Brain Mapping of Behavioral Domains Using Multi-Scale Networks and Canonical Correlation Analysis.

ABSTRACT: Simultaneous mapping of multiple behavioral domains into brain networks remains a major challenge. Here, we shed some light on this problem by employing a combination of machine learning, structural and functional brain networks at different spatial resolutions (also known as scales), together with performance scores across multiple neurobehavioral domains, including sensation, motor skills, and cognition. Provided by the Human Connectome Project, we make use of three cohorts: 640 participants for model training, 160 subjects for validation, and 200 subjects for model performance testing thus enhancing prediction generalization. Our modeling consists of two main stages, namely dimensionality reduction in brain network features at multiple scales, followed by canonical correlation analysis,

SUBMITTER: Fernandez-Iriondo I 

PROVIDER: S-EPMC9255673 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature