Evidence map›Paper›PMID 39918165›Full record

ArticleEpilepsia2025

Neural mass modeling reveals that hyperexcitability underpins slow-wave sleep changes in children with epilepsy.

Dominic M Dunstan, Samantha Y S Chan, Marc Goodfellow

Abstract read
In one paragraph

Article in Epilepsia, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Dominic M DunstanDepartment of Mathematics and Statistics, University of Exeter, Exeter, UK.ORCID https://orcid.org/0000-0003-1973-1404
Samantha Y S ChanSt George's Hospital, London, UK.ORCID https://orcid.org/0000-0003-0488-1207
Marc GoodfellowDepartment of Mathematics and Statistics, University of Exeter, Exeter, UK.ORCID https://orcid.org/0000-0002-7282-7280

Funding

Engineering and Physical Sciences Research Council 2407565St George's University Hospitals NHS Foundation Trust
6 · The paper itself

Abstract

objectiveThe relationship between sleep and epilepsy is important but imperfectly understood. We sought to understand the mechanisms that explain the differences in sleep homeostasis observed in children with epilepsy.

methodsWe used a neural mass model to replicate sleep electroencephalography (EEG) recorded from 15 children with focal lesional epilepsies and 16 healthy age-matched controls. Different parameter sets were recovered in the model for each subject.

resultsThe model revealed that sleep EEG differences are driven by enhanced firing rates in the neuronal populations of patients, which arise predominantly due to enhanced excitatory synaptic currents. These differences were more marked in patients who had seizures within 72 h after the sleep recording. Furthermore, model parameters inferred from patients resided closer to model parameters inferred from a typical seizure rhythm. SIGNIFICANCE: These results demonstrate that brain mechanisms relating to epilepsy manifest in the interictal EEG in slow-wave sleep, and that EEG recorded from patients can be mapped to synaptic deficits that may explain their predisposition to seizures. Neural mass models inferred from sleep EEG data have the potential to generate new biomarkers to predict seizure occurrence and inform treatment decisions.

Indexed as

EpilepsyModels, NeurologicalSleep, Slow-WaveAdolescentChildChild, PreschoolElectroencephalographyFemaleHumansMalechildrenEEGepilepsyneural mass modelsleep

Identifiers

PMID39918165
PMCPMC12097470

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.