Altered Granger Causal Connectivity of Resting-State Neural Networks in Patients With Leukoaraiosis-Associated Cognitive Impairment—A Cross-Sectional Study

Abstract

Background: The purpose of this study was to provide an imaging reference for the measurement of disease progression, as well as to reveal the pathogenesis of leukoaraiosis (LA). Methods: Eighty-seven subjects were divided into three groups: LA patients with vascular dementia (LA-VaD) (20 subjects: 14 female, 6 male), LA patients with vascular cognitive impairment nondementia (LA-VCIND) (32 subjects: 14 male, 18 female), and normal controls (NC) (35 subjects: 14 male, 21 female). A multivariate Granger causality analysis (mGCA) was applied to the resting-state networks (RSNs) to evaluate the possible effective connectivity within the resting-state networks retrieved by independent component analysis (ICA) from resting-state functional magnetic resonance imaging (rs-fMRI) data. Results: Ten RSNs were identified: the primary visual network, secondary visual network, auditory network, sensorimotor network, anterior default mode network, posterior default mode network, salience network, dorsal attention network, left working memory network, and the right working memory network. Using independent component analysis, significant average Z scores were found in the anterior default mode network, salience network, dorsal attention network, and right working memory network between LA-VAD and NC groups. The functional connectivity (FC) strength of the networks was different between the NC, LA-VCIND, and LA-VaD groups. Effective connectivity between RSNs was compensated by either increased or decreased effective connectivity changes in these three groups. Conclusions: The components of resting-state networks kept changing as the disease progressed. Meanwhile, the activation intensity increased at the early stage of LA and decreased as patients' cognitive impairment aggravated. Furthermore, the direction and strength of connections between these networks changed and remodeled differently. These suggest that the human brain compensates for specific functional changes at different stages.