Unknown

Dataset Information

Linked 4-Way Multimodal Brain Differences in Schizophrenia in a Large Chinese Han Population.


ABSTRACT: Multimodal fusion has been regarded as a promising tool to discover covarying patterns of multiple imaging types impaired in brain diseases, such as schizophrenia (SZ). In this article, we aim to investigate the covarying abnormalities underlying SZ in a large Chinese Han population (307 SZs, 298 healthy controls [HCs]). Four types of magnetic resonance imaging (MRI) features, including regional homogeneity (ReHo) from resting-state functional MRI, gray matter volume (GM) from structural MRI, fractional anisotropy (FA) from diffusion MRI, and functional network connectivity (FNC) resulted from group independent component analysis, were jointly analyzed by a data-driven multivariate fusion method. Results suggest that a widely distributed network disruption appears in SZ patients, with sync

SUBMITTER: Liu S 

PROVIDER: S-EPMC6403093 | biostudies-literature | 2019 Mar

REPOSITORIES: biostudies-literature