Large-Scale Synchronization Dynamics During Epileptic Seizures: A Patient-Independent EEG Network Analysis.

Overview

1. Statistics Program, King Abdullah University of Science and Technology, Thuwal 23955, Saudi Arabia

Abstract

This study examines large-scale synchronization dynamics during epileptic seizures using scalp EEG recordings, with the aim of characterizing reproducible network-level patterns across patients. Functional connectivity was estimated from the CHB-MIT database using phase-lag-based measures robust to volume conduction, specifically Imaginary Coherence and the debiased weighted phase lag index, across standard frequency bands. Synchronization features were used to train a neural network classifier evaluated under a Leave-One-Patient-Out (LOPO) validation framework to ensure patient-independent assessment. To quantify seizure-related network alterations, we introduce Relative Pathological Synchronization (RPS), defined as the median area under the ROC curve across patients. The results demonstrate that synchronization patterns deviate systematically from baseline activity in a time-dependent manner. Interhemispheric connectivity shows earlier and higher peak RPS values compared to intrahemispheric connectivity, while intrahemispheric changes develop more gradually and persist over a longer interval. Theta-band features provide the most consistent contribution, although interhemispheric synchronization involves multiple frequency bands. In addition, longer seizures are associated with higher peak RPS values. These findings indicate that large-scale synchronization patterns contain stable, patient-independent information about seizure dynamics. Specifically, interhemispheric connectivity achieved a peak RPS of 0.749 (0.609–0.891) at TAS=10 s, while intrahemispheric connectivity reached 0.640 (0.563–0.843) at TAS=30 s under strict Leave-One-Patient-Out validation.

Reproduced under the paper's license (CC BY), from the paper cited above.

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Data

Datasets cited

• doi:10.13026/c2k01r — at the source; found in the references
• physionet.org/content/chbmit — at PhysioNet; found in “Data Availability Statement”

Data Availability Statement

The original data presented in the study are openly available in PhysioNet at https://physionet.org/content/chbmit/1.0.0/ (accessed on 14 April 2026).

Reproduced under the paper's license (CC BY), from the paper cited above.

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Version 1, 28 September 2026: the first record

Recorded: type, language, journal, volume, issue, pages, dates, 2 authors, 5 keywords, 1 funder, 30 references.

Cite

This paper

Gorshkov, O., & Ombao, H. (2026). Large-Scale Synchronization Dynamics During Epileptic Seizures: A Patient-Independent EEG Network Analysis. Entropy (Basel, Switzerland), 28(6), 599. https://doi.org/10.3390/e28060599

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