LENS: Lifespan and Sleep-Stage-Resolved Normative EEG Background Slowing - Data and Code
Le résumé fourni par la source
**Objective.** Existing references for what constitutes pathological EEG background slowing are based on small samples and primarily awake recordings. To address this gap, we built LENS --- lifespan-and-sleep-stage-resolved EEG growth charts. **Methods.** 25,536 clinical EEGs (21,757 patients; infancy to >90 y) were analyzed to extract measurements of spectral power and their ratios, and used to construct sleep-stage × age growth curves (GAMLSS) scored every 15-s segment as a deviation z from its matched normal. LENS was trained on labels extracted from clinical EEG reports to identify and localize pathological focal or generalized slowing (or both), and to provide validated verbal descriptions. LENS was externally validated on two held-out 100-EEG test sets: ON-100 (18 experts) and SAI-100 (14 experts). **Results.** EEG growth curves captured development and sleep physiology. Against the panel majority LENS reached AUROC 0.946 (generalized) and 0.921 (focal), with most experts under each curve (78%, 71%), beating a foundation- model on both axes and the strongest published slowing index by 0.10--0.13 AUROC; on the external site it matched experts and beat SCORE-AI, a published reader (focal 0.93). Slowing is the least reliable expert judgement (κ 0.37-- 0.45); generated reports tracked statements in EEG reports. Clinical readers under-reported pathological slowing in sleep. **Conclusions.** One normative field detects slowing at or beyond expert and foundation-model level, yielding validated, automated stage-and-age aware EEG reports. **Significance.** LENS is the first lifespan- and sleep-stage-resolved deviation-from-normal instrument for EEG, enabling reproducible automated reporting. _Keywords:_ EEG; quantitative EEG; slowing; normative modelling; sleep; automated reporting
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