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揭示肌肉协同作用的神经基础的方法:综述与批判。

Approaches to revealing the neural basis of muscle synergies: a review and a critique.

机构信息

School of Biomedical Sciences and The Gerald Choa Neuroscience Centre, The Chinese University of Hong Kong, Hong Kong, China.

Department of Neurophysiology, National Institute of Neuroscience, Kodaira, Tokyo, Japan.

出版信息

J Neurophysiol. 2021 May 1;125(5):1580-1597. doi: 10.1152/jn.00625.2019. Epub 2021 Mar 17.

Abstract

The central nervous system (CNS) may produce coordinated motor outputs via the combination of motor modules representable as muscle synergies. Identification of muscle synergies has hitherto relied on applying factorization algorithms to multimuscle electromyographic data (EMGs) recorded during motor behaviors. Recent studies have attempted to validate the neural basis of the muscle synergies identified by independently retrieving the muscle synergies through CNS manipulations and analytic techniques such as spike-triggered averaging of EMGs. Experimental data have demonstrated the pivotal role of the spinal premotor interneurons in the synergies' organization and the presence of motor cortical loci whose stimulations offer access to the synergies, but whether the motor cortex is also involved in organizing the synergies has remained unsettled. We argue that one difficulty inherent in current approaches to probing the synergies' neural basis is that the EMG generative model based on linear combination of synergies and the decomposition algorithms used for synergy identification are not grounded on enough prior knowledge from neurophysiology. Progress may be facilitated by constraining or updating the model and algorithms with knowledge derived directly from CNS manipulations or recordings. An investigative framework based on evaluating the relevance of neurophysiologically constrained models of muscle synergies to natural motor behaviors will allow a more sophisticated understanding of motor modularity, which will help the community move forward from the current debate on the neural versus nonneural origin of muscle synergies.

摘要

中枢神经系统 (CNS) 可能通过代表肌肉协同作用的运动模块的组合来产生协调的运动输出。肌肉协同作用的识别迄今为止依赖于将分解算法应用于运动行为期间记录的多肌肉肌电图 (EMG) 数据。最近的研究试图通过 CNS 操作和分析技术(例如 EMG 的尖峰触发平均)来验证通过独立检索肌肉协同作用所确定的神经基础。实验数据证明了脊髓前运动神经元在协同作用组织中的关键作用,以及存在运动皮质部位,其刺激可以获得协同作用,但运动皮质是否也参与协同作用的组织仍未解决。我们认为,探测协同作用神经基础的当前方法所固有的一个困难是,基于协同作用的线性组合的 EMG 生成模型和用于协同作用识别的分解算法没有基于来自神经生理学的足够先验知识。通过直接从 CNS 操作或记录中获取知识来约束或更新模型和算法,可能会促进进展。基于评估神经生理学约束肌肉协同作用模型与自然运动行为相关性的研究框架,将允许对运动模块性有更深入的理解,这将有助于社区从当前关于肌肉协同作用的神经与非神经起源的争论向前发展。

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