Understanding the motor dynamics of interpersonal interactions

Many of our everyday actions are performed in a social setting and are coordinated with the actions of other people. Research has found that stable and effective social motor coordination breaks down in pathologies such as autism and schizophrenia, is related to the psychological connectedness of individuals, and consequently, important for the development of naturally interacting artificial agents. We review research that investigates the self-organizing dynamics of goal-directed interpersonal actions and then discuss experiments that investigate the temporal and spatial patterns that dynamically emerge during structured interpersonal interactions. We first demonstrate how stable state oscillatory dynamics are established in a more stereotyped hand-clapping task. Then we show how a structured conversation task can be used to evaluate how whole body activity rhythms of speaker and listener are coordinated across multiple time scales. Our ultimate goal is to be able to mathematically model the dynamics of social motor coordination, specifically, how its stable states are activated, dissolved, transformed, and exchanged over time, in order to enhance our understanding of its role in social pathologies and in creating behaviorally flexible and mutually responsive artificial human-machine systems.