Alterations in Phase Synchronization During Epileptic Seizures: A Frequency-Based Multilayer EEG Network Analysis

Epilepsy is a common neurological disorder, and electroencephalogram (EEG) is widely used for its detection and analysis. EEG-based functional brain networks play a key role in revealing epileptic seizure patterns. Multilayer networks, which can capture multiple types of interactions, have shown great potential in this domain. However, previous analysis frameworks often simplified multilayer networks into single-layer subnetworks, ignoring the multilayer structure, or adopted a multiplex analysis framework, ignoring the importance of inter-layer connections. In this study, we proposed a multi-level analysis framework for frequency-based multilayer networks, ranging from supra-adjacency matrix, subnetwork, node, layer, and global levels. We applied this framework to the TUH EEG Seizure Corpus (TUSZ) to investigate the phase synchronization changes between the interictal (between seizures) and ictal (during seizures) phases of epileptic seizures. Compared to the interictal phase, the ictal phase showed increased local connectivity, decreased overall network connectivity, and a shift from random to regular network organization. Meanwhile, cross-frequency coupling (CFC) analysis suggested that δ-γ (frontal and parietal-occipital regions) and θ-α (frontal and right frontal-temporal regions) bands are potentially associated with seizure propagation or termination. These findings provide insights for future analysis of CFC in seizures and intervention strategies by interpreting seizure propagation networks. In conclusion, our framework enables efficient multilayer network analysis in epilepsy, facilitating the identification of key frequency bands and brain regions in CFC analysis.