A Roadmap to Computational Social Neuroscience

Emmanuelle Tognoli (1) , Guillaume Dumas (2, 1, 3) , J.A. Scott Kelso (4, 1)

1 Center for Complex Systems and Brain Sciences
2 CNRS - UMR3571 - Gènes, Synapses et Cognition
3 GHFC (UMR_3571 / U-Pasteur_1) - Génétique humaine et fonctions cognitives - Human Genetics and Cognitive Functions
4 Intelligent Systems Research Centre

To complement experimental efforts toward understanding human social interactions at both neural and behavioral levels, two computational approaches are presented: (1) a fully parameterizable mathematical model of a social partner, the Human Dynamic Clamp which, by virtue of experimentally controlled interactions with real people, allows for emergent behaviors to be studied; and (2) a multiscale neurocomputational model of social behavior that enables exploration of social self-organization at all levels—from neuronal patterns to people interacting with each other. These complementary frameworks and the cross product of their analysis aim at understanding the fundamental principles governing social behavior.

Keywords: social coordination; HKB; spatiotemporal patterns; coordination dynamics

Domains: Cognitive science; Computer Science [cs]; Human-Computer Interaction [cs.HC]; Cognitive science; Neuroscience

Emmanuelle Tognoli, Guillaume Dumas, J.A. Scott Kelso. A Roadmap to Computational Social Neuroscience. 5th International Conference on Cognitive Neurodynamics, Jun 2015, Sanya, China. ⟨pasteur-01342841⟩