PDF(Pubmed)
Abstract：
The stabilization of human quiet stance is achieved by a combination of the intrinsic elastic properties of ankle muscles and an active closed-loop activation of the ankle muscles, driven by the delayed feedback of the ongoing sway angle and the corresponding angular velocity in a way of a delayed proportional (P) and derivative (D) feedback controller. It has been shown that the active component of the stabilization process is likely to operate in an intermittent manner rather than as a continuous controller: the switching policy is defined in the phase-plane, which is divided in dangerous and safe regions, separated by appropriate switching boundaries. When the state enters a dangerous region, the delayed PD control is activated, and it is switched off when it enters a safe region, leaving the system to evolve freely. In comparison with continuous feedback control, the intermittent mechanism is more robust and capable to better reproduce postural sway patterns in healthy people. However, the superior performance of the intermittent control paradigm as well as its biological plausibility, suggested by experimental evidence of the intermittent activation of the ankle muscles, leaves open the quest of a feasible learning process, by which the brain can identify the appropriate state-dependent switching policy and tune accordingly the P and D parameters. In this work, it is shown how such a goal can be achieved with a reinforcement motor learning paradigm, building upon the evidence that, in general, the basal ganglia are known to play a central role in reinforcement learning for action selection and, in particular, were found to be specifically involved in postural stabilization.
摘要：
人体安静姿态的稳定是通过踝关节肌肉固有的弹性特性和踝关节肌肉的主动闭环激活相结合来实现的,以延迟比例（P）和微分（D）反馈控制器的方式，由正在进行的摇摆角和相应的角速度的延迟反馈驱动。已经表明，稳定过程的有源组件很可能以间歇方式而不是作为连续控制器运行：切换策略在相平面中定义，分为危险和安全区域，由适当的切换边界分隔。当状态进入危险区域时，延迟PD控制被激活，当它进入安全区域时，它会被关闭，让系统自由发展。与连续反馈控制相比，间歇性机制更强大，能够更好地再现健康人的姿势摇摆模式。然而,间歇性控制范例的卓越性能及其生物学合理性，踝关节肌肉间歇性激活的实验证据表明，留下了一个可行的学习过程的探索，大脑可以识别适当的状态相关切换策略，并相应地调整P和D参数。在这项工作中,它显示了如何通过强化运动学习范式来实现这样的目标，在证据的基础上，总的来说,已知基底神经节在强化学习的动作选择中起着核心作用，特别是,被发现特别参与姿势稳定。
