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首页> 外文期刊>Journal of Computational Neuroscience >Optimality, stochasticity, and variability in motor behavior
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Optimality, stochasticity, and variability in motor behavior

机译：运动行为的最优性，随机性和可变性

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Recent theories of motor control have proposed that the nervous system acts as a stochastically optimal controller, i.e. it plans and executes motor behaviors taking into account the nature and statistics of noise. Detrimental effects of noise are converted into a principled way of controlling movements. Attractive aspects of such theories are their ability to explain not only characteristic features of single motor acts, but also statistical properties of repeated actions. Here, we present a critical analysis of stochastic optimality in motor control which reveals several difficulties with this hypothesis. We show that stochastic control may not be necessary to explain the stochastic nature of motor behavior, and we propose an alternative framework, based on the action of a deterministic controller coupled with an optimal state estimator, which relieves drawbacks of stochastic optimality and appropriately explains movement variability.
机译：最近的运动控制理论提出，神经系统起着随机最优控制器的作用，即在考虑到噪声的性质和统计之后，它计划并执行运动行为。噪声的有害影响被转换为控制运动的原理方法。这些理论的吸引人的方面是它们不仅能够解释单个动作的特征，而且能够解释重复动作的统计特性。在这里，我们对电机控制中的随机最优进行了批判性分析，揭示了这一假设的若干困难。我们证明了随机控制不一定是解释运动行为的随机性的必要条件，并且基于确定性控制器的作用和最优状态估计器，我们提出了一个替代框架，该框架可减轻随机最优性的缺点并适当地解释运动变化性。

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