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

  • Makoto Fukushima*
  • , Richard F. Betzel
  • , Ye He
  • , Martijn P. van den Heuvel
  • , Xi Nian Zuo
  • , Olaf Sporns
  • *Corresponding author for this work

Research output: Contribution to Journal › Article › Academic › peer-review

Abstract

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

Original languageEnglish
Pages (from-to)1091-1106
Number of pages16
JournalBrain Structure and Function
Volume223
Issue number3
DOIs
Publication statusPublished - 1 Apr 2018
Externally publishedYes

Funding

Funding This study was supported by the Japan Society for the Promotion of Science Postdoctoral Fellowship for Research Abroad (H28-150), the National Science Foundation/Integrative Graduate Education and Research Traineeship Training Program in the Dynamics of Brain-Body-Environment Systems at Indiana University (0903495), the National Key Basic Research and Development Program (973 Program; 2015CB351702), the Natural Sciences Foundation of China (81471740 and 81220108014), the CAS K.C. Wong Education Foundation, the J.S. McDonnell Foundation (22002082), and the National Institutes of Health (R01 AT009036-01). Data were provided in part by the Human Connectome Project (HCP), WU-Minn Consortium (Principal Investigators: David Van Essen and Kamil Ugurbil; 1U54MH091657) funded by the 16 NIH Institutes and Centers that support the NIH Blueprint for Neuroscience Research; and by the McDonnell Center for Systems Neuroscience at Washington University. The authors would like to thank Marcel A. de Reus for constructing structural networks from the HCP data. This study was supported by the Japan Society for the Promotion of Science Postdoctoral Fellowship for Research Abroad (H28-150), the National Science Foundation/Integrative Graduate Education and Research Traineeship Training Program in the Dynamics of Brain-Body-Environment Systems at Indiana University (0903495), the National Key Basic Research and Development Program (973 Program; 2015CB351702), the Natural Sciences Foundation of China (81471740 and 81220108014), the CAS K.C. Wong Education Foundation, the J.S. McDonnell Foundation (22002082), and the National Institutes of Health (R01 AT009036-01). The authors declare that they have no conflict of interest. Acknowledgements Data were provided in part by the Human Connectome Project (HCP), WU-Minn Consortium (Principal Investigators: David Van Essen and Kamil Ugurbil; 1U54MH091657) funded by the 16 NIH Institutes and Centers that support the NIH Blueprint for Neuroscience Research; and by the McDonnell Center for Systems Neuroscience at Washington University. The authors

FundersFunder number
Integrative Graduate Education and Research Traineeship Training Program
CAS K.C. Wong Education Foundation
NIH Blueprint for Neuroscience Research
Indiana University
National Science Foundation/Integrative Graduate Education and Research Traineeship Training Program
National Key Basic Research and Development Program (973 Program
National Institutes of Health
Marcel A. de Reus
K. C. Wong Education Foundation
J.S. McDonnell Foundation
McDonnell Center for Systems Neuroscience
Japan Society for the Promotion of ScienceH28-150
James S. McDonnell Foundation22002082
National Natural Science Foundation of China81471740, 81220108014
Natural Sciences Foundation of China81220108014
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National Institute of Mental HealthU54MH091657
National Basic Research Program of China (973 Program)2015CB351702
National Center for Complementary and Integrative HealthR01AT009036

    Keywords

    • Connectomics
    • Networks
    • Resting state
    • Segregation and integration
    • Structural connectivity
    • Time-resolved functional connectivity

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