patterns Following Circumscribed Network Lesions.

PubMed

Eldaief, Mark C; McMains, Stephanie; Hutchison, R Matthew; Halko, Mark A; Pascual-Leone, Alvaro

2017-05-01

Communication between cortical regions is necessary for optimal cognitive processing. Functional relationships between cortical regions can be inferred through measurements of temporal synchrony in spontaneous activity patterns. These relationships can be further elaborated by surveying effects of cortical lesions upon inter-regional connectivity. Lesions to cortical hubs and heteromodal association regions are expected to induce distributed connectivity changes and higher-order cognitive deficits, yet their functional consequences remain relatively unexplored. Here, we used resting-state fMRI to investigate intrinsic functional connectivity (FC) and graph theoretical metrics in 12 patients with circumscribed lesions of the medial prefrontal cortex (mPFC) portion of the Default Network (DN), and compared these metrics with those observed in healthy matched comparison participants and a sample of 1139 healthy individuals. Despite significant mPFC destruction, patients did not demonstrate weakened intrinsic FC among undamaged DN nodes. Instead, network-specific changes were manifested as weaker negative correlations between the DN and attentional and somatomotor networks. These findings conflict with the DN being a homogenous system functionally anchored at mPFC. Rather, they implicate a role for mPFC in mediating cross-network functional interactions. More broadly, our data suggest that lesions to association cortical hubs might induce clinical deficits by disrupting communication between interacting large-scale systems. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Decoupling function and anatomy in atlases of functional connectivity patterns: language mapping in tumor patients.

PubMed

Langs, Georg; Sweet, Andrew; Lashkari, Danial; Tie, Yanmei; Rigolo, Laura; Golby, Alexandra J; Golland, Polina

2014-12-01

In this paper we construct an atlas that summarizes functional connectivity characteristics of a cognitive process from a population of individuals. The atlas encodes functional connectivity structure in a low-dimensional embedding space that is derived from a diffusion process on a graph that represents correlations of fMRI time courses. The functional atlas is decoupled from the anatomical space, and thus can represent functional networks with variable spatial distribution in a population. In practice the atlas is represented by a common prior distribution for the embedded fMRI signals of all subjects. We derive an algorithm for fitting this generative model to the observed data in a population. Our results in a language fMRI study demonstrate that the method identifies coherent and functionally equivalent regions across subjects. The method also successfully maps functional networks from a healthy population used as a training set to individuals whose language networks are affected by tumors. Copyright © 2014. Published by Elsevier Inc.

Higher body mass index is associated with reduced posterior default mode connectivity in older adults.

PubMed

Beyer, Frauke; Kharabian Masouleh, Sharzhad; Huntenburg, Julia M; Lampe, Leonie; Luck, Tobias; Riedel-Heller, Steffi G; Loeffler, Markus; Schroeter, Matthias L; Stumvoll, Michael; Villringer, Arno; Witte, A Veronica

2017-04-11

Obesity is a complex neurobehavioral disorder that has been linked to changes in brain structure and function. However, the impact of obesity on functional connectivity and cognition in aging humans is largely unknown. Therefore, the association of body mass index (BMI), resting-state network connectivity, and cognitive performance in 712 healthy, well-characterized older adults of the Leipzig Research Center for Civilization Diseases (LIFE) cohort (60-80 years old, mean BMI 27.6 kg/m 2  ± 4.2 SD, main sample: n = 521, replication sample: n = 191) was determined. Statistical analyses included a multivariate model selection approach followed by univariate analyses to adjust for possible confounders. Results showed that a higher BMI was significantly associated with lower default mode functional connectivity in the posterior cingulate cortex and precuneus. The effect remained stable after controlling for age, sex, head motion, registration quality, cardiovascular, and genetic factors as well as in replication analyses. Lower functional connectivity in BMI-associated areas correlated with worse executive function. In addition, higher BMI correlated with stronger head motion. Using 3T neuroimaging in a large cohort of healthy older adults, independent negative associations of obesity and functional connectivity in the posterior default mode network were observed. In addition, a subtle link between lower resting-state connectivity in BMI-associated regions and cognitive function was found. The findings might indicate that obesity is associated with patterns of decreased default mode connectivity similar to those seen in populations at risk for Alzheimer's disease. Hum Brain Mapp, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

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.

Testing Proposed Neuronal Models of Effective Connectivity Within the Cortico-basal Ganglia-thalamo-cortical Loop During Loss of Consciousness.

PubMed

Crone, Julia Sophia; Lutkenhoff, Evan Scott; Bio, Branden Joseph; Laureys, Steven; Monti, Martin Max

2017-04-01

In recent years, a number of brain regions and connectivity patterns have been proposed to be crucial for loss and recovery of consciousness but have not been compared in detail. In a 3 T resting-state functional magnetic resonance imaging paradigm, we test the plausibility of these different neuronal models derived from theoretical and empirical knowledge. Specifically, we assess the fit of each model to the dynamic change in effective connectivity between specific cortical and subcortical regions at different consecutive levels of propofol-induced sedation by employing spectral dynamic causal modeling. Surprisingly, our findings indicate that proposed models of impaired consciousness do not fit the observed patterns of effective connectivity. Rather, the data show that loss of consciousness, at least in the context of propofol-induced sedation, is marked by a breakdown of corticopetal projections from the globus pallidus. Effective connectivity between the globus pallidus and the ventral posterior cingulate cortex, present during wakefulness, fades in the transition from lightly sedated to full loss of consciousness and returns gradually as consciousness recovers, thereby, demonstrating the dynamic shift in brain architecture of the posterior cingulate "hub" during changing states of consciousness. These findings highlight the functional role of a previously underappreciated direct pallido-cortical connectivity in supporting consciousness. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

The independent influences of age and education on functional brain networks and cognition in healthy older adults.

PubMed

Perry, Alistair; Wen, Wei; Kochan, Nicole A; Thalamuthu, Anbupalam; Sachdev, Perminder S; Breakspear, Michael

2017-10-01

Healthy aging is accompanied by a constellation of changes in cognitive processes and alterations in functional brain networks. The relationships between brain networks and cognition during aging in later life are moderated by demographic and environmental factors, such as prior education, in a poorly understood manner. Using multivariate analyses, we identified three latent patterns (or modes) linking resting-state functional connectivity to demographic and cognitive measures in 101 cognitively normal elders. The first mode (P = 0.00043) captures an opposing association between age and core cognitive processes such as attention and processing speed on functional connectivity patterns. The functional subnetwork expressed by this mode links bilateral sensorimotor and visual regions through key areas such as the parietal operculum. A strong, independent association between years of education and functional connectivity loads onto a second mode (P = 0.012), characterized by the involvement of key hub regions. A third mode (P = 0.041) captures weak, residual brain-behavior relations. Our findings suggest that circuits supporting lower level cognitive processes are most sensitive to the influence of age in healthy older adults. Education, and to a lesser extent, executive functions, load independently onto functional networks-suggesting that the moderating effect of education acts upon networks distinct from those vulnerable with aging. This has important implications in understanding the contribution of education to cognitive reserve during healthy aging. Hum Brain Mapp 38:5094-5114, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Identifying disease-related subnetwork connectome biomarkers by sparse hypergraph learning.

PubMed

Zu, Chen; Gao, Yue; Munsell, Brent; Kim, Minjeong; Peng, Ziwen; Cohen, Jessica R; Zhang, Daoqiang; Wu, Guorong

2018-06-14

The functional brain network has gained increased attention in the neuroscience community because of its ability to reveal the underlying architecture of human brain. In general, majority work of functional network connectivity is built based on the correlations between discrete-time-series signals that link only two different brain regions. However, these simple region-to-region connectivity models do not capture complex connectivity patterns between three or more brain regions that form a connectivity subnetwork, or subnetwork for short. To overcome this current limitation, a hypergraph learning-based method is proposed to identify subnetwork differences between two different cohorts. To achieve our goal, a hypergraph is constructed, where each vertex represents a subject and also a hyperedge encodes a subnetwork with similar functional connectivity patterns between different subjects. Unlike previous learning-based methods, our approach is designed to jointly optimize the weights for all hyperedges such that the learned representation is in consensus with the distribution of phenotype data, i.e. clinical labels. In order to suppress the spurious subnetwork biomarkers, we further enforce a sparsity constraint on the hyperedge weights, where a larger hyperedge weight indicates the subnetwork with the capability of identifying the disorder condition. We apply our hypergraph learning-based method to identify subnetwork biomarkers in Autism Spectrum Disorder (ASD) and Attention Deficit Hyperactivity Disorder (ADHD). A comprehensive quantitative and qualitative analysis is performed, and the results show that our approach can correctly classify ASD and ADHD subjects from normal controls with 87.65 and 65.08% accuracies, respectively.

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

Left-Hemispheric Microstructural Abnormalities in Children With High Functioning Autism Spectrum Disorder

PubMed Central

Peterson, Daniel; Mahajan, Rajneesh; Crocetti, Deana; Mejia, Amanda; Mostofsky, Stewart

2014-01-01

Current theories of the neurobiological basis of Autism Spectrum Disorder (ASD) posit an altered pattern of connectivity in large-scale brain networks. Here we used Diffusion Tensor Imaging to investigate the microstructural properties of the white matter that mediates inter-regional connectivity in 36 high-functioning children with ASD (HF-ASD), as compared to 37 controls. By employing an atlas-based analysis using LDDMM registration, a widespread, but left-lateralized pattern of abnormalities was revealed. The Mean Diffusivity (MD) of water in the white matter of HF-ASD children was significantly elevated throughout the left hemisphere, particularly in the outer-zone cortical white matter. Across diagnostic groups there was a significant effect of age on left hemisphere MD, with a similar reduction in MD during childhood in both TD and HF-ASD children. The increased MD in children with HF-ASD suggests hypomyelination, and may reflect increased short-range cortico-cortical connections subsequent to early white matter overgrowth. These findings also highlight left hemispheric connectivity as relevant to the pathophysiology of ASD, and indicate that the spatial distribution of microstructural abnormalities in HF-ASD is widespread, and left-lateralized. This altered left-hemispheric connectivity may contribute to deficits in communication and praxis observed in ASD. PMID:25256103

The persuasion network is modulated by drug-use risk and predicts anti-drug message effectiveness

PubMed Central

Mangus, J Michael; Turner, Benjamin O

2017-01-01

Abstract While a persuasion network has been proposed, little is known about how network connections between brain regions contribute to attitude change. Two possible mechanisms have been advanced. One hypothesis predicts that attitude change results from increased connectivity between structures implicated in affective and executive processing in response to increases in argument strength. A second functional perspective suggests that highly arousing messages reduce connectivity between structures implicated in the encoding of sensory information, which disrupts message processing and thereby inhibits attitude change. However, persuasion is a multi-determined construct that results from both message features and audience characteristics. Therefore, persuasive messages should lead to specific functional connectivity patterns among a priori defined structures within the persuasion network. The present study exposed 28 subjects to anti-drug public service announcements where arousal, argument strength, and subject drug-use risk were systematically varied. Psychophysiological interaction analyses provide support for the affective-executive hypothesis but not for the encoding-disruption hypothesis. Secondary analyses show that video-level connectivity patterns among structures within the persuasion network predict audience responses in independent samples (one college-aged, one nationally representative). We propose that persuasion neuroscience research is best advanced by considering network-level effects while accounting for interactions between message features and target audience characteristics. PMID:29140500

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.

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.

Altered resting state functional connectivity of fear and reward circuitry in comorbid PTSD and major depression.

PubMed

Zhu, Xi; Helpman, Liat; Papini, Santiago; Schneier, Franklin; Markowitz, John C; Van Meter, Page E; Lindquist, Martin A; Wager, Tor D; Neria, Yuval

2017-07-01

Individuals with comorbid posttraumatic stress disorder and major depressive disorder (PTSD-MDD) often exhibit greater functional impairment and poorer treatment response than individuals with PTSD alone. Research has not determined whether PTSD-MDD is associated with different network connectivity abnormalities than PTSD alone. We used functional magnetic resonance imaging (fMRI) to measure resting state functional connectivity (rs-FC) patterns of brain regions involved in fear and reward processing in three groups: patients with PTSD-alone (n = 27), PTSD-MDD (n = 21), and trauma-exposed healthy controls (TEHCs, n = 34). Based on previous research, seeds included basolateral amygdala (BLA), centromedial amygdala (CMA), and nucleus accumbens (NAcc). Regardless of MDD comorbidity, PTSD was associated with decreased connectivity of BLA-orbitalfrontal cortex (OFC) and CMA-thalamus pathways, key to fear processing, and fear expression, respectively. PTSD-MDD, compared to PTSD-alone and TEHC, was associated with decreased connectivity across multiple amygdala and striatal-subcortical pathways: BLA-OFC, NAcc-thalamus, and NAcc-hippocampus. Further, while both the BLA-OFC and the NAcc-thalamus pathways were correlated with MDD symptoms, PTSD symptoms correlated with the amygdala pathways (BLA-OFC; CMA-thalamus) only. Comorbid PTSD-MDD may be associated with multifaceted functional connectivity alterations in both fear and reward systems. Clinical implications are discussed. © 2016 Wiley Periodicals, Inc.

Large-scale network integration in the human brain tracks temporal fluctuations in memory encoding performance.

PubMed

Keerativittayayut, Ruedeerat; Aoki, Ryuta; Sarabi, Mitra Taghizadeh; Jimura, Koji; Nakahara, Kiyoshi

2018-06-18

Although activation/deactivation of specific brain regions have been shown to be predictive of successful memory encoding, the relationship between time-varying large-scale brain networks and fluctuations of memory encoding performance remains unclear. Here we investigated time-varying functional connectivity patterns across the human brain in periods of 30-40 s, which have recently been implicated in various cognitive functions. During functional magnetic resonance imaging, participants performed a memory encoding task, and their performance was assessed with a subsequent surprise memory test. A graph analysis of functional connectivity patterns revealed that increased integration of the subcortical, default-mode, salience, and visual subnetworks with other subnetworks is a hallmark of successful memory encoding. Moreover, multivariate analysis using the graph metrics of integration reliably classified the brain network states into the period of high (vs. low) memory encoding performance. Our findings suggest that a diverse set of brain systems dynamically interact to support successful memory encoding. © 2018, Keerativittayayut et al.

Potential function of element measurement for form-finding of wide sense tensegrity

NASA Astrophysics Data System (ADS)

Soe, C. K.; Obiya, H.; Koga, D.; Nizam, Z. M.; Ijima, K.

2018-04-01

Tensegrity is a unique morphological structure in which disconnected compression members and connected tension members make the whole structure in self-equilibrium. Many researches have been done on tensegrity structure because of its mysteriousness in form-finding analysis. This study is proposed to investigate the trends and to group into some patterns of the shape that a tensegrity structure can have under the same connectivity and support condition. In this study, tangent stiffness method adopts two different functions, namely power function and logarithm function to element measurement. Numerical examples are based on a simplex initial shape with statically determinate support condition to examine the pure effectiveness of two proposed methods. The tangent stiffness method that can evaluate strict rigid body displacement of elements has a superiority to define various measure potentials and to allow the use of virtual element stiffness freely. From the results of numerical examples, the finding of the dominant trends and patterns of the equilibrium solutions is achieved although it has many related solutions under the same circumstances.

Topologically invariant macroscopic statistics in balanced networks of conductance-based integrate-and-fire neurons.

PubMed

Yger, Pierre; El Boustani, Sami; Destexhe, Alain; Frégnac, Yves

2011-10-01

The relationship between the dynamics of neural networks and their patterns of connectivity is far from clear, despite its importance for understanding functional properties. Here, we have studied sparsely-connected networks of conductance-based integrate-and-fire (IF) neurons with balanced excitatory and inhibitory connections and with finite axonal propagation speed. We focused on the genesis of states with highly irregular spiking activity and synchronous firing patterns at low rates, called slow Synchronous Irregular (SI) states. In such balanced networks, we examined the "macroscopic" properties of the spiking activity, such as ensemble correlations and mean firing rates, for different intracortical connectivity profiles ranging from randomly connected networks to networks with Gaussian-distributed local connectivity. We systematically computed the distance-dependent correlations at the extracellular (spiking) and intracellular (membrane potential) levels between randomly assigned pairs of neurons. The main finding is that such properties, when they are averaged at a macroscopic scale, are invariant with respect to the different connectivity patterns, provided the excitatory-inhibitory balance is the same. In particular, the same correlation structure holds for different connectivity profiles. In addition, we examined the response of such networks to external input, and found that the correlation landscape can be modulated by the mean level of synchrony imposed by the external drive. This modulation was found again to be independent of the external connectivity profile. We conclude that first and second-order "mean-field" statistics of such networks do not depend on the details of the connectivity at a microscopic scale. This study is an encouraging step toward a mean-field description of topological neuronal networks.

The intrinsic resting state voice network in Parkinson's disease

PubMed Central

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

2015-01-01

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

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.

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.

Examining Neuronal Connectivity and Its Role in Learning and Memory

NASA Astrophysics Data System (ADS)

Gala, Rohan

Learning and long-term memory formation are accompanied with changes in the patterns and weights of synaptic connections in the underlying neuronal network. However, the fundamental rules that drive connectivity changes, and the precise structure-function relationships within neuronal networks remain elusive. Technological improvements over the last few decades have enabled the observation of large but specific subsets of neurons and their connections in unprecedented detail. Devising robust and automated computational methods is critical to distill information from ever-increasing volumes of raw experimental data. Moreover, statistical models and theoretical frameworks are required to interpret the data and assemble evidence into understanding of brain function. In this thesis, I first describe computational methods to reconstruct connectivity based on light microscopy imaging experiments. Next, I use these methods to quantify structural changes in connectivity based on in vivo time-lapse imaging experiments. Finally, I present a theoretical model of associative learning that can explain many stereotypical features of experimentally observed connectivity.

Critical thresholds in species` responses to landscape structure

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

With, K.A.; Crist, T.O.

1995-12-01

Critical thresholds are transition ranges across which small changes in spatial pattern produce abrupt shifts in ecological responses. Habitat fragmentation provides a familiar example of a critical threshold. As the landscape becomes dissected into smaller parcels of habitat. landscape connectivity-the functional linkage among habitat patches - may suddenly become disrupted, which may have important consequences for the distribution and persistence of populations. Landscape connectivity depends not only on the abundance and spatial patterning of habitat. but also on the habitat specificity and dispersal abilities of species. Habitat specialists with limited dispersal capabilities presumably have a much lower threshold to habitatmore » fragmentation than highly vagile species, which may perceive the landscape as functionally connected across a greater range of fragmentation severity. To determine where threshold effects in species, responses to landscape structure are likely to occur, a simulation model modified from percolation theory was developed. Our simulations predicted the distributional patterns of populations in different landscape mosaics, which we tested empirically using two grasshopper species (Orthoptera: Acrididae) that occur in the shortgrass prairie of north-central Colorado. The distribution of these two species in this grassland mosaic matched the predictions from our simulations. By providing quantitative predictions of threshold effects, this modelling approach may prove useful in the formulation of conservation strategies and assessment of land-use changes on species` distributional patterns and persistence.« less

Differentiating between bipolar and unipolar depression in functional and structural MRI studies.

PubMed

Han, Kyu-Man; De Berardis, Domenico; Fornaro, Michele; Kim, Yong-Ku

2018-03-28

Distinguishing depression in bipolar disorder (BD) from unipolar depression (UD) solely based on clinical clues is difficult, which has led to the exploration of promising neural markers in neuroimaging measures for discriminating between BD depression and UD. In this article, we review structural and functional magnetic resonance imaging (MRI) studies that directly compare UD and BD depression based on neuroimaging modalities including functional MRI studies on regional brain activation or functional connectivity, structural MRI on gray or white matter morphology, and pattern classification analyses using a machine learning approach. Numerous studies have reported distinct functional and structural alterations in emotion- or reward-processing neural circuits between BD depression and UD. Different activation patterns in neural networks including the amygdala, anterior cingulate cortex (ACC), prefrontal cortex (PFC), and striatum during emotion-, reward-, or cognition-related tasks have been reported between BD and UD. A stronger functional connectivity pattern in BD was pronounced in default mode and in frontoparietal networks and brain regions including the PFC, ACC, parietal and temporal regions, and thalamus compared to UD. Gray matter volume differences in the ACC, hippocampus, amygdala, and dorsolateral prefrontal cortex (DLPFC) have been reported between BD and UD, along with a thinner DLPFC in BD compared to UD. BD showed reduced integrity in the anterior part of the corpus callosum and posterior cingulum compared to UD. Several studies performed pattern classification analysis using structural and functional MRI data to distinguish between UD and BD depression using a supervised machine learning approach, which yielded a moderate level of accuracy in classification. Copyright © 2018 Elsevier Inc. All rights reserved.

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.

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.

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.

Reduced connectivity of the auditory cortex in patients with auditory hallucinations: a resting state functional magnetic resonance imaging study.

PubMed

Gavrilescu, M; Rossell, S; Stuart, G W; Shea, T L; Innes-Brown, H; Henshall, K; McKay, C; Sergejew, A A; Copolov, D; Egan, G F

2010-07-01

Previous research has reported auditory processing deficits that are specific to schizophrenia patients with a history of auditory hallucinations (AH). One explanation for these findings is that there are abnormalities in the interhemispheric connectivity of auditory cortex pathways in AH patients; as yet this explanation has not been experimentally investigated. We assessed the interhemispheric connectivity of both primary (A1) and secondary (A2) auditory cortices in n=13 AH patients, n=13 schizophrenia patients without auditory hallucinations (non-AH) and n=16 healthy controls using functional connectivity measures from functional magnetic resonance imaging (fMRI) data. Functional connectivity was estimated from resting state fMRI data using regions of interest defined for each participant based on functional activation maps in response to passive listening to words. Additionally, stimulus-induced responses were regressed out of the stimulus data and the functional connectivity was estimated for the same regions to investigate the reliability of the estimates. AH patients had significantly reduced interhemispheric connectivity in both A1 and A2 when compared with non-AH patients and healthy controls. The latter two groups did not show any differences in functional connectivity. Further, this pattern of findings was similar across the two datasets, indicating the reliability of our estimates. These data have identified a trait deficit specific to AH patients. Since this deficit was characterized within both A1 and A2 it is expected to result in the disruption of multiple auditory functions, for example, the integration of basic auditory information between hemispheres (via A1) and higher-order language processing abilities (via A2).

Uncoupling of microbial community structure and function in decomposing litter across beech forest ecosystems in Central Europe.

PubMed

Purahong, Witoon; Schloter, Michael; Pecyna, Marek J; Kapturska, Danuta; Däumlich, Veronika; Mital, Sanchit; Buscot, François; Hofrichter, Martin; Gutknecht, Jessica L M; Krüger, Dirk

2014-11-12

The widespread paradigm in ecology that community structure determines function has recently been challenged by the high complexity of microbial communities. Here, we investigate the patterns of and connections between microbial community structure and microbially-mediated ecological function across different forest management practices and temporal changes in leaf litter across beech forest ecosystems in Central Europe. Our results clearly indicate distinct pattern of microbial community structure in response to forest management and time. However, those patterns were not reflected when potential enzymatic activities of microbes were measured. We postulate that in our forest ecosystems, a disconnect between microbial community structure and function may be present due to differences between the drivers of microbial growth and those of microbial function.

Multi-Site Diagnostic Classification of Schizophrenia Using Discriminant Deep Learning with Functional Connectivity MRI.

