The Language of Neurons15th & 16th September 2023, Barcelona

This talk explores the concept of neural representation through the lens of active inference, a normative framework for understanding brain function. It delves into how living organisms employ generative models to minimize the discrepancy between predictions and observations (or variational free energy), emphasizing the role of generative models and belief dynamics. The talk highlights that the brain learns generative models to navigate the world adaptively, not (or not solely) to understand it. Different living organisms may possess an array of generative models, spanning from those that support action-perception cycles to those that also enable planning and imagination; from “explicit” models that involve variables for inferring external entities like objects, faces, or people, to “action-oriented models” that prioritize predicting action outcomes, omitting the need to encode external entities. Then, it elucidates how generative models and belief dynamics might link to neural representation and the implications of different types of generative models on understanding an organism’s ecological niche and cognitive capabilities. The talk concludes with open questions regarding the evolution of generative models and the development of advanced cognitive abilities – and the gradual transition from “pragmatic” to “detached” neural representations.