INTRODUCTION: The complexity of physiological signals provides important insight into the maturation and functional organization of the developing brain.

AIM(S): This study investigated age-related changes in electroencephalographic (EEG) signal complexity and their association with behavioural variability in a sample of 240 participants aged 6 to 29 years.

METHOD(S): Resting-state EEG was recorded, and Multiscale Entropy (MSE) was computed across 34 temporal scales grouped into fine, medium, and coarse ranges. Behavioural variability was assessed using performance measures from Oddball and Delayed Match-to-Sample tasks. Quadratic regression analyses were conducted to characterize age-related changes in MSE across scalp regions, and Pearson correlations examined associations between age-adjusted MSE residuals and behavioural variability.

RESULTS: MSE showed significant age-related changes across temporal scales and cortical regions, with fine-scale MSE increasing across the scalp, region-specific decreases at medium scales, and a generalized decline at coarse scales. Behavioural variability decreased with age in both tasks. Notably, fine-scale MSE residuals in central and posterior regions were negatively correlated with the coefficient of variation in the Oddball task, indicating that higher neural complexity is associated with greater behavioural stability.

CONCLUSIONS: These findings demonstrate scale- and region-specific developmental trajectories of neural complexity and support the relevance of fine-scale MSE as a marker of brain maturation linked to behavioural stability beyond traditional variability measures.

FINANCIAL SUPPORT: This research was funded by Agencia Estatal de Investigación (AEI), grant number PID2022–139151OB-I00 (FEDER funds).