Individual-Specific Areal-Level Parcellations Improve Functional Connectivity Prediction of Behavior.

ABSTRACT: Resting-state functional magnetic resonance imaging (rs-fMRI) allows estimation of individual-specific cortical parcellations. We have previously developed a multi-session hierarchical Bayesian model (MS-HBM) for estimating high-quality individual-specific network-level parcellations. Here, we extend the model to estimate individual-specific areal-level parcellations. While network-level parcellations comprise spatially distributed networks spanning the cortex, the consensus is that areal-level parcels should be spatially localized, that is, should not span multiple lobes. There is disagreement about whether areal-level parcels should be strictly contiguous or comprise multiple noncontiguous components; therefore, we considered three areal-level MS-HBM variants spanning these range of poss

SUBMITTER: Kong R 

PROVIDER: S-EPMC8757323 | biostudies-literature | 2021 Aug

REPOSITORIES: biostudies-literature