当前馈和反馈控制过程都参与时,感觉不确定性对运动学习的误差无关影响。

IF 4.3 2区 生物学
PLoS Computational Biology Pub Date : 2023-09-08 eCollection Date: 2023-09-01 DOI:10.1371/journal.pcbi.1010526
Christopher L Hewitson, David M Kaplan, Matthew J Crossley
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引用次数: 2

摘要

在运动过程中整合感官信息和在连续运动中调整运动计划对于准确、灵活的运动行为都至关重要。当正在进行的运动偏离目标时,反馈控制机构更新下降电机命令,以对抗感测到的误差。在较长的时间尺度上,误差会导致前馈规划中的自适应,从而使未来的运动变得更加准确,并且需要较少的反馈控制过程的在线调整。感官反馈被整合到正在进行的运动中的程度和运动误差驱动前馈运动计划中的自适应变化的程度都已被证明与感官不确定性成反比。然而,由于这些过程只是在相互隔离的情况下进行研究的,因此人们对它们在共同发生的真实世界运动环境中如何受到感觉不确定性的影响知之甚少。在这里,我们表明,当存在反馈积分时,与不存在反馈积分相比,感觉不确定性可能会对到达动作的前馈适应产生不同的影响。特别是,参与者在一次又一次的试验中逐渐调整自己的动作,其特点是缓慢而一致地减少误差。在这个缓慢的包络之上,参与者的初始运动矢量发生了巨大而突然的变化,这与之前试验中存在的感觉不确定性程度密切相关。然而,这些突变对感测到的移动误差的大小和方向是不敏感的。这些结果为当前不确定性下的感觉运动学习模型提出了重要问题,并为该领域的未来探索开辟了新的途径。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Error-independent effect of sensory uncertainty on motor learning when both feedforward and feedback control processes are engaged.

Error-independent effect of sensory uncertainty on motor learning when both feedforward and feedback control processes are engaged.

Error-independent effect of sensory uncertainty on motor learning when both feedforward and feedback control processes are engaged.

Error-independent effect of sensory uncertainty on motor learning when both feedforward and feedback control processes are engaged.

Integrating sensory information during movement and adapting motor plans over successive movements are both essential for accurate, flexible motor behaviour. When an ongoing movement is off target, feedback control mechanisms update the descending motor commands to counter the sensed error. Over longer timescales, errors induce adaptation in feedforward planning so that future movements become more accurate and require less online adjustment from feedback control processes. Both the degree to which sensory feedback is integrated into an ongoing movement and the degree to which movement errors drive adaptive changes in feedforward motor plans have been shown to scale inversely with sensory uncertainty. However, since these processes have only been studied in isolation from one another, little is known about how they are influenced by sensory uncertainty in real-world movement contexts where they co-occur. Here, we show that sensory uncertainty may impact feedforward adaptation of reaching movements differently when feedback integration is present versus when it is absent. In particular, participants gradually adjust their movements from trial-to-trial in a manner that is well characterised by a slow and consistent envelope of error reduction. Riding on top of this slow envelope, participants exhibit large and abrupt changes in their initial movement vectors that are strongly correlated with the degree of sensory uncertainty present on the previous trial. However, these abrupt changes are insensitive to the magnitude and direction of the sensed movement error. These results prompt important questions for current models of sensorimotor learning under uncertainty and open up new avenues for future exploration in the field.

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来源期刊
PLoS Computational Biology
PLoS Computational Biology 生物-生化研究方法
CiteScore
7.10
自引率
4.70%
发文量
820
期刊介绍: PLOS Computational Biology features works of exceptional significance that further our understanding of living systems at all scales—from molecules and cells, to patient populations and ecosystems—through the application of computational methods. Readers include life and computational scientists, who can take the important findings presented here to the next level of discovery. Research articles must be declared as belonging to a relevant section. More information about the sections can be found in the submission guidelines. Research articles should model aspects of biological systems, demonstrate both methodological and scientific novelty, and provide profound new biological insights. Generally, reliability and significance of biological discovery through computation should be validated and enriched by experimental studies. Inclusion of experimental validation is not required for publication, but should be referenced where possible. Inclusion of experimental validation of a modest biological discovery through computation does not render a manuscript suitable for PLOS Computational Biology. Research articles specifically designated as Methods papers should describe outstanding methods of exceptional importance that have been shown, or have the promise to provide new biological insights. The method must already be widely adopted, or have the promise of wide adoption by a broad community of users. Enhancements to existing published methods will only be considered if those enhancements bring exceptional new capabilities.
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