Laboratory of Neuromotor Physiology, Santa Lucia Foundation Rome, Italy.
Front Comput Neurosci. 2013 Apr 19;7:42. doi: 10.3389/fncom.2013.00042. eCollection 2013.
Controlling the movement of the arm to achieve a goal, such as reaching for an object, is challenging because it requires coordinating many muscles acting on many joints. The central nervous system (CNS) might simplify the control of reaching by directly mapping initial states and goals into muscle activations through the combination of muscle synergies, coordinated recruitment of groups of muscles with specific activation profiles. Here we review recent results from the analysis of reaching muscle patterns supporting such a control strategy. Muscle patterns for point-to-point movements can be reconstructed by the combination of a small number of time-varying muscle synergies, modulated in amplitude and timing according to movement directions and speeds. Moreover, the modulation and superposition of the synergies identified from point-to-point movements captures the muscle patterns underlying multi-phasic movements, such as reaching through a via-point or to a target whose location changes after movement initiation. Thus, the sequencing of time-varying muscle synergies might implement an intermittent controller which would allow the construction of complex movements from simple building blocks.
控制手臂的运动以达到目标,例如伸手去拿物体,这是具有挑战性的,因为它需要协调作用于多个关节的许多肌肉。中枢神经系统(CNS)可能通过肌肉协同作用的组合,直接将初始状态和目标映射到肌肉激活中,从而简化了对伸展的控制,这些肌肉协同作用协调了具有特定激活模式的肌肉群的募集。在这里,我们回顾了最近关于支持这种控制策略的伸展肌肉模式分析的结果。通过组合少量随时间变化的肌肉协同作用,可以重建点对点运动的肌肉模式,并根据运动方向和速度来调制幅度和时间。此外,从点对点运动中识别出的协同作用的调制和叠加捕获了多相运动(例如,通过中间点或到达目标)背后的肌肉模式,其中目标的位置在运动开始后发生变化。因此,时变肌肉协同作用的顺序可能实现了一种间歇控制器,该控制器可以从简单的构建块构建复杂的运动。