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Updated: Jan 21, 2026

A Versatile Murine Model of Subcortical White Matter Stroke for the Study of Axonal Degeneration and White Matter Neurobiology
Published on: March 17, 2016
Dysfunctional Architecture Underlies White Matter Hyperintensities with and without Cognitive Impairment
Wenhao Zhu1, Hao Huang1, Shiqi Yang2
1Department of Neurology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Background:
White matter hyperintensities (WMH) are common in older adults and are associated with cognitive decline. However, little is known about the functional changes underlying cognitive decline in WMH subjects.
Objectives:
To investigate whole-brain functional connectivity (FC) underpinnings of cognitive decline in WMH subjects using univariate and multivariate analyses.
Methods:
Twenty-three WMH subjects with mild cognitive impairment (WMH-MCI), 43 WMH subjects with no cognitive impairment (WMH-nCI), and 55 healthy controls underwent resting-state functional MRI scans. Whole-brain FC was calculated using the fine-grained human Brainnetome Atlas, followed by performance of between-group comparisons and FC-cognition correlation analysis. A multivariate analysis using support vector machine (SVM) was performed to classify WMH-MCI and WMH-nCI subjects based on FC.
Results:
Both the WMH-MCI and WMH-nCI subjects exhibited characteristic impaired FC patterns. Markedly reduced FC involving subcortical nuclei and cortical hub regions of cognitive networks, especially the cingulate cortex, was identified in the WMH-MCI patients. In the WMH-MCI group, several connections involving the cingulate cortex were associated with cognitive decline. The exploratory mediation analyses indicated that FC alterations could partially explain the association between WMH and cognition. Furthermore, an SVM classifier based on FC distinguished WMH-MCI and WMH-nCI subjects with 78.8% accuracy. Connections that contributed most to the classification showed a similar distribution as the connections identified in the univariate analysis.
Conclusions:
This study provides a new window into the pathophysiology of cognitive impairment in WMH subjects and offer a novel and potential approach for early detection of the cognitive impairment in WMH subjects at the individual level.
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