Evidence map›Paper›PMID 41823376›Full record

ArticleEpilepsia2026

Perturbation-induced responses improved seizure forecasting in epileptic rats.

Wei-Chih Chang, Jack Lin, Warwick Cheung, Alan Lai, Mark J Cook, David B Grayden, William C Stacey

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In one paragraph

Article in Epilepsia, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Wei-Chih ChangDepartment of Molecular & Integrative Physiology, University of Michigan, Ann Arbor, Michigan, USA.ORCID https://orcid.org/0000-0003-2339-5757
Jack LinDepartment of Neurology, University of Michigan, Ann Arbor, Michigan, USA.
Warwick CheungDepartment of Medicine, St. Vincent's Hospital Melbourne, University of Melbourne, Melbourne, Victoria, Australia.
Alan LaiDepartment of Medicine, St. Vincent's Hospital Melbourne, University of Melbourne, Melbourne, Victoria, Australia.
Mark J CookDepartment of Medicine, St. Vincent's Hospital Melbourne, University of Melbourne, Melbourne, Victoria, Australia.
David B GraydenDepartment of Medicine, St. Vincent's Hospital Melbourne, University of Melbourne, Melbourne, Victoria, Australia.ORCID https://orcid.org/0000-0002-5497-7234
William C StaceyDepartment of Neurology, University of Michigan, Ann Arbor, Michigan, USA.ORCID https://orcid.org/0000-0002-8359-8057

Funding

Biointerfaces Institute, University of MichiganLucas Family Research Fund (Michigan Medicine)Melbourne International Fee Remission ScholarshipMelbourne International Research ScholarshipNational Health and Medical Research Council 1065638NIH HHS R01-NS094399Robbins Family Research Fund (Michigan Medicine)
6 · The paper itself

Abstract

objectiveThe unpredictability of seizures is one of the most challenging aspects of uncontrolled epilepsy for patients. Prior work forecasting seizure risk has measured changes in passive intracranial electroencephalographic (EEG) signals, but currently, there are no such clinical devices available. Based upon dynamical theory, we hypothesized that the response of the brain to perturbing stimulation provides a robust measurement of seizure risk that outperforms the results from passive EEG.

methodsTo test the hypothesis, we performed more than 8 weeks of periodic electrical stimulation and continuous EEG recordings in epileptic rats induced by intrahippocampal injection of tetanus toxin, in which seizures started spontaneously.

resultsUsing the perturbation-evoked responses as a predictive biomarker of seizure risk, we built a preictal detection system that had excellent accuracy (area under the receiver operating characteristic curve > .95) at distinguishing the preictal from the interictal states. In comparison, a similar preictal detection system that used only passive features from the same experimental animals was unable to identify the preictal state better than chance. SIGNIFICANCE: Our results advocate for perturbation to be used for seizure prediction purposes, which could improve the efficacy of seizure forecasting when applied clinically.

Indexed as

BrainElectroencephalographyEpilepsySeizuresAnimalsDisease Models, AnimalElectric StimulationForecastingHippocampusMaleRatsRats, Sprague-DawleyTetanus ToxinTetanus Toxinbrain stimulationcritical slowing downcritical transitionperturbationseizure forecasting and prediction

Identifiers

PMID41823376
PMCPMC13285227

What Socratic holds

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LicenceCC BY
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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 Socratic graph.