From Data Streams to Information Flow: Information Exchange in Child-Parent Interaction

Abstract

The goal of this paper is to enhance understanding of how bodily actions between two social partners are coordinated in interpersonal interactions in naturalistic contexts. We introduce information-theoretic measures as a new approach to capturing sensorimotor dynamics in child-parent social interaction. In particular, information flows were measured based on a set of variables extracted from multimodal fine-grained behavioral data in social interactions wherein a child and a parent played with novel toys. Our results showed that information-theoretic measures can indeed capture the inherent structure of perception and action dynamics and further information exchange patterns can be used to predict successful learning through child-parent interactions. Moreover, those information flows between sensorimotor variables reveal a set of underlying perceptual and motor patterns with cognitively plausible explanations. In summary, the present study represents the first steps to connect information-theoretic measures as a mathematically rigorous framework with embodied human communication and cognition.


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