PubMed

Zeng, Ling-Li; Wang, Huaning; Hu, Panpan; Yang, Bo; Pu, Weidan; Shen, Hui; Chen, Xingui; Liu, Zhening; Yin, Hong; Tan, Qingrong; Wang, Kai; Hu, Dewen

2018-04-01

A lack of a sufficiently large sample at single sites causes poor generalizability in automatic diagnosis classification of heterogeneous psychiatric disorders such as schizophrenia based on brain imaging scans. Advanced deep learning methods may be capable of learning subtle hidden patterns from high dimensional imaging data, overcome potential site-related variation, and achieve reproducible cross-site classification. However, deep learning-based cross-site transfer classification, despite less imaging site-specificity and more generalizability of diagnostic models, has not been investigated in schizophrenia. A large multi-site functional MRI sample (n = 734, including 357 schizophrenic patients from seven imaging resources) was collected, and a deep discriminant autoencoder network, aimed at learning imaging site-shared functional connectivity features, was developed to discriminate schizophrenic individuals from healthy controls. Accuracies of approximately 85·0% and 81·0% were obtained in multi-site pooling classification and leave-site-out transfer classification, respectively. The learned functional connectivity features revealed dysregulation of the cortical-striatal-cerebellar circuit in schizophrenia, and the most discriminating functional connections were primarily located within and across the default, salience, and control networks. The findings imply that dysfunctional integration of the cortical-striatal-cerebellar circuit across the default, salience, and control networks may play an important role in the "disconnectivity" model underlying the pathophysiology of schizophrenia. The proposed discriminant deep learning method may be capable of learning reliable connectome patterns and help in understanding the pathophysiology and achieving accurate prediction of schizophrenia across multiple independent imaging sites. Copyright © 2018 German Center for Neurodegenerative Diseases (DZNE). Published by Elsevier B.V. All rights reserved.

Ventral striatal dysfunction in cocaine dependence - difference mapping for subregional resting state functional connectivity.

PubMed

Zhang, Sheng; Li, Chiang-Shan R

2018-06-18

Research of dopaminergic deficits has focused on the ventral striatum (VS) with many studies elucidating altered resting state functional connectivity (rsFC) in individuals with cocaine dependence (CD). The VS comprises functional subregions and delineation of subregional changes in rsFC requires careful consideration of the differences between addicted and healthy populations. In the current study, we parcellated the VS using whole-brain rsFC differences between CD and non-drug-using controls (HC). Voxels with similar rsFC changes formed functional clusters. The results showed that the VS was divided into 3 subclusters, in the area of the dorsal-anterior VS (daVS), dorsal posterior VS (dpVS), and ventral VS (vVS), each in association with different patterns of rsFC. The three subregions shared reduced rsFC with bilateral hippocampal/parahippocampal gyri (HG/PHG) but also showed distinct changes, including reduced vVS rsFC with ventromedial prefrontal cortex (vmPFC) and increased daVS rsFC with visual cortex in CD as compared to HC. Across CD, daVS visual cortical connectivity was positively correlated with amount of prior-month cocaine use and cocaine craving, and vVS vmPFC connectivity was negatively correlated with the extent of depression and anxiety. These findings suggest a distinct pattern of altered VS subregional rsFC in cocaine dependence, and some of the changes have eluded analyses using the whole VS as a seed region. The findings may provide new insight to delineating VS circuit deficits in cocaine dependence and provide an alternative analytical framework to address functional dysconnectivity in other mental illnesses.

Directional patterns of cross frequency phase and amplitude coupling within the resting state mimic patterns of fMRI functional connectivity

PubMed Central

Weaver, Kurt E.; Wander, Jeremiah D.; Ko, Andrew L.; Casimo, Kaitlyn; Grabowski, Thomas J.; Ojemann, Jeffrey G.; Darvas, Felix

2016-01-01

Functional imaging investigations into the brain's resting state interactions have yielded a wealth of insight into the intrinsic and dynamic neural architecture supporting cognition and behavior. Electrophysiological studies however have highlighted the fact that synchrony across large-scale cortical systems is composed of spontaneous interactions occurring at timescales beyond the traditional resolution of fMRI, a feature that limits the capacity of fMRI to draw inference on the true directional relationship between network nodes. To approach the question of directionality in resting state signals, we recorded resting state functional MRI (rsfMRI) and electrocorticography (ECoG) from four human subjects undergoing invasive epilepsy monitoring. Using a seed-point based approach, we employed phase-amplitude coupling (PAC) and biPhase Locking Values (bPLV), two measures of cross-frequency coupling (CFC) to explore both outgoing and incoming connections between the seed and all non-seed, site electrodes. We observed robust PAC between a wide range of low-frequency phase and high frequency amplitude estimates. However, significant bPLV, a CFC measure of phase-phase synchrony, was only observed at specific narrow low and high frequency bandwidths. Furthermore, the spatial patterns of outgoing PAC connectivity were most closely associated with the rsfMRI connectivity maps. Our results support the hypothesis that PAC is relatively ubiquitous phenomenon serving as a mechanism for coordinating high-frequency amplitudes across distant neuronal assemblies even in absence of overt task structure. Additionally, we demonstrate that the spatial distribution of a seed-point rsfMRI sensorimotor network is strikingly similar to specific patterns of directional PAC. Specifically, the high frequency activities of distal patches of cortex owning membership in a rsfMRI sensorimotor network were most likely to be entrained to the phase of a low frequency rhythm engendered from the neural populations at the seed-point, suggestive of greater directional coupling from the seed out to the site electrodes. PMID:26747745

Topology for Dominance for Network of Multi-Agent System

NASA Astrophysics Data System (ADS)

Szeto, K. Y.

2007-05-01

The resource allocation problem in evolving two-dimensional point patterns is investigated for the existence of good strategies for the construction of initial configuration that leads to fast dominance of the pattern by one single species, which can be interpreted as market dominance by a company in the context of multi-agent systems in econophysics. For hexagonal lattice, certain special topological arrangements of the resource in two-dimensions, such as rings, lines and clusters have higher probability of dominance, compared to random pattern. For more complex networks, a systematic way to search for a stable and dominant strategy of resource allocation in the changing environment is found by means of genetic algorithm. Five typical features can be summarized by means of the distribution function for the local neighborhood of friends and enemies as well as the local clustering coefficients: (1) The winner has more triangles than the loser has. (2) The winner likes to form clusters as the winner tends to connect with other winner rather than with losers; while the loser tends to connect with winners rather than losers. (3) The distribution function of friends as well as enemies for the winner is broader than the corresponding distribution function for the loser. (4) The connectivity at which the peak of the distribution of friends for the winner occurs is larger than that of the loser; while the peak values for friends for winners is lower. (5) The connectivity at which the peak of the distribution of enemies for the winner occurs is smaller than that of the loser; while the peak values for enemies for winners is lower. These five features appear to be general, at least in the context of two-dimensional hexagonal lattices of various sizes, hierarchical lattice, Voronoi diagrams, as well as high-dimensional random networks. These general local topological properties of networks are relevant to strategists aiming at dominance in evolving patterns when the interaction between the agents is local.

Same as it ever was: vividness modulates the similarities and differences between the neural networks that support retrieving remote and recent autobiographical memories.

PubMed

Sheldon, Signy; Levine, Brian

2013-12-01

The comparison of recent and remote autobiographical memories is often confounded by qualitative disparities across memories of different ages, such as vividness. In this study, ten individuals prospectively collected audio recordings that were used to cue memories of recent (~1 month old) and remote (~1.5 year old) everyday events. Because the retrieval cues were recorded at the time of event, they were highly potent. Although remote events did not differ in novelty, importance, or emotional change at the time at the time of encoding, half of the cues for these events induced retrieval comparable in vividness to recent events (all of which were vividly re-experienced). Recent and remote vivid memories were associated with a neural pattern that included right frontal, left parietal and limbic regions that were active early in the retrieval period. Non-vivid remote memories were associated with a later onset of a bilateral distributed pattern that included regions in the frontal, parietal, and temporal lobes. Functional connectivity analysis indicated that the left anterior hippocampus was co-activated with bilateral frontal, parahippocampal, and parietal regions for vivid memories (irrespective of memory age) early in the retrieval period, whereas non-vivid memories, alongside recent memories, showed later and broader co-activation with frontal, parietal, occipital, and temporal regions. The absence of a significant difference between the recent and remote vivid memories may be due to insufficient power to detect potential subtle differences between these conditions. Nonetheless, there was evidence for different patterns of hippocampal-neocortical connectivity for remote memories and recent memories, irrespective of vividness. These findings suggest that while there is a functional shift in hippocampal connectivity that is associated with memory age when very recent events are used, vividness is strongly associated with both activation and functional connectivity patterns irrespective of memory age. © 2013.

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.

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

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.

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

PubMed

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

2014-01-01

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

Functional Internet Literacy: Required Cognitive Skills with Implications for Instruction

ERIC Educational Resources Information Center

Johnson, Genevieve Marie

2007-01-01

Patterns of typical Internet use provide the basis for defining "functional Internet literacy." Internet use commonly includes communication, information, recreation, and commercial activities. Technical competence with connectivity, security, and downloads is a prerequisite for using the Internet for such activities. Bloom's taxonomy of cognitive…

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.

Persistence and storage of activity patterns in spiking recurrent cortical networks: modulation of sigmoid signals by after-hyperpolarization currents and acetylcholine

PubMed Central

Palma, Jesse; Grossberg, Stephen; Versace, Massimiliano

2012-01-01

Many cortical networks contain recurrent architectures that transform input patterns before storing them in short-term memory (STM). Theorems in the 1970's showed how feedback signal functions in rate-based recurrent on-center off-surround networks control this process. A sigmoid signal function induces a quenching threshold below which inputs are suppressed as noise and above which they are contrast-enhanced before pattern storage. This article describes how changes in feedback signaling, neuromodulation, and recurrent connectivity may alter pattern processing in recurrent on-center off-surround networks of spiking neurons. In spiking neurons, fast, medium, and slow after-hyperpolarization (AHP) currents control sigmoid signal threshold and slope. Modulation of AHP currents by acetylcholine (ACh) can change sigmoid shape and, with it, network dynamics. For example, decreasing signal function threshold and increasing slope can lengthen the persistence of a partially contrast-enhanced pattern, increase the number of active cells stored in STM, or, if connectivity is distance-dependent, cause cell activities to cluster. These results clarify how cholinergic modulation by the basal forebrain may alter the vigilance of category learning circuits, and thus their sensitivity to predictive mismatches, thereby controlling whether learned categories code concrete or abstract features, as predicted by Adaptive Resonance Theory. The analysis includes global, distance-dependent, and interneuron-mediated circuits. With an appropriate degree of recurrent excitation and inhibition, spiking networks maintain a partially contrast-enhanced pattern for 800 ms or longer after stimuli offset, then resolve to no stored pattern, or to winner-take-all (WTA) stored patterns with one or multiple winners. Strengthening inhibition prolongs a partially contrast-enhanced pattern by slowing the transition to stability, while strengthening excitation causes more winners when the network stabilizes. PMID:22754524

How to Compress Sequential Memory Patterns into Periodic Oscillations: General Reduction Rules

PubMed Central

Zhang, Kechen

2017-01-01

A neural network with symmetric reciprocal connections always admits a Lyapunov function, whose minima correspond to the memory states stored in the network. Networks with suitable asymmetric connections can store and retrieve a sequence of memory patterns, but the dynamics of these networks cannot be characterized as readily as that of the symmetric networks due to the lack of established general methods. Here, a reduction method is developed for a class of asymmetric attractor networks that store sequences of activity patterns as associative memories, as in a Hopfield network. The method projects the original activity pattern of the network to a low-dimensional space such that sequential memory retrievals in the original network correspond to periodic oscillations in the reduced system. The reduced system is self-contained and provides quantitative information about the stability and speed of sequential memory retrievals in the original network. The time evolution of the overlaps between the network state and the stored memory patterns can also be determined from extended reduced systems. The reduction procedure can be summarized by a few reduction rules, which are applied to several network models, including coupled networks and networks with time-delayed connections, and the analytical solutions of the reduced systems are confirmed by numerical simulations of the original networks. Finally, a local learning rule that provides an approximation to the connection weights involving the pseudoinverse is also presented. PMID:24877729

Large-scale changes in network interactions as a physiological signature of spatial neglect.

PubMed

Baldassarre, Antonello; Ramsey, Lenny; Hacker, Carl L; Callejas, Alicia; Astafiev, Serguei V; Metcalf, Nicholas V; Zinn, Kristi; Rengachary, Jennifer; Snyder, Abraham Z; Carter, Alex R; Shulman, Gordon L; Corbetta, Maurizio

2014-12-01

The relationship between spontaneous brain activity and behaviour following focal injury is not well understood. Here, we report a large-scale study of resting state functional connectivity MRI and spatial neglect following stroke in a large (n=84) heterogeneous sample of first-ever stroke patients (within 1-2 weeks). Spatial neglect, which is typically more severe after right than left hemisphere injury, includes deficits of spatial attention and motor actions contralateral to the lesion, and low general attention due to impaired vigilance/arousal. Patients underwent structural and resting state functional MRI scans, and spatial neglect was measured using the Posner spatial cueing task, and Mesulam and Behavioural Inattention Test cancellation tests. A principal component analysis of the behavioural tests revealed a main factor accounting for 34% of variance that captured three correlated behavioural deficits: visual neglect of the contralesional visual field, visuomotor neglect of the contralesional field, and low overall performance. In an independent sample (21 healthy subjects), we defined 10 resting state networks consisting of 169 brain regions: visual-fovea and visual-periphery, sensory-motor, auditory, dorsal attention, ventral attention, language, fronto-parietal control, cingulo-opercular control, and default mode. We correlated the neglect factor score with the strength of resting state functional connectivity within and across the 10 resting state networks. All damaged brain voxels were removed from the functional connectivity:behaviour correlational analysis. We found that the correlated behavioural deficits summarized by the factor score were associated with correlated multi-network patterns of abnormal functional connectivity involving large swaths of cortex. Specifically, dorsal attention and sensory-motor networks showed: (i) reduced interhemispheric functional connectivity; (ii) reduced anti-correlation with fronto-parietal and default mode networks in the right hemisphere; and (iii) increased intrahemispheric connectivity with the basal ganglia. These patterns of functional connectivity:behaviour correlations were stronger in patients with right- as compared to left-hemisphere damage and were independent of lesion volume. Our findings identify large-scale changes in resting state network interactions that are a physiological signature of spatial neglect and may relate to its right hemisphere lateralization. © The Author (2014). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Staging of cortical and deep grey matter functional connectivity changes in multiple sclerosis.

PubMed

Meijer, Kim A; Eijlers, Anand J C; Geurts, Jeroen J G; Schoonheim, Menno M

2018-02-01

Functional connectivity is known to increase as well as decrease throughout the brain in multiple sclerosis (MS), which could represent different stages of the disease. In addition, functional connectivity changes could follow the atrophy pattern observed with disease progression, that is, moving from the deep grey matter towards the cortex. This study investigated when and where connectivity changes develop and explored their clinical and cognitive relevance across different MS stages. A cohort of 121 patients with early relapsing-remitting MS (RRMS), 122 with late RRMS and 53 with secondary progressive MS (SPMS) as well as 96 healthy controls underwent MRI and neuropsychological testing. Functional connectivity changes were investigated for (1) within deep grey matter connectivity, (2) connectivity between the deep grey matter and cortex and (3) within-cortex connectivity. A post hoc regional analysis was performed to identify which regions were driving the connectivity changes. Patients with late RRMS and SPMS showed increased connectivity of the deep grey matter, especially of the putamen and palladium, with other deep grey matter structures and with the cortex. Within-cortex connectivity was decreased, especially for temporal, occipital and frontal regions, but only in SPMS relative to early RRMS. Deep grey matter connectivity alterations were related to cognition and disability, whereas within-cortex connectivity was only related to disability. Increased connectivity of the deep grey matter became apparent in late RRMS and further increased in SPMS. The additive effect of cortical network degeneration, which was only seen in SPMS, may explain the sudden clinical deterioration characteristic to this phase of the disease. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

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.

Conserved neural circuit structure across Drosophila larval development revealed by comparative connectomics.

PubMed

Gerhard, Stephan; Andrade, Ingrid; Fetter, Richard D; Cardona, Albert; Schneider-Mizell, Casey M

2017-10-23

During postembryonic development, the nervous system must adapt to a growing body. How changes in neuronal structure and connectivity contribute to the maintenance of appropriate circuit function remains unclear. Previously , we measured the cellular neuroanatomy underlying synaptic connectivity in Drosophila (Schneider-Mizell et al., 2016). Here, we examined how neuronal morphology and connectivity change between first instar and third instar larval stages using serial section electron microscopy. We reconstructed nociceptive circuits in a larva of each stage and found consistent topographically arranged connectivity between identified neurons. Five-fold increases in each size, number of terminal dendritic branches, and total number of synaptic inputs were accompanied by cell type-specific connectivity changes that preserved the fraction of total synaptic input associated with each pre-synaptic partner. We propose that precise patterns of structural growth act to conserve the computational function of a circuit, for example determining the location of a dangerous stimulus.

Reduced Hippocampal Functional Connectivity During Episodic Memory Retrieval in Autism

PubMed Central

Cooper, Rose A.; Richter, Franziska R.; Bays, Paul M.; Plaisted-Grant, Kate C.; Baron-Cohen, Simon

2017-01-01

Abstract Increasing recent research has sought to understand the recollection impairments experienced by individuals with autism spectrum disorder (ASD). Here, we tested whether these memory deficits reflect a reduction in the probability of retrieval success or in the precision of memory representations. We also used functional magnetic resonance imaging (fMRI) to study the neural mechanisms underlying memory encoding and retrieval in ASD, focusing particularly on the functional connectivity of core episodic memory networks. Adults with ASD and typical control participants completed a memory task that involved studying visual displays and subsequently using a continuous dial to recreate their appearance. The ASD group exhibited reduced retrieval success, but there was no evidence of a difference in retrieval precision. fMRI data revealed similar patterns of brain activity and functional connectivity during memory encoding in the 2 groups, though encoding-related lateral frontal activity predicted subsequent retrieval success only in the control group. During memory retrieval, the ASD group exhibited attenuated lateral frontal activity and substantially reduced hippocampal connectivity, particularly between hippocampus and regions of the fronto-parietal control network. These findings demonstrate notable differences in brain function during episodic memory retrieval in ASD and highlight the importance of functional connectivity to understanding recollection-related retrieval deficits in this population. PMID:28057726

Dynamic Changes in Amygdala Activation and Functional Connectivity in Children and Adolescents with Anxiety Disorders

PubMed Central

Swartz, Johnna R.; Phan, K. Luan; Angstadt, Mike; Fitzgerald, Kate D.; Monk, Christopher S.

2015-01-01

Anxiety disorders are associated with abnormalities in amygdala function and prefrontal cortex-amygdala connectivity. The majority of fMRI studies have examined mean group differences in amygdala activation or connectivity in children and adolescents with anxiety disorders relative to controls, but emerging evidence suggests that abnormalities in amygdala function are dependent on the timing of the task and may vary across the course of a scanning session. The goal of the present study was to extend our knowledge of the dynamics of amygdala dysfunction by examining whether changes in amygdala activation and connectivity over scanning differ in pediatric anxiety disorder patients relative to typically developing controls during an emotion processing task. Examining changes in activation over time allows for a comparison of how brain function differs during initial exposure to novel stimuli versus more prolonged exposure. Participants included 34 anxiety disorder patients and 19 controls 7 to 19 years old. Participants performed an emotional face matching task during fMRI scanning and the task was divided into thirds in order to examine change in activation over time. Results demonstrated that patients exhibited an abnormal pattern of amygdala activation characterized by an initially heightened amygdala response relative to controls at the beginning of scanning, followed by significant decreases in activation over time. In addition, controls evidenced greater prefrontal cortex-amygdala connectivity during the beginning of scanning relative to patients. These results indicate that differences in emotion processing between the groups vary from initial exposure to novel stimuli relative to more prolonged exposure. Implications are discussed regarding how this pattern of neural activation may relate to altered early-occurring or anticipatory emotion-regulation strategies and maladaptive later-occurring strategies in children and adolescents with anxiety disorders. PMID:25422963

Evolution of the vestibulo-ocular system

NASA Technical Reports Server (NTRS)

Fritzsch, B.

1998-01-01

The evolutionary and developmental changes in the eye muscle innervation, the inner ear, and the vestibulo-ocular reflex are examined. Three eye muscle patterns, based on the innervation by distinct ocular motoneurons populations, can be identified: a lamprey, an elasmobranch, and a bony fish/tetrapod pattern. Four distinct patterns of variation in the vestibular system are described: a hagfish pattern, a lamprey pattern, an elasmobranch pattern, and a bony fish/tetrapod pattern. Developmental data suggest an influence of the hindbrain on ear pattern formation, thus potentially allowing a concomitant change of eye muscle innervation and ear variation. The connections between the ear and the vestibular nuclei and between the vestibular nuclei and ocular motoneurons are reviewed, and the role of neurotrophins for pattern specification is discussed. Three patterns are recognized in central projections: a hagfish pattern, a lamprey pattern, and a pattern for jawed vertebrates. Second-order connections show both similarities and differences between distantly related species such as lampreys and mammals. For example, elasmobranchs lack an internuclear system, which is at best poorly developed in lampreys. It is suggested that the vestibulo-ocular system shows only a limited degree of variation because of the pronounced functional constraints imposed on it.

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

Semi-supervised clustering for parcellating brain regions based on resting state fMRI data

NASA Astrophysics Data System (ADS)

Cheng, Hewei; Fan, Yong

2014-03-01

Many unsupervised clustering techniques have been adopted for parcellating brain regions of interest into functionally homogeneous subregions based on resting state fMRI data. However, the unsupervised clustering techniques are not able to take advantage of exiting knowledge of the functional neuroanatomy readily available from studies of cytoarchitectonic parcellation or meta-analysis of the literature. In this study, we propose a semi-supervised clustering method for parcellating amygdala into functionally homogeneous subregions based on resting state fMRI data. Particularly, the semi-supervised clustering is implemented under the framework of graph partitioning, and adopts prior information and spatial consistent constraints to obtain a spatially contiguous parcellation result. The graph partitioning problem is solved using an efficient algorithm similar to the well-known weighted kernel k-means algorithm. Our method has been validated for parcellating amygdala into 3 subregions based on resting state fMRI data of 28 subjects. The experiment results have demonstrated that the proposed method is more robust than unsupervised clustering and able to parcellate amygdala into centromedial, laterobasal, and superficial parts with improved functionally homogeneity compared with the cytoarchitectonic parcellation result. The validity of the parcellation results is also supported by distinctive functional and structural connectivity patterns of the subregions and high consistency between coactivation patterns derived from a meta-analysis and functional connectivity patterns of corresponding subregions.

Directed functional connectivity matures with motor learning in a cortical pattern generator.

