The cost of correcting for error during sensorimotor adaptation

Ehsan Sedaghat-Nejad, R. Shadmehr
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引用次数: 6

Abstract

Significance Improving the process of learning from error can play a critical role in applied settings such as rehabilitation. Previous work has generally focused on reward as a variable that may modulate learning. However, in response to an erroneous movement, the nervous system often engages a reflex that corrects for that error, thus expending time and energy. Here, we modulated this cost of error and found that increasing the cost increased how much the brain learned from error. Thus, the landscape of the loss associated with the act of correcting for error regulates the rates of sensorimotor learning. Learning from error is often a slow process. In machine learning, the learning rate depends on a loss function that specifies a cost for error. Here, we hypothesized that during motor learning, error carries an implicit cost for the brain because the act of correcting for error consumes time and energy. Thus, if this implicit cost could be increased, it may robustly alter how the brain learns from error. To vary the implicit cost of error, we designed a task that combined saccade adaptation with motion discrimination: movement errors resulted in corrective saccades, but those corrections took time away from acquiring information in the discrimination task. We then modulated error cost using coherence of the discrimination task and found that when error cost was large, pupil diameter increased and the brain learned more from error. However, when error cost was small, the pupil constricted and the brain learned less from the same error. Thus, during sensorimotor adaptation, the act of correcting for error carries an implicit cost for the brain. Modulating this cost affects how much the brain learns from error.
在感觉运动适应过程中纠正错误的代价
意义改进从错误中学习的过程可以在康复等应用环境中发挥关键作用。以前的研究通常把奖励作为调节学习的一个变量。然而,对于一个错误的动作,神经系统通常会进行反射来纠正这个错误,从而花费时间和精力。在这里,我们调整了错误的成本,发现成本的增加增加了大脑从错误中学到的东西。因此,与纠正错误行为相关的损失的情况调节了感觉运动学习的速率。从错误中学习往往是一个缓慢的过程。在机器学习中,学习率取决于指定错误代价的损失函数。在这里,我们假设在运动学习过程中,错误会给大脑带来隐性成本,因为纠正错误的行为会消耗时间和精力。因此,如果这种隐性成本可以增加,它可能会有力地改变大脑从错误中学习的方式。为了改变隐式错误代价,我们设计了一个结合扫视适应和运动识别的任务:运动错误导致纠正性扫视,但这些纠正占用了辨别任务中获取信息的时间。然后,我们利用识别任务的一致性调节错误代价,发现当错误代价较大时,瞳孔直径增大,大脑从错误中学到的东西更多。然而,当错误代价较小时,瞳孔收缩,大脑从同样的错误中学到的东西也较少。因此,在感觉运动适应过程中,纠正错误的行为给大脑带来了隐性成本。调节这种成本会影响大脑从错误中学习的程度。
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