A Free Energy Principle for Biological Systems

By Karl J. Friston. Entropy, 2012

334 citations recorded by the source corpus.

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.

Subfields: Cognitive Neuroscience, Molecular Biology, Statistical and Nonlinear Physics

View Paper: https://www.semanticscholar.org/paper/50d548af47e5003e96bafb4ce4119a75c0a6d403

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Citations in the corpus

The math is not the territory: navigating the free energy principle (2021, positive): “…equation and, in particular, the solenoidal and irrota-tional flows that fall out of the Helmholtz decomposition thereof, of which the irro-tational flow can be conceptualised as a gradient-ascent on an attracting set (Friston 2009, 2010, 2012, 2019; Friston and Stephan 2007; Friston et al. 2008).”
Rectified Factor Networks (2015, background): “The hidden variables can be considered as the fictive causes or explanations of environmental fluctuations [43].”
Emotional States from Affective Dynamics (2013, background): “The goal of the mind is to settle into a stable, predictive internal representation of the environment, similar to a system going from a high entropy state to a low entropy state (see Friston, 2012, for a formal discussion of these principles for biological systems).”
A Quantum–Classical Model of Brain Dynamics (2023, background): “An interesting connection of GS to quantum models of decision making, which is yet to be fully explored, may be founded on the free energy principle [132, 133].”