PubMed

Day, Nancy F; Terleski, Kyle L; Nykamp, Duane Q; Nick, Teresa A

2013-02-01

Sequential motor skills may be encoded by feedforward networks that consist of groups of neurons that fire in sequence (Abeles 1991; Long et al. 2010). However, there has been no evidence of an anatomic map of activation sequence in motor control circuits, which would be potentially detectable as directed functional connectivity of coactive neuron groups. The proposed pattern generator for birdsong, the HVC (Long and Fee 2008; Vu et al. 1994), contains axons that are preferentially oriented in the rostrocaudal axis (Nottebohm et al. 1982; Stauffer et al. 2012). We used four-tetrode recordings to assess the activity of ensembles of single neurons along the rostrocaudal HVC axis in anesthetized zebra finches. We found an axial, polarized neural network in which sequential activity is directionally organized along the rostrocaudal axis in adult males, who produce a stereotyped song. Principal neurons fired in rostrocaudal order and with interneurons that were rostral to them, suggesting that groups of excitatory neurons fire at the leading edge of travelling waves of inhibition. Consistent with the synchronization of neurons by caudally travelling waves of inhibition, the activity of interneurons was more coherent in the orthogonal mediolateral axis than in the rostrocaudal axis. If directed functional connectivity within the HVC is important for stereotyped, learned song, then it may be lacking in juveniles, which sing a highly variable song. Indeed, we found little evidence for network directionality in juveniles. These data indicate that a functionally directed network within the HVC matures during sensorimotor learning and may underlie vocal patterning.

Directed functional connectivity matures with motor learning in a cortical pattern generator

PubMed Central

Day, Nancy F.; Terleski, Kyle L.; Nykamp, Duane Q.

2013-01-01

Sequential motor skills may be encoded by feedforward networks that consist of groups of neurons that fire in sequence (Abeles 1991; Long et al. 2010). However, there has been no evidence of an anatomic map of activation sequence in motor control circuits, which would be potentially detectable as directed functional connectivity of coactive neuron groups. The proposed pattern generator for birdsong, the HVC (Long and Fee 2008; Vu et al. 1994), contains axons that are preferentially oriented in the rostrocaudal axis (Nottebohm et al. 1982; Stauffer et al. 2012). We used four-tetrode recordings to assess the activity of ensembles of single neurons along the rostrocaudal HVC axis in anesthetized zebra finches. We found an axial, polarized neural network in which sequential activity is directionally organized along the rostrocaudal axis in adult males, who produce a stereotyped song. Principal neurons fired in rostrocaudal order and with interneurons that were rostral to them, suggesting that groups of excitatory neurons fire at the leading edge of travelling waves of inhibition. Consistent with the synchronization of neurons by caudally travelling waves of inhibition, the activity of interneurons was more coherent in the orthogonal mediolateral axis than in the rostrocaudal axis. If directed functional connectivity within the HVC is important for stereotyped, learned song, then it may be lacking in juveniles, which sing a highly variable song. Indeed, we found little evidence for network directionality in juveniles. These data indicate that a functionally directed network within the HVC matures during sensorimotor learning and may underlie vocal patterning. PMID:23175804

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

PubMed

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

2014-01-01

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

Dynamic functional connectivity analysis reveals transient states of dysconnectivity in schizophrenia

PubMed Central

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

2014-01-01

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

Inferring consistent functional interaction patterns from natural stimulus FMRI data

PubMed Central

Sun, Jiehuan; Hu, Xintao; Huang, Xiu; Liu, Yang; Li, Kaiming; Li, Xiang; Han, Junwei; Guo, Lei

2014-01-01

There has been increasing interest in how the human brain responds to natural stimulus such as video watching in the neuroimaging field. Along this direction, this paper presents our effort in inferring consistent and reproducible functional interaction patterns under natural stimulus of video watching among known functional brain regions identified by task-based fMRI. Then, we applied and compared four statistical approaches, including Bayesian network modeling with searching algorithms: greedy equivalence search (GES), Peter and Clark (PC) analysis, independent multiple greedy equivalence search (IMaGES), and the commonly used Granger causality analysis (GCA), to infer consistent and reproducible functional interaction patterns among these brain regions. It is interesting that a number of reliable and consistent functional interaction patterns were identified by the GES, PC and IMaGES algorithms in different participating subjects when they watched multiple video shots of the same semantic category. These interaction patterns are meaningful given current neuroscience knowledge and are reasonably reproducible across different brains and video shots. In particular, these consistent functional interaction patterns are supported by structural connections derived from diffusion tensor imaging (DTI) data, suggesting the structural underpinnings of consistent functional interactions. Our work demonstrates that specific consistent patterns of functional interactions among relevant brain regions might reflect the brain's fundamental mechanisms of online processing and comprehension of video messages. PMID:22440644

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

Multi-factorial modulation of hemispheric specialization and plasticity for language in healthy and pathological conditions: A review.

PubMed

Tzourio-Mazoyer, Nathalie; Perrone-Bertolotti, Marcela; Jobard, Gael; Mazoyer, Bernard; Baciu, Monica

2017-01-01

This review synthesizes anatomo-functional variability of language hemispheric representation and specialization (hemispheric specialization for language, HSL) as well as its modulation by several variables (demographic, anatomical, developmental, genetic, clinical, and psycholinguistic) in physiological and pathological conditions. The left hemisphere (LH) dominance for language, observed in approximately 90% of healthy individuals and in 70% of patients, is grounded by intra-hemispheric connections mediated by associative bundles such as the arcuate fasciculus and inter-hemispheric transcallosal connections mediated by the corpus callosum that connects homotopic regions of the left and right hemispheres (RH). In typical brains, inter-hemispheric inhibition, exerted from the LH to the RH, permits the LH to maintain language dominance. In pathological conditions, inter- and intra-hemispheric inhibition is decreased, inducing modifications on the degree of HSL and of language networks. HSL evaluation is classically performed in clinical practice with the Wada test and electro-cortical stimulation, gold standard methods. The advent of functional neuroimaging has allowed a more detailed assessment of the language networks and their lateralization, consistent with the results provided by the gold standard methods. In the first part, we describe anatomo-functional support for HSL in healthy conditions, its developmental course, its relationship with cognitive skills, and the various modulatory factors acting on HSL. The second section is devoted to the assessment of HSL in patients with focal and drug-resistant epilepsy (FDRE). FDRE is considered a neurological model associated with patterns of language plasticity, both before and after surgery: FDRE patients show significant modification of language networks induced by changes mediated by transcallosal connections (explaining inter-hemispheric patterns of language reorganization) or collateral connections (explaining intra-hemispheric patterns of language reorganization). Finally, we propose several predictive and explicative models of language organization and reorganization. Copyright © 2016 Elsevier Ltd. All rights reserved.

Using Dual Regression to Investigate Network Shape and Amplitude in Functional Connectivity Analyses

PubMed Central

Nickerson, Lisa D.; Smith, Stephen M.; Öngür, Döst; Beckmann, Christian F.

2017-01-01

Independent Component Analysis (ICA) is one of the most popular techniques for the analysis of resting state FMRI data because it has several advantageous properties when compared with other techniques. Most notably, in contrast to a conventional seed-based correlation analysis, it is model-free and multivariate, thus switching the focus from evaluating the functional connectivity of single brain regions identified a priori to evaluating brain connectivity in terms of all brain resting state networks (RSNs) that simultaneously engage in oscillatory activity. Furthermore, typical seed-based analysis characterizes RSNs in terms of spatially distributed patterns of correlation (typically by means of simple Pearson's coefficients) and thereby confounds together amplitude information of oscillatory activity and noise. ICA and other regression techniques, on the other hand, retain magnitude information and therefore can be sensitive to both changes in the spatially distributed nature of correlations (differences in the spatial pattern or “shape”) as well as the amplitude of the network activity. Furthermore, motion can mimic amplitude effects so it is crucial to use a technique that retains such information to ensure that connectivity differences are accurately localized. In this work, we investigate the dual regression approach that is frequently applied with group ICA to assess group differences in resting state functional connectivity of brain networks. We show how ignoring amplitude effects and how excessive motion corrupts connectivity maps and results in spurious connectivity differences. We also show how to implement the dual regression to retain amplitude information and how to use dual regression outputs to identify potential motion effects. Two key findings are that using a technique that retains magnitude information, e.g., dual regression, and using strict motion criteria are crucial for controlling both network amplitude and motion-related amplitude effects, respectively, in resting state connectivity analyses. We illustrate these concepts using realistic simulated resting state FMRI data and in vivo data acquired in healthy subjects and patients with bipolar disorder and schizophrenia. PMID:28348512

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.

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.

Regional specificity of aberrant thalamocortical connectivity in autism.

PubMed

Nair, Aarti; Carper, Ruth A; Abbott, Angela E; Chen, Colleen P; Solders, Seraphina; Nakutin, Sarah; Datko, Michael C; Fishman, Inna; Müller, Ralph-Axel

2015-11-01

Preliminary evidence suggests aberrant (mostly reduced) thalamocortical (TC) connectivity in autism spectrum disorder (ASD), but despite the crucial role of thalamus in sensorimotor functions and its extensive connectivity with cerebral cortex, relevant evidence remains limited. We performed a comprehensive investigation of region-specific TC connectivity in ASD. Resting-state functional MRI and diffusion tensor imaging (DTI) data were acquired for 60 children and adolescents with ASD (ages 7-17 years) and 45 age, sex, and IQ-matched typically developing (TD) participants. We examined intrinsic functional connectivity (iFC) and anatomical connectivity (probabilistic tractography) with thalamus, using 68 unilateral cerebral cortical regions of interest (ROIs). For frontal and parietal lobes, iFC was atypically reduced in the ASD group for supramodal association cortices, but was increased for cingulate gyri and motor cortex. Temporal iFC was characterized by overconnectivity for auditory cortices, but underconnectivity for amygdalae. Occipital iFC was broadly reduced in the ASD group. DTI indices (such as increased radial diffusion) for regions with group differences in iFC further indicated compromised anatomical connectivity, especially for frontal ROIs, in the ASD group. Our findings highlight the regional specificity of aberrant TC connectivity in ASD. Their overall pattern can be largely accounted for by functional overconnectivity with limbic and sensorimotor regions, but underconnectivity with supramodal association cortices. This could be related to comparatively early maturation of limbic and sensorimotor regions in the context of early overgrowth in ASD, at the expense of TC connectivity with later maturing cortical regions. © 2015 Wiley Periodicals, Inc.

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.

Self-organized multi-species vegetation patterns: the role of connectivity of environmental niches in natural water harvesting ecosystems

NASA Astrophysics Data System (ADS)

Callegaro, Chiara; Ursino, Nadia

2016-04-01

Self-organizing vegetation patterns are natural water harvesting systems in arid and semi-arid regions of the world and should be imitated when designing man-managed water-harvesting systems for rain-fed crop. Disconnected vegetated and bare zones, functioning as a source-sink system of resources, sustain vegetation growth and reduce water and soil losses. Mechanisms such as soil crusting over bare areas and soil loosening in vegetated areas feed back to the local net facilitation effect and contribute to maintain the patterned landscape structure. Dis-connectivity of run-off production and run-on infiltration sites reduces runoff production at the landscape scale, and increases water retention in the vegetated patches. What is the effect of species adaptation to different resource niches on the landscape structure? A minimal model for two coexisting species and soil moisture balance was formulated, to improve our understanding of the effects of species differentiation on the dynamics of plants and water at single-pattern and landscape scale within a tiger bush type ecosystem. A basic assumption of our model was that soil moisture availability is a proxy for the environmental niche of plant species. Connectivity and dis-connectivity of specific niches of adaptation of two differing plant species was an input parameter of our model, in order to test the effect of coexistence on the ecosystem structure. The ecosystem structure is the model outcome, including: patterns persistence of coexisting species; patterns persistence of one species with exclusion of the other; patterns decline with just one species surviving in a non organized structure; bare landscape with loss of both species. Results suggest that pattern-forming-species communities arise as a result of complementary niche adaptation (niche dis-connecivity), whereas niche superposition (niche connectivity) may lead to impoverishment of environmental resources and loss of vegetation cover and diversity.

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

Undifferentiated connective tissue disease and interstitial lung disease: Trying to define patterns.

PubMed

Alberti, María Laura; Paulin, Francisco; Toledo, Heidegger Mateos; Fernández, Martín Eduardo; Caro, Fabián Matías; Rojas-Serrano, Jorge; Mejía, Mayra Edith

To identify clinical or immunological features in patients with undifferentiated connective tissue disease (UCTD) associated interstitial lung disease (ILD), in order to group them and recognize different functional and high resolution computed tomography (HRCT) behavior. Retrospective cohort study. Patients meeting Kinder criteria for UCTD were included. We defined the following predictive variables: 'highly specific' connective tissue disease (CTD) manifestations (Raynaud's phenomenon, dry eyes or arthritis), high antinuclear antibody (ANA) titer (above 1: 320), and 'specific' ANA staining patterns (centromere, cytoplasmic and nucleolar patterns). We evaluated the following outcomes: change in the percentage of the predicted forced vital capacity (FVC%) during the follow-up period, and HRCT pattern. Sixty-six patients were included. Twenty-nine (43.94%) showed at least one 'highly specific' CTD manifestation, 16 (28.57%) had a 'specific' ANA staining pattern and 29 (43.94%) high ANA titer. Patients with 'highly specific' CTD manifestations were younger (mean [SD] 52 years [14.58] vs 62.08 years [9.46], P<.001), were more likely men (10.34% vs 48.65%, P<.001) and showed a smaller decline of the FVC% (median [interquartile range] 1% [-1 to 10] vs -6% [-16 to -4], P<.006). In the multivariate analysis, the presence of highly specific manifestations was associated with improvement in the FVC% (B coefficient of 13.25 [95% confidence interval, 2.41 to 24.09]). No association was observed in relation to the HRCT pattern. The presence of 'highly specific' CTD manifestations was associated with female sex, younger age and better functional behavior. These findings highlight the impact of the clinical features in the outcome of patients with UCTD ILD. Copyright © 2016 Elsevier España, S.L.U. and Sociedad Española de Reumatología y Colegio Mexicano de Reumatología. All rights reserved.

Familial Risk and a Genome-Wide Supported DRD2 Variant for Schizophrenia Predict Lateral Prefrontal-Amygdala Effective Connectivity During Emotion Processing.

PubMed

Quarto, Tiziana; Paparella, Isabella; De Tullio, Davide; Viscanti, Giovanna; Fazio, Leonardo; Taurisano, Paolo; Romano, Raffaella; Rampino, Antonio; Masellis, Rita; Popolizio, Teresa; Selvaggi, Pierluigi; Pergola, Giulio; Bertolino, Alessandro; Blasi, Giuseppe

2017-09-16

The brain functional mechanisms translating genetic risk into emotional symptoms in schizophrenia (SCZ) may include abnormal functional integration between areas key for emotion processing, such as the amygdala and the lateral prefrontal cortex (LPFC). Indeed, investigation of these mechanisms is also complicated by emotion processing comprising different subcomponents and by disease-associated state variables. Here, our aim was to investigate the relationship between risk for SCZ and effective connectivity between the amygdala and the LPFC during different subcomponents of emotion processing. Thus, we first characterized with dynamic causal modeling (DCM) physiological patterns of LPFC-amygdala effective connectivity in healthy controls (HC) during implicit and explicit emotion processing. Then, we compared DCM patterns in a subsample of HC, in patients with SCZ and in healthy siblings of patients (SIB), matched for demographics. Finally, we investigated in HC association of LPFC-amygdala effective connectivity with a genome-wide supported variant increasing genetic risk for SCZ and possibly relevant to emotion processing (DRD2 rs2514218). In HC, we found that a "bottom-up" amygdala-to-LPFC pattern during implicit processing and a "top-down" LPFC-to-amygdala pattern during explicit processing were the most likely directional models of effective connectivity. Differently, implicit emotion processing in SIB, SCZ, and HC homozygous for the SCZ risk rs2514218 C allele was associated with decreased probability for the "bottom-up" as well as with increased probability for the "top-down" model. These findings suggest that task-specific anomaly in the directional flow of information or disconnection between the amygdala and the LPFC is a good candidate endophenotype of SCZ. © The Author 2017. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Changed Hub and Corresponding Functional Connectivity of Subgenual Anterior Cingulate Cortex in Major Depressive Disorder

PubMed Central

Wu, Huawang; Sun, Hui; Xu, Jinping; Wu, Yan; Wang, Chao; Xiao, Jing; She, Shenglin; Huang, Jianwei; Zou, Wenjin; Peng, Hongjun; Lu, Xiaobing; Huang, Guimao; Jiang, Tianzi; Ning, Yuping; Wang, Jiaojian

2016-01-01

Major depressive disorder (MDD) is one of the most prevalent mental disorders. In the brain, the hubs of the brain network play a key role in integrating and transferring information between different functional modules. However, whether the changed pattern in functional network hubs contributes to the onset of MDD remains unclear. Using resting-state functional magnetic resonance imaging (rs-fMRI) and graph theory methods, we investigated whether alterations of hubs can be detected in MDD. First, we constructed the whole-brain voxel-wise functional networks and calculated a functional connectivity strength (FCS) map in each subject in 34 MDD patients and 34 gender-, age- and education level-matched healthy controls (HCs). Next, the two-sample t-test was applied to compare the FCS maps between HC and MDD patients and identified significant decrease of FCS in subgenual anterior cingulate cortex (sgACC) in MDD patients. Subsequent functional connectivity analyses of sgACC showed disruptions in functional connectivity with posterior insula, middle and inferior temporal gyrus, lingual gyrus and cerebellum in MDD patients. Furthermore, the changed FCS of sgACC and functional connections to sgACC were significantly correlated with the Hamilton Depression Rating Scale (HDRS) scores in MDD patients. The results of the present study revealed the abnormal hub of sgACC and its corresponding disrupted frontal-limbic-visual cognitive-cerebellum functional networks in MDD. These findings may provide a new insight for the diagnosis and treatment of MDD. PMID:28018183

A Brain System for Auditory Working Memory.

PubMed

Kumar, Sukhbinder; Joseph, Sabine; Gander, Phillip E; Barascud, Nicolas; Halpern, Andrea R; Griffiths, Timothy D

2016-04-20

The brain basis for auditory working memory, the process of actively maintaining sounds in memory over short periods of time, is controversial. Using functional magnetic resonance imaging in human participants, we demonstrate that the maintenance of single tones in memory is associated with activation in auditory cortex. In addition, sustained activation was observed in hippocampus and inferior frontal gyrus. Multivoxel pattern analysis showed that patterns of activity in auditory cortex and left inferior frontal gyrus distinguished the tone that was maintained in memory. Functional connectivity during maintenance was demonstrated between auditory cortex and both the hippocampus and inferior frontal cortex. The data support a system for auditory working memory based on the maintenance of sound-specific representations in auditory cortex by projections from higher-order areas, including the hippocampus and frontal cortex. In this work, we demonstrate a system for maintaining sound in working memory based on activity in auditory cortex, hippocampus, and frontal cortex, and functional connectivity among them. Specifically, our work makes three advances from the previous work. First, we robustly demonstrate hippocampal involvement in all phases of auditory working memory (encoding, maintenance, and retrieval): the role of hippocampus in working memory is controversial. Second, using a pattern classification technique, we show that activity in the auditory cortex and inferior frontal gyrus is specific to the maintained tones in working memory. Third, we show long-range connectivity of auditory cortex to hippocampus and frontal cortex, which may be responsible for keeping such representations active during working memory maintenance. Copyright © 2016 Kumar et al.

Altered long-range alpha-band synchronization during visual short-term memory retention in children born very preterm.

PubMed

Doesburg, Sam M; Ribary, Urs; Herdman, Anthony T; Miller, Steven P; Poskitt, Kenneth J; Moiseev, Alexander; Whitfield, Michael F; Synnes, Anne; Grunau, Ruth E

2011-02-01

Children born very preterm, even when intelligence is broadly normal, often experience selective difficulties in executive function and visual-spatial processing. Development of structural cortical connectivity is known to be altered in this group, and functional magnetic resonance imaging (fMRI) evidence indicates that very preterm children recruit different patterns of functional connectivity between cortical regions during cognition. Synchronization of neural oscillations across brain areas has been proposed as a mechanism for dynamically assigning functional coupling to support perceptual and cognitive processing, but little is known about what role oscillatory synchronization may play in the altered neurocognitive development of very preterm children. To investigate this, we recorded magnetoencephalographic (MEG) activity while 7-8 year old children born very preterm and age-matched full-term controls performed a visual short-term memory task. Very preterm children exhibited reduced long-range synchronization in the alpha-band during visual short-term memory retention, indicating that cortical alpha rhythms may play a critical role in altered patterns functional connectivity expressed by this population during cognitive and perceptual processing. Long-range alpha-band synchronization was also correlated with task performance and visual-perceptual ability within the very preterm group, indicating that altered alpha oscillatory mechanisms mediating transient functional integration between cortical regions may be relevant to selective problems in neurocognitive development in this vulnerable population at school age. Copyright © 2010 Elsevier Inc. All rights reserved.

Large-scale coupling dynamics of instructed reversal learning.

PubMed

Mohr, Holger; Wolfensteller, Uta; Ruge, Hannes

2018-02-15

The ability to rapidly learn from others by instruction is an important characteristic of human cognition. A recent study found that the rapid transfer from initial instructions to fluid behavior is supported by changes of functional connectivity between and within several large-scale brain networks, and particularly by the coupling of the dorsal attention network (DAN) with the cingulo-opercular network (CON). In the present study, we extended this approach to investigate how these brain networks interact when stimulus-response mappings are altered by novel instructions. We hypothesized that residual stimulus-response associations from initial practice might negatively impact the ability to implement novel instructions. Using functional imaging and large-scale connectivity analysis, we found that functional coupling between the CON and DAN was generally at a higher level during initial than reversal learning. Examining the learning-related connectivity dynamics between the CON and DAN in more detail by means of multivariate patterns analyses, we identified a specific subset of connections which showed a particularly high increase in connectivity during initial learning compared to reversal learning. This finding suggests that the CON-DAN connections can be separated into two functionally dissociable yet spatially intertwined subsystems supporting different aspects of short-term task automatization. Copyright © 2017 Elsevier Inc. All rights reserved.

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

PubMed

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

2018-04-18

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

On imputing function to structure from the behavioural effects of brain lesions.

PubMed

Young, M P; Hilgetag, C C; Scannell, J W

2000-01-29

What is the link, if any, between the patterns of connections in the brain and the behavioural effects of localized brain lesions? We explored this question in four related ways. First, we investigated the distribution of activity decrements that followed simulated damage to elements of the thalamocortical network, using integrative mechanisms that have recently been used to successfully relate connection data to information on the spread of activation, and to account simultaneously for a variety of lesion effects. Second, we examined the consequences of the patterns of decrement seen in the simulation for each type of inference that has been employed to impute function to structure on the basis of the effects of brain lesions. Every variety of conventional inference, including double dissociation, readily misattributed function to structure. Third, we tried to derive a more reliable framework of inference for imputing function to structure, by clarifying concepts of function, and exploring a more formal framework, in which knowledge of connectivity is necessary but insufficient, based on concepts capable of mathematical specification. Fourth, we applied this framework to inferences about function relating to a simple network that reproduces intact, lesioned and paradoxically restored orientating behaviour. Lesion effects could be used to recover detailed and reliable information on which structures contributed to particular functions in this simple network. Finally, we explored how the effects of brain lesions and this formal approach could be used in conjunction with information from multiple neuroscience methodologies to develop a practical and reliable approach to inferring the functional roles of brain structures.

Illuminating the multifaceted roles of neurotransmission in shaping neuronal circuitry.

PubMed

Okawa, Haruhisa; Hoon, Mrinalini; Yoshimatsu, Takeshi; Della Santina, Luca; Wong, Rachel O L

2014-09-17

Across the nervous system, neurons form highly stereotypic patterns of synaptic connections that are designed to serve specific functions. Mature wiring patterns are often attained upon the refinement of early, less precise connectivity. Much work has led to the prevailing view that many developing circuits are sculpted by activity-dependent competition among converging afferents, which results in the elimination of unwanted synapses and the maintenance and strengthening of desired connections. Studies of the vertebrate retina, however, have recently revealed that activity can play a role in shaping developing circuits without engaging competition among converging inputs that differ in their activity levels. Such neurotransmission-mediated processes can produce stereotypic wiring patterns by promoting selective synapse formation rather than elimination. We discuss how the influence of transmission may also be limited by circuit design and further highlight the importance of transmission beyond development in maintaining wiring specificity and synaptic organization of neural circuits. Copyright © 2014 Elsevier Inc. All rights reserved.

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

Defining Functional Areas in Individual Human Brains using Resting Functional Connectivity MRI

PubMed Central

Cohen, Alexander L.; Fair, Damien A.; Dosenbach, Nico U.F.; Miezin, Francis M.; Dierker, Donna; Van Essen, David C.; Schlaggar, Bradley L.; Petersen, Steven E.

2009-01-01

The cerebral cortex is anatomically organized at many physical scales starting at the level of single neurons and extending up to functional systems. Current functional magnetic resonance imaging (fMRI) studies often focus at the level of areas, networks, and systems. Except in restricted domains, (e.g. topographically-organized sensory regions), it is difficult to determine area boundaries in the human brain using fMRI. The ability to delineate functional areas non-invasively would enhance the quality of many experimental analyses allowing more accurate across-subject comparisons of independently identified functional areas. Correlations in spontaneous BOLD activity, often referred to as resting state functional connectivity (rs-fcMRI), are especially promising as a way to accurately localize differences in patterns of correlated activity across large expanses of cortex. In the current report, we applied a novel set of image analysis tools to explore the utility of rs-fcMRI for defining wide-ranging functional area boundaries. We find that rs-fcMRI patterns show sharp transitions in correlation patterns and that these putative areal boundaries can be reliably detected in individual subjects as well as in group data. Additionally, combining surface-based analysis techniques with image processing algorithms allows automated mapping of putative areal boundaries across large expanses of cortex without the need for prior information about a region’s function or topography. Our approach reliably produces maps of bounded regions appropriate in size and number for putative functional areas. These findings will hopefully stimulate further methodological refinements and validations. PMID:18367410

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

Amygdala Functional Connectivity is Reduced After the Cold Pressor Task

PubMed Central

Clewett, David; Schoeke, Andrej; Mather, Mara

2013-01-01

The amygdala forms a crucial link between central pain and stress systems. There is much evidence that psychological stress affects amygdala activity, but it is less clear how painful stressors influence subsequent amygdala functional connectivity. In the present study, we used pulsed arterial spin labeling (PASL) to investigate differences in healthy male adults’ resting-state amygdala functional connectivity following a cold pressor versus control task, with the stressor and control conditions conducted on different days. During the period of peak cortisol response to acute stress (approximately fifteen to thirty minutes after stressor onset), participants were asked to rest for six minutes with their eyes closed during a PASL scanning sequence. The cold pressor task led to reduced resting-state functional connectivity between the amygdalae and orbitofrontal cortex (OFC) and ventromedial prefrontal cortex (VMPFC), which occurred irrespective of cortisol release. The stressor also induced greater inverse connectivity between the left amygdala and dorsal anterior cingulate cortex (dACC), a brain region implicated in the down-regulation of amygdala responsivity. Furthermore, the degree of post-stressor left amygdala decoupling with the lateral OFC varied according to self-reported pain intensity during the cold pressor task. These findings indicate that the cold pressor task alters amygdala interactions with prefrontal and ACC regions 15–30 minutes after the stressor, and that these altered functional connectivity patterns are related to pain perception rather than cortisol feedback. PMID:23645370

Sex differences in normal age trajectories of functional brain networks.

PubMed

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

2015-04-01

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

Patterns and drivers for wetland connections in the Prairie Pothole Region, United States

USGS Publications Warehouse

Vanderhoof, Melanie; Christensen, Jay R.; Alexander, Laurie C.

2017-01-01

Ecosystem function in rivers, lakes and coastal waters depends on the functioning of upstream aquatic ecosystems, necessitating an improved understanding of watershed-scale interactions including variable surface-water flows between wetlands and streams. As surface water in the Prairie Pothole Region expands in wet years, surface-water connections occur between many depressional wetlands and streams. Minimal research has explored the spatial patterns and drivers for the abundance of these connections, despite their potential to inform resource management and regulatory programs including the U.S. Clean Water Act. In this study, wetlands were identified that did not intersect the stream network, but were shown with Landsat images (1990–2011) to become merged with the stream network as surface water expanded. Wetlands were found to spill into or consolidate with other wetlands within both small (2–10 wetlands) and large (>100 wetlands) wetland clusters, eventually intersecting a stream channel, most often via a riparian wetland. These surface-water connections occurred over a wide range of wetland distances from streams (averaging 90–1400 m in different ecoregions). Differences in the spatial abundance of wetlands that show a variable surface-water connection to a stream were best explained by smaller wetland-to-wetland distances, greater wetland abundance, and maximum surface-water extent. This analysis demonstrated that wetland arrangement and surface water expansion are important mechanisms for depressional wetlands to connect to streams and provides a first step to understanding the frequency and abundance of these surface-water connections across the Prairie Pothole Region.

Mapping thalamocortical functional connectivity in chronic and early stages of psychotic disorders

PubMed Central

Woodward, Neil D.; Heckers, Stephan

2015-01-01

Objective There is considerable evidence that the thalamus is abnormal in psychotic disorders. Resting-state fMRI (RS-fMRI) has revealed an intriguing pattern of thalamic dysconnectivity in psychosis characterized by reduced prefrontal cortex (PFC) connectivity and increased somatomotor-thalamic connectivity. However, critical knowledge gaps remain with respect to the onset, anatomical specificity, and clinical correlates of thalamic dysconnectivity in psychosis. Method RS-fMRI was collected on 105 healthy subjects and 148 individuals with psychosis, including 53 early stage psychosis patients. Using all 253 subjects, the thalamus was parceled into functional regions-of-interest (ROIs) on the basis of connectivity with six a-priori defined cortical ROIs covering most of the cortical mantle. Functional connectivity between each cortical ROI and its corresponding thalamic ROI was quantified and compared across groups. Significant differences in the ROI-to-ROI analysis were followed up with voxel-wise seed-based analyses to further localize thalamic dysconnectivity. Results ROI analysis revealed reduced PFC-thalamic connectivity and increased somatomotor-thalamic connectivity in both chronic and early stages psychosis patients. PFC hypo-connectivity and motor cortex hyper-connectivity correlated in patients suggesting they result from a common pathophysiological mechanism. Seed-based analyses revealed thalamic hypo-connectivity in psychosis localized to dorsolateral PFC, medial PFC, and cerebellar areas of the well-described ‘executive control’ network. Across all subjects, thalamic connectivity with areas of the fronto-parietal network correlated with cognitive functioning, including verbal learning and memory. Conclusions Thalamocortical dysconnectivity is present in both chronic and early stages of psychosis, includes reduced thalamic connectivity with the executive control network, and is related to cognitive impairment. PMID:26248537

The persuasion network is modulated by drug-use risk and predicts anti-drug message effectiveness.

PubMed

Huskey, Richard; Mangus, J Michael; Turner, Benjamin O; Weber, René

2017-12-01

While a persuasion network has been proposed, little is known about how network connections between brain regions contribute to attitude change. Two possible mechanisms have been advanced. One hypothesis predicts that attitude change results from increased connectivity between structures implicated in affective and executive processing in response to increases in argument strength. A second functional perspective suggests that highly arousing messages reduce connectivity between structures implicated in the encoding of sensory information, which disrupts message processing and thereby inhibits attitude change. However, persuasion is a multi-determined construct that results from both message features and audience characteristics. Therefore, persuasive messages should lead to specific functional connectivity patterns among a priori defined structures within the persuasion network. The present study exposed 28 subjects to anti-drug public service announcements where arousal, argument strength, and subject drug-use risk were systematically varied. Psychophysiological interaction analyses provide support for the affective-executive hypothesis but not for the encoding-disruption hypothesis. Secondary analyses show that video-level connectivity patterns among structures within the persuasion network predict audience responses in independent samples (one college-aged, one nationally representative). We propose that persuasion neuroscience research is best advanced by considering network-level effects while accounting for interactions between message features and target audience characteristics. © The Author (2017). Published by Oxford University Press.

Network Mechanisms of Clinical Response to Transcranial Magnetic Stimulation in Posttraumatic Stress Disorder and Major Depressive Disorder.

PubMed

Philip, Noah S; Barredo, Jennifer; van 't Wout-Frank, Mascha; Tyrka, Audrey R; Price, Lawrence H; Carpenter, Linda L

2018-02-01

Repetitive transcranial magnetic stimulation (TMS) therapy can modulate pathological neural network functional connectivity in major depressive disorder (MDD). Posttraumatic stress disorder is often comorbid with MDD, and symptoms of both disorders can be alleviated with TMS therapy. This is the first study to evaluate TMS-associated changes in connectivity in patients with comorbid posttraumatic stress disorder and MDD. Resting-state functional connectivity magnetic resonance imaging was acquired before and after TMS therapy in 33 adult outpatients in a prospective open trial. TMS at 5 Hz was delivered, in up to 40 daily sessions, to the left dorsolateral prefrontal cortex. Analyses used a priori seeds relevant to TMS, posttraumatic stress disorder, or MDD (subgenual anterior cingulate cortex [sgACC], left dorsolateral prefrontal cortex, hippocampus, and basolateral amygdala) to identify imaging predictors of response and to evaluate clinically relevant changes in connectivity after TMS, followed by leave-one-out cross-validation. Imaging results were explored using data-driven multivoxel pattern activation. More negative pretreatment connectivity between the sgACC and the default mode network predicted clinical improvement, as did more positive amygdala-to-ventromedial prefrontal cortex connectivity. After TMS, symptom reduction was associated with reduced connectivity between the sgACC and the default mode network, left dorsolateral prefrontal cortex, and insula, and reduced connectivity between the hippocampus and the salience network. Multivoxel pattern activation confirmed seed-based predictors and correlates of treatment outcomes. These results highlight the central role of the sgACC, default mode network, and salience network as predictors of TMS response and suggest their involvement in mechanisms of action. Furthermore, this work indicates that there may be network-based biomarkers of clinical response relevant to these commonly comorbid disorders. Published by Elsevier Inc.

Lobular patterns of cerebellar resting-state connectivity in adults with Autism Spectrum Disorder.

PubMed

Olivito, Giusy; Lupo, Michela; Laghi, Fiorenzo; Clausi, Silvia; Baiocco, Roberto; Cercignani, Mara; Bozzali, Marco; Leggio, Maria

2018-03-01

Autism spectrum disorder is a neurodevelopmental disorder characterized by core deficits in social functioning. Core autistics traits refer to poor social and imagination skills, poor attention-switching/strong focus of attention, exceptional attention to detail, as expressed by the autism-spectrum quotient. Over the years, the importance of the cerebellum in the aetiology of autism spectrum disorder has been acknowledged. Neuroimaging studies have provided a strong support to this view, showing both structural and functional connectivity alterations to affect the cerebellum in autism spectrum disorder. According to the underconnectivity theory, disrupted connectivity within cerebello-cerebral networks has been specifically implicated in the aetiology of autism spectrum disorder. However, inconsistent results have been generated across studies. In this study, an integrated approach has been used in a selected population of adults with autism spectrum disorder to analyse both cerebellar morphometry and functional connectivity. In individuals with autism spectrum disorder, a decreased cerebellar grey matter volume affected the right Crus II, a region showing extensive connections with cerebral areas related to social functions. This grey matter reduction correlates with the degree of autistic traits as measured by autism-spectrum quotient. Interestingly, altered functional connectivity was found between the reduced cerebellar Crus II and contralateral cerebral regions, such as frontal and temporal areas. Overall, the present data suggest that adults with autism spectrum disorder present with specific cerebellar structural alterations that may affect functional connectivity within cerebello-cerebral modules relevant to social processing and account for core autistics traits. © 2017 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

Mnemonic training reshapes brain networks to support superior memory

PubMed Central

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

2017-01-01

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

Amygdala subnuclei response and connectivity during emotional processing.

PubMed

Hrybouski, Stanislau; Aghamohammadi-Sereshki, Arash; Madan, Christopher R; Shafer, Andrea T; Baron, Corey A; Seres, Peter; Beaulieu, Christian; Olsen, Fraser; Malykhin, Nikolai V

2016-06-01

The involvement of the human amygdala in emotion-related processing has been studied using functional magnetic resonance imaging (fMRI) for many years. However, despite the amygdala being comprised of several subnuclei, most studies investigated the role of the entire amygdala in processing of emotions. Here we combined a novel anatomical tracing protocol with event-related high-resolution fMRI acquisition to study the responsiveness of the amygdala subnuclei to negative emotional stimuli and to examine intra-amygdala functional connectivity. The greatest sensitivity to the negative emotional stimuli was observed in the centromedial amygdala, where the hemodynamic response amplitude elicited by the negative emotional stimuli was greater and peaked later than for neutral stimuli. Connectivity patterns converge with extant findings in animals, such that the centromedial amygdala was more connected with the nuclei of the basal amygdala than with the lateral amygdala. Current findings provide evidence of functional specialization within the human amygdala. Copyright © 2016 Elsevier Inc. All rights reserved.

Integrative Mechanisms of Oriented Neuronal Migration in the Developing Brain

PubMed Central

Evsyukova, Irina; Plestant, Charlotte; Anton, E.S.

2014-01-01

The emergence of functional neuronal connectivity in the developing cerebral cortex depends on neuronal migration. This process enables appropriate positioning of neurons and the emergence of neuronal identity so that the correct patterns of functional synaptic connectivity between the right types and numbers of neurons can emerge. Delineating the complexities of neuronal migration is critical to our understanding of normal cerebral cortical formation and neurodevelopmental disorders resulting from neuronal migration defects. For the most part, the integrated cell biological basis of the complex behavior of oriented neuronal migration within the developing mammalian cerebral cortex remains an enigma. This review aims to analyze the integrative mechanisms that enable neurons to sense environmental guidance cues and translate them into oriented patterns of migration toward defined areas of the cerebral cortex. We discuss how signals emanating from different domains of neurons get integrated to control distinct aspects of migratory behavior and how different types of cortical neurons coordinate their migratory activities within the developing cerebral cortex to produce functionally critical laminar organization. PMID:23937349

Long-Term Memory Stabilized by Noise-Induced Rehearsal

PubMed Central

Wei, Yi

2014-01-01

Cortical networks can maintain memories for decades despite the short lifetime of synaptic strengths. Can a neural network store long-lasting memories in unstable synapses? Here, we study the effects of ongoing spike-timing-dependent plasticity (STDP) on the stability of memory patterns stored in synapses of an attractor neural network. We show that certain classes of STDP rules can stabilize all stored memory patterns despite a short lifetime of synapses. In our model, unstructured neural noise, after passing through the recurrent network connections, carries the imprint of all memory patterns in temporal correlations. STDP, combined with these correlations, leads to reinforcement of all stored patterns, even those that are never explicitly visited. Our findings may provide the functional reason for irregular spiking displayed by cortical neurons and justify models of system memory consolidation. Therefore, we propose that irregular neural activity is the feature that helps cortical networks maintain stable connections. PMID:25411507

Exploring connectivity with large-scale Granger causality on resting-state functional MRI.

PubMed

DSouza, Adora M; Abidin, Anas Z; Leistritz, Lutz; Wismüller, Axel

2017-08-01

Large-scale Granger causality (lsGC) is a recently developed, resting-state functional MRI (fMRI) connectivity analysis approach that estimates multivariate voxel-resolution connectivity. Unlike most commonly used multivariate approaches, which establish coarse-resolution connectivity by aggregating voxel time-series avoiding an underdetermined problem, lsGC estimates voxel-resolution, fine-grained connectivity by incorporating an embedded dimension reduction. We investigate application of lsGC on realistic fMRI simulations, modeling smoothing of neuronal activity by the hemodynamic response function and repetition time (TR), and empirical resting-state fMRI data. Subsequently, functional subnetworks are extracted from lsGC connectivity measures for both datasets and validated quantitatively. We also provide guidelines to select lsGC free parameters. Results indicate that lsGC reliably recovers underlying network structure with area under receiver operator characteristic curve (AUC) of 0.93 at TR=1.5s for a 10-min session of fMRI simulations. Furthermore, subnetworks of closely interacting modules are recovered from the aforementioned lsGC networks. Results on empirical resting-state fMRI data demonstrate recovery of visual and motor cortex in close agreement with spatial maps obtained from (i) visuo-motor fMRI stimulation task-sequence (Accuracy=0.76) and (ii) independent component analysis (ICA) of resting-state fMRI (Accuracy=0.86). Compared with conventional Granger causality approach (AUC=0.75), lsGC produces better network recovery on fMRI simulations. Furthermore, it cannot recover functional subnetworks from empirical fMRI data, since quantifying voxel-resolution connectivity is not possible as consequence of encountering an underdetermined problem. Functional network recovery from fMRI data suggests that lsGC gives useful insight into connectivity patterns from resting-state fMRI at a multivariate voxel-resolution. Copyright © 2017 Elsevier B.V. All rights reserved.

Changes in interhemispheric motor connectivity after muscle fatigue

NASA Astrophysics Data System (ADS)

Peltier, Scott; LaConte, Stephen M.; Niyazov, Dmitriy; Liu, Jing; Sahgal, Vinod; Yue, Guang; Hu, Xiaoping

2005-04-01

Synchronized oscillations in resting state timecourses have been detected in recent fMRI studies. These oscillations are low frequency in nature (< 0.08 Hz), and seem to be a property of symmetric cortices. These fluctuations are important as a potential signal of interest, which could indicate connectivity between functionally related areas of the brain. It has also been shown that the synchronized oscillations decrease in some spontaneous pathological states. Thus, detection of these functional connectivity patterns may help to serve as a gauge of normal brain activity. The cognitive effects of muscle fatigue are not well characterized. Sustained fatigue has the potential to dynamically alter activity in brain networks. In this work, we examined the interhemispheric correlations in the left and right primary motor cortices and how they change with muscle fatigue. Resting-state functional MRI imaging was done before and after a repetitive unilateral fatigue task. We find that the number of significant correlations in the bilateral motor network decreases with fatigue. These results suggest that resting-state interhemispheric motor cortex functional connectivity is affected by muscle fatigue.

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

Data-Driven Sequence of Changes to Anatomical Brain Connectivity in Sporadic Alzheimer's Disease.

PubMed

Oxtoby, Neil P; Garbarino, Sara; Firth, Nicholas C; Warren, Jason D; Schott, Jonathan M; Alexander, Daniel C

2017-01-01

Model-based investigations of transneuronal spreading mechanisms in neurodegenerative diseases relate the pattern of pathology severity to the brain's connectivity matrix, which reveals information about how pathology propagates through the connectivity network. Such network models typically use networks based on functional or structural connectivity in young and healthy individuals, and only end-stage patterns of pathology, thereby ignoring/excluding the effects of normal aging and disease progression. Here, we examine the sequence of changes in the elderly brain's anatomical connectivity over the course of a neurodegenerative disease. We do this in a data-driven manner that is not dependent upon clinical disease stage, by using event-based disease progression modeling. Using data from the Alzheimer's Disease Neuroimaging Initiative dataset, we sequence the progressive decline of anatomical connectivity, as quantified by graph-theory metrics, in the Alzheimer's disease brain. Ours is the first single model to contribute to understanding all three of the nature, the location, and the sequence of changes to anatomical connectivity in the human brain due to Alzheimer's disease. Our experimental results reveal new insights into Alzheimer's disease: that degeneration of anatomical connectivity in the brain may be a viable, even early, biomarker and should be considered when studying such neurodegenerative diseases.

Brain network informed subject community detection in early-onset schizophrenia.

PubMed

Yang, Zhi; Xu, Yong; Xu, Ting; Hoy, Colin W; Handwerker, Daniel A; Chen, Gang; Northoff, Georg; Zuo, Xi-Nian; Bandettini, Peter A

2014-07-03

Early-onset schizophrenia (EOS) offers a unique opportunity to study pathophysiological mechanisms and development of schizophrenia. Using 26 drug-naïve, first-episode EOS patients and 25 age- and gender-matched control subjects, we examined intrinsic connectivity network (ICN) deficits underlying EOS. Due to the emerging inconsistency between behavior-based psychiatric disease classification system and the underlying brain dysfunctions, we applied a fully data-driven approach to investigate whether the subjects can be grouped into highly homogeneous communities according to the characteristics of their ICNs. The resultant subject communities and the representative characteristics of ICNs were then associated with the clinical diagnosis and multivariate symptom patterns. A default mode ICN was statistically absent in EOS patients. Another frontotemporal ICN further distinguished EOS patients with predominantly negative symptoms. Connectivity patterns of this second network for the EOS patients with predominantly positive symptom were highly similar to typically developing controls. Our post-hoc functional connectivity modeling confirmed that connectivity strength in this frontotemporal circuit was significantly modulated by relative severity of positive and negative syndromes in EOS. This study presents a novel subtype discovery approach based on brain networks and proposes complex links between brain networks and symptom patterns in EOS.

Functional connectivity between the cerebrum and cerebellum in social cognition: A multi-study analysis.

PubMed

Van Overwalle, Frank; Mariën, Peter

2016-01-01

This multi-study connectivity analysis explores the functional connectivity of the cerebellum with the cerebrum in social mentalizing, that is, understanding the mind of another person. The analysis covers 5 studies (n=92) involving abstract and complex forms of social mentalizing such as (a) person and group impression formation based on behavioral descriptions and (b) constructing personal counterfactual events (i.e., how the past could have turned out better). The results suggest that cerebellar activity during these social processes reflects a domain-specific mentalizing functionality that is strongly connected with a corresponding mentalizing network in the cerebrum. A significant pattern of connectivity was found linking the dorsal medial prefrontal cortex (mPFC) and the right temporo-parietal junction (TPJ) with the right posterior cerebellum, and linking the latter with the left TPJ. In addition, in the cerebrum, further connectivity was found through links of the bilateral TPJ with the dorsal mPFC, orbitofrontal cortex and between right and left TPJ. The discussion centers on the role of these cerebro-cerebellar connections in matching external information from the cerebrum with internal predictions generated by the cerebellum. These internal predictions might involve the sequencing of the person's behaviors. Copyright © 2015 Elsevier Inc. All rights reserved.

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.

Corticostriatal connectivity fingerprints: Probability maps based on resting-state functional connectivity.

