Digital Screener of Socio-Motor Agency Balancing Autonomy and Control

Dyadic social interactions evoke complex dynamics between two agents that while exchanging unequal levels of body autonomy and motor control, may find a fine balance to take turns and gradually build social rapport. To study the evolution of such complex interactions, we currently rely exclusively on subjective pencil and paper means. Here we complement this approach with objective biometrics of socio-motor behaviors conducive of socio-motor agency. Using a common clinical test as the backdrop of our study to probe social interactions between a child and a clinician, we demonstrate new ways to streamline the detection of social readiness potential in both typically developing and autistic children. We highlight differences between males and females and uncover a new data type amenable to generalize our results to any social settings. The new methods convert dyadic bodily biorhythmic activity into spike trains and demonstrates that in the context of dyadic behavioral analyses, they are well characterized by a continuous gamma process independent from corresponding binary spike rates. We offer a new framework that combines stochastic analyses, nonlinear dynamics, and information theory, to facilitate scaling the screening and tracking of social interactions with applications to autism.