A Free Energy Principle for Biological Systems

被引:208
|
作者
Karl, Friston [1 ]
机构
[1] Wellcome Trust Ctr Neuroimaging, Inst Neurol, London WC1N 3BG, England
来源
ENTROPY | 2012年 / 14卷 / 11期
基金
英国惠康基金;
关键词
ergodicity; Bayesian; random dynamical system; self-organization; free energy; surprise; THERMODYNAMICS; UNCERTAINTY; EQUATIONS; BRAIN;
D O I
10.3390/e14112100
中图分类号
O4 [物理学];
学科分类号
0702 ;
摘要
This paper describes a free energy principle that tries to explain the ability of biological systems to resist a natural tendency to disorder. It appeals to circular causality of the sort found in synergetic formulations of self-organization (e.g., the slaving principle) and models of coupled dynamical systems, using nonlinear Fokker Planck equations. Here, circular causality is induced by separating the states of a random dynamical system into external and internal states, where external states are subject to random fluctuations and internal states are not. This reduces the problem to finding some (deterministic) dynamics of the internal states that ensure the system visits a limited number of external states; in other words, the measure of its (random) attracting set, or the Shannon entropy of the external states is small. We motivate a solution using a principle of least action based on variational free energy (from statistical physics) and establish the conditions under which it is formally equivalent to the information bottleneck method. This approach has proved useful in understanding the functional architecture of the brain. The generality of variational free energy minimisation and corresponding information theoretic formulations may speak to interesting applications beyond the neurosciences; e.g., in molecular or evolutionary biology.
引用
收藏
页码:2100 / 2121
页数:22
相关论文
共 50 条
  • [41] The Hard Problem of Consciousness and the Free Energy Principle
    Solms, Mark
    FRONTIERS IN PSYCHOLOGY, 2019, 9
  • [42] Computational enactivism under the free energy principle
    Korbak, Tomasz
    SYNTHESE, 2021, 198 (03) : 2743 - 2763
  • [43] The free energy principle induces neuromorphic development
    Fields, Chris
    Friston, Karl
    Glazebrook, James F.
    Levin, Michael
    Marciano, Antonino
    NEUROMORPHIC COMPUTING AND ENGINEERING, 2022, 2 (04):
  • [44] Application of the Free Energy Principle to Estimation and Control
    van de Laar, Thijs
    Ozcelikkale, Ayca
    Wymeersch, Henk
    IEEE TRANSACTIONS ON SIGNAL PROCESSING, 2021, 69 : 4234 - 4244
  • [45] Computational enactivism under the free energy principle
    Tomasz Korbak
    Synthese, 2021, 198 : 2743 - 2763
  • [46] An Overview of the Free Energy Principle and Related Research
    Zhang, Zhengquan
    Xu, Feng
    NEURAL COMPUTATION, 2024, 36 (05) : 963 - 1021
  • [47] Emotional Valence and the Free-Energy Principle
    Joffily, Mateus
    Coricelli, Giorgio
    PLOS COMPUTATIONAL BIOLOGY, 2013, 9 (06)
  • [48] Models of the Translation Process and the Free Energy Principle
    Carl, Michael
    ENTROPY, 2023, 25 (06)
  • [49] A Free-Energy Principle for Representation Learning
    Gao, Yansong
    Chaudhari, Pratik
    25TH AMERICAS CONFERENCE ON INFORMATION SYSTEMS (AMCIS 2019), 2019,
  • [50] Exploring the free-energy landscapes of biological systems with steered molecular dynamics
    Chen, L. Y.
    PHYSICAL CHEMISTRY CHEMICAL PHYSICS, 2011, 13 (13) : 6176 - 6183