Learning of action through adaptive combination of motor primitives
Learning of action through adaptive combination of motor primitives
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DOI：
10.1038/35037588
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发表时间：
2000-10-12
期刊：
影响因子：
64.8
通讯作者：
Shadmehr, R
中科院分区：
文献类型：
--
作者：
Thoroughman, KA;Shadmehr, R
了解大脑如何构建运动仍然是神经科学的一个基本挑战。大脑可以通过运动基元的灵活组合来控制复杂的运动（1），其中每个基元是感觉运动图中的计算元素，其将期望的肢体轨迹转换为运动命令。理论研究表明，系统学习动作的能力取决于其原语的形状（2）。使用错误模式的时间序列分析，在这里，我们表明，人类通过灵活的基元组合，具有高斯样的调整功能编码手的速度，学习达到运动的动态。推断出的基元的广泛调谐预测了大脑表示粘性动力学的能力的局限性。我们发现预测的局限性和受试者对新力场的适应之间存在密切的一致性。衍生原语的数学特性类似于小脑中浦肯野细胞的调谐曲线。这些细胞的活动可以编码作为动力学学习基础的基元。
Understanding how the brain constructs movements remains a fundamental challenge in neuroscience. The brain may control complex movements through flexible combination of motor primitives(1), where each primitive is an element of computation in the sensorimotor map that transforms desired limb trajectories into motor commands. Theoretical studies have shown that a system's ability to learn action depends on the shape of its primitives(2). Using a time-series analysis of error patterns, here we show that humans learn the dynamics of reaching movements through a flexible combination of primitives that have gaussian-like tuning functions encoding hand velocity. The wide tuning of the inferred primitives predicts limitations on the brain's ability to represent viscous dynamics. We find close agreement between the predicted limitations and the subjects' adaptation to new force fields. The mathematical properties of the derived primitives resemble the tuning curves of Purkinje cells in the cerebellum. The activity of these cells may encode primitives that underlie the learning of dynamics.