EEG signatures of motor development in early childhood: a systematic review

Abstract Background Early identification of motor developmental disorders is limited due to lack of objective neural markers that characterize typical neurodevelopmental patterns. This systematic review interprets and synthesizes existing evidence to propose a framework of EEG signatures associated with motor development in children aged 0-5 years, which may help inform future benchmarks for early assessment and intervention. Methods Following PRISMA guidelines, we searched published and gray literature across five databases between 2000 and 2025 (registered protocol). Included studies examined EEG during task-based, resting-state, or sleep studies linked to motor milestones, task performance, or standardized motor assessments. Study quality was assessed using the NIH tool. Results From 35 studies including 1107 neurotypical children, we identified four study types: action observation, action execution, combined observation/execution, and resting/sleep EEG. Mu rhythm desynchronization (6–13 Hz) emerged as the most common marker of motor maturation, with mu peak increasing from 6–9 Hz in infants to 8.5–10 Hz in preschoolers. Motor experience strengthened neural responses, sleep features (slow-wave activity and spindles) predicted future motor outcomes, and beta oscillations supported action prediction and coordination. Conclusion EEG shows promise as a non-invasive tool for tracking early motor development. However, methodological heterogeneity underscores the need for standardized research before EEG can reliably identify atypical development or monitor intervention response. Impact This review synthesizes EEG signatures in children 0–5 years and shows that mu rhythm desynchronization (6–13 Hz) is the most common correlate of early motor development. First review to combine task-based EEG (watching and doing actions) with resting and sleep EEG in this age group. This review identifies EEG features, including alpha and beta rhythms, slow-wave activity, spindles, and connectivity patterns linked to motor skills, suggesting their potential as early objective correlates of typical motor development.