Identifying covariate-related subnetworks for whole-brain connectome analysis.

ABSTRACT: Whole-brain connectome data characterize the connections among distributed neural populations as a set of edges in a large network, and neuroscience research aims to systematically investigate associations between brain connectome and clinical or experimental conditions as covariates. A covariate is often related to a number of edges connecting multiple brain areas in an organized structure. However, in practice, neither the covariate-related edges nor the structure is known. Therefore, the understanding of underlying neural mechanisms relies on statistical methods that are capable of simultaneously identifying covariate-related connections and recognizing their network topological structures. The task can be challenging because of false-positive noise and almost infinite possibilities of

SUBMITTER: Chen S 

PROVIDER: S-EPMC11017127 | biostudies-literature | 2024 Apr

REPOSITORIES: biostudies-literature