PubMed

Jaspers, Ellen; Balsters, Joshua H; Kassraian Fard, Pegah; Mantini, Dante; Wenderoth, Nicole

2017-03-01

Over the last decade, structure-function relationships have begun to encompass networks of brain areas rather than individual structures. For example, corticostriatal circuits have been associated with sensorimotor, limbic, and cognitive information processing, and damage to these circuits has been shown to produce unique behavioral outcomes in Autism, Parkinson's Disease, Schizophrenia and healthy ageing. However, it remains an open question how abnormal or absent connectivity can be detected at the individual level. Here, we provide a method for clustering gross morphological structures into subregions with unique functional connectivity fingerprints, and generate network probability maps usable as a baseline to compare individual cases against. We used connectivity metrics derived from resting-state fMRI (N = 100), in conjunction with hierarchical clustering methods, to parcellate the striatum into functionally distinct clusters. We identified three highly reproducible striatal subregions, across both hemispheres and in an independent replication dataset (N = 100) (dice-similarity values 0.40-1.00). Each striatal seed region resulted in a highly reproducible distinct connectivity fingerprint: the putamen showed predominant connectivity with cortical and cerebellar sensorimotor and language processing areas; the ventromedial striatum cluster had a distinct limbic connectivity pattern; the caudate showed predominant connectivity with the thalamus, frontal and occipital areas, and the cerebellum. Our corticostriatal probability maps agree with existing connectivity data in humans and non-human primates, and showed a high degree of replication. We believe that these maps offer an efficient tool to further advance hypothesis driven research and provide important guidance when investigating deviant connectivity in neurological patient populations suffering from e.g., stroke or cerebral palsy. Hum Brain Mapp 38:1478-1491, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

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

PubMed

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

2018-06-01

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

Functional connectivity density mapping: comparing multiband and conventional EPI protocols.

PubMed

Cohen, Alexander D; Tomasi, Dardo; Shokri-Kojori, Ehsan; Nencka, Andrew S; Wang, Yang

2018-06-01

Functional connectivity density mapping (FCDM) is a newly developed data-driven technique that quantifies the number of local and global functional connections for each voxel in the brain. In this study, we evaluated reproducibility, sensitivity, and specificity of both local functional connectivity density (lFCD) and global functional connectivity density (gFCD). We compared these metrics using the human connectome project (HCP) compatible high-resolution (2 mm isotropic, TR = 0.8 s) multiband (MB), and more typical, lower resolution (3.5 mm isotropic, TR = 2.0 s) single-band (SB) resting state functional MRI (rs-fMRI) acquisitions. Furthermore, in order to be more clinically feasible, only rs-fMRI scans that lasted seven minutes were tested. Subjects were scanned twice within a two-week span. We found sensitivity and specificity increased and reproducibility either increased or did not change for the MB compared to the SB acquisitions. The MB scans also showed improved gray matter/white matter contrast compared to the SB scans. The lFCD and gFCD patterns were similar across MB and SB scans and confined predominantly to gray matter. We also observed a strong spatial correlation of FCD between MB and SB scans indicating the two acquisitions provide similar information. These findings indicate high-resolution MB acquisitions improve the quality of FCD data, and seven minute rs-fMRI scan can provide robust FCD measurements.

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

PubMed Central

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

2015-01-01

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

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

PubMed

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

2015-08-01

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

Structural connectivity of the developing human amygdala.

PubMed

Saygin, Zeynep M; Osher, David E; Koldewyn, Kami; Martin, Rebecca E; Finn, Amy; Saxe, Rebecca; Gabrieli, John D E; Sheridan, Margaret

2015-01-01

A large corpus of research suggests that there are changes in the manner and degree to which the amygdala supports cognitive and emotional function across development. One possible basis for these developmental differences could be the maturation of amygdalar connections with the rest of the brain. Recent functional connectivity studies support this conclusion, but the structural connectivity of the developing amygdala and its different nuclei remains largely unstudied. We examined age related changes in the DWI connectivity fingerprints of the amygdala to the rest of the brain in 166 individuals of ages 5-30. We also developed a model to predict age based on individual-subject amygdala connectivity, and identified the connections that were most predictive of age. Finally, we segmented the amygdala into its four main nucleus groups, and examined the developmental changes in connectivity for each nucleus. We observed that with age, amygdalar connectivity becomes increasingly sparse and localized. Age related changes were largely localized to the subregions of the amygdala that are implicated in social inference and contextual memory (the basal and lateral nuclei). The central nucleus' connectivity also showed differences with age but these differences affected fewer target regions than the basal and lateral nuclei. The medial nucleus did not exhibit any age related changes. These findings demonstrate increasing specificity in the connectivity patterns of amygdalar nuclei across age.

Collective motion patterns of swarms with delay coupling: Theory and experiment.

PubMed

Szwaykowska, Klementyna; Schwartz, Ira B; Mier-Y-Teran Romero, Luis; Heckman, Christoffer R; Mox, Dan; Hsieh, M Ani

2016-03-01

The formation of coherent patterns in swarms of interacting self-propelled autonomous agents is a subject of great interest in a wide range of application areas, ranging from engineering and physics to biology. In this paper, we model and experimentally realize a mixed-reality large-scale swarm of delay-coupled agents. The coupling term is modeled as a delayed communication relay of position. Our analyses, assuming agents communicating over an Erdös-Renyi network, demonstrate the existence of stable coherent patterns that can be achieved only with delay coupling and that are robust to decreasing network connectivity and heterogeneity in agent dynamics. We also show how the bifurcation structure for emergence of different patterns changes with heterogeneity in agent acceleration capabilities and limited connectivity in the network as a function of coupling strength and delay. Our results are verified through simulation as well as preliminary experimental results of delay-induced pattern formation in a mixed-reality swarm.

Collective motion patterns of swarms with delay coupling: Theory and experiment

NASA Astrophysics Data System (ADS)

Szwaykowska, Klementyna; Schwartz, Ira B.; Mier-y-Teran Romero, Luis; Heckman, Christoffer R.; Mox, Dan; Hsieh, M. Ani

2016-03-01

The formation of coherent patterns in swarms of interacting self-propelled autonomous agents is a subject of great interest in a wide range of application areas, ranging from engineering and physics to biology. In this paper, we model and experimentally realize a mixed-reality large-scale swarm of delay-coupled agents. The coupling term is modeled as a delayed communication relay of position. Our analyses, assuming agents communicating over an Erdös-Renyi network, demonstrate the existence of stable coherent patterns that can be achieved only with delay coupling and that are robust to decreasing network connectivity and heterogeneity in agent dynamics. We also show how the bifurcation structure for emergence of different patterns changes with heterogeneity in agent acceleration capabilities and limited connectivity in the network as a function of coupling strength and delay. Our results are verified through simulation as well as preliminary experimental results of delay-induced pattern formation in a mixed-reality swarm.

Motor Neurons Tune Premotor Activity in a Vertebrate Central Pattern Generator

PubMed Central

2017-01-01

Central patterns generators (CPGs) are neural circuits that drive rhythmic motor output without sensory feedback. Vertebrate CPGs are generally believed to operate in a top-down manner in which premotor interneurons activate motor neurons that in turn drive muscles. In contrast, the frog (Xenopus laevis) vocal CPG contains a functionally unexplored neuronal projection from the motor nucleus to the premotor nucleus, indicating a recurrent pathway that may contribute to rhythm generation. In this study, we characterized the function of this bottom-up connection. The X. laevis vocal CPG produces a 50–60 Hz “fast trill” song used by males during courtship. We recorded “fictive vocalizations” in the in vitro CPG from the laryngeal nerve while simultaneously recording premotor activity at the population and single-cell level. We show that transecting the motor-to-premotor projection eliminated the characteristic firing rate of premotor neurons. Silencing motor neurons with the intracellular sodium channel blocker QX-314 also disrupted premotor rhythms, as did blockade of nicotinic synapses in the motor nucleus (the putative location of motor neuron-to-interneuron connections). Electrically stimulating the laryngeal nerve elicited primarily IPSPs in premotor neurons that could be blocked by a nicotinic receptor antagonist. Our results indicate that an inhibitory signal, activated by motor neurons, is required for proper CPG function. To our knowledge, these findings represent the first example of a CPG in which precise premotor rhythms are tuned by motor neuron activity. SIGNIFICANCE STATEMENT Central pattern generators (CPGs) are neural circuits that produce rhythmic behaviors. In vertebrates, motor neurons are not commonly known to contribute to CPG function, with the exception of a few spinal circuits where the functional significance of motor neuron feedback is still poorly understood. The frog hindbrain vocal circuit contains a previously unexplored connection from the motor to premotor region. Our results indicate that motor neurons activate this bottom-up connection, and blocking this signal eliminates normal premotor activity. These findings may promote increased awareness of potential involvement of motor neurons in a wider range of CPGs, perhaps clarifying our understanding of network principles underlying motor behaviors in numerous organisms, including humans. PMID:28219984

Influence of White and Gray Matter Connections on Endogenous Human Cortical Oscillations

PubMed Central

Hawasli, Ammar H.; Kim, DoHyun; Ledbetter, Noah M.; Dahiya, Sonika; Barbour, Dennis L.; Leuthardt, Eric C.

2016-01-01

Brain oscillations reflect changes in electrical potentials summated across neuronal populations. Low- and high-frequency rhythms have different modulation patterns. Slower rhythms are spatially broad, while faster rhythms are more local. From this observation, we hypothesized that low- and high-frequency oscillations reflect white- and gray-matter communications, respectively, and synchronization between low-frequency phase with high-frequency amplitude represents a mechanism enabling distributed brain-networks to coordinate local processing. Testing this common understanding, we selectively disrupted white or gray matter connections to human cortex while recording surface field potentials. Counter to our original hypotheses, we found that cortex consists of independent oscillatory-units (IOUs) that maintain their own complex endogenous rhythm structure. IOUs are differentially modulated by white and gray matter connections. White-matter connections maintain topographical anatomic heterogeneity (i.e., separable processing in cortical space) and gray-matter connections segregate cortical synchronization patterns (i.e., separable temporal processing through phase-power coupling). Modulation of distinct oscillatory modules enables the functional diversity necessary for complex processing in the human brain. PMID:27445767

Distribution of Orientation Selectivity in Recurrent Networks of Spiking Neurons with Different Random Topologies

PubMed Central

Sadeh, Sadra; Rotter, Stefan

2014-01-01

Neurons in the primary visual cortex are more or less selective for the orientation of a light bar used for stimulation. A broad distribution of individual grades of orientation selectivity has in fact been reported in all species. A possible reason for emergence of broad distributions is the recurrent network within which the stimulus is being processed. Here we compute the distribution of orientation selectivity in randomly connected model networks that are equipped with different spatial patterns of connectivity. We show that, for a wide variety of connectivity patterns, a linear theory based on firing rates accurately approximates the outcome of direct numerical simulations of networks of spiking neurons. Distance dependent connectivity in networks with a more biologically realistic structure does not compromise our linear analysis, as long as the linearized dynamics, and hence the uniform asynchronous irregular activity state, remain stable. We conclude that linear mechanisms of stimulus processing are indeed responsible for the emergence of orientation selectivity and its distribution in recurrent networks with functionally heterogeneous synaptic connectivity. PMID:25469704

Identifying enhanced cortico-basal ganglia loops associated with prolonged dance training

PubMed Central

Li, Gujing; He, Hui; Huang, Mengting; Zhang, Xingxing; Lu, Jing; Lai, Yongxiu; Luo, Cheng; Yao, Dezhong

2015-01-01

Studies have revealed that prolonged, specialized training combined with higher cognitive conditioning induces enhanced brain alternation. In particular, dancers with long-term dance experience exhibit superior motor control and integration with their sensorimotor networks. However, little is known about the functional connectivity patterns of spontaneous intrinsic activities in the sensorimotor network of dancers. Our study examined the functional connectivity density (FCD) of dancers with a mean period of over 10 years of dance training in contrast with a matched non-dancer group without formal dance training using resting-state fMRI scans. FCD was mapped and analyzed, and the functional connectivity (FC) analyses were then performed based on the difference of FCD. Compared to the non-dancers, the dancers exhibited significantly increased FCD in the precentral gyri, postcentral gyri and bilateral putamen. Furthermore, the results of the FC analysis revealed enhanced connections between the middle cingulate cortex and the bilateral putamen and between the precentral and the postcentral gyri. All findings indicated an enhanced functional integration in the cortico-basal ganglia loops that govern motor control and integration in dancers. These findings might reflect improved sensorimotor function for the dancers consequent to long-term dance training. PMID:26035693

Unsupervised classification of major depression using functional connectivity MRI.

PubMed

Zeng, Ling-Li; Shen, Hui; Liu, Li; Hu, Dewen

2014-04-01

The current diagnosis of psychiatric disorders including major depressive disorder based largely on self-reported symptoms and clinical signs may be prone to patients' behaviors and psychiatrists' bias. This study aims at developing an unsupervised machine learning approach for the accurate identification of major depression based on single resting-state functional magnetic resonance imaging scans in the absence of clinical information. Twenty-four medication-naive patients with major depression and 29 demographically similar healthy individuals underwent resting-state functional magnetic resonance imaging. We first clustered the voxels within the perigenual cingulate cortex into two subregions, a subgenual region and a pregenual region, according to their distinct resting-state functional connectivity patterns and showed that a maximum margin clustering-based unsupervised machine learning approach extracted sufficient information from the subgenual cingulate functional connectivity map to differentiate depressed patients from healthy controls with a group-level clustering consistency of 92.5% and an individual-level classification consistency of 92.5%. It was also revealed that the subgenual cingulate functional connectivity network with the highest discriminative power primarily included the ventrolateral and ventromedial prefrontal cortex, superior temporal gyri and limbic areas, indicating that these connections may play critical roles in the pathophysiology of major depression. The current study suggests that subgenual cingulate functional connectivity network signatures may provide promising objective biomarkers for the diagnosis of major depression and that maximum margin clustering-based unsupervised machine learning approaches may have the potential to inform clinical practice and aid in research on psychiatric disorders. Copyright © 2013 Wiley Periodicals, Inc.

Default mode of brain function in monkeys.

PubMed

Mantini, Dante; Gerits, Annelis; Nelissen, Koen; Durand, Jean-Baptiste; Joly, Olivier; Simone, Luciano; Sawamura, Hiromasa; Wardak, Claire; Orban, Guy A; Buckner, Randy L; Vanduffel, Wim

2011-09-07

Human neuroimaging has revealed a specific network of brain regions-the default-mode network (DMN)-that reduces its activity during goal-directed behavior. So far, evidence for a similar network in monkeys is mainly indirect, since, except for one positron emission tomography study, it is all based on functional connectivity analysis rather than activity increases during passive task states. Here, we tested whether a consistent DMN exists in monkeys using its defining property. We performed a meta-analysis of functional magnetic resonance imaging data collected in 10 awake monkeys to reveal areas in which activity consistently decreases when task demands shift from passive tasks to externally oriented processing. We observed task-related spatially specific deactivations across 15 experiments, implying in the monkey a functional equivalent of the human DMN. We revealed by resting-state connectivity that prefrontal and medial parietal regions, including areas 9/46d and 31, respectively, constitute the DMN core, being functionally connected to all other DMN areas. We also detected two distinct subsystems composed of DMN areas with stronger functional connections between each other. These clusters included areas 24/32, 8b, and TPOC and areas 23, v23, and PGm, respectively. Such a pattern of functional connectivity largely fits, but is not completely consistent with anatomical tract tracing data in monkeys. Also, analysis of afferent and efferent connections between DMN areas suggests a multisynaptic network structure. Like humans, monkeys increase activity during passive epochs in heteromodal and limbic association regions, suggesting that they also default to internal modes of processing when not actively interacting with the environment.

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.

Default Mode of Brain Function in Monkeys

PubMed Central

Mantini, Dante; Gerits, Annelis; Nelissen, Koen; Durand, Jean-Baptiste; Joly, Olivier; Simone, Luciano; Sawamura, Hiromasa; Wardak, Claire; Orban, Guy A.; Buckner, Randy L.; Vanduffel, Wim

2013-01-01

Human neuroimaging has revealed a specific network of brain regions—the default-mode network (DMN)—that reduces its activity during goal-directed behavior. So far, evidence for a similar network in monkeys is mainly indirect, since, except for one positron emission tomography study, it is all based on functional connectivity analysis rather than activity increases during passive task states. Here, we tested whether a consistent DMN exists in monkeys using its defining property. We performed a meta-analysis of functional magnetic resonance imaging data collected in 10 awake monkeys to reveal areas in which activity consistently decreases when task demands shift from passive tasks to externally oriented processing. We observed task-related spatially specific deactivations across 15 experiments, implying in the monkey a functional equivalent of the human DMN. We revealed by resting-state connectivity that prefrontal and medial parietal regions, including areas 9/46d and 31, respectively, constitute the DMN core, being functionally connected to all other DMN areas. We also detected two distinct subsystems composed of DMN areas with stronger functional connections between each other. These clusters included areas 24/32, 8b, and TPOC and areas 23, v23, and PGm, respectively. Such a pattern of functional connectivity largely fits, but is not completely consistent with anatomical tract tracing data in monkeys. Also, analysis of afferent and efferent connections between DMN areas suggests a multisynaptic network structure. Like humans, monkeys increase activity during passive epochs in heteromodal and limbic association regions, suggesting that they also default to internal modes of processing when not actively interacting with the environment. PMID:21900574

Integration and Segregation of Default Mode Network Resting-State Functional Connectivity in Transition-Age Males with High-Functioning Autism Spectrum Disorder: A Proof-of-Concept Study.

PubMed

Joshi, Gagan; Arnold Anteraper, Sheeba; Patil, Kaustubh R; Semwal, Meha; Goldin, Rachel L; Furtak, Stephannie L; Chai, Xiaoqian Jenny; Saygin, Zeynep M; Gabrieli, John D E; Biederman, Joseph; Whitfield-Gabrieli, Susan

2017-11-01

The aim of this study is to assess the resting-state functional connectivity (RsFc) profile of the default mode network (DMN) in transition-age males with autism spectrum disorder (ASD). Resting-state blood oxygen level-dependent functional magnetic resonance imaging data were acquired from adolescent and young adult males with high-functioning ASD (n = 15) and from age-, sex-, and intelligence quotient-matched healthy controls (HCs; n = 16). The DMN was examined by assessing the positive and negative RsFc correlations of an average of the literature-based conceptualized major DMN nodes (medial prefrontal cortex [mPFC], posterior cingulate cortex, bilateral angular, and inferior temporal gyrus regions). RsFc data analysis was performed using a seed-driven approach. ASD was characterized by an altered pattern of RsFc in the DMN. The ASD group exhibited a weaker pattern of intra- and extra-DMN-positive and -negative RsFc correlations, respectively. In ASD, the strength of intra-DMN coupling was significantly reduced with the mPFC and the bilateral angular gyrus regions. In addition, the polarity of the extra-DMN correlation with the right hemispheric task-positive regions of fusiform gyrus and supramarginal gyrus was reversed from typically negative to positive in the ASD group. A wide variability was observed in the presentation of the RsFc profile of the DMN in both HC and ASD groups that revealed a distinct pattern of subgrouping using pattern recognition analyses. These findings imply that the functional architecture profile of the DMN is altered in ASD with weaker than expected integration and segregation of DMN RsFc. Future studies with larger sample sizes are warranted.

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.

Wetland Hydrologic Connectivity to Downstream Waters: A Classification Approach and National Assessment

NASA Astrophysics Data System (ADS)

Leibowitz, S. G.; Hill, R. A.; Weber, M.; Jones, C., Jr.; Rains, M. C.; Creed, I. F.; Christensen, J.

2017-12-01

Connectivity has become a major focus of hydrological and ecological studies. Connectivity enhances fluxes among landscape features, whereas isolation eliminates or reduces such flows. Thus connectivity can be an important characteristic controlling ecosystem services. Hydrologic connectivity is particularly significant, since chemical and biological flows are often associated with water movement. Wetlands have many important functions, and the degree to which they are hydrologically connected influences the effect they have on downstream waters. Wetlands with high connectivity can serve as sources (e.g., net exporters of dissolved organic carbon), while those with low connectivity can function as sinks (e.g., net importers of suspended sediments). We developed a system to classify wetlands based on type, magnitude, and frequency of hydrologic connectivity with downstream waters. We determined type (riparian, non-riparian surface, and non-riparian subsurface) by considering soil and bedrock permeability. For magnitude, we developed indices to represent travel time based on Manning's kinematic and Darcy's equations. We used soil drainage class as an indicator of frequency. We also included an index that assesses relative level of anthropogenic impacts to connectivity (e.g., presence of canals and ditches and impervious surfaces). The classification system was designed to be applied at various spatial scales using available data. The system was applied to 4.7 million wetlands in the conterminous United States, using the National Land Cover Dataset and other nationally available geospatial data, and the resulting maps were assessed for patterns in wetland connectivity. While wetland connectivity was dominated by fast, frequent riparian connections nationally, distributions of connectivity were characteristic for each region. Consideration of these distributions of connectivity should promote better management of watershed functions such as flood control and water quality improvement.

Altered thalamo-cortical resting state functional connectivity in smokers.

PubMed

Wang, Chaoyan; Bai, Jie; Wang, Caihong; von Deneen, Karen M; Yuan, Kai; Cheng, Jingliang

2017-07-13

The thalamus has widespread connections with the prefrontal cortex (PFC) and modulates communication between the striatum and PFC, which is crucial to the neural mechanisms of smoking. However, relatively few studies focused on the thalamic resting state functional connectivity (RSFC) patterns and their association with smoking behaviors in smokers. 24 young male smokers and 24 non-smokers were enrolled in our study. Fagerström Test for Nicotine Dependence (FTND) was used to assess the nicotine dependence level. The bilateral thalamic RSFC patterns were compared between smokers and non-smokers. The relationship between neuroimaging findings and smoking behaviors (FTND and pack-years) were also investigated in smokers. Relative to nonsmokers, smokers showed reduced RSFC strength between the left thalamus and several brain regions, i.e. the right dorsolateral prefrontal cortex (dlPFC), the anterior cingulate cortex (ACC) and the bilateral caudate. In addition, the right thalamus showed reduced RSFC with the right dlPFC as well as the bilateral insula in smokers. Therefore, the findings in the current study revealed the reduced RSFC of the thalamus with the dlPFC, the ACC, the insula and the caudate in smokers, which provided new insights into the roles of the thalamus in nicotine addiction from a function integration perspective. Copyright © 2017 Elsevier B.V. All rights reserved.

Claustrum projections to prefrontal cortex in the capuchin monkey (Cebus apella)

PubMed Central

Reser, David H.; Richardson, Karyn E.; Montibeller, Marina O.; Zhao, Sherry; Chan, Jonathan M. H.; Soares, Juliana G. M.; Chaplin, Tristan A.; Gattass, Ricardo; Rosa, Marcello G. P.

