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

doi:10.1016/j.neuroimage.2017.08.044

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 Journal › Review article › Academic › peer-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 language	English
Pages (from-to)	406-416
Number of pages	11
Journal	NeuroImage
Volume	180
DOIs	https://doi.org/10.1016/j.neuroimage.2017.08.044
Publication status	Published - 15 Oct 2018
Externally published	Yes

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

Funders	Funder number
CAS K.C. Wong Education Foundation	1U54MH091657
Integrative Graduate Education and Research Traineeship Training Program
J.S. McDonnell Foundation	22002082
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 Health	R01 AT009036-01
National Institute of Mental Health	U54MH091657
NIH Blueprint for Neuroscience Research
James S. McDonnell Foundation
Indiana University	0903495
Uehara Memorial Foundation
McDonnell Center for Systems Neuroscience
Japan Society for the Promotion of Science
National Natural Science Foundation of China	81471740, 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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title = "Fluctuations between high- and low-modularity topology in time-resolved functional connectivity",

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.",

keywords = "Connectomics, Modularity, Networks, Resting state, Time-resolved functional connectivity",

author = "Makoto Fukushima and Betzel, {Richard F.} and Ye He and {de Reus}, {Marcel A.} and {van den Heuvel}, {Martijn P.} and Zuo, {Xi Nian} and Olaf Sporns",

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AU - Fukushima, Makoto

AU - Betzel, Richard F.

AU - He, Ye

AU - de Reus, Marcel A.

AU - van den Heuvel, Martijn P.

AU - Zuo, Xi Nian

AU - Sporns, Olaf

PY - 2018/10/15

Y1 - 2018/10/15

N2 - 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.

AB - 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.

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KW - Modularity

KW - Networks

KW - Resting state

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ER -

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

Abstract

Funding

Keywords

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