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	25 Jan 2024
Held at	Österreichische Akademie der Wissenschaften (ÖAW), Austria