2014-01-01

We examined the pattern of retrograde tracer distribution in the claustrum following intracortical injections into the frontal pole (area 10), and in dorsal (area 9), and ventral lateral (area 12) regions of the rostral prefrontal cortex in the tufted capuchin monkey (Cebus apella). The resulting pattern of labeled cells was assessed in relation to the three-dimensional geometry of the claustrum, as well as recent reports of claustrum-prefrontal connections in other primates. Claustrum-prefrontal projections were extensive, and largely concentrated in the ventral half of the claustrum, especially in the rostral 2/3 of the nucleus. Our data are consistent with a topographic arrangement of claustrum-cortical connections in which prefrontal and association cortices receive connections largely from the rostral and medial claustrum. Comparative aspects of claustrum-prefrontal topography across primate species and the implications of claustrum connectivity for understanding of cortical functional networks are explored, and we hypothesize that the claustrum may play a role in controlling or switching between resting state and task-associated cortical networks. PMID:25071475

Deep neural network with weight sparsity control and pre-training extracts hierarchical features and enhances classification performance: Evidence from whole-brain resting-state functional connectivity patterns of schizophrenia

PubMed Central

Kim, Junghoe; Calhoun, Vince D.; Shim, Eunsoo; Lee, Jong-Hwan

2015-01-01

Functional connectivity (FC) patterns obtained from resting-state functional magnetic resonance imaging data are commonly employed to study neuropsychiatric conditions by using pattern classifiers such as the support vector machine (SVM). Meanwhile, a deep neural network (DNN) with multiple hidden layers has shown its ability to systematically extract lower-to-higher level information of image and speech data from lower-to-higher hidden layers, markedly enhancing classification accuracy. The objective of this study was to adopt the DNN for whole-brain resting-state FC pattern classification of schizophrenia (SZ) patients vs. healthy controls (HCs) and identification of aberrant FC patterns associated with SZ. We hypothesized that the lower-to-higher level features learned via the DNN would significantly enhance the classification accuracy, and proposed an adaptive learning algorithm to explicitly control the weight sparsity in each hidden layer via L1-norm regularization. Furthermore, the weights were initialized via stacked autoencoder based pre-training to further improve the classification performance. Classification accuracy was systematically evaluated as a function of (1) the number of hidden layers/nodes, (2) the use of L1-norm regularization, (3) the use of the pre-training, (4) the use of framewise displacement (FD) removal, and (5) the use of anatomical/functional parcellation. Using FC patterns from anatomically parcellated regions without FD removal, an error rate of 14.2% was achieved by employing three hidden layers and 50 hidden nodes with both L1-norm regularization and pre-training, which was substantially lower than the error rate from the SVM (22.3%). Moreover, the trained DNN weights (i.e., the learned features) were found to represent the hierarchical organization of aberrant FC patterns in SZ compared with HC. Specifically, pairs of nodes extracted from the lower hidden layer represented sparse FC patterns implicated in SZ, which was quantified by using kurtosis/modularity measures and features from the higher hidden layer showed holistic/global FC patterns differentiating SZ from HC. Our proposed schemes and reported findings attained by using the DNN classifier and whole-brain FC data suggest that such approaches show improved ability to learn hidden patterns in brain imaging data, which may be useful for developing diagnostic tools for SZ and other neuropsychiatric disorders and identifying associated aberrant FC patterns. PMID:25987366

FROM SELECTIVE VULNERABILITY TO CONNECTIVITY: INSIGHTS FROM NEWBORN BRAIN IMAGING

PubMed Central

Miller, Steven P.; Ferriero, Donna M

2009-01-01

The ability to image the newborn brain during development has provided new information regarding the effects of injury on brain development at different vulnerable time periods. Studies in animal models of brain injury correlate beautifully with what is now observed in the human newborn. We now know that injury at term results in a predilection for gray matter injury while injury in the premature brain results in a white matter predominant pattern although recent evidence suggests a blurring of this distinction. These injuries affect how the brain matures subsequently and again, imaging has led to new insights that allow us to match function and structure. This review will focus on these patterns of injury that are so critically determined by age at insult. In addition, this review will highlight how the brain responds to these insults with changes in connectivity that have profound functional consequences. PMID:19712981

Development of thalamocortical connectivity during infancy and its cognitive correlations.

PubMed

Alcauter, Sarael; Lin, Weili; Smith, J Keith; Short, Sarah J; Goldman, Barbara D; Reznick, J Steven; Gilmore, John H; Gao, Wei

2014-07-02

Although commonly viewed as a sensory information relay center, the thalamus has been increasingly recognized as an essential node in various higher-order cognitive circuits, and the underlying thalamocortical interaction mechanism has attracted increasing scientific interest. However, the development of thalamocortical connections and how such development relates to cognitive processes during the earliest stages of life remain largely unknown. Leveraging a large human pediatric sample (N = 143) with longitudinal resting-state fMRI scans and cognitive data collected during the first 2 years of life, we aimed to characterize the age-dependent development of thalamocortical connectivity patterns by examining the functional relationship between the thalamus and nine cortical functional networks and determine the correlation between thalamocortical connectivity and cognitive performance at ages 1 and 2 years. Our results revealed that the thalamus-sensorimotor and thalamus-salience connectivity networks were already present in neonates, whereas the thalamus-medial visual and thalamus-default mode network connectivity emerged later, at 1 year of age. More importantly, brain-behavior analyses based on the Mullen Early Learning Composite Score and visual-spatial working memory performance measured at 1 and 2 years of age highlighted significant correlations with the thalamus-salience network connectivity. These results provide new insights into the understudied early functional brain development process and shed light on the behavioral importance of the emerging thalamocortical connectivity during infancy. Copyright © 2014 the authors 0270-6474/14/349067-09$15.00/0.

Identifying HIV associated neurocognitive disorder using large-scale Granger causality analysis on resting-state functional MRI

NASA Astrophysics Data System (ADS)

DSouza, Adora M.; Abidin, Anas Z.; Leistritz, Lutz; Wismüller, Axel

2017-02-01

We investigate the applicability of large-scale Granger Causality (lsGC) for extracting a measure of multivariate information flow between pairs of regional brain activities from resting-state functional MRI (fMRI) and test the effectiveness of these measures for predicting a disease state. Such pairwise multivariate measures of interaction provide high-dimensional representations of connectivity profiles for each subject and are used in a machine learning task to distinguish between healthy controls and individuals presenting with symptoms of HIV Associated Neurocognitive Disorder (HAND). Cognitive impairment in several domains can occur as a result of HIV infection of the central nervous system. The current paradigm for assessing such impairment is through neuropsychological testing. With fMRI data analysis, we aim at non-invasively capturing differences in brain connectivity patterns between healthy subjects and subjects presenting with symptoms of HAND. To classify the extracted interaction patterns among brain regions, we use a prototype-based learning algorithm called Generalized Matrix Learning Vector Quantization (GMLVQ). Our approach to characterize connectivity using lsGC followed by GMLVQ for subsequent classification yields good prediction results with an accuracy of 87% and an area under the ROC curve (AUC) of up to 0.90. We obtain a statistically significant improvement (p<0.01) over a conventional Granger causality approach (accuracy = 0.76, AUC = 0.74). High accuracy and AUC values using our multivariate method to connectivity analysis suggests that our approach is able to better capture changes in interaction patterns between different brain regions when compared to conventional Granger causality analysis known from the literature.

Limbic hyperconnectivity in the vegetative state.

PubMed

Di Perri, Carol; Bastianello, Stefano; Bartsch, Andreas J; Pistarini, Caterina; Maggioni, Giorgio; Magrassi, Lorenzo; Imberti, Roberto; Pichiecchio, Anna; Vitali, Paolo; Laureys, Steven; Di Salle, Francesco

2013-10-15

To investigate functional connectivity between the default mode network (DMN) and other networks in disorders of consciousness. We analyzed MRI data from 11 patients in a vegetative state and 7 patients in a minimally conscious state along with age- and sex-matched healthy control subjects. MRI data analysis included nonlinear spatial normalization to compensate for disease-related anatomical distortions. We studied brain connectivity data from resting-state MRI temporal series, combining noninferential (independent component analysis) and inferential (seed-based general linear model) methods. In DMN hypoconnectivity conditions, a patient's DMN functional connectivity shifts and paradoxically increases in limbic structures, including the orbitofrontal cortex, insula, hypothalamus, and the ventral tegmental area. Concurrently with DMN hypoconnectivity, we report limbic hyperconnectivity in patients in vegetative and minimally conscious states. This hyperconnectivity may reflect the persistent engagement of residual neural activity in self-reinforcing neural loops, which, in turn, could disrupt normal patterns of connectivity.

Cardiovascular functioning, personality, and the social world: the domain of hierarchical power.

PubMed

Newton, Tamara L

2009-02-01

The present paper considers connections between cardiovascular functioning (i.e., disease status and acute stress responses) and social dominance, and its counterpart, social submissiveness, both of which are part of the broader domain of "hierarchical power" [Bugental, D.B., 2000. Acquisition of the algorithms of social life: a domain-based approach. Psychological Bulletin 126, 187-219]. Empirical research on connections between dominance/submissiveness and cardiovascular morbidity and mortality in humans is reviewed, as is research on dominance/submissiveness and cardiovascular reactivity to, and recovery from, acute stressors. Three general conclusions are established. First, in both cross-sectional and longitudinal investigations, trait and behavioral indicators of dominance have been positively associated with cardiovascular disease severity, incidence, and progression, whereas preliminary evidence from two studies suggests that trait submissiveness may protect against poorer disease outcomes. Second, among men and women, trait dominance is associated with reactivity to and recovery from acute stressors, particularly social challenges. Third, linkages between dominance/submissiveness and cardiovascular functioning, especially cardiovascular reactivity, are characterized by gender-specific patterning, and this patterning emerges as a function of social context. Implications for the next generation of research concerning social dominance, gender, and cardiovascular functioning are discussed.

Altered Functional Connectivity of Cognitive-Related Cerebellar Subregions in Alzheimer’s Disease

PubMed Central

Zheng, Weimin; Liu, Xingyun; Song, Haiqing; Li, Kuncheng; Wang, Zhiqun

2017-01-01

Alzheimer’s disease (AD) is the most common cause of dementia. Previous studies have found disrupted resting state functional connectivities (rsFCs) in various brain networks in the AD patients. However, few studies have focused on the rsFCs of the cerebellum and its sub-regions in the AD patients. In this study, we collected resting-state functional magnetic resonance imaging (rs-fMRI) data including 32 AD patients and 38 healthy controls (HCs). We selected two cognitive-related subregions of the cerebellum as seed region and mapped the whole-brain rsFCs for each subregion. We identified several distinct rsFC patterns of the two cognitive-related cerebellar subregions: default-mode network (DMN), frontoparietal network (FPN), visual network (VN) and sensorimotor network (SMN). Compared with the controls, the AD patients showed disrupted rsFCs in several different networks (DMN, VN and SMN), predicting the impairment of the functional integration in the cerebellum. Notably, these abnormal rsFCs of the two cerebellar subregions were closely associated with cognitive performance. Collectively, we demonstrated the distinct rsFCs patterns of cerebellar sub-regions with various functional networks, which were differentially impaired in the AD patients. PMID:28559843

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

Constrained synaptic connectivity in functional mammalian neuronal networks grown on patterned surfaces.

PubMed

Wyart, Claire; Ybert, Christophe; Bourdieu, Laurent; Herr, Catherine; Prinz, Christelle; Chatenay, Didier

2002-06-30

The use of ordered neuronal networks in vitro is a promising approach to study the development and the activity of small neuronal assemblies. However, in previous attempts, sufficient growth control and physiological maturation of neurons could not be achieved. Here we describe an original protocol in which polylysine patterns confine the adhesion of cellular bodies to prescribed spots and the neuritic growth to thin lines. Hippocampal neurons in these networks are maintained healthy in serum free medium up to 5 weeks in vitro. Electrophysiology and immunochemistry show that neurons exhibit mature excitatory and inhibitory synapses and calcium imaging reveals spontaneous activity of neurons in isolated networks. We demonstrate that neurons in these geometrical networks form functional synapses preferentially to their first neighbors. We have, therefore, established a simple and robust protocol to constrain both the location of neuronal cell bodies and their pattern of connectivity. Moreover, the long term maintenance of the geometry and the physiology of the networks raises the possibility of new applications for systematic screening of pharmacological agents and for electronic to neuron devices.

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

NASA Astrophysics Data System (ADS)

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

2014-03-01

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

[Landscape connectivity of waterbody network in the new reclamation region of Lianyungang based on effective distance model].

PubMed

Qiao, Fu-Zhen; Zheng, Zhong-Ming; Li, Jia-Lin; Zheng, Wen-Bing

2014-08-01

Landscape connectivity is an important indicator to measure effectiveness of landscape ecological services. Waterbody connectivity in Lianyun New City, the new reclamation region of Lianyungang, was investigated based on GIS technology and effective distance model. The results showed that the total connectivity of waterbodies was poor in Lanyun New City. Connectivity of patches was related to characteristics of ecological process, ecological services value and spatial arrangement. The higher the ecosystem services value of patches was, the greater its contribution to the overall water landscape connectivity was. Some patches with long strip structure played a key role to improve the landscape connectivity. By classifying the importance of connectivity and functional groups of waterbody patches, planning of waterbodies in Lianyun New City conformed to the theory of non-substitutable pattern developed by Forman. Waterbody patches with corresponding functions should be considered with priority when planning and building a new city. The present study demonstrated that connectivity of patches should be an important factor to be considered in ecological landscape planning. Construction of ecological corridors should not only take the number of ecological landscapes into consideration, but also pay attention to spatial arrangement of landscapes in order to improve the overall landscape connectivity.

The cerebellum and cognition: evidence from functional imaging studies.

PubMed

Stoodley, Catherine J

2012-06-01

Evidence for a role of the human cerebellum in cognitive functions comes from anatomical, clinical and neuroimaging data. Functional neuroimaging reveals cerebellar activation during a variety of cognitive tasks, including language, visual-spatial, executive, and working memory processes. It is important to note that overt movement is not a prerequisite for cerebellar activation: the cerebellum is engaged during conditions which either control for motor output or do not involve motor responses. Resting-state functional connectivity data reveal that, in addition to networks underlying motor control, the cerebellum is part of "cognitive" networks with prefrontal and parietal association cortices. Consistent with these findings, regional differences in activation patterns within the cerebellum are evident depending on the task demands, suggesting that the cerebellum can be broadly divided into functional regions based on the patterns of anatomical connectivity between different regions of the cerebellum and sensorimotor and association areas of the cerebral cortex. However, the distinct contribution of the cerebellum to cognitive tasks is not clear. Here, the functional neuroimaging evidence for cerebellar involvement in cognitive functions is reviewed and related to hypotheses as to why the cerebellum is active during such tasks. Identifying the precise role of the cerebellum in cognition-as well as the mechanism by which the cerebellum modulates performance during a wide range of tasks-remains a challenge for future investigations.

Electroconvulsive therapy-induced brain functional connectivity predicts therapeutic efficacy in patients with schizophrenia: a multivariate pattern recognition study.

PubMed

Li, Peng; Jing, Ri-Xing; Zhao, Rong-Jiang; Ding, Zeng-Bo; Shi, Le; Sun, Hong-Qiang; Lin, Xiao; Fan, Teng-Teng; Dong, Wen-Tian; Fan, Yong; Lu, Lin

2017-05-11

Previous studies suggested that electroconvulsive therapy can influence regional metabolism and dopamine signaling, thereby alleviating symptoms of schizophrenia. It remains unclear what patients may benefit more from the treatment. The present study sought to identify biomarkers that predict the electroconvulsive therapy response in individual patients. Thirty-four schizophrenia patients and 34 controls were included in this study. Patients were scanned prior to treatment and after 6 weeks of treatment with antipsychotics only (n = 16) or a combination of antipsychotics and electroconvulsive therapy (n = 13). Subject-specific intrinsic connectivity networks were computed for each subject using a group information-guided independent component analysis technique. Classifiers were built to distinguish patients from controls and quantify brain states based on intrinsic connectivity networks. A general linear model was built on the classification scores of first scan (referred to as baseline classification scores) to predict treatment response. Classifiers built on the default mode network, the temporal lobe network, the language network, the corticostriatal network, the frontal-parietal network, and the cerebellum achieved a cross-validated classification accuracy of 83.82%, with specificity of 91.18% and sensitivity of 76.47%. After the electroconvulsive therapy, psychosis symptoms of the patients were relieved and classification scores of the patients were decreased. Moreover, the baseline classification scores were predictive for the treatment outcome. Schizophrenia patients exhibited functional deviations in multiple intrinsic connectivity networks which were able to distinguish patients from healthy controls at an individual level. Patients with lower classification scores prior to treatment had better treatment outcome, indicating that the baseline classification scores before treatment is a good predictor for treatment outcome. CONNECTIVITY NETWORKS REVEAL GOOD CANDIDATES FOR BRAIN STIMULATION: Connectivity patterns in the brain may help identify patients with schizophrenia most likely to benefit from electroconvulsive therapy. A team led by Lin Lu from Peking University, China, and Yong Fan from the University of Pennsylvania, USA, took functional magnetic resonance imaging (MRI) scans of 34 people with schizophrenia and 34 control individuals without mental illness. Those with schizophrenia were scanned before and after treatment; some received antipsychotics alone, others received medication plus electroconvulsive therapy. The researchers created organizational brain maps known as "intrinsic connectivity networks" for each individual, and showed that the neuroimaging pattern could discriminate between people with and without schizophrenia. For the schizophrenia patients, the connectivity networks taken prior to treatment also helped predict who would benefit from the brain-stimulation procedure. Such a biomarker could prove a useful diagnostic tool for clinicians.

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.

Desynchronization and Plasticity of Striato-frontal Connectivity in Major Depressive Disorder.

PubMed

Leaver, Amber M; Espinoza, Randall; Joshi, Shantanu H; Vasavada, Megha; Njau, Stephanie; Woods, Roger P; Narr, Katherine L

2016-10-17

Major depressive disorder (MDD) is associated with dysfunctional corticolimbic networks, making functional connectivity studies integral for understanding the mechanisms underlying MDD pathophysiology and treatment. Resting-state functional connectivity (RSFC) studies analyze patterns of temporally coherent intrinsic brain activity in "resting-state networks" (RSNs). The default-mode network (DMN) has been of particular interest to depression research; however, a single RSN is unlikely to capture MDD pathophysiology in its entirety, and the DMN itself can be characterized by multiple RSNs. This, coupled with conflicting previous results, underscores the need for further research. Here, we measured RSFC in MDD by targeting RSNs overlapping with corticolimbic regions and further determined whether altered patterns of RSFC were restored with electroconvulsive therapy (ECT). MDD patients exhibited hyperconnectivity between ventral striatum (VS) and the ventral default-mode network (vDMN), while simultaneously demonstrating hypoconnectivity with the anterior DMN (aDMN). ECT influenced this pattern: VS-vDMN hyperconnectivity was significantly reduced while VS-aDMN hypoconnectivity only modestly improved. RSFC between the salience RSN and dorsomedial prefrontal cortex was also reduced in MDD, but was not affected by ECT. Taken together, our results support a model of ventral/dorsal imbalance in MDD and further suggest that the VS is a key structure contributing to this desynchronization. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

A Brain Network Processing the Age of Faces

PubMed Central

Homola, György A.; Jbabdi, Saad; Beckmann, Christian F.; Bartsch, Andreas J.

2012-01-01

Age is one of the most salient aspects in faces and of fundamental cognitive and social relevance. Although face processing has been studied extensively, brain regions responsive to age have yet to be localized. Using evocative face morphs and fMRI, we segregate two areas extending beyond the previously established face-sensitive core network, centered on the inferior temporal sulci and angular gyri bilaterally, both of which process changes of facial age. By means of probabilistic tractography, we compare their patterns of functional activation and structural connectivity. The ventral portion of Wernicke's understudied perpendicular association fasciculus is shown to interconnect the two areas, and activation within these clusters is related to the probability of fiber connectivity between them. In addition, post-hoc age-rating competence is found to be associated with high response magnitudes in the left angular gyrus. Our results provide the first evidence that facial age has a distinct representation pattern in the posterior human brain. We propose that particular face-sensitive nodes interact with additional object-unselective quantification modules to obtain individual estimates of facial age. This brain network processing the age of faces differs from the cortical areas that have previously been linked to less developmental but instantly changeable face aspects. Our probabilistic method of associating activations with connectivity patterns reveals an exemplary link that can be used to further study, assess and quantify structure-function relationships. PMID:23185334

Chromatin interaction networks revealed unique connectivity patterns of broad H3K4me3 domains and super enhancers in 3D chromatin.

PubMed

Thibodeau, Asa; Márquez, Eladio J; Shin, Dong-Guk; Vera-Licona, Paola; Ucar, Duygu

2017-10-31

Broad domain promoters and super enhancers are regulatory elements that govern cell-specific functions and harbor disease-associated sequence variants. These elements are characterized by distinct epigenomic profiles, such as expanded deposition of histone marks H3K27ac for super enhancers and H3K4me3 for broad domains, however little is known about how they interact with each other and the rest of the genome in three-dimensional chromatin space. Using network theory methods, we studied chromatin interactions between broad domains and super enhancers in three ENCODE cell lines (K562, MCF7, GM12878) obtained via ChIA-PET, Hi-C, and Hi-CHIP assays. In these networks, broad domains and super enhancers interact more frequently with each other compared to their typical counterparts. Network measures and graphlets revealed distinct connectivity patterns associated with these regulatory elements that are robust across cell types and alternative assays. Machine learning models showed that these connectivity patterns could effectively discriminate broad domains from typical promoters and super enhancers from typical enhancers. Finally, targets of broad domains in these networks were enriched in disease-causing SNPs of cognate cell types. Taken together these results suggest a robust and unique organization of the chromatin around broad domains and super enhancers: loci critical for pathologies and cell-specific functions.

Alterations of resting state networks and structural connectivity in relation to the prefrontal and anterior cingulate cortices in late prematurity.

PubMed

Degnan, Andrew J; Wisnowski, Jessica L; Choi, SoYoung; Ceschin, Rafael; Bhushan, Chitresh; Leahy, Richard M; Corby, Patricia; Schmithorst, Vincent J; Panigrahy, Ashok

2015-01-07

Late preterm birth is increasingly recognized as a risk factor for cognitive and social deficits. The prefrontal cortex is particularly vulnerable to injury in late prematurity because of its protracted development and extensive cortical connections. Our study examined children born late preterm without access to advanced postnatal care to assess structural and functional connectivity related to the prefrontal cortex. Thirty-eight preadolescents [19 born late preterm (34-36 /7 weeks gestational age) and 19 at term] were recruited from a developing community in Brazil. Participants underwent neuropsychological testing. Individuals underwent three-dimensional T1-weighted, diffusion-weighted, and resting state functional MRI. Probabilistic tractography and functional connectivity analyses were carried out using unilateral seeds combining the medial prefrontal cortex and the anterior cingulate cortex. Late preterm children showed increased functional connectivity within regions of the default mode, salience, and central-executive networks from both right and left frontal cortex seeds. Decreased functional connectivity was observed within the right parahippocampal region from left frontal seeding. Probabilistic tractography showed a pattern of decreased streamlines in frontal white matter pathways and the corpus callosum, but also increased streamlines in the left orbitofrontal white matter and the right frontal white matter when seeded from the right. Late preterm children and term control children scored similarly on neuropsychological testing. Prefrontal cortical connectivity is altered in late prematurity, with hyperconnectivity observed in key resting state networks in the absence of neuropsychological deficits. Abnormal structural connectivity indicated by probabilistic tractography suggests subtle changes in white matter development, implying disruption of normal maturation during the late gestational period.

Altered amygdalar resting-state connectivity in depression is explained by both genes and environment.

