A fingerprint of the epileptogenic zone in human epilepsies
Olesya Grinenko,Jian Li,John C. Mosher,Irene Z. Wang,Juan Bulacio,Jorge Gonzalez-Martinez,Dileep Nair,Imad Najm,Richard M. Leahy,Patrick Chauvel +9 more
TLDR
Using time-frequency analysis during the pre-ictal-to-ictsal transition, Grinenko et al. identify a fingerprint of the epileptogenic zone that is consistent with a pathophysiological role of fast inhibitory interneurons in seizure onset.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.read more
Citations
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Journal ArticleDOI
Changing concepts in presurgical assessment for epilepsy surgery
TL;DR: The importance of looking beyond the EEG seizure onset zone and considering focal epilepsy as a brain network disease in which long-range connections need to be taken into account is highlighted, and how new diagnostic techniques are revealing essential information in the brain that was previously hidden from view is explored.
Journal ArticleDOI
Localization of the Epileptogenic Zone Using High Frequency Oscillations
TL;DR: High-frequency oscillations are suggested to be a promising biomarker of the EZ, with a potential to improve surgical success in patients with drug-resistant epilepsy without the need to record seizures, but in order to establish HFOs as a clinical biomarker, the following issues need to be addressed.
Journal ArticleDOI
Intracranial EEG in the 21st Century
Barbara C. Jobst,Fabrice Bartolomei,Beate Diehl,Birgit Frauscher,Philippe Kahane,Lorella Minotti,Ashwini Sharan,Nastasia Tardy,Gregory A. Worrell,Jean Gotman +9 more
TL;DR: Improved techniques to record and interpret iEEG may in the future lead to a greater proportion of patients being seizure free after epilepsy surgery, and advanced computational methods such as determining the epileptogenicity index and similar measures may enhance standard clinical interpretation.
Journal ArticleDOI
The effect of seizure spread to the amygdala on respiration and onset of ictal central apnea.
William P. Nobis,Karina A. González Otárula,Jessica W. Templer,Elizabeth E. Gerard,Stephen VanHaerents,Gregory Lane,Guangyu Zhou,Joshua M. Rosenow,Christina Zelano,Stephan U. Schuele +9 more
TL;DR: The findings suggest that activation of amygdalar networks is correlated with central apnea during seizures and suggests a further role in dysfunctional breathing states seen during seizures, with implications for SUDEP pathophysiology.
Journal ArticleDOI
Resolving the Micro-Macro Disconnect to Address Core Features of Seizure Networks.
TL;DR: The need for a more complete view of epilepsy is discussed, outlining how key features at the cellular and microcircuit level can significantly impact disease mechanisms that are not captured by the most common methodology to study epilepsy, electroencephalography (EEG).
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