Network variants are similar between task and rest states

Brian T. Kraus, Diana Perez, Zach Ladwig, Benjamin A. Seitzman, Ally Dworetsky, Steven E. Petersen, Caterina Gratton*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

10 Scopus citations


Recent work has demonstrated that individual-specific variations in functional networks (termed “network variants”) can be identified in individuals using resting state functional magnetic resonance imaging (fMRI). These network variants exhibit reliability over time, suggesting that they may be trait-like markers of individual differences in brain organization. However, while networks variants are reliable at rest, is is still untested whether they are stable between task and rest states. Here, we use precision data from the Midnight Scan Club (MSC) to demonstrate that (1) task data can be used to identify network variants reliably, (2) these network variants show substantial spatial overlap with those observed in rest, although state-specific effects are present, (3) network variants assign to similar canonical functional networks in task and rest states, and (4) single tasks or a combination of multiple tasks produce similar network variants to rest. Together, these findings further reinforce the trait-like nature of network variants and demonstrate the utility of using task data to define network variants.

Original languageEnglish (US)
Article number117743
StatePublished - Apr 1 2021

ASJC Scopus subject areas

  • Neurology
  • Cognitive Neuroscience


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