The role of uncertainty in human motor learning and adaptation

描述（由申请人提供）：在拟议的研究中，我们将描述神经系统如何处理运动学习中的不确定性。受试者将在虚拟环境中将光标从起始位置移动到目标位置。视觉反馈将被操纵，以引起关于状态、反馈或其相关性的不确定性。我们的实验将专注于探索由此产生的逐个尝试学习。不确定性对运动学习的影响的拟议分析是由来自统计框架的强有力的假设驱动的。有了预期的结果，我们将能够反驳形式化不确定性如何影响学习的贝叶斯模型，或者反驳假设不确定性对学习没有影响的状态空间模型。重要的是，不确定性是人类行为的核心因素，定量地了解其作用比任何特定的建模框架都重要。该研究计划的长期目标是从计算的角度回答运动学习中的基本和重要问题，并为改善运动康复提供工具。公共卫生相关性神经系统需要在日常生活功能中存在不确定性的情况下学习，并且存在疾病。基于统计学的见解，这项研究将测试影响神经系统从视觉运动错误中学习的关键因素。具体来说，我们将了解错误的时间，幅度和视觉呈现如何影响运动学习。机器人康复方法的选择导致错误反馈如何通过最大化研究测试变得有效和相关。当我们提出基本问题时，预计结果将推广到广泛的运动学习任务。

DESCRIPTION (provided by applicant): In the proposed research, we will characterize how the nervous system deals with uncertainty in motor learning. Subjects will move a cursor from a starting position to a target position in a virtual environment. Visual feedback will be manipulated to induce uncertainty about the state, the feedback, or its relevance. Our experiments will focus on probing the resulting trial-by-trial learning. The proposed analysis of the influence of uncertainty on motor learning is driven by strong hypotheses derived from a statistical framework. With the expected results we will either be able to refute Bayesian models that formalize how uncertainty affects learning or refute state space models that assume that uncertainty has no influence on learning. Importantly, uncertainty is a central factor for human behavior and quantitatively understanding its role is important beyond any specific modeling framework. The long term objectives of this research program are to answer basic and important questions in motor learning from a computational perspective and to provide tools for improving motor rehabilitation. PUBLIC HEALTH RELEVANCE The nervous system needs to learn in the presence of uncertainty within the functions of everyday life, and in the presence of disease. Based on statistical insights, this study will test key factors that affect the way the nervous system learns from visuo-motor errors. Specifically, we will understand how the times, magnitudes and the visual presentation of errors affect motor learning. Choices in robotic rehabilitation approaches result in how error feedback can be made effective and relevant through maximizing research testing. As we ask fundamental questions, the results are expected to generalize to a wide range of motor learning tasks.