Laine Christopher M, Valero-Cuevas Francisco J
Brain-Body Dynamics Laboratory, Department of Biomedical Engineering, Division of Biokinesiology and Physical Therapy, University of Southern California, Los Angeles, California.
Brain-Body Dynamics Laboratory, Department of Biomedical Engineering, Division of Biokinesiology and Physical Therapy, University of Southern California, Los Angeles, California
J Neurophysiol. 2017 Sep 1;118(3):1775-1783. doi: 10.1152/jn.00204.2017. Epub 2017 Jun 28.
Coherence analysis has the ability to identify the presence of common descending drive shared by motor unit pools and reveals its spectral properties. However, the link between spectral properties of shared neural drive and functional interactions among muscles remains unclear. We assessed shared neural drive between muscles of the thumb and index finger while participants executed two mechanically distinct precision pinch tasks, each requiring distinct functional coordination among muscles. We found that shared neural drive was systematically reduced or enhanced at specific frequencies of interest (~10 and ~40 Hz). While amplitude correlations between surface EMG signals also exhibited changes across tasks, only their coherence has strong physiological underpinnings indicative of neural binding. Our results support the use of intermuscular coherence as a tool to detect when coactivated muscles are members of a functional group or synergy of neural origin. Furthermore, our results demonstrate the advantages of considering neural binding at 10, ~20, and >30 Hz, as indicators of task-dependent neural coordination strategies. It is often unclear whether correlated activity among muscles reflects their neural binding or simply reflects the constraints defining the task. Using the fact that high-frequency coherence between EMG signals (>6 Hz) is thought to reflect shared neural drive, we demonstrate that coherence analysis can reveal the neural origin of distinct muscle coordination patterns required by different tasks.
相干分析能够识别运动单位池共享的共同下行驱动的存在,并揭示其频谱特性。然而,共享神经驱动的频谱特性与肌肉之间功能相互作用的联系仍不清楚。我们在参与者执行两项机械上不同的精确捏取任务时,评估了拇指和食指肌肉之间的共享神经驱动,每项任务都需要肌肉之间不同的功能协调。我们发现,在特定的感兴趣频率(约10赫兹和约40赫兹)下,共享神经驱动会系统性地降低或增强。虽然表面肌电图信号之间的幅度相关性在不同任务中也表现出变化,但只有它们的相干性具有表明神经联结的强大生理基础。我们的结果支持将肌间相干性用作一种工具,以检测共同激活的肌肉何时是神经起源的功能组或协同作用的成员。此外,我们的结果证明了将10赫兹、约20赫兹和大于30赫兹的神经联结作为任务依赖性神经协调策略指标的优势。肌肉之间的相关活动究竟是反映了它们的神经联结还是仅仅反映了定义任务的限制,通常并不明确。利用肌电图信号之间的高频相干性(>6赫兹)被认为反映共享神经驱动这一事实,我们证明了相干分析可以揭示不同任务所需的不同肌肉协调模式的神经起源。