Brain and Mind Institute, Western University, London, ON, Canada.
Robarts Research Institute, Western University, London, ON, Canada.
Eur J Neurosci. 2021 Mar;53(5):1605-1620. doi: 10.1111/ejn.15056. Epub 2020 Dec 6.
Previous work has shown that humans account for and learn novel properties or the arm's dynamics, and that such learning causes changes in both the predictive (i.e., feedforward) control of reaching and reflex (i.e., feedback) responses to mechanical perturbations. Here we show that similar observations hold in old-world monkeys (Macaca fascicularis). Two monkeys were trained to use an exoskeleton to perform a single-joint elbow reaching and to respond to mechanical perturbations that created pure elbow motion. Both of these tasks engaged robust shoulder muscle activity as required to account for the torques that typically arise at the shoulder when the forearm rotates around the elbow joint (i.e., intersegmental dynamics). We altered these intersegmental arm dynamics by having the monkeys generate the same elbow movements with the shoulder joint either free to rotate, as normal, or fixed by the robotic manipulandum, which eliminates the shoulder torques caused by forearm rotation. After fixing the shoulder joint, we found a systematic reduction in shoulder muscle activity. In addition, after releasing the shoulder joint again, we found evidence of kinematic aftereffects (i.e., reach errors) in the direction predicted if failing to compensate for normal arm dynamics. We also tested whether such learning transfers to feedback responses evoked by mechanical perturbations and found a reduction in shoulder feedback responses, as appropriate for these altered arm intersegmental dynamics. Demonstrating this learning and transfer in non-human primates will allow the investigation of the neural mechanisms involved in feedforward and feedback control of the arm's dynamics.
先前的研究表明，人类能够掌握和学习新的属性或手臂的动力学特性，并且这种学习会导致对到达的预测性（即前馈）控制和对机械扰动的反射（即反馈）响应发生变化。在这里，我们展示了在旧世界猴（Macaca fascicularis）中也存在类似的观察结果。两只猴子接受训练，使用外骨骼来执行单关节肘部伸展运动，并对产生纯肘部运动的机械扰动做出反应。这两个任务都需要有强壮的肩部肌肉活动，以补偿通常在前臂绕肘部关节旋转时在肩部产生的扭矩（即，节间动力学）。我们通过让猴子以正常方式让肩部自由旋转或通过机器人操纵器固定肩部关节来产生相同的肘部运动，从而改变这些节间手臂动力学。固定肩部关节后，我们发现肩部肌肉活动有系统地减少。此外，再次释放肩部关节后，我们发现了在未能补偿正常手臂动力学时，运动学后效（即，到达误差）在预测方向上的证据。我们还测试了这种学习是否可以转移到由机械扰动引起的反馈响应中，并发现肩部反馈响应减少，这与这些改变的节间手臂动力学是相适应的。在非人类灵长类动物中证明这种学习和转移，将允许研究手臂动力学的前馈和反馈控制涉及的神经机制。
