Cognitive sciences have approached social cognition from two complementary perspectives. On the one hand, social psychology and behavioural economics have mostly emphasized mentalizing, social perception, and our ability to model other minds. On the other hand, developmental psychology and motor neuroscience have more focused on imitating, social interaction, and our propensity to coordinate with others’ behaviour. This polarization leads to a « chicken-egg paradox » regarding the origin of social cognition in humans: while the former claim that we need to model others to interact with them; the later argue that we first need to interact with others to model their minds. Those two perspectives operate at different levels of explanation with different conceptual and mathematical formalisms. For instance, while Bayesian statistics captures social computations well during offline economic games, social coordination during sensorimotor coupling is better modelled using dynamical systems. In this talk, I will illustrate how we can operationalize a « social physiology » modelling human cognition as a multi-scale complex system that interfaces biological and social processes. The term « physiology » was introduced by Claude Bernard not as a medical subfield but rather as a systemic and integrative posture towards biological functions (1865). Here, we will expand this posture by including social functions, using experimental approaches in both natural and artificial agents. We will start with multi-brain neuroscience and how inter-brain connectivity provides a quantitative marker for bridging the gap between intra-personal mechanisms and inter-personal dynamics. Then, we will continue with neuro-inspired artificial intelligence and how the observations initially described in interactive social neuroscience can inspire architectures for virtual avatars and machine learning algorithms.
Bio
Guillaume Dumas is an associate professor of computational psychiatry at the Faculty of Medicine of the University of Montreal and director of the laboratoire de Psychiatrie de Précision et de Physiologie Sociale du Centre de recherche du CHU Sainte-Justine. He holds the IVADO chair in “AI and mental health”, the FRQS J1 scholarship in “AI and digital health” and is an associate academic member at Mila – the Quebec Institute of Artificial Intelligence. He was previously a permanent researcher in neuroscience and computational biology at the Pasteur Institute (Paris, France). Before that, he was a postdoctoral researcher at the Center for Complex Systems and Brain Sciences (FAU, USA). He holds an engineering degree in advanced engineering and computer science (École Centrale Paris), two masters (theoretical physics, Université Paris-Saclay; cognitive sciences, ENS/EHESS/Paris 5), a doctorate in cognitive neuroscience (Sorbonne Université), and the HDR in Clinical Neurosciences (Université de Paris).