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Identifying topological motif patterns of human brain functional networks.

ABSTRACT: Recent imaging connectome studies demonstrated that the human functional brain network follows an efficient small-world topology with cohesive functional modules and highly connected hubs. However, the functional motif patterns that represent the underlying information flow remain largely unknown. Here, we investigated motif patterns within directed human functional brain networks, which were derived from resting-state functional magnetic resonance imaging data with controlled confounding hemodynamic latencies. We found several significantly recurring motifs within the network, including the two-node reciprocal motif and five classes of three-node motifs. These recurring motifs were distributed in distinct patterns to support intra- and inter-module functional connectivity, which also promoted integration and segregation in network organization. Moreover, the significant participation of several functional hubs in the recurring motifs exhibited their critical role in global integration. Collectively, our findings highlight the basic architecture governing brain network organization and provide insight into the information flow mechanism underlying intrinsic brain activities. Hum Brain Mapp 38:2734-2750, 2017. © 2017 Wiley Periodicals, Inc.

SUBMITTER: Wei Y

PROVIDER: S-EPMC6866742 | biostudies-literature | 2017 May

REPOSITORIES: biostudies-literature

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Identifying topological motif patterns of human brain functional networks.

Wei Yongbin Y Liao Xuhong X Yan Chaogan C He Yong Y Xia Mingrui M

Human brain mapping 20170303 5

Recent imaging connectome studies demonstrated that the human functional brain network follows an efficient small-world topology with cohesive functional modules and highly connected hubs. However, the functional motif patterns that represent the underlying information flow remain largely unknown. Here, we investigated motif patterns within directed human functional brain networks, which were derived from resting-state functional magnetic resonance imaging data with controlled confounding hemody ...[more]

PMID: 28256774

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Project description:Despite an increasing amount of specific correlation studies between structural and functional connectivity, there is still a need for combined studies, especially in pathological conditions. Impairments of brain white matter (WM) and diffuse axonal injuries are commonly suspected to be responsible for the disconnection hypothesis in traumatic brain injury (TBI) patients. Moreover, our previous research on TBI patients shows a strong relationship between abnormalities in topological organization of brain networks and behavioral deficits. In this study, we combined task-related functional connectivity (using event-related fMRI) with structural connectivity (derived from fiber tractography using diffusion MRI data) estimates in the same participants (17 adults with TBI and 16 controls), allowing for direct comparison between graph metrics of the different imaging modalities. Connectivity matrices were computed covering the switching motor network, which includes the basal ganglia, anterior cingulate cortex/supplementary motor area, and anterior insula/inferior frontal gyrus. The edges constituting this network consisted of the partial correlations between the fMRI time series from each node of the switching motor network. The interregional anatomical connections between the switching-related areas were determined using the fiber tractography results. We found that graph metrics and hubs obtained showed no agreement in both groups. The topological properties of brain functional networks could not be solely accounted for by the properties of the underlying structural networks. However, combining complementary information from both imaging modalities could improve accuracy in prediction of switching performance. Direct comparison between functional task-related and anatomical structural connectivity, presented here for the first time in TBI patients, links two powerful approaches to map the patterns of brain connectivity that may underlie behavioral deficits in brain-injured patients.

Dataset Information

Identifying topological motif patterns of human brain functional networks.

Publications

Identifying topological motif patterns of human brain functional networks.

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