Age-Related Changes in EEG Signal Complexity and Behavioral Variability from Childhood to Adulthood: A Multiscale Entropy Approach.

The complexity of physiological signals provides insight into the maturation and functional organization of the developing brain. This study investigated age-related changes in electroencephalographic (EEG) signal complexity and their association with behavioral variability in 240 participants aged 6 to 29 years. EEG signals were recorded during the resting state, and Multiscale Entropy (MSE) was computed across 34 temporal scales, grouped into fine, medium, and coarse scales. Behavioral variability was assessed using measures from Oddball and Delayed Match-to-Sample tasks. Quadratic regression analyses characterized age-related changes in MSE across scalp regions, and Pearson correlations evaluated associations between age-adjusted residuals of MSE and behavioral variability. The results showed that MSE changed with age across temporal scales in all cortical regions. Developmentally, MSE showed a significant age-related increase at fine scales across the entire scalp, region-specific decreases at medium scales, and a generalized decrease at coarse scales. Behavioral variability decreased with age across both tasks. Notably, fine-scale age residual MSE in central and posterior regions was negatively correlated with the coefficient of variation in the Oddball task, indicating that higher neural complexity supports more stable performance. These findings suggest scale- and region-specific age-related changes in neural complexity and suggest that fine-scale MSE captures aspects of brain maturation related to behavioral stability beyond traditional variability measures.