Neural representations of dynamic social interactions

Humans effortlessly learn attributes of other individuals and their complex web of connections through navigating the social world1,2. Yet, the neural mechanisms that transform these transient interactions into structured, multidimensional knowledge remain unknown3,4. Here, using a naturalistic fMRI paradigm5, we develop a computational framework to demonstrate how the human brain factorizes and integrates dynamic social interactions to construct multiplex social graphs. This approach not only predicts neural responses during movie-viewing but also allows for the reconstruction of subjective social cognitive maps directly from brain activity. Crucially, the relational geometry of these reconstructed maps accurately predicts inferred personality traits, indicating that relational and trait knowledge emerge from a shared neural representation reflecting interactional dynamics. These findings reveal an organizing computational principle by which the brain transforms dynamic social experiences into structured cognitive maps6, providing a key mechanism for the emergence of multiplex social knowledge in the human mind.