Decomposing Predictive Information in Social Dynamics

Abstract

Social behaviors include some of the most interesting interactions in living systems yet their principled characterization remains unsolved. Here we suggest that at the core of social interactions is the notion of mutual prediction, which we analyze in the context of two male zebrafish engaged in a dominance contest. Using 3D velocity trajectories, we construct the mutual information between a two-animal past and one-animal future, and we quantify the redundant, unique, and synergistic components using partial information decomposition across time windows. We find that predictive information decomposition naturally aligns with important social concepts, such as mirroring and dominance. At contest end, we find asymmetries in self-unique and redundant information that reflect the emergent dominance relationship. Applied to mecp2 zebrafish mutants, an autism model, we find that predictive information is reduced overall, but especially for synergistic flows, which is indicative of difficulties in more complex social dynamics. Significance StatementSocial interactions are rich and diverse, ranging from mirroring to complementary actions. A unifying framework for defining and analyzing such interaction types has long been needed. Here, based on modern information theory, we formulate how the past state of interacting organisms encodes the future state of an individual. This framework provides a natural decomposition of pairwise social dynamics into mirroring, independent action, directed influence, and joint action. Applied to dominance contests in zebrafish, these modes of interaction capture distinct phases of conflict, their assessment strategies, and the resulting dominance relationships. Moreover, our analysis reveals a specific disruption in the social behavior of mutant zebrafish linked to autism, shedding new light on impairments in communication and social learning.