Evidence map›Paper›PMID 40202808›Full record

ArticleEpilepsia2025

EEG signal dimension is an index of seizure propensity and antiseizure medication effects in a mouse model of acquired epilepsy.

Massimo Rizzi, Peter J West, Annamaria Vezzani, Karen S Wilcox, Alessandro Giuliani

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 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

5 authors.

Massimo RizziDepartment of Acute Brain and Cardiovascular Injury, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Milan, Italy.ORCID https://orcid.org/0000-0002-5477-2263
Peter J WestAnticonvulsant Drug Development Program, Department of Pharmacology & Toxicology, University of Utah, Salt Lake City, Utah, USA.ORCID https://orcid.org/0000-0002-5774-5180
Annamaria VezzaniDepartment of Acute Brain and Cardiovascular Injury, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Milan, Italy.ORCID https://orcid.org/0000-0003-0573-6175
Karen S WilcoxAnticonvulsant Drug Development Program, Department of Pharmacology & Toxicology, University of Utah, Salt Lake City, Utah, USA.ORCID https://orcid.org/0000-0003-2660-8826
Alessandro GiulianiEnvironment and Health Department, Istituto Superiore di Sanitá, Rome, Italy.ORCID https://orcid.org/0000-0002-4640-804X

Funding

SCREENING OF INVESTIGATIONAL THERAPEUTICS TO TREAT, MODIFY OR PREVENT EPILEPSY FOR THE NINDS EPILEPSY THERAPY SCREENING PROGRAM (ETSP)75N95022C00007 · NIDA · UTAH STATE HIGHER EDUCATION SYSTEM--UNIVERSITY OF UTAH · PI WILCOX, KAREN · 2022 to 2025
$20.9M
NIDA NIH HHS 75N95022C00007NINDS NIH HHS HHS 75N95022C00007
6 · The paper itself

Abstract

objectiveVariability in the frequency, timing, and pattern of seizures may influence the assessment of the effect of antiseizure medications (ASMs) when measuring seizure frequency, especially in patients with infrequent seizures. A low seizure rate is an exclusion criterion for enrollment of patients with epilepsy in clinical trials and requires prolonged periods of seizure monitoring, thus delaying appropriate treatment interventions. We investigated whether an electroencephalogram (EEG)-based complexity measure of seizure susceptibility of epileptic mice provides a reliable alternative to seizure frequency for evaluating the efficacy of ASMs.

methodsWe used a mouse model of acquired epilepsy characterized by variability in seizure frequency over time and among mice, as observed in humans. We analyzed EEG recordings from chronic epileptic mice (n = 106) at baseline and during treatment with phenobarbital, valproate, carbamazepine, or phenytoin. We used recurrence quantification analysis to detect increased autocorrelation and critical slowing-down, two signatures of criticality that together contribute to estimate the dimension of phase-space of the EEG signals. The measurements of dimension and seizure frequency were compared as proxies for seizure susceptibility by correlation tests and evaluation of ASM efficacy.

resultsDimension provided a statistically robust (inverse) estimate of seizure susceptibility of mice, including mice with low seizure frequency or no seizures during the observation periods. In contrast, seizure frequency provided a reliable measure only in mice with a high seizure rate. Consistently, evaluation of ASM efficacy using dimension variations accurately reproduced seizure responsiveness patterns in this mouse model. SIGNIFICANCE: EEG-based dimension provides a reliable measure of mouse propensity to experience seizures as well as ASM efficacy, regardless of seizure rates. Measuring dimension variation should facilitate the inclusion of subjects with low seizure rate in preclinical and clinical trials while also shortening the periods of monitoring. This could accelerate both the development of new treatments and therapeutic decisions in the medical field.

Indexed as

AnticonvulsantsElectroencephalographyEpilepsySeizuresAnimalsDisease Models, AnimalMaleMiceMice, Inbred C57BLValproic AcidAnticonvulsantsValproic Acid(auto)correlationcomplex systemscritical slowing‐downdimensionearly warning signalsnonlinear analysisrecurrence quantification analysis (RQA)seizure susceptibility

Identifiers

PMID40202808
PMCPMC12353893

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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.