From Traditional Tasks to Hyperscanning: Exploratory Evidence for Selective Modulation of Sensorimotor Neurodynamics Using Time-Resolved Generalized Additive Model Analysis.

Sensorimotor rhythms in the mu (8-13 Hz) and beta (13-30 Hz) frequency ranges provide a canonical window into action-related neural dynamics. While these rhythms are known to reflect movement preparation, execution, and postmovement regulation, less is known about how their temporal organization varies across increasingly ecological interactional contexts. Here, we used a four-tier scalable experimental design (SED) based on the rock-paper-scissors (RPS) game to examine sensorimotor event-related desynchronization/synchronization (ERD/ERS) across contexts ranging from individual computer-based tasks to real-time dyadic hyperscanning. Mu, beta, and a mu + beta composite ERD/ERS activity were analyzed over canonical central sensorimotor electrodes and aligned to a common motor event (button press). Time-resolved generalized additive models (GAMs) were used to estimate nonlinear trajectories. Pairwise contrasts were evaluated using max-statistic permutation testing across time. Most comparisons among computer-based conditions did not survive correction. Suprathreshold clusters found were selective rather than widespread. Across measures, statistical differences were seen in contrasts involving the hyperscanning condition: during real-time reciprocal interaction. Given that ecological embedding, participant cohort, acquisition system and interactional features were partially bundled across tiers, the findings should be interpreted as exploratory evidence for temporally structured modulation rather than causal isolation of interactional context. Nevertheless, the results are consistent with the possibility that engagement and/or reciprocity-related processes may contribute to the temporal organization of sensorimotor neurodynamics. Finally, the study illustrates how SEDs and time-resolved analyses can help bridge traditional laboratory paradigms and increasingly ecological approaches to human neuroscience.