Revisiting deterministic motor sequence learning: EEG correlates and methodological challenges

Motor sequence learning refers to the transformation of discrete movements into integrated and automatized action patterns, underlying skill acquisition. Electroencephalography (EEG), with its high temporal resolution, enables the investigation of the neural dynamics underlying this process. However, despite a growing number of studies, findings remain fragmented and a framework of EEG correlates of deterministic motor sequence learning is still lacking. In this review, we critically examined twenty-three studies to characterize the EEG correlates associated with deterministic motor sequence learning. We aimed to disentangle sequence-specific neural changes from general practice effects, independently of participants' awareness of embedded regularities. We discuss key methodological aspects, including experimental design, control conditions, and awareness assessment. Despite substantial methodological heterogeneity and weaknesses in experimental control, electrophysiological findings converge on the view that learning reflects a shift toward more efficient processing. Learning-related changes include modulation of midline frontal negativities linked to performance monitoring, reductions in midline theta activity indicative of decreased top-down control demands, alpha-band alterations that may support improved stimulus prediction and motor preparation and beta activity, showing mixed general and sequence effects, supports response-related motor and cognitive plan shifts. Evidence on connectivity is more limited but points to reduced functional coupling during learning, while resting-state theta power and motor beta connectivity appear to predict training-related gains. By synthesizing current evidence, this review provides a critical appraisal of the field and recommendations for future research. contributing to a more consistent and interpretable framework for studying the neurophysiological basis of motor sequence learning.