Dept. of Engineering Science & Mechanics, Penn State University, University Park, PA 16802, USA.
Hum Mov Sci. 2013 Oct;32(5):899-923. doi: 10.1016/j.humov.2013.07.019. Epub 2013 Nov 7.
Fluctuations in the repeated performance of human movements have been the subject of intense scrutiny because they are generally believed to contain important information about the function and health of the neuromotor system. A variety of approaches has been brought to bear to study these fluctuations. However it is frequently difficult to understand how to synthesize different perspectives to give a coherent picture. Here, we describe a conceptual framework for the experimental study of motor variability that helps to unify geometrical methods, which focus on the role of motor redundancy, with dynamical methods that characterize the error-correcting processes regulating the performance of skilled tasks. We describe how goal functions, which mathematically specify the task strategy being employed, together with ideas from the control of redundant systems, allow one to formulate simple, experimentally testable dynamical models of inter-trial fluctuations. After reviewing the basic theory, we present a list of five general hypotheses on the structure of fluctuations that can be expected in repeated trials of goal-directed tasks. We review recent experimental applications of this general approach, and show how it can be used to precisely characterize the error-correcting control used by human subjects.
人体运动重复性波动一直是深入研究的课题,因为人们普遍认为这些波动包含有关运动神经系统功能和健康的重要信息。已经提出了多种方法来研究这些波动。然而,要理解如何综合不同的观点以形成一致的认识通常是困难的。在这里,我们描述了一个用于研究运动变异性的实验的概念框架,该框架有助于统一专注于运动冗余作用的几何方法和表征调节熟练任务性能的纠错过程的动力学方法。我们描述了目标函数如何与从冗余系统控制中得到的思想相结合,从而允许人们对目标导向任务的试验间波动制定简单的、可通过实验检验的动力学模型。在回顾了基本理论之后,我们提出了一个关于在目标导向任务的重复试验中可预期的波动结构的五个一般假设的列表。我们回顾了这种通用方法的最新实验应用,并展示了如何使用它来精确地描述人类受试者使用的纠错控制。