4.8 Article

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

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NATURE COMMUNICATIONS
卷 10, 期 -, 页码 -

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NATURE PORTFOLIO
DOI: 10.1038/s41467-019-10317-7

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资金

  1. CHIST-ERA IVAN project [20CH21 174081]
  2. Center for Biomedical Imaging (CIBM) of the Geneva-Lausanne Universities
  3. EPFL
  4. Singapore MOE Tier 2 [MOE2014-T2-2-016]
  5. NUS Strategic Research [DPRT/944/09/14]
  6. NUS SOM Aspiration Fund [R185000271720]
  7. Singapore NMRC [CBRG/0088/2015]
  8. NUS YIA
  9. Singapore NRF fellowship [NRF-NRFF2017-06]
  10. NIH [K99AG054573]
  11. Neuroimaging Informatics and Analysis Center [1P30NS098577]
  12. 16 NIH Institutes and Centers [1U54MH091-657]
  13. McDonnell Center for Systems Neuroscience at Washington University
  14. Swiss National Science Foundation (SNF) [20CH21_174081] Funding Source: Swiss National Science Foundation (SNF)

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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.

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