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

TL;DR
This study explores how the brain's functional connectivity networks fluctuate between high and low modularity states over time, revealing distinct spatial and temporal patterns and their relation to individual differences.
Contribution
It characterizes the spatiotemporal properties of time-resolved brain networks during high and low modularity periods, linking short-term network configurations to long-term modularity.
Findings
High modularity periods show increased dissociation of the default mode network.
Low modularity periods exhibit heterogeneous and variable network interactions.
Occurrence of modularity states varies across individuals with moderate test-retest reliability.
Abstract
Modularity is an important topological attribute for functional brain networks. Recent 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 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…
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