School of Psychology and Centre for Human Brain Health, University of Birmingham, Birmingham, United Kingdom.
Department of Clinical and Movement Neuroscience, Queens Square Institute of Neurology, University College London, London, United Kingdom.
J Neurophysiol. 2022 Jul 1;128(1):86-104. doi: 10.1152/jn.00467.2021. Epub 2022 Jun 1.
Reward has consistently been shown to enhance motor behavior; however, its beneficial effects appear to be largely unspecific. For example, reward is associated with both rapid and training-dependent improvements in performance, with a mechanistic account of these effects currently lacking. Here we tested the hypothesis that these distinct reward-based improvements are driven by dissociable reward types: monetary incentive and performance feedback. Whereas performance feedback provides information on how well a motor task has been completed (knowledge of performance), monetary incentive increases the motivation to perform optimally without providing a performance-based learning signal. showed that groups who received monetary incentive rapidly improved movement times (MTs), using a novel sequential reaching task. In contrast, only groups with correct performance-based feedback showed learning-related improvements. Importantly, pairing both maximized MT performance gains and accelerated movement fusion. Fusion describes an optimization process during which neighboring sequential movements blend together to form singular actions. Results from served as a replication and showed that fusion led to enhanced performance speed while also improving movement efficiency through increased smoothness. Finally, showed that these improvements in performance persist for 24 h even without reward availability. This highlights the dissociable impact of monetary incentive and performance feedback, with their combination maximizing performance gains and leading to stable improvements in the speed and efficiency of sequential actions. Our work provides a mechanistic framework for how reward influences motor behavior. Specifically, we show that rapid improvements in speed and accuracy are driven by reward presented in the form of money, whereas knowledge of performance through performance feedback leads to training-based improvements. Importantly, combining both maximized performance gains and led to improvements in movement quality through fusion, which describes an optimization process during which sequential movements blend into a single action.
奖励一直被证明可以增强运动行为；然而，它的有益效果似乎在很大程度上是不特定的。例如，奖励与表现的快速和依赖于训练的改善都有关联，而目前缺乏对这些影响的机械解释。在这里，我们测试了这样一个假设，即这些不同的基于奖励的改善是由可分离的奖励类型驱动的：金钱激励和绩效反馈。虽然绩效反馈提供了关于运动任务完成情况的信息（绩效知识），但金钱激励增加了以最佳方式执行任务的动机，而不提供基于绩效的学习信号。研究表明，接受金钱激励的小组迅速改善了运动时间（MTs），使用了一种新的序列到达任务。相比之下，只有具有正确基于绩效的反馈的小组表现出与学习相关的改善。重要的是，两者的结合最大限度地提高了 MT 性能的提高，并加速了运动融合。融合描述了一个优化过程，在此过程中，相邻的序列运动融合在一起形成单一的动作。研究的结果作为一个复制，表明融合导致了增强的性能速度，同时通过增加平滑度来提高运动效率。最后，研究表明，即使没有奖励，这些性能的提高也会持续 24 小时。这突出了金钱激励和绩效反馈的可分离影响，它们的结合最大限度地提高了性能增益，并导致了序列动作的速度和效率的稳定提高。我们的工作为奖励如何影响运动行为提供了一个机械框架。具体来说，我们表明，速度和准确性的快速提高是由金钱形式的奖励驱动的，而通过绩效反馈获得的绩效知识则导致基于训练的改善。重要的是，两者的结合最大限度地提高了性能增益，并通过融合提高了运动质量，融合描述了一个优化过程，在此过程中，序列运动融合成一个单一的动作。
