A Universal Theory of Brain Function

Head to https://squarespace.com/artem to save 10% off your first purchase of a website or domain using code ARTEM Socials: X/Twitter: https://x.com/ArtemKRSV Patreon: https://patreon.com/artemkirsanov My name is Artem, I'm a graduate student at NYU Center for Neural Science and researcher at Flatiron Institute. In this video explore Free Energy Principle – a powerful framework in neuroscience, which aims to explain brain function as predicting sensory observations through building models of the world. We discuss generative and recognition models, the role of priors, variational inference, and how free energy principle explains some every day observations such as optical illusion. This is a high-level conceptual, rather than mathematical treatment. Outline: 00:00 Introduction 01:34 Role of world models 03:56 Free Energy as tradeoff between accuracy and complexity 05:20 Sponsor: Squarespace 06:35 Generative Model 10:03 Priors 12:18 Approximate Inference via Recognition Model 14:14 Free Energy balance revisited 16:34 Explanation for optical illusion 17:55 Review References: Bogacz, Rafal. “A Tutorial on the Free-Energy Framework for Modelling Perception and Learning.” Journal of Mathematical Psychology 76 (February 2017): 198–211. https://doi.org/10.1016/j.jmp.2015.11.003. Friston, Karl. “Learning and Inference in the Brain.” Neural Networks 16, no. 9 (November 2003): 1325–52. https://doi.org/10.1016/j.neunet.2003.06.005. Friston, Karl, Thomas FitzGerald, Francesco Rigoli, Philipp Schwartenbeck, John O⿿Doherty, and Giovanni Pezzulo. “Active Inference and Learning.” Neuroscience & Biobehavioral Reviews 68 (September 2016): 862–79. https://doi.org/10.1016/j.neubiorev.2016.06.022. Parr, Thomas, Giovanni Pezzulo, and K. J. Friston. Active Inference: The Free Energy Principle in Mind, Brain, and Behavior. Cambridge, Massachusetts: The MIT Press, 2022. Icons by Freepik and Biorender