ArticleBrain : a journal of neurology2018
A fingerprint of the epileptogenic zone in human epilepsies.
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.
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Who cites it
86 citing papers in PubMed, 2 syntheses or guidelines pooled it, 215 citations in OpenAlex.
- Pooled it
- Decoding Intracranial EEG With Machine Learning: A Systematic Review.Frontiers in human neuroscience · 2022Pooled it
- How to Recognize and Manage Missing Key Electrodes in Defining the Epileptogenic Zone.Epilepsy currents · 2026Article
- Magnetoencephalography (MEG) Augments Semiology in Stereotactic Electroencephalography (SEEG) Evaluations.Brain sciences · 2026Article
- The seizure embedding map: a spatio-temporal transformer for comparing patients by ictal intracranial EEG features at scale.Journal of neural engineering · 2026Article
- Thalamo-cortical synchrony shapes seizure expression in human temporal lobe epilepsy.Nature communications · 2026Article
- Invasive neurophysiology and whole brain connectomics for neural decoding in patients with brain implants.Nature biomedical engineering · 2026Article
- Three-Phase Seizure Segmentation in Stereotactic EEG Using Envelope-Based Multivariate Changepoint Analysis.Annals of biomedical engineering · 2026Article
- Spike-fast activity interplay: A gateway to seizure.Epilepsia · 2026Article
- Harmonic patterns embedded in ictal EEG signals in focal epilepsy: new insight into the epileptogenic zone.BMC medicine · 2026Article
- Integrating data across oscillatory power bands predicts the seizure onset zone in focal epilepsies.Brain communications · 2026Article
- Static and dynamic intracerebral signal analysis reveals protective networks against seizures in drug-resistant focal epilepsy.Brain communications · 2026Article
- The Seizure Embedding Map: A Spatio-Temporal Transformer for Comparing Patients by Ictal Intracranial EEG Features at Scale.medRxiv : the preprint server for health sciences · 2025Article
- Mesial-to-lateral gradients of epileptiform activity to localize mesial temporal lobe epilepsy.Epilepsia · 2025Article
- Time-Frequency Fingerprint Analysis in SEEG Source-Space to Identify the Epileptogenic Zone.Annals of clinical and translational neurology · 2025Article
- Visual Features in Stereo-Electroencephalography to Predict Surgical Outcome: A Multicenter Study.Annals of neurology · 2025Article
- Virtual brain twins for stimulation in epilepsy.Nature computational science · 2025Article
- Learning From PU Data Using Disentangled Representations.Proceedings. International Conference on Image Processing · 2025Article
- Morphometrics of the preserved post-surgical hemisphere in pediatric drug-resistant epilepsy and implications for post-operative cognition.bioRxiv : the preprint server for biology · 2025Article
- Multimodal quantitative analysis guides precise preoperative localization of epilepsy.Journal of neurology · 2025Review
26 more citing papers are in PubMed but not listed here.
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10 authors at 2 institutions in 1 country.
Funding
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.
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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.