MOVE Research Institute, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands;
MOVE Research Institute, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands; Donders Institute for Brain, Cognition and Behavior, Radboud University, Nijmegen Medical Centre, Nijmegen, The Netherlands;
J Appl Physiol (1985). 2014 May 15;116(10):1263-71. doi: 10.1152/japplphysiol.01092.2013. Epub 2014 Mar 20.
Many studies have addressed corticomuscular coherence (CMC), but broad applications are limited by low coherence values and the variability across subjects and recordings. Here, we investigated how the use of high-density surface electromyography (HDsEMG) can improve the detection of CMC. Sixteen healthy subjects performed isometric contractions at six low-force levels using a pinch-grip, while HDsEMG of the adductor pollicis transversus and flexor and abductor pollicis brevis and whole-head magnetoencephalography were recorded. Different configurations were constructed from the HDsEMG grid, such as a bipolar and Laplacian montage, as well as a montage based on principal component analysis (PCA). CMC was estimated for each configuration, and the strength of coherence was compared across configurations. As expected, performance of the precision-grip task resulted in significant CMC in the β-frequency band (16-26 Hz). Compared with a bipolar EMG montage, all multichannel configurations obtained from the HDsEMG grid revealed a significant increase in CMC. The configuration, based on PCA, showed the largest (37%) increase. HDsEMG did not reduce the between-subject variability; rather, many configurations showed an increased coefficient of variation. Increased CMC presumably reflects the ability of HDsEMG to counteract inherent EMG signal factors-such as amplitude cancellation-which impact the detection of oscillatory inputs. In contrast, the between-subject variability of CMC most likely has a cortical origin.
许多研究都涉及皮质肌层相干性(CMC),但由于相干值较低以及在不同个体和记录之间的可变性,其广泛应用受到限制。在这里,我们研究了高密度表面肌电图(HDsEMG)的使用如何提高 CMC 的检测。16 名健康受试者使用夹握力在六个低力水平下进行等长收缩,同时记录拇指对掌横肌、屈肌和展肌的 HDsEMG 以及全头脑磁图。从 HDsEMG 网格构建了不同的配置,例如双极和拉普拉斯蒙太奇,以及基于主成分分析(PCA)的蒙太奇。为每个配置估计了 CMC,并比较了配置之间的相干强度。正如预期的那样,精密抓握任务的表现导致β频带(16-26 Hz)的 CMC 显著。与双极肌电图蒙太奇相比,从 HDsEMG 网格获得的所有多通道配置均显示 CMC 显著增加。基于 PCA 的配置显示出最大的(37%)增加。HDsEMG 并没有降低个体间的可变性;相反,许多配置显示出变异系数增加。增加的 CMC 可能反映了 HDsEMG 对抗固有肌电图信号因素的能力,例如幅度抵消,这会影响对振荡输入的检测。相比之下,CMC 的个体间可变性很可能具有皮质起源。