Bridging the Explanatory Gap between Neuronal Activity and Cognition through Multilevel Causal Modeling

Description

Explaining how neuronal activity gives rise to cognition remains the
most significant challenge in cognitive neuroscience. In the first part
of this talk, I will introduce neuro-cognitive multilevel causal
modeling (NC-MCM), a mathematical framework that bridges the explanatory
gap between neuronal activity and cognition by construing cognitive
states as causally consistent abstractions of neuronal states. I will
then show how the NC-MCM framework enables us to reason interchangeably
about the dynamics and behavior of an organism on the neuronal and
cognitive levels. In the second part of this talk, I will present an
algorithm for learning NC-MCMs from neuronal activation patterns and
demonstrate its ability to learn cognitive states of the nematode C.
elegans from calcium imaging data.

Period	6 Jun 2023
Held at	Institut du Cerveau et de la Moelle Epinière, France