Network variants are similar between task and rest states

Abstract

Recent work has demonstrated that individual-specific variations in functional networks (that we call "network variants") can be identified in individuals using functional magnetic resonance imaging (fMRI). These network variants exhibit reliability over time with resting-state fMRI data. These properties have suggested that network variants may be trait-like markers of individual differences in brain organization. Another test of this conclusion would be to examine if network variants 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 different 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.