Lifespan EEG Reference Charts Reveal Aperiodic Confounds in Beta-Band Biomarkers Across Neurological and Neuropsychiatric Disorders

Beta oscillations are among the most prominent scalp EEG rhythms and are implicated in motor control, cognition, and multiple neurological disorders, but the lack of large-scale normative data and persistent methodological inconsistency have blocked development of the reliable reference frameworks needed for clinical translation. The authors attribute this to two unresolved problems: age-dependent neurophysiological changes that produce inherently non-linear beta trajectories across the lifespan, and the confounding influence of aperiodic 1/f activity in conventional beta analyses, which shifts independently with both maturation and pathology.

To address these, the study establishes the first comprehensive lifespan reference charts for beta oscillations using a sample of N = 22,094 individuals spanning ages 1 to 100 years, applying complementary analytic approaches that isolate periodic oscillations from aperiodic background activity. The authors then quantify disorder-specific deviations in beta power and frequency across seven neurological and neuropsychiatric disorders.

Beta power followed a non-linear, tri-phasic trajectory: it increased through childhood and adolescence, peaked around age 50, and declined in later life. Unadjusted and aperiodic-adjusted beta frequency showed opposing developmental trajectories; the adjusted measure revealed a previously uncharacterized adolescent dip that reached its minimum around ages 12–13, a pattern consistent across all brain lobes and both sexes. Clinically, beta power was reduced across most patient groups, with effect sizes varying by disorder and brain lobe. Schizophrenia spectrum disorders were a notable exception, showing reduced absolute beta power but increased aperiodic-adjusted beta power — a distinction undetectable without aperiodic decomposition.

The authors conclude that aperiodic 1/f activity does not merely scale beta measurements but reverses their apparent developmental trajectory, a systematic bias that — if left unaccounted for — fundamentally misrepresents how beta frequency matures across the lifespan and obscures disorder-specific oscillatory signatures in clinical populations. This makes aperiodic decomposition a prerequisite for developing beta-band biomarkers suitable for clinical use.