PubMed

Córdova-Palomera, Aldo; Tornador, Cristian; Falcón, Carles; Bargalló, Nuria; Nenadic, Igor; Deco, Gustavo; Fañanás, Lourdes

2015-10-01

Recent findings indicate that alterations of the amygdalar resting-state fMRI connectivity play an important role in the etiology of depression. While both depression and resting-state brain activity are shaped by genes and environment, the relative contribution of genetic and environmental factors mediating the relationship between amygdalar resting-state connectivity and depression remain largely unexplored. Likewise, novel neuroimaging research indicates that different mathematical representations of resting-state fMRI activity patterns are able to embed distinct information relevant to brain health and disease. The present study analyzed the influence of genes and environment on amygdalar resting-state fMRI connectivity, in relation to depression risk. High-resolution resting-state fMRI scans were analyzed to estimate functional connectivity patterns in a sample of 48 twins (24 monozygotic pairs) informative for depressive psychopathology (6 concordant, 8 discordant and 10 healthy control pairs). A graph-theoretical framework was employed to construct brain networks using two methods: (i) the conventional approach of filtered BOLD fMRI time-series and (ii) analytic components of this fMRI activity. Results using both methods indicate that depression risk is increased by environmental factors altering amygdalar connectivity. When analyzing the analytic components of the BOLD fMRI time-series, genetic factors altering the amygdala neural activity at rest show an important contribution to depression risk. Overall, these findings show that both genes and environment modify different patterns the amygdala resting-state connectivity to increase depression risk. The genetic relationship between amygdalar connectivity and depression may be better elicited by examining analytic components of the brain resting-state BOLD fMRI signals. © 2015 Wiley Periodicals, Inc.

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.

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

PubMed

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

2013-05-01

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

Nanocapillary Atmospheric Pressure Plasma Jet: A Tool for Ultrafine Maskless Surface Modification at Atmospheric Pressure.

PubMed

Motrescu, Iuliana; Nagatsu, Masaaki

2016-05-18

With respect to microsized surface functionalization techniques we proposed the use of a maskless, versatile, simple tool, represented by a nano- or microcapillary atmospheric pressure plasma jet for producing microsized controlled etching, chemical vapor deposition, and chemical modification patterns on polymeric surfaces. In this work we show the possibility of size-controlled surface amination, and we discuss it as a function of different processing parameters. Moreover, we prove the successful connection of labeled sugar chains on the functionalized microscale patterns, indicating the possibility to use ultrafine capillary atmospheric pressure plasma jets as versatile tools for biosensing, tissue engineering, and related biomedical applications.

Deregulated expression of connective tissue growth factor (CTGF/CCN2) is linked to poor outcome in human cancer.

PubMed

Wells, Julia E; Howlett, Meegan; Cole, Catherine H; Kees, Ursula R

2015-08-01

Connective tissue growth factor (CTGF/CCN2) has long been associated with human cancers. The role it plays in these neoplasms is diverse and tumour specific. Recurring patterns in clinical outcome, histological desmoplasia and mechanisms of action have been found. When CTGF is overexpressed compared to low-expressing normal tissue or is underexpressed compared to high-expressing normal tissue, the functional outcome favours tumour survival and disease progression. CTGF acts by altering proliferation, drug resistance, angiogenesis, adhesion and migration contributing to metastasis. The pattern of CTGF expression and tumour response helps to clarify the role of this matricellular protein across a multitude of human cancers. © 2014 UICC.

Interaction of language, auditory and memory brain networks in auditory verbal hallucinations.

PubMed

Ćurčić-Blake, Branislava; Ford, Judith M; Hubl, Daniela; Orlov, Natasza D; Sommer, Iris E; Waters, Flavie; Allen, Paul; Jardri, Renaud; Woodruff, Peter W; David, Olivier; Mulert, Christoph; Woodward, Todd S; Aleman, André

2017-01-01

Auditory verbal hallucinations (AVH) occur in psychotic disorders, but also as a symptom of other conditions and even in healthy people. Several current theories on the origin of AVH converge, with neuroimaging studies suggesting that the language, auditory and memory/limbic networks are of particular relevance. However, reconciliation of these theories with experimental evidence is missing. We review 50 studies investigating functional (EEG and fMRI) and anatomic (diffusion tensor imaging) connectivity in these networks, and explore the evidence supporting abnormal connectivity in these networks associated with AVH. We distinguish between functional connectivity during an actual hallucination experience (symptom capture) and functional connectivity during either the resting state or a task comparing individuals who hallucinate with those who do not (symptom association studies). Symptom capture studies clearly reveal a pattern of increased coupling among the auditory, language and striatal regions. Anatomical and symptom association functional studies suggest that the interhemispheric connectivity between posterior auditory regions may depend on the phase of illness, with increases in non-psychotic individuals and first episode patients and decreases in chronic patients. Leading hypotheses involving concepts as unstable memories, source monitoring, top-down attention, and hybrid models of hallucinations are supported in part by the published connectivity data, although several caveats and inconsistencies remain. Specifically, possible changes in fronto-temporal connectivity are still under debate. Precise hypotheses concerning the directionality of connections deduced from current theoretical approaches should be tested using experimental approaches that allow for discrimination of competing hypotheses. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

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.

Normalization of Intrinsic Neural Circuits Governing Tourette's Syndrome Using Cranial Electrotherapy Stimulation.

PubMed

Qiao, Jianping; Weng, Shenhong; Wang, Pengwei; Long, Jun; Wang, Zhishun

2015-05-01

The aim of this study was to investigate the normalization of the intrinsic functional activity and connectivity of TS adolescents before and after the cranial electrotherapy stimulation (CES) with alpha stim device. We performed resting-state functional magnetic resonance imaging on eight adolescents before and after CES with mean age of about nine-years old who had Tourette's syndrome with moderate to severe tics symptom. Independent component analysis (ICA) with hierarchical partner matching method was used to examine the functional connectivity between regions within cortico-striato-thalamo-cortical (CSTC) circuit. Granger causality was used to investigate effective connectivity among these regions detected by ICA. We then performed pattern classification on independent components with significant group differences that served as endophenotype markers to distinguish the adolescents between TS and the normalized ones after CES. Results showed that TS adolescents after CES treatment had stronger functional activity and connectivity in anterior cingulate cortex (ACC), caudate and posterior cingulate cortex while had weaker activity in supplementary motor area within the motor pathway compared with TS before CES. The results suggest that the functional activity and connectivity in motor pathway was suppressed while activities in the control portions within CSTC loop including ACC and caudate were increased in TS adolescents after CES compared with adolescents before CES. The normalization of the balance between motor and control portions of the CSTC circuit may result in the recovery of TS adolescents.

The role of the right temporoparietal junction in attention and social interaction as revealed by ALE meta-analysis

PubMed Central

Rottschy, C.; Oberwelland, E.; Bzdok, D.; Fox, P. T.; Eickhoff, S. B.; Fink, G. R.; Konrad, K.

2016-01-01

The right temporoparietal junction (rTPJ) is frequently associated with different capacities that to shift attention to unexpected stimuli (reorienting of attention) and to understand others’ (false) mental state [theory of mind (ToM), typically represented by false belief tasks]. Competing hypotheses either suggest the rTPJ representing a unitary region involved in separate cognitive functions or consisting of subregions subserving distinct processes. We conducted activation likelihood estimation (ALE) meta-analyses to test these hypotheses. A conjunction analysis across ALE meta-analyses delineating regions consistently recruited by reorienting of attention and false belief studies revealed the anterior rTPJ, suggesting an overarching role of this specific region. Moreover, the anatomical difference analysis unravelled the posterior rTPJ as higher converging in false belief compared with reorienting of attention tasks. This supports the concept of an exclusive role of the posterior rTPJ in the social domain. These results were complemented by meta-analytic connectivity mapping (MACM) and resting-state functional connectivity (RSFC) analysis to investigate whole-brain connectivity patterns in task-constrained and task-free brain states. This allowed for detailing the functional separation of the anterior and posterior rTPJ. The combination of MACM and RSFC mapping showed that the posterior rTPJ has connectivity patterns with typical ToM regions, whereas the anterior part of rTPJ co-activates with the attentional network. Taken together, our data suggest that rTPJ contains two functionally fractionated subregions: while posterior rTPJ seems exclusively involved in the social domain, anterior rTPJ is involved in both, attention and ToM, conceivably indicating an attentional shifting role of this region. PMID:24915964

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.

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.

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.

Rethinking the role of the rTPJ in attention and social cognition in light of the opposing domains hypothesis: findings from an ALE-based meta-analysis and resting-state functional connectivity

PubMed Central

Kubit, Benjamin; Jack, Anthony I.

2013-01-01

The right temporo-parietal junction (rTPJ) has been associated with two apparently disparate functional roles: in attention and in social cognition. According to one account, the rTPJ initiates a “circuit-breaking” signal that interrupts ongoing attentional processes, effectively reorienting attention. It is argued this primary function of the rTPJ has been extended beyond attention, through a process of evolutionarily cooption, to play a role in social cognition. We propose an alternative account, according to which the capacity for social cognition depends on a network which is both distinct from and in tension with brain areas involved in focused attention and target detection: the default mode network (DMN). Theory characterizing the rTPJ based on the area's purported role in reorienting may be falsely guided by the co-occurrence of two distinct effects in contiguous regions: activation of the supramarginal gyrus (SMG), associated with its functional role in target detection; and the transient release, during spatial reorienting, of suppression of the angular gyrus (AG) associated with focused attention. Findings based on meta-analysis and resting functional connectivity are presented which support this alternative account. We find distinct regions, possessing anti-correlated patterns of resting connectivity, associated with social reasoning (AG) and target detection (SMG) at the rTPJ. The locus for reorienting was spatially intermediate between the AG and SMG and showed a pattern of connectivity with similarities to social reasoning and target detection seeds. These findings highlight a general methodological concern for brain imaging. Given evidence that certain tasks not only activate some areas but also suppress activity in other areas, it is suggested that researchers need to distinguish two distinct putative mechanisms, either of which may produce an increase in activity in a brain area: functional engagement in the task vs. release of suppression. PMID:23847497

Patterned Arrays of Functional Lateral Heterostructures via Sequential Template-Directed Printing.

PubMed

Li, Yifan; Su, Meng; Li, Zheng; Huang, Zhandong; Li, Fengyu; Pan, Qi; Ren, Wanjie; Hu, Xiaotian; Song, Yanlin

2018-04-30

The precise integration of microscale dots and lines with controllable interfacing connections is highly important for the fabrication of functional devices. To date, the solution-processible methods are used to fabricate the heterogeneous micropatterns for different materials. However, for increasingly miniaturized and multifunctional devices, it is extremely challenging to engineer the uncertain kinetics of a solution on the microstructures surfaces, resulting in uncontrollable interface connections and poor device performance. Here, a sequential template-directed printing process is demonstrated for the fabrication of arrayed microdots connected by microwires through the regulation of the Rayleigh-Taylor instability of material solution or suspension. Flexibility in the control of fluidic behaviors can realize precise interface connection between the micropatterns, including the microwires traversing, overlapping or connecting the microdots. Moreover, various morphologies such as circular, rhombic, or star-shaped microdots as well as straight, broken or curved microwires can be achieved. The lateral heterostructure printed with two different quantum dots displays bright dichromatic photoluminescence. The ammonia gas sensor printed by polyaniline and silver nanoparticles exhibits a rapid response time. This strategy can construct heterostructures in a facile manner by eliminating the uncertainty of the multimaterials interface connection, which will be promising for the development of novel lateral functional devices. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Molecular, Cellular and Functional Events in Axonal Sprouting after Stroke

PubMed Central

Kathirvelu, Balachander; Schweppe, Catherine A; Nie, Esther H

2016-01-01

Stroke is the leading cause of adult disability. Yet there is a limited degree of recovery in this disease. One of the mechanisms of recovery is the formation of new connections in the brain and spinal cord after stroke: post-stroke axonal sprouting. Studies indicate that post-stroke axonal sprouting occurs in mice, rats, primates and humans. Inducing post-stroke axonal sprouting in specific connections enhances recovery; blocking axonal sprouting impairs recovery. Behavioral activity patterns after stroke modify the axonal sprouting response. A unique regenerative molecular program mediates this aspect of tissue repair in the CNS. The types of connections that are formed after stroke indicate three patterns of axonal sprouting after stroke: Reactive, Reparative and Unbounded Axonal Sprouting. These differ in mechanism, location, relationship to behavioral recovery and, importantly, in their prospect for therapeutic manipulation to enhance tissue repair. PMID:26874223

Shared atypical default mode and salience network functional connectivity between autism and schizophrenia.

PubMed

Chen, Heng; Uddin, Lucina Q; Duan, Xujun; Zheng, Junjie; Long, Zhiliang; Zhang, Youxue; Guo, Xiaonan; Zhang, Yan; Zhao, Jingping; Chen, Huafu

2017-11-01

Schizophrenia and autism spectrum disorder (ASD) are two prevalent neurodevelopmental disorders sharing some similar genetic basis and clinical features. The extent to which they share common neural substrates remains unclear. Resting-state fMRI data were collected from 35 drug-naïve adolescent participants with first-episode schizophrenia (15.6 ± 1.8 years old) and 31 healthy controls (15.4 ± 1.6 years old). Data from 22 participants with ASD (13.1 ± 3.1 years old) and 21 healthy controls (12.9 ± 2.9 years old) were downloaded from the Autism Brain Imaging Data Exchange. Resting-state functional networks were constructed using predefined regions of interest. Multivariate pattern analysis combined with multi-task regression feature selection methods were conducted in two datasets separately. Classification between individuals with disorders and controls was achieved with high accuracy (schizophrenia dataset: accuracy = 83%; ASD dataset: accuracy = 80%). Shared atypical brain connections contributing to classification were mostly present in the default mode network (DMN) and salience network (SN). These functional connections were further related to severity of social deficits in ASD (p = 0.002). Distinct atypical connections were also more related to the DMN and SN, but showed different atypical connectivity patterns between the two disorders. These results suggest some common neural mechanisms contributing to schizophrenia and ASD, and may aid in understanding the pathology of these two neurodevelopmental disorders. Autism Res 2017, 10: 1776-1786. © 2017 International Society for Autism Research, Wiley Periodicals, Inc. Autism spectrum disorder (ASD) and schizophrenia are two common neurodevelopmental disorders which share several genetic and behavioral features. The present study identified common neural mechanisms contributing to ASD and schizophrenia using resting-state functional MRI data. The results may help to understand the pathology of these two neurodevelopmental disorders. © 2017 International Society for Autism Research, Wiley Periodicals, 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.

Atypical prefrontal cortical responses to joint/non-joint attention in children with autism spectrum disorder (ASD): A functional near-infrared spectroscopy study

PubMed Central

Zhu, Huilin; Li, Jun; Fan, Yuebo; Li, Xinge; Huang, Dan; He, Sailing

2015-01-01

Autism spectrum disorder (ASD) is a neuro-developmental disorder, characterized by impairments in one’s capacity for joint attention. In this study, functional near-infrared spectroscopy (fNIRS) was applied to study the differences in activation and functional connectivity in the prefrontal cortex between children with autism spectrum disorder (ASD) and typically developing (TD) children. 21 ASD and 20 TD children were recruited to perform joint and non-joint attention tasks. Compared with TD children, children with ASD showed reduced activation and atypical functional connectivity pattern in the prefrontal cortex during joint attention. The atypical development of left prefrontal cortex might play an important role in social cognition defects of children with ASD. PMID:25798296

Clinical Applications of Resting State Functional Connectivity

PubMed Central

Fox, Michael D.; Greicius, Michael

2010-01-01

During resting conditions the brain remains functionally and metabolically active. One manifestation of this activity that has become an important research tool is spontaneous fluctuations in the blood oxygen level-dependent (BOLD) signal of functional magnetic resonance imaging (fMRI). The identification of correlation patterns in these spontaneous fluctuations has been termed resting state functional connectivity (fcMRI) and has the potential to greatly increase the translation of fMRI into clinical care. In this article we review the advantages of the resting state signal for clinical applications including detailed discussion of signal to noise considerations. We include guidelines for performing resting state research on clinical populations, outline the different areas for clinical application, and identify important barriers to be addressed to facilitate the translation of resting state fcMRI into the clinical realm. PMID:20592951

Hydrologic Connectivity: a Framework to Understand Threshold Behaviour in Semi-Arid Landscapes.

NASA Astrophysics Data System (ADS)

Saco, Patricia; Rodriguez, Jose; Keesstra, Saskia; Moreno-de las Heras, Mariano; Sandi, Steven; Baartman, Jantiene; Cerdà, Artemi

2017-04-01

Anthropogenic activities and climate change are imposing an unprecedented pressure on arid and semi-arid ecosystems, where shortage of water can trigger shifts in landscapes' structures and function leading to degradation and desertification. Hydrological connectivity is a useful framework for understanding water redistribution and scaling issues associated to runoff and sediment production, since human and/or natural disturbances alter the surface water availability and pathways increasing/decreasing connectivity. In this presentation, we illustrate the use of the connectivity framework for several examples of dryland systems that are analysed at a variety of spatial and temporal scales. In doing so, we draw particular attention to the analysis of co-evolution of system structures and function, and how they drive threshold behaviour leading to desertification and degradation. We first analyse the case of semi-arid rangelands, where feedbacks between decline in vegetation density and landscape erosion reinforces degradation processes driven by changes in connectivity until a threshold is crossed above which the return to a functional system is unlikely. We then focus on semi-arid wetlands, where decreases in water volumes promotes dryland vegetation encroachment that changes drainage conditions and connectivity potentially reinforcing redistribution of flow paths to other wetland areas. The examples presented highlight the need to incorporate a co-evolutionary framework for the analysis of changing connectivity patterns and the emergence of thresholds in arid and semi-arid systems.

Dynamic connectivity regression: Determining state-related changes in brain connectivity

PubMed Central

Cribben, Ivor; Haraldsdottir, Ragnheidur; Atlas, Lauren Y.; Wager, Tor D.; Lindquist, Martin A.

2014-01-01

Most statistical analyses of fMRI data assume that the nature, timing and duration of the psychological processes being studied are known. However, often it is hard to specify this information a priori. In this work we introduce a data-driven technique for partitioning the experimental time course into distinct temporal intervals with different multivariate functional connectivity patterns between a set of regions of interest (ROIs). The technique, called Dynamic Connectivity Regression (DCR), detects temporal change points in functional connectivity and estimates a graph, or set of relationships between ROIs, for data in the temporal partition that falls between pairs of change points. Hence, DCR allows for estimation of both the time of change in connectivity and the connectivity graph for each partition, without requiring prior knowledge of the nature of the experimental design. Permutation and bootstrapping methods are used to perform inference on the change points. The method is applied to various simulated data sets as well as to an fMRI data set from a study (N=26) of a state anxiety induction using a socially evaluative threat challenge. The results illustrate the method’s ability to observe how the networks between different brain regions changed with subjects’ emotional state. PMID:22484408

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.

Contributions of Feature Binding During Encoding and Functional Connectivity of the Medial Temporal Lobe Structures to Episodic Memory Deficits Across the Prodromal and First-Episode Phases of Schizophrenia

PubMed Central

Haut, Kristen M.; van Erp, Theo G. M.; Knowlton, Barbara; Bearden, Carrie E.; Subotnik, Kenneth; Ventura, Joseph; Nuechterlein, Keith H.; Cannon, Tyrone D.

2014-01-01

Patients with and at risk for psychosis may have difficulty using associative strategies to facilitate episodic memory encoding and recall. In parallel studies, patients with first-episode schizophrenia (n = 27) and high psychosis risk (n = 28) compared with control participants (n = 22 and n = 20, respectively) underwent functional MRI during a remember-know memory task. Psychophysiological interaction analyses, using medial temporal lobe (MTL) structures as regions of interest, were conducted to measure functional connectivity patterns supporting successful episodic memory. During encoding, patients with first-episode schizophrenia demonstrated reduced functional coupling between MTL regions and regions involved in stimulus representations, stimulus selection, and cognitive control. Relative to control participants and patients with high psychosis risk who did not convert to psychosis, patients with high psychosis risk who later converted to psychosis also demonstrated reduced connectivity between MTL regions and auditory-verbal and visual-association regions. These results suggest that episodic memory deficits in schizophrenia are related to inefficient recruitment of cortical connections involved in associative memory formation; such deficits precede the onset of psychosis among those individuals at high clinical risk. PMID:25750836

Contributions of Feature Binding During Encoding and Functional Connectivity of the Medial Temporal Lobe Structures to Episodic Memory Deficits Across the Prodromal and First-Episode Phases of Schizophrenia.

PubMed

Haut, Kristen M; van Erp, Theo G M; Knowlton, Barbara; Bearden, Carrie E; Subotnik, Kenneth; Ventura, Joseph; Nuechterlein, Keith H; Cannon, Tyrone D

2015-03-01

Patients with and at risk for psychosis may have difficulty using associative strategies to facilitate episodic memory encoding and recall. In parallel studies, patients with first-episode schizophrenia ( n = 27) and high psychosis risk ( n = 28) compared with control participants ( n = 22 and n = 20, respectively) underwent functional MRI during a remember-know memory task. Psychophysiological interaction analyses, using medial temporal lobe (MTL) structures as regions of interest, were conducted to measure functional connectivity patterns supporting successful episodic memory. During encoding, patients with first-episode schizophrenia demonstrated reduced functional coupling between MTL regions and regions involved in stimulus representations, stimulus selection, and cognitive control. Relative to control participants and patients with high psychosis risk who did not convert to psychosis, patients with high psychosis risk who later converted to psychosis also demonstrated reduced connectivity between MTL regions and auditory-verbal and visual-association regions. These results suggest that episodic memory deficits in schizophrenia are related to inefficient recruitment of cortical connections involved in associative memory formation; such deficits precede the onset of psychosis among those individuals at high clinical risk.

Heterogeneity within the frontoparietal control network and its relationship to the default and dorsal attention networks.

PubMed

Dixon, Matthew L; De La Vega, Alejandro; Mills, Caitlin; Andrews-Hanna, Jessica; Spreng, R Nathan; Cole, Michael W; Christoff, Kalina

2018-02-13

The frontoparietal control network (FPCN) plays a central role in executive control. It has been predominantly viewed as a unitary domain general system. Here, we examined patterns of FPCN functional connectivity (FC) across multiple conditions of varying cognitive demands, to test for FPCN heterogeneity. We identified two distinct subsystems within the FPCN based on hierarchical clustering and machine learning classification analyses of within-FPCN FC patterns. These two FPCN subsystems exhibited distinct patterns of FC with the default network (DN) and the dorsal attention network (DAN). FPCN A exhibited stronger connectivity with the DN than the DAN, whereas FPCN B exhibited the opposite pattern. This twofold FPCN differentiation was observed across four independent datasets, across nine different conditions (rest and eight tasks), at the level of individual-participant data, as well as in meta-analytic coactivation patterns. Notably, the extent of FPCN differentiation varied across conditions, suggesting flexible adaptation to task demands. Finally, we used meta-analytic tools to identify several functional domains associated with the DN and DAN that differentially predict activation in the FPCN subsystems. These findings reveal a flexible and heterogeneous FPCN organization that may in part emerge from separable DN and DAN processing streams. We propose that FPCN A may be preferentially involved in the regulation of introspective processes, whereas FPCN B may be preferentially involved in the regulation of visuospatial perceptual attention.

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.

Deconstructing white matter connectivity of human amygdala nuclei with thalamus and cortex subdivisions in vivo.

