Tseng Ya-Weng, Scholz John P, Schöner Gregor, Hotchkiss Lawrence
Physical Therapy Department and Biomechanics and Movement Science Program, 307 McKinly Laboratory, University of Delaware, Newark 19716, USA.
Exp Brain Res. 2003 Apr;149(3):276-88. doi: 10.1007/s00221-002-1357-5. Epub 2003 Jan 31.
Given the number of muscles and joints of the arm, more ways are available to produce an identical hand movement when pointing to a target than are strictly necessary. How the nervous system manages these abundant degrees of freedom was the focus of this study of pointing to targets of low and high indices of difficulty (ID). Two essential features of movement synergies were examined. The first reflects the preferred relations among the outputs of each movement element and was studied through principal component analysis. The second feature of synergy reflects the flexibility of those relationships evidenced by the use of multiple, goal-equivalent solutions to joint coordination. This second feature, which is the main focus of this report, was studied using the uncontrolled manifold approach. Motor abundance was defined operationally as the component of variance of joint combinations that left unchanged the value of important performance variables (goal-equivalent variability, GEV). This variance component was contrasted with the component of variance leading to a change in the value of these variables (non-goal-equivalent variability, NGEV). The difference between GEV and NGEV was evaluated with respect to the performance variables movement extent, movement direction, and path of the arm's center of mass. More than 90% of the variance of joint motions across the pointing trial were accounted for by one principal component, indicating a consistent temporal coupling among most joint motions in a single functional synergy. The flexible nature of this synergy was revealed by the variability analysis. All subjects had significantly higher GEV than NGEV for most of the movement path. Thus, variable patterns of joint coordination did not represent noise but the use of equivalent coordinative solutions related to stabilizing important performance variables. Higher GEV than NGEV was present regardless of the task's ID. One exception was at the time of peak velocity, leading to poorer control of movement extent than movement direction. Increasing the task's ID led to an overall reduction of joint configuraion variance, particularly GEV. These results support earlier work indicating that the use of goal-equivalent solutions to joint coordination is a common feature of the control of this and many other motor tasks. Functionally important performance variables appear to be controlled through flexible but task-specific coordination among the motor elements.
鉴于手臂的肌肉和关节数量众多，指向目标时产生相同手部动作的方式比严格所需的方式更多。神经系统如何管理这些丰富的自由度是这项针对难度指数（ID）低和高的目标指向研究的重点。研究了运动协同作用的两个基本特征。第一个特征反映了每个运动元素输出之间的优选关系，并通过主成分分析进行研究。协同作用的第二个特征反映了通过使用多种目标等效的关节协调解决方案所证明的这些关系的灵活性。本报告的主要重点是第二个特征，使用非受控流形方法进行研究。运动丰富性在操作上被定义为关节组合方差的组成部分，该部分使重要性能变量的值（目标等效变异性，GEV）保持不变。将该方差分量与导致这些变量值变化的方差分量（非目标等效变异性，NGEV）进行对比。针对性能变量运动范围、运动方向和手臂质心路径评估了GEV和NGEV之间的差异。在整个指向试验中，超过90%的关节运动方差由一个主成分解释，表明在单个功能协同作用中大多数关节运动之间存在一致的时间耦合。变异性分析揭示了这种协同作用的灵活性。在大多数运动路径上，所有受试者的GEV均显著高于NGEV。因此，关节协调的可变模式并不代表噪声，而是使用与稳定重要性能变量相关的等效协调解决方案。无论任务的ID如何，GEV均高于NGEV。一个例外是在峰值速度时，导致对运动范围的控制比对运动方向的控制更差。增加任务的ID会导致关节配置方差总体降低，尤其是GEV。这些结果支持了早期的研究工作，表明使用目标等效的关节协调解决方案是控制此任务和许多其他运动任务的一个共同特征。功能上重要的性能变量似乎是通过运动元素之间灵活但特定于任务的协调来控制的。
