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

Research output: Contribution to journalArticlepeer-review

106 Scopus citations

Abstract

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
Volume116
Issue number45
DOIs
StatePublished - 2019
Externally publishedYes

Bibliographical note

Funding Information:
We thank Joshua S. Siegel and Deanna M. Barch for assistance with the Human Connectome Project data. This research was supported by NIH Grant T32NS073547 (to B.A.S.), NIH Grant F32NS092290 (to C.G.), NIH Grant R01MH118370 (to C.G.), NIH Grant R25MH112473 (to T.O.L.), NIH Grant T32NS047987 (to B.T.K.), National Science Foundation Graduate Research Fellowship Program Award DGE-1143954 (to A.W.G.), an American Psychological Association Dissertation Research Award (to A.W.G.), NIH Grant K01MH104592 (to D.J.G.), a Dart Neuroscience, LLC Grant (to K.B.M.), a McDonnell Foundation Collaborative Activity Award (to S.E.P.), NIH Grant R01NS32979 (to S.E.P.), NIH Grant R01NS06424 (to S.E.P.), and Career Development Award 1IK2CX001680 (to E.M.G.) from the US Department of Veterans Affairs Clinical Sciences Research and Development Service. The contents of this manuscript do not represent the views of the US Department of Veterans Affairs or the United States Government.

Funding Information:
ACKNOWLEDGMENTS. We thank Joshua S. Siegel and Deanna M. Barch for assistance with the Human Connectome Project data. This research was supported by NIH Grant T32NS073547 (to B.A.S.), NIH Grant F32NS092290 (to C.G.), NIH Grant R01MH118370 (to C.G.), NIH Grant R25MH112473 (to T.O.L.), NIH Grant T32NS047987 (to B.T.K.), National Science Foundation Graduate Research Fellowship Program Award DGE-1143954 (to A.W.G.), an American Psychological Association Dissertation Research Award (to A.W.G.), NIH Grant K01MH104592 (to D.J.G.), a Dart Neuroscience, LLC Grant (to K.B.M.), a McDonnell Foundation Collaborative Activity Award (to S.E.P.), NIH Grant R01NS32979 (to S.E.P.), NIH Grant R01NS06424 (to S.E.P.), and Career Development Award 1IK2CX001680 (to E.M.G.) from the US Department of Veterans Affairs Clinical Sciences Research and Development Service. The contents of this manuscript do not represent the views of the US Department of Veterans Affairs or the United States Government.

Publisher Copyright:
© 2019 National Academy of Sciences. All rights reserved.

Keywords

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

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