Optimal feedback control as a theory of motor coordination
Optimal feedback control as a theory of motor coordination
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DOI：
10.1038/nn963
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发表时间：
2002-11-01
影响因子：
25
通讯作者：
Jordan, MI
中科院分区：
文献类型：
--
作者：
Todorov, E;Jordan, MI
运动控制中的一个中心问题是了解如何协调许多生物力学自由度以实现共同的目标。协调的一个特别令人费解的方面是，行为目标是可靠和重复地实现的，动作的细节很少重现。现有的理论框架要么强调目标实现，要么强调运动变异性的丰富性，但未能协调两者。这里，我们提出了一种基于随机最优反馈控制的替代理论。我们表明，面对不确定性，最优策略是允许冗余(与任务无关)维度的可变性。这种策略不会强制执行所需的轨迹，而是更智能地使用反馈，只纠正那些干扰任务目标的偏差。在这个框架下，任务约束的可变性、目标导向的修正、运动协同、受控参数、简化规则和离散的协调模式自然产生。我们提供了一系列运动任务的实验结果来支持这一理论。
A central problem in motor control is understanding how the many biomechanical degrees of freedom are coordinated to achieve a common goal. An especially puzzling aspect of coordination is that behavioral goals are achieved reliably and repeatedly with movements rarely reproducible in their detail. Existing theoretical frameworks emphasize either goal achievement or the richness of motor variability, but fail to reconcile the two. Here we propose an alternative theory based on stochastic optimal feedback control. We show that the optimal strategy in the face of uncertainty is to allow variability in redundant (task-irrelevant) dimensions. This strategy does not enforce a desired trajectory, but uses feedback more intelligently, correcting only those deviations that interfere with task goals. From this framework, task-constrained variability, goal-directed corrections, motor synergies, controlled parameters, simplifying rules and discrete coordination modes emerge naturally. We present experimental results from a range of motor tasks to support this theory.