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在线控制伸手过程中本体感觉和视觉反馈的整合。

Integration of proprioceptive and visual feedback during online control of reaching.

机构信息

Centre for Neuroscience Studies, Queen's University, Kingston, Ontario, Canada.

Institute of Communication Technologies, Electronics and Applied Mathematics, Louvain-la-Neuve, Belgium.

出版信息

J Neurophysiol. 2022 Feb 1;127(2):354-372. doi: 10.1152/jn.00639.2020. Epub 2021 Dec 15.

Abstract

Visual and proprioceptive feedback both contribute to perceptual decisions, but it remains unknown how these feedback signals are integrated together or consider factors such as delays and variance during online control. We investigated this question by having participants reach to a target with randomly applied mechanical and/or visual disturbances. We observed that the presence of visual feedback during a mechanical disturbance did not increase the size of the muscle response significantly but did decrease variance, consistent with a dynamic Bayesian integration model. In a control experiment, we verified that vision had a potent influence when mechanical and visual disturbances were both present but opposite in sign. These results highlight a complex process for multisensory integration, where visual feedback has a relatively modest influence when the limb is mechanically disturbed, but a substantial influence when visual feedback becomes misaligned with the limb. Visual feedback is more accurate, but proprioceptive feedback is faster. How should you integrate these sources of feedback to guide limb movement? As predicted by dynamic Bayesian models, the size of the muscle response to a mechanical disturbance was essentially the same whether visual feedback was present or not. Only under artificial conditions, such as when shifting the position of a cursor representing hand position, can one observe a muscle response from visual feedback.

摘要

视觉和本体感觉反馈都有助于知觉决策,但目前尚不清楚这些反馈信号是如何整合在一起的,或者在在线控制期间如何考虑延迟和方差等因素。我们通过让参与者用随机施加的机械和/或视觉干扰来达到目标来研究这个问题。我们观察到,在机械干扰期间存在视觉反馈并没有显著增加肌肉反应的幅度,但确实降低了方差,这与动态贝叶斯整合模型一致。在一个对照实验中,我们验证了当机械和视觉干扰同时存在但方向相反时,视觉具有很强的影响。这些结果突出了多感觉整合的一个复杂过程,在肢体受到机械干扰时,视觉反馈的影响相对较小,但当视觉反馈与肢体不一致时,视觉反馈的影响就很大。视觉反馈更准确,但本体感觉反馈更快。你应该如何整合这些反馈源来指导肢体运动?正如动态贝叶斯模型所预测的那样,无论是否存在视觉反馈,肌肉对机械干扰的反应幅度基本相同。只有在人工条件下,例如当移动代表手位置的光标位置时,才能观察到来自视觉反馈的肌肉反应。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5b3c/8794063/2973d2e6b43f/jn-00639-2020r01.jpg

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