Brain Behav. 2026 Aug;16(8):e71667. doi: 10.1002/brb3.71667.
ABSTRACT
BACKGROUND: While structural covariance analysis is adept at assessing morphometric correlations among broadly distributed brain regions, limited research has focused on alterations in structural covariance networks post-stroke. This study aims to identify significant brain gray matter changes and distinct structural covariance patterns in stroke patients.
METHODS: Nineteen post-stroke patients (17 males, aged 50.79 ± 11.98 years) and 19 healthy controls (11 males, 44.32 ± 13.34 years) underwent structural magnetic resonance imaging. Source-based morphometry (SBM) analysis was utilized to explore alterations in independent components representing gray matter structural networks. Between-group comparisons were performed while controlling for age and gender. Structural covariance networks were constructed to explore changes in these patterns among stroke patients.
RESULTS: SBM analysis identified 13 independent components (ICs). Compared to controls, post-stroke patients exhibited significant alterations in gray matter in the subcortical network (IC 4, IC 8, and IC 10). Additionally, in post-stroke patients, there was a reduction in structural covariance between the subcortical-cerebellar networks, accompanied by an increase between the subcortical-prefrontal networks.
CONCLUSION: The present findings highlight structural abnormalities within the subcortical network and significant alterations in the structural interactions between the subcortical, cerebellar, and prefrontal networks in stroke patients. The observed findings suggest large-scale anatomical reorganization following stroke and provide insight into network-level neuroanatomical alterations associated with post-stroke functional deficits.
PMID:42603270 | DOI:10.1002/brb3.71667