Bayesian mechanics of perceptual inference and motor control in the brain

• Published in: Biological cybernetics Vol. 115; no. 1; pp. 87 - 102
• Main Author: Kim, Chang Sub
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01-02-2021; Springer Nature B.V
• Subjects: Bayesian analysis; Bioinformatics; Biomedical and Life Sciences; Biomedicine; Brain; Complex Systems; Computer Appl. in Life Sciences; Equations of motion; Free energy; Inference; Mathematical analysis; Mechanics (physics); Motor task performance; Neurobiology; Neurosciences; Original; Original Article; Principle of least action; Proprioception; Continuous state-space model; Limit cycles; Free energy principle; Motor signal; Bayesian mechanics; Neural phase space
• ISSN: 0340-1200; 1432-0770
• DOI: 10.1007/s00422-021-00859-9

The free energy principle (FEP) in the neurosciences stipulates that all viable agents induce and minimize informational free energy in the brain to fit their environmental niche. In this study, we continue our effort to make the FEP a more physically principled formalism by implementing free energy minimization based on the principle of least action. We build a Bayesian mechanics (BM) by casting the formulation reported in the earlier publication (Kim in Neural Comput 30:2616–2659, 2018,
https://doi.org/10.1162/neco_a_01115
) to considering active inference beyond passive perception. The BM is a neural implementation of variational Bayes under the FEP in continuous time. The resulting BM is provided as an effective Hamilton’s equation of motion and subject to the control signal arising from the brain’s prediction errors at the proprioceptive level. To demonstrate the utility of our approach, we adopt a simple agent-based model and present a concrete numerical illustration of the brain performing recognition dynamics by integrating BM in neural phase space. Furthermore, we recapitulate the major theoretical architectures in the FEP by comparing our approach with the common state-space formulations.