Department of Kinesiology, Michigan State University, East Lansing, MI, USA.
Department of Kinesiology, Michigan State University, East Lansing, MI, USA.
Neuroscience. 2021 Dec 15;479:157-168. doi: 10.1016/j.neuroscience.2021.10.021. Epub 2021 Oct 27.
Many contexts in motor learning require a learner to change from an existing movement solution to a novel movement solution to perform the same task. Recent evidence has pointed to motor variability prior to learning as a potential marker for predicting individual differences in motor learning. However, it is not known if this variability is predictive of the ability to adopt a new movement solution for the same task. Here, we examined this question in the context of a redundant precision task requiring control of motor variability. Fifty young adults learned a precision task that involved throwing a virtual puck toward a target using both hands. Because the speed of the puck depended on the sum of speeds of both hands, this task could be achieved using multiple solutions. Participants initially performed a baseline task where there was no constraint on the movement solution, and then performed a novel task where they were constrained to adopt a specific movement solution requiring asymmetric left and right hand speeds. Results showed that participants were able to learn the new solution, and this change was associated with changes in both the amount and structure of variability. However, increased baseline motor variability did not facilitate initial or final task performance when using the new solution - in fact, greater variability was associated with higher errors. These results suggest that motor variability is not necessarily indicative of flexibility and highlight the role of the task context in determining the relation between motor variability and learning.
许多运动学习的情境都需要学习者从现有的运动解决方案转变为新的运动解决方案，以完成相同的任务。最近的证据表明，学习前的运动可变性可以作为预测个体运动学习差异的潜在指标。然而，目前尚不清楚这种可变性是否可以预测个体在同一任务中采用新运动解决方案的能力。在这里，我们在需要控制运动可变性的冗余精度任务的背景下研究了这个问题。五十名年轻人学习了一项使用双手投掷虚拟冰球到目标的精度任务。由于冰球的速度取决于双手速度的总和，因此可以通过多种解决方案来实现这项任务。参与者最初执行了一项没有运动解决方案限制的基线任务，然后执行了一项新任务，他们被要求采用一种需要左手和右手速度不对称的特定运动解决方案。结果表明，参与者能够学习新的解决方案，并且这种变化与可变性的数量和结构的变化都有关。然而，当使用新的解决方案时，基线运动可变性的增加并没有促进初始或最终的任务表现——事实上，更大的可变性与更高的错误率相关。这些结果表明，运动可变性并不一定表示灵活性，并且突出了任务情境在确定运动可变性和学习之间关系中的作用。
