Pundik Svetlana, Skelly Margaret M, McCabe Jessica P, Salameh Ahlam I, Anderson Trenley, Duncan Kelsey Rose, Hisel Terri, Carr Sarah J A
Department of Veterans Affairs Northeast Ohio Healthcare System (VANEOHS), Cleveland, Ohio, USA.
School of Medicine, Case Western Reserve University, Cleveland, Ohio, USA.
Brain Behav. 2025 May;15(5):e70519. doi: 10.1002/brb3.70519.
Stroke disrupts functional brain connectivity, yet how this relates to lower limb motor and sensory abilities is not well understood. Greater knowledge of movement-related brain connectivity can aide in the development of better interventions for recovery after stroke. Our objective was to evaluate the relationship between lower limb performance and resting-state functional connectivity (rsFC) of large-scale brain networks for individuals with chronic motor deficits (> 6 months) after stroke.
Resting-state functional magnetic resonance imaging and lower limb clinical measures were collected for 37 individuals. Regions of interest (ROI)-to-ROI connectivity analysis was conducted for cortical sensorimotor network (SMN) (cortical SMN), SMN with both cortical and subcortical ROIs (SMN), and default mode network (DMN). Relationship of ROI-ROI connectivity and clinical measures or lesion load was assessed using general linear models. Graph theory metrics (global efficiency, clustering coefficient, and betweenness centrality) were related to clinical measures using elastic nets analysis.
Greater connectivity between several SMN and DMN ROI pairs was associated with better gait speed, Timed-Up-and-Go score, and monofilament perception. The majority of ROI pairs showing statistically significant relationship with clinical measures were interhemispheric, non-homologous, and cortical-to-subcortical. Elastic net analysis for graph theory metrics revealed complexity and multi-directionality of the relationship of the individual ROIs to clinical outcomes and lesion load. There were unique sets of ROIs associated with each clinical measure for different graph metrics.
rsFC between specific ROIs within SMN and DMN are related to lower limb performance. Non-homologous interhemispheric ROI-to-ROI connectivity was featured in the analysis. Graph theory analysis demonstrates the complex role that an individual ROI has in relation to sensorimotor function of lower extremity.
Clinicialtrials.gov registration number NCT03666533.
中风会破坏大脑的功能连接，但这种破坏与下肢运动和感觉能力之间的关系尚不清楚。深入了解与运动相关的大脑连接，有助于开发更好的中风后康复干预措施。我们的目标是评估中风后慢性运动功能缺损（>6个月）患者的下肢功能与大规模脑网络静息态功能连接（rsFC）之间的关系。
收集了37名个体的静息态功能磁共振成像数据和下肢临床测量数据。对皮质感觉运动网络（SMN）（皮质SMN）、包含皮质和皮质下感兴趣区域（ROI）的SMN以及默认模式网络（DMN）进行了ROI间连接性分析。使用一般线性模型评估ROI间连接性与临床测量指标或病变负荷之间的关系。通过弹性网分析将图论指标（全局效率、聚类系数和介数中心性）与临床测量指标相关联。
多个SMN和DMN的ROI对之间更强的连接性与更好的步态速度、计时起立行走测试得分和单丝觉相关。大多数与临床测量指标呈现统计学显著关系的ROI对是半球间、非同源且皮质到皮质下的。图论指标的弹性网分析揭示了各个ROI与临床结果及病变负荷之间关系的复杂性和多向性。不同的图指标与每个临床测量指标相关联的ROI集各不相同。
SMN和DMN内特定ROI之间的rsFC与下肢功能相关。分析中呈现出非同源半球间ROI到ROI的连接性。图论分析表明个体ROI在下肢感觉运动功能中发挥的复杂作用。
Clinicaltrials.gov注册号NCT03666533。
