Lecture 2: Active inference and belief propagation in the brain

О мероприятии

В рамках визита Карла Фристона будет организована серия мастер-классов

A masterclass in the free energy principle

This workshop comprises three lectures covering the various aspects of the free energy principle (delivered by its principal architect – Karl Friston); namely, biological self organisation in dynamical systems like the brain and how this leads to predictive coding and embodied (active) inference. The second lecture deals with equivalent formulations of active inference for models of the world that can be described in terms of discrete states (and time steps). The final lecture will consider recent advances in Bayesian model selection and averaging in the brain that provide a formalism for artificial curiosity and insight.

Lecture 2: Active inference and belief propagation in the brain.

This presentation considers deep temporal models in the brain. It builds on previous formulations of active inference to simulate behaviour and electrophysiological responses under deep (hierarchical) generative models of discrete state transitions. The deeply structured temporal aspect of these models means that evidence is accumulated over distinct temporal scales, enabling inferences about narratives (i.e., temporal scenes). Se illustrate this behaviour in terms of Bayesian belief updating – and associated neuronal processes – to reproduce the epistemic foraging seen in reading. These simulations reproduce these sort of perisaccadic delay period activity and local field potentials seen empirically; including evidence accumulation and place cell activity. Finally, we exploit the deep structure of these models to simulate responses to local (e.g., font type) and global (e.g., semantic) violations; reproducing mismatch negativity and P300 responses respectively. These simulations are presented as an example of how to use basic principles to constrain our understanding of system architectures in the brain – and the functional imperatives that may apply to neuronal networks.

рабочий язык мероприятия: английский

Программа мероприятия