ArticleNeurology2025
Quantitative EEG Biomarkers in the Genetic Epilepsies and Associations With Neurologic Outcomes.
Article in Neurology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Translatable electrophysiological and behavioral abnormalities in a humanized model of SYNGAP1-disorder.Molecular psychiatry · 2026Article
- A prospective natural history study protocol for clinical trial readiness in synaptic disorders.Epilepsia · 2026Article
- The use of quantitative electroencephalography in evaluating epilepsy treatment.Acta epileptologica · 2026Review
- Excess EEG beta-band oscillations in Dup15q syndrome correlate with clinical severity.Translational psychiatry · 2026Article
- The Synaptic Clock: SynGAP1 as a Molecular Timer of Postsynaptic Density Consolidation.Biomolecules · 2026Review
- Article
- STXBP1 Syndrome: Biotechnological Advances, Challenges, and Perspectives in Gene Therapy, Experimental Models, and Translational Research.Biotech (Basel (Switzerland)) · 2025Review
- Dimensionality reduction of quantitative EEG and clinical profiles uncover associations with monogenic neurodevelopmental phenotypes in SNAREopathies.Frontiers in neuroscience · 2025Article
- Research progress inFrontiers in neurologyReview
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12 authors.
Funding
Abstract
BACKGROUND AND
objectivesEEG plays an integral part in the diagnosis and management of children with genetic epilepsies. Nevertheless, how quantitative EEG features differ between genetic epilepsies and neurologic outcomes remains largely unknown. In this study, we aimed to identify quantitative EEG biomarkers in
methodsWe retrospectively collected clinical scalp EEGs from the Children's Hospital of Philadelphia. After removing artifacts and epochs with excess noise or altered state from EEGs, we extracted spectral features. We validated our preprocessing pipeline by comparing automatically detected posterior dominant rhythm (PDR) with annotations from clinical EEG reports. Next, as a coarse measure of pathologic slowing, we compared the alpha-delta bandpower ratio between controls and patients with different genetic epilepsies. We then trained random forest models with localized spectral features to predict diagnoses of
resultsWe evaluated EEGs from individuals with pathogenic variants in DISCUSSION: These results suggest that some genetic epilepsies and functional outcome measures have distinct quantitative EEG signatures. Furthermore, EEG spectral features are predictive of some functional outcome measures. Large-scale retrospective quantitative analysis of clinical EEGs has the potential to discover novel biomarkers and to quantify and track individuals' disease progression across development.
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