Brain and Mind Institute, Western University, London, Ontario, Canada.
Robarts Research Institute, Western University, London, Ontario, Canada.
J Neurophysiol. 2020 Mar 1;123(3):1193-1205. doi: 10.1152/jn.00696.2019. Epub 2020 Feb 26.
Generalizing newly learned movement patterns beyond the training context is challenging for most motor learning situations. Here we tested whether learning of a new physical property of the arm during self-initiated reaching generalizes to new arm configurations. Human participants performed a single-joint elbow reaching task and/or countered mechanical perturbations that created pure elbow motion with the shoulder joint free to rotate or locked by the manipulandum. With the shoulder free, we found activation of shoulder extensor muscles for pure elbow extension trials, appropriate for countering torques that arise at the shoulder due to forearm rotation. After locking the shoulder joint, we found a partial reduction in shoulder muscle activity, appropriate because locking the shoulder joint cancels the torques that arise at the shoulder due to forearm rotation. In our first three experiments, we tested whether and to what extent this partial reduction in shoulder muscle activity generalizes when reaching in different situations: ) different initial shoulder orientation, ) different initial elbow orientation, and ) different reach distance/speed. We found generalization for the different shoulder orientation and reach distance/speed as measured by a reliable reduction in shoulder activity in these situations but no generalization for the different elbow orientation. In our fourth experiment, we found that generalization is also transferred to feedback control by applying mechanical perturbations and observing reflex responses in a distinct shoulder orientation. These results indicate that partial learning of new intersegmental dynamics is not sufficient for modifying a general internal model of arm dynamics. Here we show that partially learning to reduce shoulder muscle activity following shoulder fixation generalizes to other movement conditions, but it does not generalize globally. These findings suggest that the partial learning of new intersegmental dynamics is not sufficient for modifying a general internal model of the arm's dynamics.
将新习得的运动模式泛化到训练环境之外是大多数运动学习情况面临的挑战。在这里,我们测试了在自我发起的手臂伸展任务中,学习手臂新的物理特性是否会泛化到新的手臂构型。人类参与者执行了单关节肘部伸展任务,并/或对抗机械干扰,这些干扰会产生纯肘部运动,同时允许肩部关节自由旋转或由操纵器锁定。在肩部自由的情况下,我们发现纯肘部伸展试验中激活了肩部伸肌,这适合抵消由于前臂旋转而在肩部产生的扭矩。在锁定肩部关节后,我们发现肩部肌肉活动部分减少,这是因为锁定肩部关节会抵消由于前臂旋转而在肩部产生的扭矩。在我们的前三个实验中,我们测试了当在不同情况下进行伸展时,这种肩部肌肉活动的部分减少是否以及在多大程度上可以泛化:)不同的初始肩部姿势,)不同的初始肘部姿势,和)不同的伸展距离/速度。我们发现,在这些情况下,肩部活动的可靠减少表明了不同肩部姿势和伸展距离/速度的泛化,但对不同肘部姿势没有泛化。在我们的第四个实验中,我们发现通过在不同的肩部姿势下施加机械干扰并观察反射反应,这种泛化也会转移到反馈控制中。这些结果表明,对新的节间动力学的部分学习不足以修改手臂动力学的一般内部模型。在这里,我们表明,在肩部固定后部分学习减少肩部肌肉活动会泛化到其他运动条件,但不会全局泛化。这些发现表明,对新的节间动力学的部分学习不足以修改手臂动力学的一般内部模型。