The interaction between changes of muscle activation and cortical network dynamics during isometric elbow contraction: a sEMG and fNIRS study

作者：Xiaohan Wang, Zichong Luo, Mingxia Zhang, Weihua Zhao, Songyun Xie, Seng Fat Wong, Huijing Hu, Le Li · 发表于：Frontiers in Bioengineering and Biotechnology · 年份：2023 · DOI：10.3389/fbioe.2023.1176054 · 被引用次数：34 · 研究领域：Muscle activation and electromyography studies、Motor Control and Adaptation、Transcranial Magnetic Stimulation Studies

Objective: The relationship between muscle activation during motor tasks and cerebral cortical activity remains poorly understood. The aim of this study was to investigate the correlation between brain network connectivity and the non-linear characteristics of muscle activation changes during different levels of isometric contractions. Methods: Twenty-one healthy subjects were recruited and were asked to perform isometric elbow contractions in both dominant and non-dominant sides. Blood oxygen concentrations in brain from functional Near-infrared Spectroscopy (fNIRS) and surface electromyography (sEMG) signals in the biceps brachii (BIC) and triceps brachii (TRI) muscles were recorded simultaneously and compared during 80% and 20% of maximum voluntary contraction (MVC). Functional connectivity, effective connectivity, and graph theory indicators were used to measure information interaction in brain activity during motor tasks. The non-linear characteristics of sEMG signals, fuzzy approximate entropy (fApEn), were used to evaluate the signal complexity changes in motor tasks. Pearson correlation analysis was used to examine the correlation between brain network characteristic values and sEMG parameters under different task conditions. Results: The effective connectivity between brain regions in motor tasks in dominant side was significantly higher than that in non-dominant side under different contractions (p < 0.05). The results of graph theory analysis showed that the cluste...