Evidence map›Paper›PMID 40387232›Full record

ArticleEpilepsia2025

Mesial-to-lateral gradients of epileptiform activity to localize mesial temporal lobe epilepsy.

Carlos A Aguila, Alfredo Lucas, Sarah Lavelle, Akash R Pattnaik, Juri Kim, William K S Ojemann, Devin Ma, Mariam Josyula, Nina Petillo, Joshua J LaRocque and 7 more

Abstract readMulticenter Study
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
  2. An Implantable Device that Converses with Patients and Learns to Co-Manage Epilepsy.medRxiv : the preprint server for health sciences · 2026
    Article
  3. 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

17 authors.

Carlos A AguilaDepartment of Bioengineering, School of Engineering and Applied Sciences, University of Pennsylvania, Philadelphia, Pennsylvania, USA.ORCID https://orcid.org/0009-0003-9460-3549
Alfredo LucasDepartment of Bioengineering, School of Engineering and Applied Sciences, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
Sarah LavelleCenter for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
Akash R PattnaikDepartment of Bioengineering, School of Engineering and Applied Sciences, University of Pennsylvania, Philadelphia, Pennsylvania, USA.ORCID https://orcid.org/0000-0002-2474-1685
Juri KimDepartment of Bioengineering, School of Engineering and Applied Sciences, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
William K S OjemannDepartment of Bioengineering, School of Engineering and Applied Sciences, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
Devin MaDepartment of Bioengineering, School of Engineering and Applied Sciences, University of Pennsylvania, Philadelphia, Pennsylvania, USA.ORCID https://orcid.org/0009-0002-0426-7960
Mariam JosyulaCenter for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
Nina PetilloCenter for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
Joshua J LaRocqueCenter for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
Saurabh R SinhaCenter for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
Colin A EllisCenter for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
Alexandra ParashosDepartment of Neurology, Medical University of South Carolina, Charleston, South Carolina, USA.
Ezequiel GleichgerrchtDepartment of Neurology, Medical University of South Carolina, Charleston, South Carolina, USA.ORCID https://orcid.org/0000-0002-4212-4146
Kathryn A DavisCenter for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
Brian LittDepartment of Bioengineering, School of Engineering and Applied Sciences, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
Erin C ConradDepartment of Bioengineering, School of Engineering and Applied Sciences, University of Pennsylvania, Philadelphia, Pennsylvania, USA.

Funding

Implementing a Maternal health and PRegnancy Outcomes Vision for Everyone (IMPROVE)UL1TR002378 · NCATS · EMORY UNIVERSITY · PI Andres J Garcia, Elizabeth O. Ofili · 2017 to 2026
$92.1M
Institutional Career Development CoreKL2TR002381 · NCATS · EMORY UNIVERSITY · PI HENRY M BLUMBERG, Anandi Nayan Sheth · 2017 to 2026
$14.1M
Ghost in the Machine: Melding Brain, Computer and BehaviorDP1NS122038 · NINDS · UNIVERSITY OF PENNSYLVANIA · PI LITT, BRIAN · 2020 to 2024
$5.7M
Training Program in Neuroengineering and MedicineT32NS091006 · NINDS · UNIVERSITY OF PENNSYLVANIA · PI Brian Litt · 2015 to 2026
$4.1M
Biomarkers to Predict Outcome from Responsive Brain Stimulation for EpilepsyR61NS125568 · NINDS · UNIVERSITY OF PENNSYLVANIA · PI DAVIS, KATHRYN ADAMIAK · 2023 to 2025
$3.6M
Optimized Intracranial EEG Targeting in Focal Epilepsy based upon Neuroimaging ConnectomicsR01NS116504 · NINDS · UNIVERSITY OF PENNSYLVANIA · PI DAVIS, KATHRYN ADAMIAK · 2021 to 2025
$3.3M
Guiding epilepsy surgery using network models and Stereo EEGR01NS125137 · NINDS · UNIVERSITY OF PENNSYLVANIA · PI BASSETT, DANIELLE SMITH, LITT, BRIAN · 2022 to 2025
$2.8M
Quantitative interictal networks to localize seizure generatorsK23NS121401 · NINDS · UNIVERSITY OF PENNSYLVANIA · PI Erin Conrad · 2022 to 2026
$1.2M
Polygenic risk in familial epilepsyK23NS121520 · NINDS · UNIVERSITY OF PENNSYLVANIA · PI ELLIS, COLIN · 2021 to 2025
$1.1M
Burroughs Wellcome FundGeorgia Clinical and Translational Science Alliance KL2TR002381Georgia Clinical and Translational Science Alliance UL1TR002378Jonathan and Bonnie RothbergMirowski Family FoundationNational Science Foundation DGE-1845298National Science Foundation DGE-2236662NCATS NIH HHS KL2 TR002381NCATS NIH HHS UL1 TR002378Neil and Barbara SmitNIH HHS K23NS121520NIH HHS R01NS125137NINDS NIH HHS 5T32NS091006-08NINDS NIH HHS DP1 NS122038NINDS NIH HHS DP1NS122038NINDS NIH HHS K23 NS121401NINDS NIH HHS K23 NS121520NINDS NIH HHS NINDS K23 NS121401-01A1NINDS NIH HHS R01 NS116504NINDS NIH HHS R01 NS125137NINDS NIH HHS R61 NS125568NINDS NIH HHS T32 NS091006
6 · The paper itself

Abstract

objectiveMesial temporal lobe epilepsy is a common localization of drug-resistant epilepsy in adults. Patients often undergo intracranial electroencephalographic monitoring to confirm localization and determine candidacy for focal ablation or resection. Clinicians primarily base surgical decision-making on seizure onset patterns, with imaging abnormalities and information from interictal epileptiform discharge (spikes) used as ancillary data. How the morphology and timing of spikes within multielectrode sequences may inform surgical planning is unknown, in part due to the lack of measurement methods for large datasets. We hypothesized that patients with mesial temporal lobe epilepsy have a distinct mesial-to-lateral spike gradient that differentiates them from other epilepsy localizations.

methodsIn a multicenter study at the University of Pennsylvania and the Medical University of South Carolina, we analyzed the timing and morphology of spikes and seizure high-frequency energy ratio in 75 patients with drug-resistant epilepsy. We compared these features across patients with mesial temporal lobe epilepsy, temporal neocortical epilepsy, and other localizations.

resultsA logistic regression model combining all features predicted a clinical localization of mesial temporal lobe epilepsy in unseen patients with an area under the receiver operating characteristic curve of .82 (compared to an area under the receiver operating characteristic curve of .70 for seizure-only features, DeLong test p = .08) and an average precision of .84. Spike rate was the most important feature in the combined model. SIGNIFICANCE: These findings advance surgical planning by demonstrating that quantitative spike analysis can effectively supplement seizure data in localizing mesial temporal lobe epilepsy. This approach could reduce reliance on prolonged seizure monitoring, potentially decreasing patient risk and hospitalization costs while improving surgical targeting. Our results support incorporating automated spike analysis into standard clinical workflows for epilepsy surgery evaluation.

Indexed as

Drug Resistant EpilepsyEpilepsy, Temporal LobeAdolescentAdultElectrocorticographyElectroencephalographyFemaleHumansMaleMiddle AgedYoung Adultfeature extractioninterictalmesial temporal lobe epilepsyseizure onset zone localizationstereo‐encephalography

Identifiers

PMID40387232
PMCPMC12212069

What Socratic holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

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.