Closed-Loop Construction and Analysis of Cortico-Muscular-Cortical Functional Network After Stroke

磁刺激 神经科学 运动皮层 冲程(发动机) 初级运动皮层 透视图(图形) 电动机系统 电动机控制 功能磁共振成像 心理学 计算机科学 物理医学与康复 刺激 医学 人工智能 物理 热力学
作者
Jinbiao Liu,Gansheng Tan,Jixian Wang,Yina Wei,Yixuan Sheng,Hui Meng Chang,Qing Xie,Honghai Liu
出处
期刊:IEEE Transactions on Medical Imaging [Institute of Electrical and Electronics Engineers]
卷期号:41 (6): 1575-1586 被引量:7
标识
DOI:10.1109/tmi.2022.3143133
摘要

Brain networks allow a topological understanding into the pathophysiology of stroke-induced motor deficits, and have been an influential tool for investigating brain functions. Unfortunately, currently applied methods generally lack in the recognition of the dynamic changes in the cortical networks related to muscle activity, which is crucial to clarify the alterations of the cooperative working patterns in the motor control system after stroke. In this study, we integrate corticomuscular and intermuscular interactions to cortico-cortical network and propose a novel closed-loop construction of cortico-muscular-cortical functional network, named closed-loop network (CLN). Directional characteristic in terms of differentiating causal interactions is endowed on basis of the CLN framework, further expanding the definition of functional connectivity (FC) and effective connectivity (EC) dedicated to CLN. Next, CLN is applied to stroke patients to reveal the underlying after-effects mechanism of low frequency repetitive transcranial magnetic stimulation (rTMS) induced alterations of cortical physiologic functions during movement. Results show that the short-term modulation of rTMS is reflected in the enhancement of information interaction within the interhemispheric primary motor regions and inhibition of the coupling between motor cortex and effector muscles. CLN provides a new perspective for the study of motor-related cortical networks with muscle activities involvement instead of being restricted to brain network analysis of behaviors.
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