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用于视觉运动适应的感觉预测误差信号的分解

Decomposition of a sensory prediction error signal for visuomotor adaptation.

作者信息

Butcher Peter A, Taylor Jordan A

机构信息

Department of Psychology, Princeton University.

出版信息

J Exp Psychol Hum Percept Perform. 2018 Feb;44(2):176-194. doi: 10.1037/xhp0000440. Epub 2017 May 15.

Abstract

To accomplish effective motor control, the brain contains an internal forward model that predicts the expected sensory consequence of a motor command. When this prediction is inaccurate, a sensory prediction error is produced which adapts the forward model to make more accurate predictions of future movements. Other types of errors, such as task performance errors or reward, play less of a role in adapting a forward model. This raises the following question: What unique information is conveyed by the sensory prediction error that results in forward model adaptation? sensory prediction errors typically contain both the magnitude and direction of the error, but it is unclear if both components are necessary for adaptation or a single component is sufficient. In this article, we address this by having participants learn to counter a visuomotor rotation, which induces an angular mismatch between movements of the hand and visual feedback. We manipulated the information content of the visual feedback, in the form of a line, which accurately represented only the magnitude (distance), direction, or both magnitude and direction, of the virtual cursor relative to the target. We demonstrate that sensorimotor adaptation does not occur, or is minimal, when feedback is limited to information about the magnitude of an error. In contrast, sensorimotor adaptation is present when feedback is limited only to the direction of an error or when it contains combined direction and magnitude information. This result stands in contrast to current computational models of cerebellar-based sensorimotor adaptation that use error magnitude to drive adaptation. (PsycINFO Database Record

摘要

为实现有效的运动控制,大脑包含一个内部前向模型,该模型可预测运动指令的预期感觉结果。当此预测不准确时,就会产生感觉预测误差,该误差会使前向模型进行调整,以便对未来运动做出更准确的预测。其他类型的误差,如任务执行误差或奖励,在调整前向模型方面所起的作用较小。这就引出了以下问题:导致前向模型调整的感觉预测误差传达了哪些独特信息?感觉预测误差通常包含误差的大小和方向,但尚不清楚这两个成分对于调整是否都是必需的,还是单个成分就足够了。在本文中,我们通过让参与者学习对抗视觉运动旋转来解决这个问题,这种旋转会导致手部运动与视觉反馈之间出现角度不匹配。我们以线条的形式操纵视觉反馈的信息内容,该线条仅准确表示虚拟光标相对于目标的大小(距离)、方向,或大小和方向两者。我们证明,当反馈仅限于误差大小的信息时,感觉运动适应不会发生,或者非常小。相比之下,当反馈仅限于误差方向或包含方向和大小的组合信息时,感觉运动适应就会出现。这一结果与当前基于小脑的感觉运动适应计算模型形成对比,后者使用误差大小来驱动适应。(PsycINFO数据库记录)

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