A growth chart of brain function from infancy to adolescence based on EEG

Background In children, objective, quantitative tools that determine functional neurodevelopment are scarce and rarely scalable for clinical use. Direct recordings of cortical activity using routinely acquired electroencephalography (EEG) offer reliable measures of brain function. Methods We developed and validated a measure of functional brain age (FBA) using a residual neural network -based interpretation of the paediatric EEG. In this cross-sectional study, we included 1056 children with typical development ranging in age from 1 month to 18 years. We analysed a 10- to 15 -min segment of 18 -channel EEG recorded during light sleep (N1 and N2 states). Findings The FBA had a weighted mean absolute error (wMAE) of 0.85 years (95% CI: 0.69-1.02; n =1056). A twochannel version of the FBA had a wMAE of 1.51 years (95% CI: 1.30-1.73; n = 1056) and was validated on an independent set of EEG recordings (wMAE = 2.27 years, 95% CI: 1.90-2.65; n = 723). Group -level maturational delays were also detected in a small cohort of children with Trisomy 21 (Cohen's d = 0.36, p = 0.028). Interpretation A FBA, based on EEG, is an accurate, practical and scalable automated tool to track brain function maturation throughout childhood with accuracy comparable to widely used physical growth charts.