Friston Karl J, Daunizeau Jean, Kilner James, Kiebel Stefan J
The Wellcome Trust Centre for Neuroimaging, Institute of Neurology, University College London, 12 Queen Square, London, WC1N 3BG, UK.
Biol Cybern. 2010 Mar;102(3):227-60. doi: 10.1007/s00422-010-0364-z. Epub 2010 Feb 11.
We have previously tried to explain perceptual inference and learning under a free-energy principle that pursues Helmholtz's agenda to understand the brain in terms of energy minimization. It is fairly easy to show that making inferences about the causes of sensory data can be cast as the minimization of a free-energy bound on the likelihood of sensory inputs, given an internal model of how they were caused. In this article, we consider what would happen if the data themselves were sampled to minimize this bound. It transpires that the ensuing active sampling or inference is mandated by ergodic arguments based on the very existence of adaptive agents. Furthermore, it accounts for many aspects of motor behavior; from retinal stabilization to goal-seeking. In particular, it suggests that motor control can be understood as fulfilling prior expectations about proprioceptive sensations. This formulation can explain why adaptive behavior emerges in biological agents and suggests a simple alternative to optimal control theory. We illustrate these points using simulations of oculomotor control and then apply to same principles to cued and goal-directed movements. In short, the free-energy formulation may provide an alternative perspective on the motor control that places it in an intimate relationship with perception.
我们之前曾尝试在自由能原理的框架下解释知觉推理和学习，该原理遵循了亥姆霍兹的研究议程，即从能量最小化的角度来理解大脑。很容易证明，在给定感官数据产生方式的内部模型的情况下，对感官数据的原因进行推理可以被视为最小化感官输入可能性的自由能边界。在本文中，我们考虑如果对数据本身进行采样以最小化这个边界会发生什么。结果表明，基于适应性主体的存在，遍历性论证要求进行随后的主动采样或推理。此外，它解释了运动行为的许多方面，从视网膜稳定到目标导向。特别是，它表明运动控制可以被理解为满足对本体感觉的先验期望。这种表述可以解释适应性行为在生物主体中为何会出现，并为最优控制理论提供了一种简单的替代方案。我们通过眼动控制模拟来说明这些观点，然后将相同的原理应用于线索引导和目标导向运动。简而言之，自由能表述可能为运动控制提供一个替代视角，使运动控制与知觉建立紧密联系。
