Signal-dependent noise determines motor planning
Signal-dependent noise determines motor planning
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DOI：
10.1038/29528
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发表时间：
1998-08-20
期刊：
影响因子：
64.8
通讯作者：
Wolpert, DM
中科院分区：
文献类型：
--
作者：
Harris, CM;Wolpert, DM
当我们进行跳跃性眼球运动或目标导向的手臂运动时，眼睛或手臂可以采取无数种可能的轨迹来达到目标（1,2）。然而，人类表现出高度刻板的轨迹，其中眼睛和手的速度曲线在短暂的运动中是平滑和对称的（3,4）。在这里，我们提出了一个统一的理论，基于单一的生理假设，即神经控制信号被噪声破坏，其方差随着控制信号的大小而增加。我们建议，在存在这种信号相关噪声的情况下，选择轨迹的形状以最小化最终眼睛或手臂位置的方差。这种最小方差理论准确地预测了扫视和手臂运动的轨迹，以及菲特定律所描述的速度-精度权衡(5)。根据经验发现，这些轮廓对眼睛或手臂的动态变化具有鲁棒性（6,7）7。此外，在绘制运动过程中，路径曲率和手速度之间的关系再现了经验的“三分之二幂律”（8,9）。这个理论为眼睛和手臂的运动控制提供了一个简单而有力的统一视角。
When we make saccadic eye movements or goal-directed arm movements, there is an infinite number of possible trajectories that the eye or arm could take to reach the target(1,2). However, humans show highly stereotyped trajectories in which velocity profiles of both the eye and hand are smooth and symmetric for brief movements(3,4). Here we present a unifying theory of eye and arm movements based on the single physiological assumption that the neural control signals are corrupted by noise whose variance increases with the size of the control signal. We propose that in the presence of such signal-dependent noise, the shape of a trajectory is selected to minimize the variance of the final eye or arm position. This minimum-variance theory accurately predicts the trajectories of both saccades and arm movements and the speed-accuracy trade-off described by Fitt's law(5). These profiles are robust to changes in the dynamics of the eye or arm, as found empirically(6,7) 7. Moreover, the relation between path curvature and hand velocity during drawing movements reproduces the empirical 'two-thirds power law'(8,9). This theory provides a simple and powerful unifying perspective for both eye and arm movement control.