Free-energy and the brain
Free-energy and the brain
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DOI：
10.1007/s11229-007-9237-y
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发表时间：
2007-12-01
期刊：
影响因子：
1.5
通讯作者：
Stephan, Klaas E.
中科院分区：
文献类型：
--
作者：
Friston, Karl J.;Stephan, Klaas E.
如果一个人用现代理论来阐述亥姆霍兹关于知觉的观点，他就会得出一个知觉推理和学习的模型，这个模型可以解释一系列显著的神经生物学事实。使用统计物理学的结构，可以证明，推断是什么导致我们的感觉输入和学习感觉中枢中的因果关系的问题可以使用完全相同的原理来解决。此外，推理和学习可以以生物学上合理的方式进行。随后的计划依赖于经验贝叶斯和层次模型的感觉信息是如何产生的。分层模型的使用使大脑能够以动态和上下文敏感的方式构建先前的期望。这个方案提供了一个原则性的方法来理解大脑组织和反应的许多方面。在本文中，我们认为这些感知过程只是符合自由能原理的系统的一个涌现特性。这里考虑的自由能代表了与环境进行任何交换所固有的惊奇的一种约束，这种交换是在其状态或配置所编码的期望之下进行的。一个系统可以通过改变它的配置来改变它对环境的采样方式，或者改变它的期望值，从而使自由能最小化。这些变化分别对应于行动和感知，并导致与环境的适应性交换，这是生物系统的特征。这种处理意味着系统的状态和结构编码的环境的隐式和概率模型。我们将研究大脑所需要的模型，以及自由能的最小化如何解释其动力学和结构。
If one formulates Helmholtz's ideas about perception in terms of modern-day theories one arrives at a model of perceptual inference and learning that can explain a remarkable range of neurobiological facts. Using constructs from statistical physics it can be shown that the problems of inferring what cause our sensory inputs and learning causal regularities in the sensorium can be resolved using exactly the same principles. Furthermore, inference and learning can proceed in a biologically plausible fashion. The ensuing scheme rests on Empirical Bayes and hierarchical models of how sensory information is generated. The use of hierarchical models enables the brain to construct prior expectations in a dynamic and context-sensitive fashion. This scheme provides a principled way to understand many aspects of the brain's organisation and responses. In this paper, we suggest that these perceptual processes are just one emergent property of systems that conform to a free-energy principle. The free-energy considered here represents a bound on the surprise inherent in any exchange with the environment, under expectations encoded by its state or configuration. A system can minimise free-energy by changing its configuration to change the way it samples the environment, or to change its expectations. These changes correspond to action and perception, respectively, and lead to an adaptive exchange with the environment that is characteristic of biological systems. This treatment implies that the system's state and structure encode an implicit and probabilistic model of the environment. We will look at models entailed by the brain and how minimisation of free-energy can explain its dynamics and structure.