The free energy principle for action and perception: A mathematical review

Authored by Anil K Seth, Christopher L Buckley, Chang Sub Kim, Simon McGregor

Date Published: 2017

DOI: 10.1016/j.jmp.2017.09.004

Sponsors: No sponsors listed

Platforms: No platforms listed

Model Documentation: Other Narrative Mathematical description

Model Code URLs: Model code not found

Abstract

The `free energy principle' (FEP) has been suggested to provide a unified theory of the brain, integrating data and theory relating to action, perception, and learning. The theory and implementation of the FEP combines insights from Helmholtzian `perception as inference', machine learning theory, and statistical thermodynamics. Here, we provide a detailed mathematical evaluation of a suggested biologically plausible implementation of the FEP that has been widely used to develop the theory. Our objectives are (i) to describe within a single article the mathematical structure of this implementation of the FEP; (ii) provide a simple but complete agent-based model utilising the FEP and (iii) to disclose the assumption structure of this implementation of the FEP to help elucidate its significance for the brain sciences. (C) 2017 The Authors. Published by Elsevier Inc.

Tags

Agent-based model action Inference Perception Brain Free energy principle Bayesian brain Motor control Cortex