Biomechanics, Rehabilitation, and Integrative Neuroscience (BRaIN) Lab, UC Davis School of Medicine, Sacramento, CA, USA.
UC Davis Center for Neuroengineering and Medicine, University of California, Davis, Davis, CA, USA.
Sci Rep. 2022 May 27;12(1):8953. doi: 10.1038/s41598-022-12225-1.
Stroke survivors often exhibit gait dysfunction which compromises self-efficacy and quality of life. Muscle Synergy Analysis (MSA), derived from electromyography (EMG), has been argued as a method to quantify the complexity of descending motor commands and serve as a direct correlate of neural function. However, controversy remains regarding this interpretation, specifically attribution of MSA as a neuromarker. Here we sought to determine the relationship between MSA and accepted neurophysiological parameters of motor efficacy in healthy controls, high (HFH), and low (LFH) functioning stroke survivors. Surface EMG was collected from twenty-four participants while walking at their self-selected speed. Concurrently, transcranial magnetic stimulation (TMS) was administered, during walking, to elicit motor evoked potentials (MEPs) in the plantarflexor muscles during the pre-swing phase of gait. MSA was able to differentiate control and LFH individuals. Conversely, motor neurophysiological parameters, including soleus MEP area, revealed that MEP latency differentiated control and HFH individuals. Significant correlations were revealed between MSA and motor neurophysiological parameters adding evidence to our understanding of MSA as a correlate of neural function and highlighting the utility of combining MSA with other relevant outcomes to aid interpretation of this analysis technique.
中风幸存者常表现出行走功能障碍，这会降低其自我效能感和生活质量。肌协同分析（MSA）源自肌电图（EMG），被认为是量化下行运动指令复杂性的一种方法，并可作为神经功能的直接相关物。然而，对于这种解释仍然存在争议，特别是将 MSA 归因于神经标志物。在这里，我们试图确定 MSA 与健康对照组、高功能（HFH）和低功能（LFH）中风幸存者的公认运动效能神经生理学参数之间的关系。我们从二十四名参与者中收集了表面肌电图，同时让他们以自定速度行走。在行走过程中，我们同时进行经颅磁刺激（TMS），以在行走的预摆阶段诱发足底屈肌的运动诱发电位（MEP）。MSA 能够区分对照组和 LFH 个体。相反，运动神经生理学参数，包括比目鱼肌 MEP 面积，表明 MEP 潜伏期区分了对照组和 HFH 个体。MSA 与运动神经生理学参数之间存在显著相关性，这为我们理解 MSA 作为神经功能的相关物提供了更多证据，并强调了将 MSA 与其他相关结果相结合以辅助解释这种分析技术的实用性。
