Tanaka Hirokazu, Tai Meihua, Qian Ning
Center for Neurobiology and Behavior and Department of Physiology and Cellular Biophysics, Columbia University, New York, NY 10032, USA.
Neural Comput. 2004 Oct;16(10):2021-40. doi: 10.1162/0899766041732431.
We investigated the differences between two well-known optimization principles for understanding movement planning: the minimum variance (MV) model of Harris and Wolpert (1998) and the minimum torque change (MTC) model of Uno, Kawato, and Suzuki (1989). Both models accurately describe the properties of human reaching movements in ordinary situations (e.g., nearly straight paths and bell-shaped velocity profiles). However, we found that the two models can make very different predictions when external forces are applied or when the movement duration is increased. We considered a second-order linear system for the motor plant that has been used previously to simulate eye movements and single-joint arm movements and were able to derive analytical solutions based on the MV and MTC assumptions. With the linear plant, the MTC model predicts that the movement velocity profile should always be symmetrical, independent of the external forces and movement duration. In contrast, the MV model strongly depends on the movement duration and the system's degree of stability; the latter in turn depends on the total forces. The MV model thus predicts a skewed velocity profile under many circumstances. For example, it predicts that the peak location should be skewed toward the end of the movement when the movement duration is increased in the absence of any elastic force. It also predicts that with appropriate viscous and elastic forces applied to increase system stability, the velocity profile should be skewed toward the beginning of the movement. The velocity profiles predicted by the MV model can even show oscillations when the plant becomes highly oscillatory. Our analytical and simulation results suggest specific experiments for testing the validity of the two models.
哈里斯和沃尔珀特(1998年)的最小方差(MV)模型以及宇野、川胜和铃木(1989年)的最小扭矩变化(MTC)模型。这两种模型都能准确描述在普通情况下人类伸手动作的特性(例如,近乎直线的路径和钟形速度曲线)。然而,我们发现当施加外力或增加运动持续时间时,这两种模型会做出非常不同的预测。我们考虑了一个先前用于模拟眼球运动和单关节手臂运动的二阶线性运动系统,并能够基于MV和MTC假设推导出解析解。对于线性运动系统,MTC模型预测运动速度曲线应始终是对称的,与外力和运动持续时间无关。相比之下,MV模型强烈依赖于运动持续时间和系统的稳定程度;而后者又取决于总力。因此,MV模型在许多情况下预测速度曲线会出现偏斜。例如,它预测在没有任何弹力的情况下增加运动持续时间时,峰值位置应偏向运动末尾。它还预测,施加适当的粘性力和弹力以提高系统稳定性时,速度曲线应偏向运动开头。当运动系统变得高度振荡时,MV模型预测的速度曲线甚至会出现振荡。我们的分析和模拟结果为测试这两种模型的有效性提出了具体的实验。