A fingerprint of the epileptogenic zone in human epilepsies

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.

Keywords: epilepsy surgery; epileptogenic zone; high-frequency oscillations; imaging methodology; stereo-EEG.

Figure 1

SEEG recording and time-frequency plots of seizure onset. (A) The SEEG time series. Bipolar montage was applied by taking the difference between signals from two adjacent contacts. Ictal onset is marked as ‘0’, full duration of the segment is 40 s (from −20 s to 20 s). (B) The Morlet time frequency maps corresponding to each bipolar contact pair in A. Each graph shows 20 s before the seizure onset to 20 s after the seizure onset, along the horizontal axis. The vertical axis represents frequencies from 1 Hz to 200 Hz, logarithmically spaced and spectrally flattened to emphasize the higher frequencies. Contacts in the resected area are outlined in blue. The pattern characterized by the combination of a spike, multiband fast activity and suppression is localized inside the resected area (yellow arrow), while broadband fast activity (black arrow) and suppression without sustained fast activity (white arrow) are localized outside the resected area.

Figure 2

Example of pre-ictal to ictal transitions in the epileptogenic zone. Channel R5-R6 from Fig. 1A from 5 s before to 20 s after the ictal onset is shown in (A) and the corresponding time frequency plot (logarithmic scale) is shown in B. The time frequency plot shows the proposed ‘fingerprint’: a combination of pre-ictal spikes, multi-band fast activity and simultaneous suppression of slower background frequencies. Note that fast activity is characterized by multiple bands that are not harmonically related, chirp at different frequency rates, and whose amplitudes vary independently across bands.

Figure 3

Illustration of feature extraction procedure. (A–D) Fast activity extraction. (A) Original post-onset time-frequency plot. (B) Frangi filtering result. (C) Thresholding result. (D) Final morphological cleaning result. (E–H) Suppression extraction. (E) Original post-onset time-frequency plot with ideal suppression region. (F) Guided filtering result. (G) Fast activity-based spatial constraint. (H) Final thresholding result. (I–K) Preictal spikes extraction. (I) Original pre-onset time-frequency plot. (J) Median statistics for each time point. (K) Small circles indicate major local maxima as the spike candidates.

Figure 4

Implantation maps with schematic representation of the resection margins (red) and bipolar SEEG channels identified by the algorithm as true positive (TP) and false positive (FP). *Electrodes on the maps are marked: (i) as red if they contain true positive (TP) channels (potentially epileptogenic inside the resection); (ii) as green if they contain false positive (FP) channels (potentially epileptogenic outside the resection); (iii) as black if they contain only true negative (TN) channels (not potentially epileptogenic outside the resection); (iv) as black in the red-shaded area if they contain false negative (FN) channels (not potentially epileptogenic inside the resection). Boundaries of prior resections are schematically shaded in yellow (only Patients 3 and 9 had a previous resection).

Figure 5

Boxplots of maximum frequency and timing comparison. (A) Maximum frequency of fast activity inside and outside resection; (B) maximum frequency of fast activity inside resection classified as epileptogenic zone and non-epileptogenic zone contacts. (C) The start time of fast activity inside and outside resection. (D) The start time of fast activity inside resection classified as epileptogenic zone and non- epileptogenic zone contacts. (E) The maximum frequency of suppression inside and outside resection. (D) The maximum frequency of suppression inside resection classified as epileptogenic zone and non- epileptogenic zone contacts. The boxplot spans the two central quartiles of the data around the median (red line), and the whiskers extend to a maximum of 1.5 times the box span, or to the last data point, whichever is shorter. The remaining data points are outliers. EZ = epileptogenic zone.

Figure 6

Scatter plot of maximum frequency of fast activity versus maximum frequency of suppression for contacts. (A) Classified as epileptogenic zone inside the resection; (B) classified as non- epileptogenic zone inside the resection and (C) outside the resection region. The presence of suppression was determined by thresholding 70 largest suppression areas for contacts inside the resection region and outside separately, resulting in 40 contacts in (A), 30 contacts in (B) and 70 contacts in (C).