Trait-like variants in human functional brain networks

Benjamin A. Seitzman*, Caterina Gratton, Timothy O. Laumann, Evan M. Gordon, Babatunde Adeyemo, Ally Dworetsky, Brian T. Kraus, Adrian W. Gilmore, Jeffrey J. Berg, Mario Ortega, Annie Nguyen, Deanna J. Greene, Kathleen B. McDermott, Steven M. Nelson, Christina N. Lessov-Schlaggar, Bradley L. Schlaggar, Nico U.F. Dosenbach, Steven E. Petersen

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

99 Scopus citations


Resting-state functional magnetic resonance imaging (fMRI) has provided converging descriptions of group-level functional brain organization. Recent work has revealed that functional networks identified in individuals contain local features that differ from the group-level description. We define these features as network variants. Building on these studies, we ask whether distributions of network variants reflect stable, trait-like differences in brain organization. Across several datasets of highly-sampled individuals we show that 1) variants are highly stable within individuals, 2) variants are found in characteristic locations and associate with characteristic functional networks across large groups, 3) task-evoked signals in variants demonstrate a link to functional variation, and 4) individuals cluster into subgroups on the basis of variant characteristics that are related to differences in behavior. These results suggest that distributions of network variants may reflect stable, trait-like, functionally relevant individual differences in functional brain organization.

Original languageEnglish (US)
Pages (from-to)22851-22861
Number of pages11
JournalProceedings of the National Academy of Sciences of the United States of America
Issue number45
StatePublished - 2019


  • Functional connectivity
  • Individual differences
  • Networks
  • Resting-state

ASJC Scopus subject areas

  • General


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