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肌肉协同作用的时间控制与 alpha 波段神经驱动有关。

Temporal control of muscle synergies is linked with alpha-band neural drive.

机构信息

Chan Division of Occupational Science and Occupational Therapy, University of Southern California, Los Angeles, CA, USA.

Department of Computer Science, University of Southern California, Los Angeles, CA, USA.

出版信息

J Physiol. 2021 Jul;599(13):3385-3402. doi: 10.1113/JP281232. Epub 2021 May 31.

Abstract

KEY POINTS

It is theorized that the nervous system controls groups of muscles together as functional units, or 'synergies', resulting in correlated electromyographic (EMG) signals among muscles. However, such correlation does not necessarily imply group-level neural control. Oscillatory synchronization (coherence) among EMG signals implies neural coupling, but it is not clear how this relates to control of muscle synergies. EMG was recorded from seven arm muscles of 10 adult participants rotating an upper limb ergometer, and EMG-EMG coherence, EMG amplitude correlations and their relationship with each other were characterized. A novel method to derive multi-muscle synergies from EMG-EMG coherence is presented and these are compared with classically defined synergies. Coherent alpha-band (8-16 Hz) drive was strongest among muscles whose gross activity levels are well correlated within a given task. The cross-muscle distribution and temporal modulation of coherent alpha-band drive suggests a possible role in the neural coordination/monitoring of synergies.

ABSTRACT

During movement, groups of muscles may be controlled together by the nervous system as an adaptable functional entity, or 'synergy'. The rules governing when (or if) this occurs during voluntary behaviour in humans are not well understood, at least in part because synergies are usually defined by correlated patterns of muscle activity without regard for the underlying structure of their neural control. In this study, we investigated the extent to which comodulation of muscle output (i.e. correlation of electromyographic (EMG) amplitudes) implies that muscles share intermuscular neural input (assessed via EMG-EMG coherence analysis). We first examined this relationship among pairs of upper limb muscles engaged in an arm cycling task. We then applied a novel multidimensional EMG-EMG coherence analysis allowing synergies to be characterized on the basis of shared neural drive. We found that alpha-band coherence (8-16 Hz) is related to the degree to which overall muscle activity levels correlate over time. The extension of this coherence analysis to describe the cross-muscle distribution and temporal modulation of alpha-band drive revealed a close match to the temporal and structural features of traditionally defined muscle synergies. Interestingly, the coherence-derived neural drive was inversely associated with, and preceded, changes in EMG amplitudes by ∼200 ms. Our novel characterization of how alpha-band neural drive is dynamically distributed among muscles is a fundamental step forward in understanding the neural origins and correlates of muscle synergies.

摘要

要点

理论上,神经系统将肌肉群作为功能单元(或“协同作用”)进行控制,导致肌肉之间存在相关的肌电图(EMG)信号。然而,这种相关性并不一定意味着存在肌肉群水平的神经控制。EMG 信号之间的振荡同步(相干性)暗示着神经耦合,但尚不清楚这与肌肉协同作用的控制有何关系。对 10 名成年参与者旋转上肢测力计时的 7 块手臂肌肉进行了 EMG 记录,并对 EMG-EMG 相干性、EMG 幅度相关性及其相互关系进行了特征描述。提出了一种从 EMG-EMG 相干性中推导出多肌肉协同作用的新方法,并将其与经典定义的协同作用进行了比较。在给定任务中,肌肉的总体活动水平高度相关的情况下,相干的 alpha 波段(8-16 Hz)驱动力最强。相干 alpha 波段驱动力的跨肌肉分布和时变调制表明,它可能在协同作用的神经协调/监测中发挥作用。

摘要

在运动过程中,肌肉群可能作为一种适应性的功能实体(或“协同作用”)由神经系统一起控制。在人类自愿行为中,这种情况发生的时间(或是否发生)的规则尚不清楚,这至少部分是因为协同作用通常是通过肌肉活动的相关模式来定义的,而不考虑其神经控制的潜在结构。在这项研究中,我们调查了肌肉输出的共调制(即肌电图(EMG)幅度的相关性)在多大程度上暗示肌肉共享肌肉间神经输入(通过 EMG-EMG 相干分析评估)。我们首先研究了参与手臂循环任务的上肢肌肉对之间的这种关系。然后,我们应用了一种新的多维 EMG-EMG 相干分析方法,允许根据共享的神经驱动来描述协同作用。我们发现,alpha 波段相干性(8-16 Hz)与肌肉总体活动水平随时间相关的程度有关。将这种相干性分析扩展到描述 alpha 波段驱动的跨肌肉分布和时变调制,揭示了与传统定义的肌肉协同作用的时间和结构特征非常吻合。有趣的是,相干性衍生的神经驱动与 EMG 幅度的变化反向相关,且大约提前 200 ms。我们对 alpha 波段神经驱动如何在肌肉之间动态分布的新描述是理解肌肉协同作用的神经起源和相关性的重要一步。

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