Visuomotor feedback gains upregulate during the learning of novel dynamics.
Visuomotor feedback gains upregulate during the learning of novel dynamics.
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DOI：
10.1152/jn.01123.2011
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发表时间：
2012-07
影响因子：
2.5
通讯作者：
Franklin DW
中科院分区：
文献类型：
--
作者：
Franklin S;Wolpert DM;Franklin DW
在学习新动态的早期阶段，肌肉活动的变化主要是由于纠正反馈反应。随着前馈控制的学习，这些反馈对整个运动指令的贡献逐渐减少。反馈使用的暂时增加可能仅仅是由于早期学习中的大误差，要么是增益不变，要么是增益略有下调，要么是前馈预测不足时反馈增益的上调。因此，我们研究了感觉运动控制系统在适应机器人操纵臂产生的新力场时是否会改变反馈增益。为了探究学习过程中的反馈增益，我们测量了手在伸手过程中视觉位置快速变化时的非自愿快速视觉运动反应的幅度。我们发现，每当动态变化时，快速视觉运动反应的幅度都会大幅增加：无论是在力场首次出现时，还是在力场被移除时。我们证实这些反馈增益的变化不仅仅是背景负载变化的副产品，通过证明这种快速的视觉运动响应不是负载敏感的。我们的研究结果表明，当感觉运动控制系统出现错误时，它会增加视觉运动反馈通路的增益来处理意外干扰，直到前馈控制器学习到适当的动态。我们建议这些反馈增益随着动力学知识的不确定性增加而上调，以抵消任何错误或干扰，并确保准确和熟练的运动。
At an early stage of learning novel dynamics, changes in muscle activity are mainly due to corrective feedback responses. These feedback contributions to the overall motor command are gradually reduced as feedforward control is learned. The temporary increased use of feedback could arise simply from the large errors in early learning with either unaltered gains or even slightly downregulated gains, or from an upregulation of the feedback gains when feedforward prediction is insufficient. We therefore investigated whether the sensorimotor control system alters feedback gains during adaptation to a novel force field generated by a robotic manipulandum. To probe the feedback gains throughout learning, we measured the magnitude of involuntary rapid visuomotor responses to rapid shifts in the visual location of the hand during reaching movements. We found large increases in the magnitude of the rapid visuomotor response whenever the dynamics changed: both when the force field was first presented, and when it was removed. We confirmed that these changes in feedback gain are not simply a byproduct of the change in background load, by demonstrating that this rapid visuomotor response is not load sensitive. Our results suggest that when the sensorimotor control system experiences errors, it increases the gain of the visuomotor feedback pathways to deal with the unexpected disturbances until the feedforward controller learns the appropriate dynamics. We suggest that these feedback gains are upregulated with increased uncertainty in the knowledge of the dynamics to counteract any errors or disturbances and ensure accurate and skillful movements.
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