Towards an information-theoretic social neuroscience

Social neuroscience sets out to uncover the neural mechanisms and dynamics of human sociality. Interpersonal coordination on various levels—neural, behavioural, physiological, affective, linguistic— are hallmarks of successful social communication and cooperation. However, describing these complex, interdependent dynamics has been limited by current methodological approaches, owing to a restrictive repertoire of tools and the absence of a unified, standardised methodological framework. Here, we identify information theory, the mathematical theory of communication, as a particularly well-suited conceptual framework to address this shortfall, given its appropriate sensitivity to complex dynamics, including potential nonlinearity and higher-order interactions, and its data-driven approach. Indeed, with its firm grounding in computational, cognitive, and systems neuroscience, the introduction of information-theoretic quantities and methods into social neuroscience is perhaps overdue. This Perspective presents the case for a unified information-theoretic framework to describe and model the complex dynamics of social systems whilst generating new, open research questions.