Center for Integrative Neuroscience and Department of Physiology and Sloan-Swartz Center for Theoretical Neurobiology, University of California, San Francisco, San Francisco, California 94143.
Center for Integrative Neuroscience and Department of Physiology and.
J Neurosci. 2014 Sep 3;34(36):12071-80. doi: 10.1523/JNEUROSCI.3001-13.2014.
Even well practiced movements cannot be repeated without variability. This variability is thought to reflect "noise" in movement preparation or execution. However, we show that, for both professional baseball pitchers and macaque monkeys making reaching movements, motor variability can be decomposed into two statistical components, a slowly drifting mean and fast trial-by-trial fluctuations about the mean. The preparatory activity of dorsal premotor cortex/primary motor cortex neurons in monkey exhibits similar statistics. Although the neural and behavioral drifts appear to be correlated, neural activity does not account for trial-by-trial fluctuations in movement, which must arise elsewhere, likely downstream. The statistics of this drift are well modeled by a double-exponential autocorrelation function, with time constants similar across the neural and behavioral drifts in two monkeys, as well as the drifts observed in baseball pitching. These time constants can be explained by an error-corrective learning processes and agree with learning rates measured directly in previous experiments. Together, these results suggest that the central contributions to movement variability are not simply trial-by-trial fluctuations but are rather the result of longer-timescale processes that may arise from motor learning.
即使是经过充分练习的动作，也不能在没有可变性的情况下重复。这种可变性被认为反映了运动准备或执行中的“噪声”。然而，我们表明，对于专业棒球投手和猕猴进行的伸手动作，运动可变性可以分解为两个统计分量，即缓慢漂移的平均值和平均值周围的快速逐次波动。猴子的背侧运动前皮质/初级运动皮质神经元的预备活动表现出类似的统计特性。尽管神经和行为漂移似乎相关，但神经活动并不能解释运动中的逐次波动，这些波动必然来自其他地方，可能在下游。这种漂移的统计特性可以通过双指数自相关函数很好地建模，在两只猴子以及棒球投球中观察到的神经和行为漂移中，时间常数相似。这些时间常数可以通过纠错学习过程来解释，并且与之前实验中直接测量的学习率一致。综上所述，这些结果表明，运动可变性的中枢贡献不仅仅是逐次波动，而是更长时间尺度过程的结果，这些过程可能来自运动学习。
