Fluctuations between high- and low-modularity topology in time-resolved functional connectivity

Makoto Fukushima*, Richard F. Betzel, Ye He, Marcel A. de Reus, Martijn P. van den Heuvel, Xi Nian Zuo, Olaf Sporns

*Corresponding author for this work

Research output: Contribution to JournalReview articleAcademicpeer-review

Abstract

Modularity is an important topological attribute for functional brain networks. Recent human fMRI studies have reported that modularity of functional networks varies not only across individuals being related to demographics and cognitive performance, but also within individuals co-occurring with fluctuations in network properties of functional connectivity, estimated over short time intervals. However, characteristics of these time-resolved functional networks during periods of high and low modularity have remained largely unexplored. In this study we investigate basic spatiotemporal properties of time-resolved networks in the high and low modularity periods during rest, with a particular focus on their spatial connectivity patterns, temporal homogeneity and test-retest reliability. We show that spatial connectivity patterns of time-resolved networks in the high and low modularity periods are represented by increased and decreased dissociation of the default mode network module from task-positive network modules, respectively. We also find that the instances of time-resolved functional connectivity sampled from within the high (respectively, low) modularity period are relatively homogeneous (respectively, heterogeneous) over time, indicating that during the low modularity period the default mode network interacts with other networks in a variable manner. We confirmed that the occurrence of the high and low modularity periods varies across individuals with moderate inter-session test-retest reliability and that it is correlated with previously-reported individual differences in the modularity of functional connectivity estimated over longer timescales. Our findings illustrate how time-resolved functional networks are spatiotemporally organized during periods of high and low modularity, allowing one to trace individual differences in long-timescale modularity to the variable occurrence of network configurations at shorter timescales.

Original languageEnglish
Pages (from-to)406-416
Number of pages11
JournalNeuroImage
Volume180
DOIs
Publication statusPublished - 15 Oct 2018
Externally publishedYes

Funding

M.F. was supported by a Uehara Memorial Foundation Postdoctoral Fellowship and a Japan Society for the Promotion of Science Postdoctoral Fellowship for Research Abroad. O.S. was supported by the J.S. McDonnell Foundation ( 22002082 ) and the National Institutes of Health ( R01 AT009036-01 ). R.F.B. was supported by the National Science Foundation/Integrative Graduate Education and Research Traineeship Training Program in the Dynamics of Brain-Body-Environment Systems at Indiana University ( 0903495 ). X.N.Z was supported by the National Key Basic Research and Development Program (973 Program; 2015CB351702 ) and the Natural Sciences Foundation of China ( 81471740 , 81220108014 ). X.N.Z. and O.S. are members of an international collaboration team (trial stage) supported by the CAS K.C. Wong Education Foundation . Data were provided in part by the Human Connectome Project, 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. Appendix A

FundersFunder number
CAS K.C. Wong Education Foundation1U54MH091657
Integrative Graduate Education and Research Traineeship Training Program
J.S. McDonnell Foundation22002082
National Key Basic Research and Development Program (973 Program
National Science Foundation/Integrative Graduate Education and Research Traineeship Training Program
Natural Sciences Foundation of China
National Science Foundation
National Institutes of HealthR01 AT009036-01
National Institute of Mental HealthU54MH091657
NIH Blueprint for Neuroscience Research
James S. McDonnell Foundation
Indiana University0903495
Uehara Memorial Foundation
McDonnell Center for Systems Neuroscience
Japan Society for the Promotion of Science
National Natural Science Foundation of China81471740, 81220108014
National Basic Research Program of China (973 Program)2015CB351702
K. C. Wong Education Foundation

    Keywords

    • Connectomics
    • Modularity
    • Networks
    • Resting state
    • Time-resolved functional connectivity

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