Neural and behavioural manifold dynamics align across interacting individuals

Coordinating actions with others is fundamental for social behaviour, requiring the nervous system to continuously adapt motor output to a partner's evolving behaviour. Yet the neural population principles supporting such coordination remain poorly understood. To address this, we investigated interpersonal coordination across two dual-EEG studies comprising 44 dyads (88 participants) engaged in either instructed finger movement synchronization or spontaneous face-to-face interaction. Combining kinematics-informed deep contrastive learning with dynamical-systems modelling, we identified low-dimensional neural manifolds. These manifolds aligned geometrically and temporally across interacting partners, mirrored their coordinated behaviour, and uncovered interpersonal alignment not captured by traditional synchrony measures. Importantly, these manifolds exhibited flexible attractor-like organization consistent with a synergistic, dynamical account of motor control, with attractor properties that were co-regulated across partners. Collectively, we propose a novel mechanism in which interpersonal coordination emerges through the intermittent updating of internally organized dynamics by a partner's movements. More broadly, our results establish movement-informed latent-space modeling as a framework for uncovering the low-dimensional population dynamics linking neural activity, neuromuscular control and interpersonal coordination.