Perception and Motor Systems Laboratory, School of Human Movement Studies, University of Queensland, Brisbane, Australia.
Hum Mov Sci. 2010 Oct;29(5):684-700. doi: 10.1016/j.humov.2010.01.008. Epub 2010 Jul 31.
Reaching to visual targets engages the nervous system in a series of transformations between sensory information and motor commands to muscles. We recently showed that visuomotor adaptation requiring modulation of the activity of the same muscles is more efficient than adaptation requiring a transition to different muscles. Here I specifically tested for adaptation at the level of the final transformation into muscle activation by assessing generalization to unpracticed areas of the workspace, and propose a computational model with modulation of muscle synergies. In the experiment, a visuomotor rotation was applied during a center-out isometric torque production task carefully configured such that adaptation and generalization could be achieved either by only rescaling the contribution of the same muscles, or by additionally requiring the recruitment of different muscles. Consistent with our previous finding, the time course of directional errors revealed that the degree of adaptation was substantially lower (by 28.1%) for the latter case. More importantly, directional error obtained for generalization that required, in principle, to recruit different muscles from these implicated in the adaptation was more than twice that of other generalization areas. Taken together, these results suggest that modulation within an original muscle synergy contributed to visuomotor adaptation, and that synergy recomposition imposed a limitation on both adaptation and generalization. I reproduced these results with a model of the sensorimotor transformation which includes two population codes, one for the sensory network and one for the motor network. Muscle synergies are defined as linear combination of muscles by connections of the motor network, and modulation of these synergies are elicited by adaptation of the weight of these connections. Finally, I speculate that the limitation imposed on synergy recomposition originates in the balance of inhibitory and excitatory mechanisms that operate at different levels of the nervous system, and that contribute to the functional organization of muscle recruitment by focusing activity on relevant muscles.
伸手去抓视觉目标会使神经系统在感觉信息和肌肉运动指令之间进行一系列转换。我们最近发现，需要调节同一肌肉活动的视动适应比需要过渡到不同肌肉的适应更有效。在这里，我通过评估对未练习工作空间区域的泛化来专门测试最终转化为肌肉激活的适应，提出了一个具有肌肉协同作用调制的计算模型。在实验中，在精心配置的中心向外等速扭矩产生任务期间施加视动旋转，使得适应和泛化可以通过仅缩放相同肌肉的贡献来实现，或者通过另外需要募集不同的肌肉来实现。与我们之前的发现一致，方向误差的时间过程表明，对于后者情况，适应的程度要低得多（低 28.1%）。更重要的是，对于需要从适应过程中涉及的肌肉中招募不同肌肉的泛化，获得的方向误差是其他泛化区域的两倍多。总的来说，这些结果表明，原始肌肉协同作用内的调制有助于视动适应，并且协同作用的重新组合对适应和泛化都施加了限制。我使用包括两个群体代码的传感器 - 运动转换模型再现了这些结果，一个用于感觉网络，一个用于运动网络。肌肉协同作用被定义为运动网络连接的肌肉的线性组合，并且这些协同作用的调制是通过这些连接的权重适应引起的。最后，我推测对协同作用重新组合施加的限制源自在神经系统的不同水平上运作的抑制和兴奋机制之间的平衡，通过将活动集中在相关肌肉上，有助于肌肉募集的功能组织。
