Trait-like variants in human functional brain networks

Autor: Deanna J. Greene, Nico U.F. Dosenbach, Brian Kraus, Babatunde Adeyemo, Evan M. Gordon, Steven M. Nelson, Mario Ortega, Kathleen B. McDermott, Caterina Gratton, Ally Dworetsky, Steven E. Petersen, Benjamin A. Seitzman, Christina N. Lessov-Schlaggar, Timothy O. Laumann, Bradley L. Schlaggar, Jeffrey J. Berg, Annie L. Nguyen, Adrian W. Gilmore
Rok vydání: 2019
Předmět:
Zdroj: Proceedings of the National Academy of Sciences. 116:22851-22861
ISSN: 1091-6490
0027-8424
DOI: 10.1073/pnas.1902932116
Popis: 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.
Databáze: OpenAIRE