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ORIGINAL RESEARCH article
Front. Netw. Physiol.
Sec. Networks in the Brain System
Volume 4 - 2024 |
doi: 10.3389/fnetp.2024.1441998
This article is part of the Research Topic The Network Theory of Epilepsy at Twenty View all 11 articles
Connectivity of High-Frequency Bursts as SOZ Localization Biomarker
Provisionally accepted- Department of Biomedical Engineering, Samueli School of Engineering, University of California, Irvine, Irvine, California, United States
For patients with refractory epilepsy, the seizure onset zone (SOZ) plays an essential role in determining the specific regions of the brain that will be surgically resected. High-frequency oscillations (HFOs) and connectivity-based approaches have been identified among the potential biomarkers to localize the SOZ. However, there is no consensus on how connectivity between HFO events should be estimated, nor on its subject-specific short-term reliability. Therefore, we propose the channel-level connectivity dispersion (CLCD) as a metric to quantify the variability in synchronization between individual electrodes and to identify clusters of electrodes with abnormal synchronization, which we hypothesize to be associated with the SOZ. In addition, we developed a specialized filtering method that reduces oscillatory components caused by filtering broadband artifacts, such as sharp transients, spikes, or direct current shifts. Our connectivity estimates are therefore robust to the presence of these waveforms. To calculate our metric, we start by creating binary signals indicating the presence of high-frequency bursts in each channel, from which we calculate the pairwise connectivity between channels. Then, the CLCD is calculated by combining the connectivity matrices and measuring the variability in each electrode's combined connectivity values. We test our method using two independent open-access datasets comprising intracranial electroencephalography signals from 89 and 15 patients with refractory epilepsy, respectively. . Recordings in these datasets were sampled at approximately 1000Hz, and our proposed CLCDs were estimated in the ripple band (80-200Hz).Recordings in these datasets were sampled at approximately 1000Hz, and our proposed CLCDs were estimated in the ripple band . Across all patients in the first dataset, the average ROC-AUC was 0.73, and the average Cohen's d was 1.05, while in the second dataset, the average ROC-AUC was 0.78 and Cohen's d was 1.07. On average, SOZ channels had lower CLCD values than non-SOZ channels. Furthermore, based on the second dataset, which includes surgical outcomes (Engel I-IV), our analysis suggested that higher CLCD interquartile (as a measure of CLCD distribution spread) is associated with favorable outcomes (Engel I). This suggests that CLCD could significantly assist in identifying SOZ clusters and, therefore,provide an additional tool in surgical planning for epilepsy patients.
Keywords: Seizure onset zone, intracranial EEG, connectivity, Gabor transform, Robust filtering, Epilepsy, high frequency oscillation, ripple
Received: 01 Jun 2024; Accepted: 05 Sep 2024.
Copyright: © 2024 Pinto Orellana and Lopour. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Beth Lopour, Department of Biomedical Engineering, Samueli School of Engineering, University of California, Irvine, Irvine, 92697-2700, California, United States
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