Generalized Motor Programs in Writing, Drawing, and Aimed Movements

理论假设，熟练的人类动作，从最简单的指点动作到更复杂的多手势动作，都是由“运动程序”指导的。尽管我们很少意识到这些程序，但它们的作用是将指令结构传递给肌肉，这样就可以最大限度地减少对缓慢的、基于反馈的纠错过程的依赖。运动程序泛化的想法源于计算机程序的类比，并表明运动程序具有形式参数，当运动进行时，这些参数具有特定于情况的值。这项研究的重点是是否以及如何推广运动程序，以便一个单一的表征足以控制相关的、尽管可能是新的运动变化。这项研究将在三个经验领域解决这些问题，即手写、简单的绘画动作和具有过多自由度的有针对性的动作。笔迹方面的工作将考察当受试者被限制在一个或多个方面偏离正常表现条件时，高度过度学习的技能的变化：例如，大小、速度或效应器。这项研究将确定需要从基于运动程序的控制策略转变为基于反馈的运动近似策略的约束的类型和大小。通过绘制简单的图形，第二条研究线将评估迁移的性质和程度，当人们偶尔被要求在一组特定的限制下产生一个图形时，他们正在学习通过在不同的限制下进行反馈练习来产生一个图形。这些实验中的学习迁移模式将为运动程序的泛化提供证据，并将为探索运动程序具有层次结构的可能性提供一种方法。第三条研究路线将调查用于解决当有过多自由度可用于执行有针对性的动作时发生的规划模糊所使用的策略和约束。与前两条研究路线不同，前两条研究路线假设类似于基于已有信息修改的运动程序概括，在本研究中，运动程序及其概括将被建模为动态约束优化过程的结果。从这项研究中获得的关于运动程序结构和功能的见解有可能应用于需要协调运动的技能的训练、运动障碍的诊断和治疗以及机器人系统中运动的规划和表示。

Theory posits that skilled human movements, from the simplest pointing movements to more elaborate multi-gesture movements, are directed by "motor programs." Although we are seldom aware of these programs, they act to structure commands to muscles so that movements can be made with minimal reliance on slow, feedback- based, error-correcting processes. The idea of motor-program generalization stems from the computer-program analogy and suggests that motor programs have formal parameters which take on situation-specific values when a movement is made. The focus of this research is whether and how motor programs can be generalized so that a single representation is sufficient to control related, although perhaps novel, variations of a movement. The research will address these issues in three empirical domains, handwriting, simple drawing movements, and aimed movements made with excess degrees of freedom. The work on handwriting will examine changes in a highly overlearned skill when subjects are constrained to deviate from normal performance conditions in one or more ways: e.g., size, speed, or effector. This research will identify the type and magnitude of constraints that necessitate a shift from the motor- program-based, control strategy to a feedback-based strategy of movement approximation. Using drawing of simple figures, the second line of research will assess the nature and degree of transfer that occurs when people occasionally are asked to produce, under a particular set of constraints, a figure which they are learning to produce, by practicing with feedback, under a different set of constraints. The patterns of learning transfer in these experiments will provide evidence about motor program generalization and will provide a way to explore the possibility that motor programs have a hierarchical structure. The third line of research will investigate the strategies and constraints used to resolve the planning ambiguity that occurs when excess degrees of freedom are available to perform aimed movements. Unlike the first two lines of research, which assume an analogy to motor-program generalization based on the modification of pre-existing information, in this research motor programs and their generalization will be modeled as the result of a process of dynamic constraint optimization. The insights about the structure and function of motor programs gained from this research have potential for application to the training of skills requiring coordinated movement, the diagnosis and treatment of movement disorders, and the planning and representation of movements in robotic systems.