Flexible modulation of premotor mu rhythm waveform shape predicts human motor sequence learning

Motor sequence learning recruits a distributed sensorimotor network. Within this network, the premotor cortex (PMC) encodes and represents sequence information while the primary motor cortex (M1) executes movement sequences. Like M1, PMC neuronal populations exhibit mu (8-13 Hz) rhythms, which are typically non-sinusoidal. Previous studies showed that mu rhythm phase gates corticospinal transmission, sensitivity to LTP-like plasticity, and learning-related corticospinal plasticity. However, these studies treated mu peak and trough phases as discrete functional states and focused exclusively on M1. Here, we characterized mu phase-dependent mechanisms of motor sequence learning by measuring waveform shape, which is a more holistic measure that treats peak and trough phases as continuous components of the same oscillatory cycle. Using cycle-by-cycle analysis of resting EEG, we quantified the peak-trough symmetry of mu rhythms recorded over premotor regions during, before, and after healthy adults (25 females, 11 males) practiced a serial reaction time task (SRTT) containing a repeating, embedded sequence (sequence group) or no sequence (no-sequence group). As learning progressed, premotor mu rhythms became more symmetric in the sequence than the no-sequence group; these symmetry increases were also more positively correlated with skill acquisition in the sequence than the no-sequence group. Further, premotor mu asymmetry before task exposure predicted sequence acquisition, such that participants with longer baseline trough phases acquired greater skill and showed larger learning-related increases in mu peak-trough symmetry. Overall, these findings provide first evidence that motor sequence learning re-shapes premotor mu rhythms, consistent with learning-related redistribution of cortical excitability across the mu cycle.Significance statement Motor sequence learning requires coordinated activity between premotor and sensorimotor cortices. Although sensorimotor mu rhythm phase gates LTP-like corticospinal plasticity, the effects of TMS on motor learning, and learning-related plasticity, the role of premotor mu waveform shape in motor sequence learning is unknown. Using cycle-by-cycle analysis, we characterized mu peak-trough symmetry recorded over premotor regions before, during, and after healthy adults learned an implicit motor sequence or completed a control task. We found that premotor mu peak-trough symmetry progressively increased during learning, with baseline asymmetries and learning-related symmetry increases both predicting sequence learning. Our findings suggest that sequence learning redistributes excitability across the mu cycle and identify premotor mu rhythm waveform shape as a novel marker of motor sequence learning.