Cheung Vincent C K, d'Avella Andrea, Bizzi Emilio
McGovern Institute for Brain Research, MIT, Cambridge, MA 02139, USA.
J Neurophysiol. 2009 Mar;101(3):1235-57. doi: 10.1152/jn.01387.2007. Epub 2008 Dec 17.
It has been suggested that the motor system may circumvent the difficulty of controlling many degrees of freedom in the musculoskeletal apparatus by generating motor outputs through a combination of discrete muscle synergies. How a discretely organized motor system compensates for diverse perturbations has remained elusive. Here, we investigate whether motor responses observed after an inertial-load perturbation can be generated by altering the recruitment of synergies normally used for constructing unperturbed movements. Electromyographic (EMG, 13 muscles) data were collected from the bullfrog hindlimb during natural behaviors before, during, and after the same limb was loaded by a weight attached to the calf. Kinematic analysis reveals the absence of aftereffect on load removal, suggesting that load-related EMG changes were results of immediate motor pattern adjustments. We then extracted synergies from EMGs using the nonnegative matrix factorization algorithm and developed a procedure for assessing the extent of synergy sharing across different loading conditions. Most synergies extracted were found to be activated in all loaded and unloaded conditions. However, for certain synergies, the amplitude, duration, and/or onset time of their activation bursts were up- or down-modulated during loading. Behavioral parameterizations reveal that load-related modulation of synergy activations depended on the behavioral variety (e.g., kick direction and amplitude) and the movement phase performed. Our results suggest that muscle synergies are robust across different dynamic conditions and immediate motor adjustments can be accomplished by modulating synergy activations. An appendix describes the novel procedure we developed, useful for discovering shared and specific features from multiple data sets.
有人提出，运动系统可能通过离散肌肉协同作用的组合产生运动输出，从而规避在肌肉骨骼系统中控制多个自由度的困难。一个离散组织的运动系统如何补偿各种扰动仍然不清楚。在这里，我们研究了在惯性负载扰动后观察到的运动反应是否可以通过改变通常用于构建未受扰动运动的协同作用的募集来产生。在同一肢体被绑在小腿上的重物加载之前、期间和之后的自然行为中，从牛蛙后肢收集肌电图（EMG，13块肌肉）数据。运动学分析表明，负载移除后没有后效，这表明与负载相关的肌电图变化是即时运动模式调整的结果。然后，我们使用非负矩阵分解算法从肌电图中提取协同作用，并开发了一种程序来评估不同负载条件下协同作用共享的程度。发现大多数提取的协同作用在所有加载和未加载条件下都被激活。然而，对于某些协同作用，其激活爆发的幅度、持续时间和/或起始时间在加载过程中被上调或下调。行为参数化表明，协同作用激活的负载相关调制取决于行为多样性（例如，踢腿方向和幅度）和执行的运动阶段。我们的结果表明，肌肉协同作用在不同的动态条件下是稳健的，即时运动调整可以通过调节协同作用激活来实现。附录描述了我们开发的新程序，该程序有助于从多个数据集中发现共享和特定特征。
