Скачать или смотреть Network Variants Show Stability Across Task and Rest States (Brian Kraus, MA)

In this talk, I will review recent work showing 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. While the reliability of network variants has previously been demonstrated at rest, here I present evidence on their stability across rest and task states. Using precision data from the Midnight Scan Club (MSC), I will discuss how (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. I will then talk about how this result opens up many new datasets for network variant analysis, and how I plan to utilize this finding for analyzing datasets from clinical populations.