ArticleEBioMedicine2024
A growth chart of brain function from infancy to adolescence based on EEG.
Article in EBioMedicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- A dataset of EEG and ECG recordings around the onset of NREM sleep from infancy to adolescence.Scientific data · 2026Article
- Myelination-attention-empowered deep learning model improved brain age prediction in children below 2 years of age.Pediatric radiology · 2026Article
- Capturing individual variation in children's electroencephalograms during nREM sleep.PLoS computational biology · 2026Article
- Decoding brain age predictions from sleep electroencephalography across infancy to adolescence.Scientific reports · 2025Article
- Exploring neurodevelopment through oscillatory and aperiodic EEG activity: methodological and clinical consideration.Frontiers in human neuroscience · 2025Review
- EEG-based brain age prediction in infants-toddlers: Implications for early detection of neurodevelopmental disorders.Developmental cognitive neuroscience · 2025Article
- An adaptive transformer-based framework for advanced brain activity mapping and intelligent neurotherapeutic decision support.Frontiers in human neuroscience · 2025Article
- Prediction of chronological age from resting-state EEG power in the first three years of life.medRxiv : the preprint server for health sciences · 2024Article
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Authors and funding
10 authors.
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Abstract
backgroundIn 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.
methodsWe 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).
findingsThe FBA had a weighted mean absolute error (wMAE) of 0.85 years (95% CI: 0.69-1.02; n = 1056). A two-channel 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).
interpretationA 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.
fundingThis research was supported by the National Health and Medical Research Council, Australia, Helsinki University Diagnostic Center Research Funds, Finnish Academy, Finnish Paediatric Foundation, and Sigrid Juselius Foundation.
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