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The Nervous System Uses Nonspecific Motor Learning in Response to Random Perturbations of Varying Nature

机译:神经系统使用非特定的运动学习来响应变化的自然随机扰动

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摘要

We constantly make small errors during movement and use them to adapt our future movements. Movement experiments often probe this error-driven learning by perturbing movements and analyzing the after-effects. Past studies have applied perturbations of varying nature such as visual disturbances, position- or velocity-dependent forces and modified inertia properties of the limb. However, little is known about how the specific nature of a perturbation influences subsequent movements. For a single perturbation trial, the nature of a perturbation may be highly uncertain to the nervous system, given that it receives only noisy information. One hypothesis is that the nervous system can use this rough estimate to partially correct for the perturbation on the next trial. Alternatively, the nervous system could ignore uncertain information about the nature of the perturbation and resort to a nonspecific adaptation. To study how the brain estimates and responds to incomplete sensory information, we test these two hypotheses using a trial-by-trial adaptation experiment. On each trial, the nature of the perturbation was chosen from six distinct types, including a visuomotor rotation and different force fields. We observed that corrective forces aiming to oppose the perturbation in the following trial were independent of the nature of the perturbation. Our results suggest that the nervous system uses a nonspecific strategy when it has high uncertainty about the nature of perturbations during trial-by-trial learning.
机译:我们在运动过程中经常犯一些小错误,并利用它们来适应我们未来的运动。运动实验通常通过扰动运动并分析后效应来探究这种错误驱动的学习。过去的研究已经应用了各种性质的摄动,例如视觉障碍,与位置或速度有关的力以及肢体的惯性特性发生了变化。但是,人们对扰动的特殊性质如何影响随后的运动知之甚少。对于单次扰动试验,由于其仅接收到嘈杂的信息,因此扰动的性质对于神经系统可能是高度不确定的。一种假设是神经系统可以使用此粗略估计来部分纠正下一次试验中的摄动。或者,神经系统可能会忽略有关扰动性质的不确定信息,而采取非特异性适应。为了研究大脑如何估计和响应不完整的感官信息,我们使用逐项试验适应性实验检验了这两个假设。在每个试验中,扰动的性质均从六种不同的类型中选择,包括可见运动旋转和不同的力场。我们观察到,在接下来的试验中,旨在抵抗微扰的矫正力与微扰的性质无关。我们的结果表明,当神经系统在逐项学习过程中对扰动的性质具有高度不确定性时,它会使用非特定策略。

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