PubMed

Abivardi, Aslan; Bach, Dominik R

2017-08-01

Structural alterations in long-range amygdala connections are proposed to crucially underlie several neuropsychiatric disorders. While progress has been made in elucidating the function of these connections, our understanding of their structure in humans remains sparse and non-systematic. Harnessing diffusion-weighted imaging and probabilistic tractography in humans, we investigate connections between two main amygdala nucleus groups, thalamic nuclei, and cortex. We first parcellated amygdala into deep (basolateral) and superficial (centrocortical) nucleus groups, and thalamus into six subregions, using previously established protocols based on connectivity. Cortex was parcellated based on T1-weighted images. We found substantial amygdala connections to thalamus, with different patterns for the two amygdala nuclei. Crucially, we describe direct subcortical connections between amygdala and paraventricular thalamus. Different from rodents but similar to non-human primates, these are more pronounced for basolateral than centrocortical amygdala. Substantial white-matter connectivity between amygdala and visual pulvinar is also more pronounced for basolateral amygdala. Furthermore, we establish detailed connectivity profiles for basolateral and centrocortical amygdala to cortical regions. These exhibit cascadic connections with sensory cortices as suggested previously based on tracer methods in non-human animals. We propose that the quantitative connectivity profiles provided here may guide future work on normal and pathological function of human amygdala. Hum Brain Mapp 38:3927-3940, 2017. © 2017 Wiley Periodicals, Inc. © 2017 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

Deconstructing white matter connectivity of human amygdala nuclei with thalamus and cortex subdivisions in vivo

PubMed Central

2017-01-01

Abstract Structural alterations in long‐range amygdala connections are proposed to crucially underlie several neuropsychiatric disorders. While progress has been made in elucidating the function of these connections, our understanding of their structure in humans remains sparse and non‐systematic. Harnessing diffusion‐weighted imaging and probabilistic tractography in humans, we investigate connections between two main amygdala nucleus groups, thalamic nuclei, and cortex. We first parcellated amygdala into deep (basolateral) and superficial (centrocortical) nucleus groups, and thalamus into six subregions, using previously established protocols based on connectivity. Cortex was parcellated based on T1‐weighted images. We found substantial amygdala connections to thalamus, with different patterns for the two amygdala nuclei. Crucially, we describe direct subcortical connections between amygdala and paraventricular thalamus. Different from rodents but similar to non‐human primates, these are more pronounced for basolateral than centrocortical amygdala. Substantial white‐matter connectivity between amygdala and visual pulvinar is also more pronounced for basolateral amygdala. Furthermore, we establish detailed connectivity profiles for basolateral and centrocortical amygdala to cortical regions. These exhibit cascadic connections with sensory cortices as suggested previously based on tracer methods in non‐human animals. We propose that the quantitative connectivity profiles provided here may guide future work on normal and pathological function of human amygdala. Hum Brain Mapp 38:3927–3940, 2017. © 2017 Wiley Periodicals, Inc. PMID:28512761

Structural Connectivity of the Developing Human Amygdala

PubMed Central

Saygin, Zeynep M.; Osher, David E.; Koldewyn, Kami; Martin, Rebecca E.; Finn, Amy; Saxe, Rebecca; Gabrieli, John D.E.; Sheridan, Margaret

2015-01-01

A large corpus of research suggests that there are changes in the manner and degree to which the amygdala supports cognitive and emotional function across development. One possible basis for these developmental differences could be the maturation of amygdalar connections with the rest of the brain. Recent functional connectivity studies support this conclusion, but the structural connectivity of the developing amygdala and its different nuclei remains largely unstudied. We examined age related changes in the DWI connectivity fingerprints of the amygdala to the rest of the brain in 166 individuals of ages 5-30. We also developed a model to predict age based on individual-subject amygdala connectivity, and identified the connections that were most predictive of age. Finally, we segmented the amygdala into its four main nucleus groups, and examined the developmental changes in connectivity for each nucleus. We observed that with age, amygdalar connectivity becomes increasingly sparse and localized. Age related changes were largely localized to the subregions of the amygdala that are implicated in social inference and contextual memory (the basal and lateral nuclei). The central nucleus’ connectivity also showed differences with age but these differences affected fewer target regions than the basal and lateral nuclei. The medial nucleus did not exhibit any age related changes. These findings demonstrate increasing specificity in the connectivity patterns of amygdalar nuclei across age. PMID:25875758

Disrupted Topological Patterns of Large-Scale Network in Conduct Disorder

PubMed Central

Jiang, Yali; Liu, Weixiang; Ming, Qingsen; Gao, Yidian; Ma, Ren; Zhang, Xiaocui; Situ, Weijun; Wang, Xiang; Yao, Shuqiao; Huang, Bingsheng

2016-01-01

Regional abnormalities in brain structure and function, as well as disrupted connectivity, have been found repeatedly in adolescents with conduct disorder (CD). Yet, the large-scale brain topology associated with CD is not well characterized, and little is known about the systematic neural mechanisms of CD. We employed graphic theory to investigate systematically the structural connectivity derived from cortical thickness correlation in a group of patients with CD (N = 43) and healthy controls (HCs, N = 73). Nonparametric permutation tests were applied for between-group comparisons of graphical metrics. Compared with HCs, network measures including global/local efficiency and modularity all pointed to hypo-functioning in CD, despite of preserved small-world organization in both groups. The hubs distribution is only partially overlapped with each other. These results indicate that CD is accompanied by both impaired integration and segregation patterns of brain networks, and the distribution of highly connected neural network ‘hubs’ is also distinct between groups. Such misconfiguration extends our understanding regarding how structural neural network disruptions may underlie behavioral disturbances in adolescents with CD, and potentially, implicates an aberrant cytoarchitectonic profiles in the brain of CD patients. PMID:27841320

The Cortical Connectivity of the Prefrontal Cortex in the Monkey Brain

PubMed Central

Yeterian, Edward H.; Pandya, Deepak N.; Tomaiuolo, Francesco; Petrides, Michael

2011-01-01

One dimension of understanding the functions of the prefrontal cortex is knowledge of cortical connectivity. We have surveyed three aspects of prefrontal cortical connections: local projections (within the frontal lobe), the termination patterns of long association (post-Rolandic) projections, and the trajectories of major fiber pathways. The local connections appear to be organized in relation to dorsal (hippocampal origin) and ventral (paleocortical origin) architectonic trends. According to the proposal of a dual origin of the cerebral cortex, cortical areas can be traced as originating from archicortex (hippocampus) on the one hand, and paleocortex, on the other hand, in a stepwise manner (e.g., Sanides, 1969; Pandya and Yeterian, 1985). Prefrontal areas within each trend are connected with less architectonically differentiated areas, and, on the other hand, with more differentiated areas. Such organization may allow for the systematic exchange of information within each architectonic trend. The long connections of the prefrontal cortex with post-Rolandic regions seem to be organized preferentially in relation to dorsal and ventral prefrontal architectonic trends. Prefrontal areas are connected with post-Rolandic auditory, visual and somatosensory association areas, and with multimodal and paralimbic regions. This long connectivity likely works in conjunction with local connections to serve prefrontal cortical functions. The afferent and efferent connections of the prefrontal cortex with post-Rolandic regions are conveyed by specific long association pathways. These pathways as well appear to be organized in relation to dorsal and ventral prefrontal architectonic trends. Finally, although prefrontal areas have preferential connections in relation to dual architectonic trends, it is clear that there are interconnections between and among areas in each trend, which may provide a substrate for the overall integrative function of the prefrontal cortex. Prefrontal corticocortical connectivity may help to elucidate both region-specific and integrative perspectives on the functions of the prefrontal cortex. PMID:21481342

OpenNFT: An open-source Python/Matlab framework for real-time fMRI neurofeedback training based on activity, connectivity and multivariate pattern analysis.

PubMed

Koush, Yury; Ashburner, John; Prilepin, Evgeny; Sladky, Ronald; Zeidman, Peter; Bibikov, Sergei; Scharnowski, Frank; Nikonorov, Artem; De Ville, Dimitri Van

2017-08-01

Neurofeedback based on real-time functional magnetic resonance imaging (rt-fMRI) is a novel and rapidly developing research field. It allows for training of voluntary control over localized brain activity and connectivity and has demonstrated promising clinical applications. Because of the rapid technical developments of MRI techniques and the availability of high-performance computing, new methodological advances in rt-fMRI neurofeedback become possible. Here we outline the core components of a novel open-source neurofeedback framework, termed Open NeuroFeedback Training (OpenNFT), which efficiently integrates these new developments. This framework is implemented using Python and Matlab source code to allow for diverse functionality, high modularity, and rapid extendibility of the software depending on the user's needs. In addition, it provides an easy interface to the functionality of Statistical Parametric Mapping (SPM) that is also open-source and one of the most widely used fMRI data analysis software. We demonstrate the functionality of our new framework by describing case studies that include neurofeedback protocols based on brain activity levels, effective connectivity models, and pattern classification approaches. This open-source initiative provides a suitable framework to actively engage in the development of novel neurofeedback approaches, so that local methodological developments can be easily made accessible to a wider range of users. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Long-term memory stabilized by noise-induced rehearsal.

PubMed

Wei, Yi; Koulakov, Alexei A

2014-11-19

Cortical networks can maintain memories for decades despite the short lifetime of synaptic strengths. Can a neural network store long-lasting memories in unstable synapses? Here, we study the effects of ongoing spike-timing-dependent plasticity (STDP) on the stability of memory patterns stored in synapses of an attractor neural network. We show that certain classes of STDP rules can stabilize all stored memory patterns despite a short lifetime of synapses. In our model, unstructured neural noise, after passing through the recurrent network connections, carries the imprint of all memory patterns in temporal correlations. STDP, combined with these correlations, leads to reinforcement of all stored patterns, even those that are never explicitly visited. Our findings may provide the functional reason for irregular spiking displayed by cortical neurons and justify models of system memory consolidation. Therefore, we propose that irregular neural activity is the feature that helps cortical networks maintain stable connections. Copyright © 2014 the authors 0270-6474/14/3415804-12$15.00/0.

TRMM-TMI Satellite Observed Soil Moisture and Vegetation Density (1998-2005) Show Strong Connection with El Nino in Eastern Australia

NASA Technical Reports Server (NTRS)

Liu, Yi; van Dijk, Albert I.J.M.; Owe, Manfred

2007-01-01

Spatiotemporal patterns in soil moisture and vegetation water content across mainland Australia were investigated from 1998 through 2005, using TRMMITMI passive microwave observations. The Empirical Orthogonal Function technique was used to extract dominant spatial and temporal patterns in retrieved estimates of moisture content for the top 1-cm of soil (theta) and vegetation moisture content (via optical depth tau). The dominant temporal theta and tau patterns were strongly correlated to El Nino/Southern Oscillation (ENSO) in spring (3 = 0.90), and to a progressively lesser extent autumn, summer and winter. The Indian Ocean Dipole (IOD) index also explained part of the variation in spring 8 and z. Cluster analysis suggested that the regions most affected by ENS0 are mainly located in eastern Australia. The results suggest that the drought conditions experienced in eastern Australia since 2000 an clearly expressed in these satellite observations have a strong connection with ENSO patterns.

Vigilance in the Laboratory Predicts Avoidance in the Real World: A Dimensional Analysis of Neural, Behavioral, and Ecological Momentary Data in Anxious Youth

PubMed Central

Silk, Jennifer S.; Ladouceur, Cecile D.; Ryan, Neal D.; Dahl, Ronald E.; Forbes, Erika E.; Siegle, Greg J.

2016-01-01

Vigilance and avoidance of threat are observed in anxious adults during laboratory tasks, and are posited to have real-world clinical relevance, but data are mixed in anxious youth. We propose that vigilance-avoidance patterns will become evident in anxious youth through a focus on individual differences and real-world strategic avoidance. Decreased functional connectivity between the amygdala and prefrontal cortex (PFC) could play a mechanistic role in this link. 78 clinically anxious youth completed a dot-probe task to assess vigilance to threat while undergoing fMRI. Real-world avoidance was assessed using Ecological Momentary Assessment (EMA) of self-reported suppression and distraction during negative life events. Vigilance towards threat was positively associated with EMA distraction and suppression. Functional connectivity between a right amygdala seed region and dorsomedial and right dorsolateral PFC regions was inversely related to EMA distraction. Dorsolateral PFC-amygdalar connectivity statistically mediated the relationship between attentional vigilance and real-world distraction. Findings suggest anxious youth showing attentional vigilance toward threat are more likely to use suppression and distraction to regulate negative emotions. Reduced PFC control over limbic reactivity is a possible neural substrate of this pattern. These findings lend ecological validity to laboratory vigilance assessments and suggest PFC-amygdalar connectivity is a neural mechanism bridging laboratory and naturalistic contexts. PMID:27010577

Attractor neural networks with resource-efficient synaptic connectivity

NASA Astrophysics Data System (ADS)

Pehlevan, Cengiz; Sengupta, Anirvan

Memories are thought to be stored in the attractor states of recurrent neural networks. Here we explore how resource constraints interplay with memory storage function to shape synaptic connectivity of attractor networks. We propose that given a set of memories, in the form of population activity patterns, the neural circuit choses a synaptic connectivity configuration that minimizes a resource usage cost. We argue that the total synaptic weight (l1-norm) in the network measures the resource cost because synaptic weight is correlated with synaptic volume, which is a limited resource, and is proportional to neurotransmitter release and post-synaptic current, both of which cost energy. Using numerical simulations and replica theory, we characterize optimal connectivity profiles in resource-efficient attractor networks. Our theory explains several experimental observations on cortical connectivity profiles, 1) connectivity is sparse, because synapses are costly, 2) bidirectional connections are overrepresented and 3) are stronger, because attractor states need strong recurrence.

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.

Transport on Riemannian manifold for functional connectivity-based classification.

PubMed

Ng, Bernard; Dressler, Martin; Varoquaux, Gaël; Poline, Jean Baptiste; Greicius, Michael; Thirion, Bertrand

2014-01-01

We present a Riemannian approach for classifying fMRI connectivity patterns before and after intervention in longitudinal studies. A fundamental difficulty with using connectivity as features is that covariance matrices live on the positive semi-definite cone, which renders their elements inter-related. The implicit independent feature assumption in most classifier learning algorithms is thus violated. In this paper, we propose a matrix whitening transport for projecting the covariance estimates onto a common tangent space to reduce the statistical dependencies between their elements. We show on real data that our approach provides significantly higher classification accuracy than directly using Pearson's correlation. We further propose a non-parametric scheme for identifying significantly discriminative connections from classifier weights. Using this scheme, a number of neuroanatomically meaningful connections are found, whereas no significant connections are detected with pure permutation testing.

Cytoarchitecture and Cortical Connections of the Anterior Insula and Adjacent Frontal Motor Fields in the Rhesus Monkey

PubMed Central

Morecraft, RJ; Stilwell-Morecraft, KS; Ge, J; Cipolloni, PB; Pandya, DN

2015-01-01

The cytoarchitecture and cortical connections of the ventral motor region are investigated using Nissl, and NeuN staining methods and the fluorescent retrograde tract tracing technique in the rhesus monkey. On the basis of gradual laminar differentiation, it is shown that the ventral motor region stems from the ventral proisocortical area (anterior insula and dorsal Sylvian opercular region). The cytoarchitecture of the ventral motor region is shown to progress in three lines, as we have recently shown for the dorsal motor region. Namely, root (anterior insular and dorsal Sylvian opercular area ProM), belt (ventral premotor cortex) and core (precentral motor cortex) lines. This stepwise architectonic organization is supported by the overall patterns of corticocortical connections. Areas in each line are sequentially interconnected (intralineal connections) and all lines are interconnected (interlinear connections). Moreover, root areas, as well as some of the belt areas of the ventral and dorsal trend are interconnected. The ventral motor region is also connected with the ventral somatosensory areas in a topographic manner. The root and belt areas of ventral motor region are connected with paralimbic, multimodal and prefrontal (outer belt) areas. In contrast, the core area has a comparatively more restricted pattern of corticocortical connections. This architectonic and connectional organization is consistent in part, with the functional organization of the ventral motor region as reported in behavioral and neuroimaging studies which include the mediation of facial expression and emotion, communication, phonic articulation, and language in human. PMID:26496798

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

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.

Functional Connectivity Changes in Systemic Lupus Erythematosus: A Resting-State Study.

PubMed

Nystedt, Jessika; Mannfolk, Peter; Jönsen, Andreas; Bengtsson, Anders; Nilsson, Petra; Sundgren, Pia C; Strandberg, Tor O

2018-05-01

To investigate resting-state functional connectivity of lupus patients and associated subgroups according to the ACR NPSLE case definitions (ACR ad hoc). In addition, we investigated whether or not the observed alterations correlated with disease duration, the systemic lupus erythematosus (SLE)-Disease Activity Index-2000 (SLEDAI-2k), and Systemic Lupus International Collaborating Clinical/ACR organ damage index (SDI)-scores. Anatomical 3T magnetic resonance imaging (MRI) and resting-state functional MRI were performed in 61 female lupus patients (mean age = 37.0 years, range = 18.2-52.0 years) and 20 gender- and age-matched controls (mean age = 36.2 years, range = 23.3-52.2 years) in conjunction with clinical examination and laboratory testing. Whole-brain voxelwise functional connectivity analysis with permutation testing was performed to extract network components that differed in lupus patients relative to healthy controls (HCs). Lupus patients exhibited both inter- and intranetwork hypo- and hyperconnectivity involving several crucial networks. We found reduced connectivity within the default mode network (DMN), the central executive network (CEN), and in-between the DMN and CEN in lupus patients. Increased connectivity was primarily observed within and between the sensory motor network in lupus patients when compared to HCs. Comparing lupus patients with and without neuropsychiatric symptoms, hypoconnectivity was more pronounced in the group with neuropsychiatric complaints. The functional connectivity of SLE patients was both positively and negatively correlated to duration of disease. We conclude that SLE patients in general and neuropsychiatric SLE patients in particular experience altered brain connectivity. These patterns may be due both to direct neuronal damage and compensatory mechanisms through neuronal rewiring and recruitment and may partly explain neuropsychiatric symptoms in SLE patients.

Common and Distinct Neural Mechanisms of Attentional Switching and Response Conflict

PubMed Central

Kim, Chobok; Johnson, Nathan F.; Gold, Brian T.

2012-01-01

The human capacities for overcoming prepotent actions and flexibly switching between tasks represent cornerstones of cognitive control. Functional neuroimaging has implicated a diverse set of brain regions contributing to each of these cognitive control processes. However, the extent to which attentional switching and response conflict draw on shared or distinct neural mechanisms remains unclear. The current study examined the neural correlates of response conflict and attentional switching using event-related functional magnetic resonance imaging (fMRI) and a fully randomized 2×2 design. We manipulated an arrow-word version of the Stroop task to measure conflict and switching in the context of a single task decision, in response to a common set of stimuli. Under these common conditions, both behavioral and imaging data showed significant main effects of conflict and switching but no interaction. However, conjunction analyses identified frontal regions involved in both switching and response conflict, including the dorsal anterior cingulate cortex (dACC) and left inferior frontal junction. In addition, connectivity analyses demonstrated task-dependent functional connectivity patterns between dACC and inferior temporal cortex for attentional switching and between dACC and posterior parietal cortex for response conflict. These results suggest that the brain makes use of shared frontal regions, but can dynamically modulate the connectivity patterns of some of those regions, to deal with attentional switching and response conflict. PMID:22750124

Common and distinct neural mechanisms of attentional switching and response conflict.

PubMed

Kim, Chobok; Johnson, Nathan F; Gold, Brian T

2012-08-21

The human capacities for overcoming prepotent actions and flexibly switching between tasks represent cornerstones of cognitive control. Functional neuroimaging has implicated a diverse set of brain regions contributing to each of these cognitive control processes. However, the extent to which attentional switching and response conflict draw on shared or distinct neural mechanisms remains unclear. The current study examined the neural correlates of response conflict and attentional switching using event-related functional magnetic resonance imaging (fMRI) and a fully randomized 2×2 design. We manipulated an arrow-word version of the Stroop task to measure conflict and switching in the context of a single task decision, in response to a common set of stimuli. Under these common conditions, both behavioral and imaging data showed significant main effects of conflict and switching but no interaction. However, conjunction analyses identified frontal regions involved in both switching and response conflict, including the dorsal anterior cingulate cortex (dACC) and left inferior frontal junction. In addition, connectivity analyses demonstrated task-dependent functional connectivity patterns between dACC and inferior temporal cortex for attentional switching and between dACC and posterior parietal cortex for response conflict. These results suggest that the brain makes use of shared frontal regions, but can dynamically modulate the connectivity patterns of some of those regions, to deal with attentional switching and response conflict. Copyright © 2012 Elsevier B.V. All rights reserved.

Using Spatial Multiple Regression to Identify Intrinsic Connectivity Networks Involved in Working Memory Performance

PubMed Central

Gordon, Evan M.; Stollstorff, Melanie; Vaidya, Chandan J.

2012-01-01

Many researchers have noted that the functional architecture of the human brain is relatively invariant during task performance and the resting state. Indeed, intrinsic connectivity networks (ICNs) revealed by resting-state functional connectivity analyses are spatially similar to regions activated during cognitive tasks. This suggests that patterns of task-related activation in individual subjects may result from the engagement of one or more of these ICNs; however, this has not been tested. We used a novel analysis, spatial multiple regression, to test whether the patterns of activation during an N-back working memory task could be well described by a linear combination of ICNs delineated using Independent Components Analysis at rest. We found that across subjects, the cingulo-opercular Set Maintenance ICN, as well as right and left Frontoparietal Control ICNs, were reliably activated during working memory, while Default Mode and Visual ICNs were reliably deactivated. Further, involvement of Set Maintenance, Frontoparietal Control, and Dorsal Attention ICNs was sensitive to varying working memory load. Finally, the degree of left Frontoparietal Control network activation predicted response speed, while activation in both left Frontoparietal Control and Dorsal Attention networks predicted task accuracy. These results suggest that a close relationship between resting-state networks and task-evoked activation is functionally relevant for behavior, and that spatial multiple regression analysis is a suitable method for revealing that relationship. PMID:21761505

Prolonged fasting impairs neural reactivity to visual stimulation.

PubMed

Kohn, N; Wassenberg, A; Toygar, T; Kellermann, T; Weidenfeld, C; Berthold-Losleben, M; Chechko, N; Orfanos, S; Vocke, S; Laoutidis, Z G; Schneider, F; Karges, W; Habel, U

2016-01-01

Previous literature has shown that hypoglycemia influences the intensity of the BOLD signal. A similar but smaller effect may also be elicited by low normal blood glucose levels in healthy individuals. This may not only confound the BOLD signal measured in fMRI, but also more generally interact with cognitive processing, and thus indirectly influence fMRI results. Here we show in a placebo-controlled, crossover, double-blind study on 40 healthy subjects, that overnight fasting and low normal levels of glucose contrasted to an activated, elevated glucose condition have an impact on brain activation during basal visual stimulation. Additionally, functional connectivity of the visual cortex shows a strengthened association with higher-order attention-related brain areas in an elevated blood glucose condition compared to the fasting condition. In a fasting state visual brain areas show stronger coupling to the inferior temporal gyrus. Results demonstrate that prolonged overnight fasting leads to a diminished BOLD signal in higher-order occipital processing areas when compared to an elevated blood glucose condition. Additionally, functional connectivity patterns underscore the modulatory influence of fasting on visual brain networks. Patterns of brain activation and functional connectivity associated with a broad range of attentional processes are affected by maturation and aging and associated with psychiatric disease and intoxication. Thus, we conclude that prolonged fasting may decrease fMRI design sensitivity in any task involving attentional processes when fasting status or blood glucose is not controlled.