Unrevealing Reliable Cortical Parcellation of Individual Brains Using Resting-State Functional Magnetic Resonance Imaging and Masked Graph Convolutions.

ABSTRACT: Brain parcellation helps to understand the structural and functional organization of the cerebral cortex. Resting-state functional magnetic resonance imaging (fMRI) and connectivity analysis provide useful information to delineate individual brain parcels in vivo. We proposed an individualized cortical parcellation based on graph neural networks (GNN) to learn the reliable functional characteristics of each brain parcel on a large fMRI dataset and to infer the areal probability of each vertex on unseen subjects. A subject-specific confidence mask was implemented in the GNN model to account for the tradeoff between the topographic alignment across subjects and functional homogeneity of brain parcels on individual brains. The individualized brain parcellation achieved better functiona

SUBMITTER: Qiu W 

PROVIDER: S-EPMC8959420 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature