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Evidence that robot-assisted gait training modulates neuroplasticity after stroke: An fMRI pilot study based on graph theory analysis

步态训练 冲程(发动机) 物理医学与康复 神经可塑性 康复 心理学 磁共振成像 功能磁共振成像 医学 物理疗法 内科学 神经科学 放射科 机械工程 工程类
作者
Zhiqing Tang,Yaxian Zhao,Xinting Sun,Ying Liu,Wenlong Su,Tianhao Liu,Xiaonian Zhang,Hao Zhang
出处
期刊:Brain Research [Elsevier BV]
卷期号:1842: 149113-149113
标识
DOI:10.1016/j.brainres.2024.149113
摘要

To investigate alterations of whole-brain network after stroke and therapeutic mechanisms of robot-assisted gait training (RAGT). 21 S patients and 20 healthy subjects were enrolled, with the stroke patients randomized to either control group (n = 11) or robot group (n = 10), and resting-state functional magnetic resonance imaging data were collected. The global network metrics were obtained using graph theory analysis and compared between stroke patients and healthy subjects, and the effect of the RAGT on the whole-brain networks was explored. Compared to healthy subjects, area under the curve (AUC) for small-worldness (σ), clustering coefficient (Cp), global efficiency (Eg) and mean local efficiency (Eloc) were significantly lower in stroke patients, whereas AUC for characteristic path length (Lp) were significantly higher. Compared with the control group, patients in robot group showed significant improvement in lower limb motor function, balance function and walking function after intervention, with a significant reduction in the AUC of Cp. Moreover, the improvement of walking function was positively correlated with the changes of AUC of σ and Eg, and negatively correlated with the changes of AUC of Cp. Small-worldness and network efficiency were significantly reduced after stroke, whereas RAGT decreased characteristic path length and promoted normalization of the whole-brain network, and this change was associated with improvement in walking function. Our findings reveal the mechanism by which RAGT regulates network reorganization and neuroplasticity after stroke.
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