Resting brain dynamics at different timescales capture distinct aspects of human behavior

Raphaël Liégeois (), Jingwei Li, Ru Kong, Csaba Orban, Dimitri Van De Ville, Tian Ge, Mert R. Sabuncu and B. T. Thomas Yeo ()
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Raphaël Liégeois: National University of Singapore
Jingwei Li: National University of Singapore
Ru Kong: National University of Singapore
Csaba Orban: National University of Singapore
Dimitri Van De Ville: Institute of Bioengineering, Centre for Neuroprosthetics, École Polytechnique Fédérale de Lausanne
Tian Ge: Psychiatric & Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital
Mert R. Sabuncu: Cornell University
B. T. Thomas Yeo: National University of Singapore

Nature Communications, 2019, vol. 10, issue 1, 1-9

Abstract: Abstract Linking human behavior to resting-state brain function is a central question in systems neuroscience. In particular, the functional timescales at which different types of behavioral factors are encoded remain largely unexplored. The behavioral counterparts of static functional connectivity (FC), at the resolution of several minutes, have been studied but behavioral correlates of dynamic measures of FC at the resolution of a few seconds remain unclear. Here, using resting-state fMRI and 58 phenotypic measures from the Human Connectome Project, we find that dynamic FC captures task-based phenotypes (e.g., processing speed or fluid intelligence scores), whereas self-reported measures (e.g., loneliness or life satisfaction) are equally well explained by static and dynamic FC. Furthermore, behaviorally relevant dynamic FC emerges from the interconnections across all resting-state networks, rather than within or between pairs of networks. Our findings shed new light on the timescales of cognitive processes involved in distinct facets of behavior.

Date: 2019
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DOI: 10.1038/s41467-019-10317-7

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