How is a motor skill learned? Change and invariance at the levels of task success and trajectory control
How is a motor skill learned? Change and invariance at the levels of task success and trajectory control
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DOI：
10.1152/jn.00856.2011
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发表时间：
2012-07-01
影响因子：
2.5
通讯作者：
Mazzoni, Pietro
中科院分区：
文献类型：
--
作者：
Shmuelof, Lior;Krakauer, John W.;Mazzoni, Pietro
L，克拉考尔JW，马佐尼P.运动技能是如何学会的？在任务成功和轨迹控制水平上的变化和不变。神经生理学杂志108：578-594,2012。2012年4月18日首次出版；DOI：10.1152/jn.00856.2011。-公众花大价钱观看熟练的汽车表演。然而，值得注意的是，近几十年来，与运动适应(在外部干扰下恢复到基线表现)相比，运动技能学习(超过基线水平的表现改进)受到的实验关注较少。运动技能可以在任务成功和动作质量的水平上进行评估，但这两个水平之间的联系仍然知之甚少。我们设计了一项运动技能任务，要求在视觉上引导手腕的弯曲运动而不受干扰，我们将任务级别的技能学习定义为速度-精度权衡函数(SAF)的变化。在有限速度范围内的实践导致了SAF的全球转移。我们询问了SAF如何映射到轨迹运动学的变化，以建立任务级性能和精细运动控制之间的联系。虽然平均轨迹有很小的变化，但性能的改善主要包括试验间变异性的减少和运动平稳性的增加。我们发现了改善反馈控制的证据，这可以解释变异性的减少，但不排除其他解释，如皮质表示中的信噪比增加。有趣的是，亚运动结构保持学习不变。SAF对各种困难的全球概括表明，这项任务的技能表现在一个时间上可扩展的网络中。我们认为，运动技能习得可以被描述为运动变异性的缓慢减少，这不同于基于模型的更快的学习，后者减少了适应范例中的系统错误。
Shmuelof L, Krakauer JW, Mazzoni P. How is a motor skill learned? Change and invariance at the levels of task success and trajectory control. J Neurophysiol 108: 578-594, 2012. First published April 18, 2012; doi:10.1152/jn.00856.2011.-The public pays large sums of money to watch skilled motor performance. Notably, however, in recent decades motor skill learning (performance improvement beyond baseline levels) has received less experimental attention than motor adaptation (return to baseline performance in the setting of an external perturbation). Motor skill can be assessed at the levels of task success and movement quality, but the link between these levels remains poorly understood. We devised a motor skill task that required visually guided curved movements of the wrist without a perturbation, and we defined skill learning at the task level as a change in the speed-accuracy trade-off function (SAF). Practice in restricted speed ranges led to a global shift of the SAF. We asked how the SAF shift maps onto changes in trajectory kinematics, to establish a link between task-level performance and fine motor control. Although there were small changes in mean trajectory, improved performance largely consisted of reduction in trial-to-trial variability and increase in movement smoothness. We found evidence for improved feedback control, which could explain the reduction in variability but does not preclude other explanations such as an increased signal-to-noise ratio in cortical representations. Interestingly, submovement structure remained learning invariant. The global generalization of the SAF across a wide range of difficulty suggests that skill for this task is represented in a temporally scalable network. We propose that motor skill acquisition can be characterized as a slow reduction in movement variability, which is distinct from faster model-based learning that reduces systematic error in adaptation paradigms.