Self-organization and circular causation as synergetic foundations of social interaction: a multilayer network perspective

, which frames interpersonal coordination as a self-organizing process in multilayer networks, where circular causation across levels gives rise to emergent order parameters. These order parameters-dynamical, capturing temporal patterns such as shared oscillations and phase relationships, and structural, reflecting stable network topologies or hyper-brain modules-serve as measurable markers of collective organization. Empirical examples from hyperscanning, ensemble music performance, choral singing, and romantic interactions demonstrate how local interactions within and between subsystems or brains stabilize macro-level coordination patterns, providing preliminary support for the framework. The hypothesis predicts that stronger and more symmetrical coupling across neural, autonomic, and/or behavioral layers will produce more robust and persistent alignment between interacting individuals. This framework integrates network neuroscience, dynamical systems theory, and synergetics, offering a novel conceptual and methodological roadmap for investigating the mechanisms of social cognition and collective behavior.