Disrupted intrinsic functional brain topology in patients with basal ganglia ischemic stroke

基底节缺血性卒中患者的固有功能性脑拓扑结构紊乱

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Abstract

BACKGROUND: Ischemic stroke affecting the basal ganglia disrupts motor, cognitive, and emotional functions, yet the underlying neural network mechanisms remain poorly understood. This study aimed to investigate alterations in brain network topology in patients with acute basal ganglia ischemic stroke (BGIS) through use of resting-state functional magnetic resonance imaging (rs-fMRI) and graph theory analysis (GTA). METHODS: We constructed whole-brain functional networks and analyzed global and local topological properties in 82 patients with acute BGIS and compared them those in 83 healthy controls (HCs) using the Dosenbach atlas. RESULTS: Both groups retained small-world attributes (Sigma >1). However, patients with BGIS exhibited significantly lower normalized clustering coefficient (Gamma, P=0.016), small-worldness (Sigma, P=0.021), and modularity (P=0.025), indicating disrupted local network organization. Local centrality analyses revealed significantly higher degree centrality (DC) (false-discovery rate-corrected Q <0.05), betweenness centrality (Q <0.05), and eigenvector centrality (Q <0.05) in the right precentral gyrus (a motor hub) in patients with BGIS. Conversely, lower centrality was observed in cognitive and emotional hubs, including the left ventral prefrontal cortex (Q <0.05 for DC, betweenness centrality, and eigenvector centrality) and the right dorsolateral superior frontal gyrus (Q <0.05 for DC). Global efficiency and assortativity were preserved (P>0.05). No direct associations between these network alterations and clinical scales persistent in the multiple comparisons. CONCLUSIONS: This study identified a BGIS-induced reconfiguration of brain network topology, characterized by a tendency toward randomization, compensatory hyperconnectivity in motor regions, and impaired integration in cognitive networks. The findings indicated the right precentral gyrus to be a pivotal hub for poststroke recovery and offers novel insights into network-level mechanisms and potential targets for neuromodulatory interventions.

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