Evidence map›Paper›PMID 29253102›Full record

ArticleBrain : a journal of neurology2018

A fingerprint of the epileptogenic zone in human epilepsies.

Olesya Grinenko, Jian Li, John C Mosher, Irene Z Wang, Juan C Bulacio, Jorge Gonzalez-Martinez, Dileep Nair, Imad Najm, Richard M Leahy, Patrick Chauvel

Open access · hybridAbstract readVideo-Audio Media
In one paragraph

Article in Brain : a journal of neurology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 86 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
86citing papers in PubMed, 2 pooled it
7.2field-weighted citation impact, top 2% of its field
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

86 citing papers in PubMed, 2 syntheses or guidelines pooled it, 215 citations in OpenAlex.

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  17. Virtual brain twins for stimulation in epilepsy.Nature computational science · 2025
    Article
  18. Learning From PU Data Using Disentangled Representations.Proceedings. International Conference on Image Processing · 2025
    Article
  19. Article
  20. Review

26 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

10 authors at 2 institutions in 1 country.

Olesya GrinenkoEpilepsy Center, Cleveland Clinic Neurological Institute, Cleveland OH, USA.
Jian LiSignal and Image Processing Institute, University of Southern California, Los Angeles CA, USA.
John C MosherEpilepsy Center, Cleveland Clinic Neurological Institute, Cleveland OH, USA.
Irene Z WangEpilepsy Center, Cleveland Clinic Neurological Institute, Cleveland OH, USA.
Juan C BulacioEpilepsy Center, Cleveland Clinic Neurological Institute, Cleveland OH, USA.
Jorge Gonzalez-MartinezEpilepsy Center, Cleveland Clinic Neurological Institute, Cleveland OH, USA.
Dileep NairEpilepsy Center, Cleveland Clinic Neurological Institute, Cleveland OH, USA.
Imad NajmEpilepsy Center, Cleveland Clinic Neurological Institute, Cleveland OH, USA.
Richard M LeahySignal and Image Processing Institute, University of Southern California, Los Angeles CA, USA.
Patrick ChauvelEpilepsy Center, Cleveland Clinic Neurological Institute, Cleveland OH, USA.
Cleveland Clinic · USUniversity of Southern California · US

Funding

Tools for Large-Scale Platform-Independent MEG Data AnalysisR01EB009048 · NIBIB · MASSACHUSETTS GENERAL HOSPITAL · PI HAMALAINEN, MATTI, LEAHY, RICHARD M · 2009 to 2016
$4.6M
A Brain Atlas for Mapping Connectivity in Focal EpilepsyR01NS089212 · NINDS · CLEVELAND CLINIC LERNER COM-CWRU · PI LEAHY, RICHARD M, MOSHER, JOHN COMPTON · 2015 to 2019
$2.7M
NIBIB NIH HHS R01 EB009048NINDS NIH HHS R01 NS089212
6 · The paper itself

Abstract

Defining a bio-electrical marker for the brain area responsible for initiating a seizure remains an unsolved problem. Fast gamma activity has been identified as the most specific marker for seizure onset, but conflicting results have been reported. In this study, we describe an alternative marker, based on an objective description of interictal to ictal transition, with the aim of identifying a time-frequency pattern or 'fingerprint' that can differentiate the epileptogenic zone from areas of propagation. Seventeen patients who underwent stereoelectroencephalography were included in the study. Each had seizure onset characterized by sustained gamma activity and were seizure-free after tailored resection or laser ablation. We postulated that the epileptogenic zone was always located inside the resection region based on seizure freedom following surgery. To characterize the ictal frequency pattern, we applied the Morlet wavelet transform to data from each pair of adjacent intracerebral electrode contacts. Based on a visual assessment of the time-frequency plots, we hypothesized that a specific time-frequency pattern in the epileptogenic zone should include a combination of (i) sharp transients or spikes; preceding (ii) multiband fast activity concurrent; with (iii) suppression of lower frequencies. To test this hypothesis, we developed software that automatically extracted each of these features from the time-frequency data. We then used a support vector machine to classify each contact-pair as being within epileptogenic zone or not, based on these features. Our machine learning system identified this pattern in 15 of 17 patients. The total number of identified contacts across all patients was 64, with 58 localized inside the resected area. Subsequent quantitative analysis showed strong correlation between maximum frequency of fast activity and suppression inside the resection but not outside. We did not observe significant discrimination power using only the maximum frequency or the timing of fast activity to differentiate contacts either between resected and non-resected regions or between contacts identified as epileptogenic versus non-epileptogenic. Instead of identifying a single frequency or a single timing trait, we observed the more complex pattern described above that distinguishes the epileptogenic zone. This pattern encompasses interictal to ictal transition and may extend until seizure end. Its time-frequency characteristics can be explained in light of recent models emphasizing the role of fast inhibitory interneurons acting on pyramidal cells as a prominent mechanism in seizure triggering. The pattern clearly differentiates the epileptogenic zone from areas of propagation and, as such, represents an epileptogenic zone 'fingerprint'.awx306media15687076823001.

Indexed as

Brain MappingAdolescentAdultAgedBrain WavesChild, PreschoolElectroencephalographyEpilepsyFemaleHumansMaleMiddle AgedTime FactorsYoung Adultepilepsy surgeryepileptogenic zonehigh-frequency oscillationsimaging methodologystereo-EEG

Identifiers

PMID29253102
PMCPMC5837527
OpenAlexW2774781962

What OpenQuestion 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 OpenQuestion graph.