IEEE Trans Neural Syst Rehabil Eng. 2017 Dec;25(12):2427-2440. doi: 10.1109/TNSRE.2017.2769659.
Functional tasks of the upper extremity can be executed by a variety of muscular patterns, independent of the direction, speed and load of the task. This large number of degrees of freedom imposes a significant control burden on the CNS. Previous studies suggested that the human cortex synchronizes a discrete number of neural functional units within the brainstem and spinal cord, i.e. muscle synergies, by linearly combining them to execute a great repertoire of movements. Further exploring this control mechanism, we aim to study whether a single set of muscle synergies might be generalized to express movements in different directions. This was implemented by using a modified version of the non-negative matrix factorization algorithm on EMG data sets of the upper extremity of healthy people. Our twelve participants executed hand-reaching movements in multiple directions. Muscle synergies that were extracted from movements to the center of the reaching space could be generalized to synergies for other movement directions. This finding was also supported by the application of a weighted correlation matrix, the similarity index and the results of the K-means cluster analysis. This might reinforce the notion that the CNS flexibly combines a single set of small number of synergies in different amplitudes to modulate movement for different directions.
上肢的功能任务可以通过多种肌肉模式来完成,而与任务的方向、速度和负荷无关。这种大量的自由度给中枢神经系统带来了巨大的控制负担。先前的研究表明,人类大脑皮层通过线性组合这些神经功能单元(即肌肉协同作用)来同步脑干和脊髓内的离散数量的神经功能单元,以执行大量的运动。为了进一步探索这种控制机制,我们旨在研究一组肌肉协同作用是否可以推广到表达不同方向的运动。这是通过使用一种改进的非负矩阵分解算法,对健康人上肢的肌电图数据集进行实现的。我们的 12 名参与者执行了多个方向的手伸运动。从到达空间中心的运动中提取的肌肉协同作用可以推广到其他运动方向的协同作用。这一发现也得到了加权相关矩阵、相似指数和 K-均值聚类分析结果的支持。这可能加强了这样一种观点,即中枢神经系统灵活地组合了少量的协同作用,以不同的幅度来调节不同方向的运动。