Evidence map›Paper›PMID 40944492›Full record

ArticleAnnals of neurology2026

Behavior Decoding Delineates Seizure Microfeatures and Associated Sudden Death Risks in Mouse Models of Epilepsy.

Yuyan Shen, Jaden Thomas, Xianhui Chen, Jaden Zelidon, Mariam Najeeb, Abigayle Hahn, Ping Zhang, Aaron Sathyanesan, Bin Gu

Abstract read
In one paragraph

Article in Annals of neurology, 2026. 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

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

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5 · Who and what money

Authors and funding

9 authors.

Yuyan ShenDepartment of Neuroscience, The Ohio State University, Columbus, OH.
Jaden ThomasData Analytics Program, The Ohio State University, Columbus, OH.
Xianhui ChenDepartment of Computer Science and Engineering, The Ohio State University, Columbus, OH.
Jaden ZelidonNeuroscience Program, The Ohio State University, Columbus, OH.
Mariam NajeebNeuroscience Program, The Ohio State University, Columbus, OH.
Abigayle HahnPre-medicine Program, College of Arts and Sciences, University of Dayton, Dayton, OH.
Ping ZhangDepartment of Computer Science and Engineering, The Ohio State University, Columbus, OH.
Aaron SathyanesanDepartment of Biology, College of Arts and Sciences, University of Dayton, Dayton, OH.ORCID 0000-0002-9226-7831
Bin GuDepartment of Neuroscience, The Ohio State University, Columbus, OH.ORCID 0000-0002-6846-5563

Funding

Closed-loop rescue of sudden unexpected death in epilepsy by regulating dorsal raphe functionsR01NS140338 · NINDS · OHIO STATE UNIVERSITY · PI Bin Gu · 2025 to 2026
$770k
Congressionally Directed Medical Research Programs (BG) W81XWH2210212National Institute of Neurological Disorders and Stroke (BG) 1R01NS140338-01A1National Science Foundation (PZ) 2145625NINDS NIH HHS R01 NS140338OSU Chronic Brain Injury Discovery Theme (BG and PZ) PilotOSU The Translational Data Analytics Institute (BG and PZ) Pilot
6 · The paper itself

Abstract

objectiveBehavior and motor manifestations are distinctive yet often overlooked features of epileptic seizures. Seizures can result in transient disruptions in motor control, often organized into specific behavioral sequences that can inform seizure types, onset zones, and outcomes. However, refined analysis of behaviors in epilepsy remains challenging. Current manual video inspection approaches are subjective, time-consuming, and often overlook the intricate behavioral dynamics and action kinematics. This study investigates whether artificial intelligence (AI)-aided tools can unravel complex behavior repertoire that can delineate seizure outcomes in a data-driven manner.

methodsWe utilized two AI-aided tools, DeepLabCut (DLC) and Behavioral Segmentation of Open Field in DLC (B-SOiD), to decode underexplored behavior and action domains of induced seizures in a population of 32 inbred mouse strains that mimic human genetic diversity and a mouse model of Angelman syndrome.

resultsOur automated behavior classification tool identified 63 interpretable behavior groups. Analysis of these behavior groups demonstrates significant differential behavior usage and complexity that can delineate distinct seizure states, unravel intrinsic seizure progression over time, and inform mouse sex, strain backgrounds, and specific pathogenic mutations. We also identified seizure behavior transition dynamics and action/subaction kinematics, like hindlimb motions, that can determine the risks of sudden unexpected death in epilepsy (SUDEP).

interpretationThese behavior microfeatures can facilitate preclinical mechanistic studies and antiseizure medication screening at scales. These findings also underscore the translational potential of video-based seizure behavior decoding in both inpatient and outpatient settings, including analyzing videos captured by home surveillance devices and ubiquitous smartphones. ANN NEUROL 2026;99:231-247.

Indexed as

Artificial IntelligenceBehavior, AnimalDeath, SuddenEpilepsySeizuresSudden Unexpected Death in EpilepsyAnimalsDisease Models, AnimalFemaleMaleMiceVideo Recording

Identifiers

PMID40944492
PMCPMC12812430

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LicenceCC BY-NC
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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.