Please use this identifier to cite or link to this item: https://doi.org/10.1038/s41467-019-10317-7
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dc.titleResting brain dynamics at different timescales capture distinct aspects of human behavior
dc.contributor.authorLiégeois, R.
dc.contributor.authorLi, J.
dc.contributor.authorKong, R.
dc.contributor.authorOrban, C.
dc.contributor.authorVan De Ville, D.
dc.contributor.authorGe, T.
dc.contributor.authorSabuncu, M.R.
dc.contributor.authorYeo, B.T.T.
dc.date.accessioned2021-12-06T04:20:07Z
dc.date.available2021-12-06T04:20:07Z
dc.date.issued2019
dc.identifier.citationLiégeois, R., Li, J., Kong, R., Orban, C., Van De Ville, D., Ge, T., Sabuncu, M.R., Yeo, B.T.T. (2019). Resting brain dynamics at different timescales capture distinct aspects of human behavior. Nature Communications 10 (1) : 2317. ScholarBank@NUS Repository. https://doi.org/10.1038/s41467-019-10317-7
dc.identifier.issn2041-1723
dc.identifier.urihttps://scholarbank.nus.edu.sg/handle/10635/209514
dc.description.abstractLinking 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. © 2019, The Author(s).
dc.publisherNature Publishing Group
dc.rightsAttribution 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.sourceScopus OA2019
dc.typeArticle
dc.contributor.departmentLIFE SCIENCES INSTITUTE
dc.contributor.departmentELECTRICAL AND COMPUTER ENGINEERING
dc.description.doi10.1038/s41467-019-10317-7
dc.description.sourcetitleNature Communications
dc.description.volume10
dc.description.issue1
dc.description.page2317
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