Source tracing with spatial phase gradients in epileptiform activity localizes seizure onset zone

<i>Objective</i>. Sources of epileptic traveling waves offer critical insights into seizure onset zone (SOZ) localization, making them invaluable for preoperative assessment in patients with epilepsy. However, the absence of tailored source-tracing methods and the inherent instability of epileptiform activity make it difficult to achieve reliable source identification for SOZ localization. This study aimed to analyze the propagation pattern during seizure events and develop a framework to trace the sources of epileptic expanding traveling waves (ETWs).<i>Approach</i>. 101 seizure events were recorded from five 4-Aminopyridine-induced acute cortical rat epilepsy models. In each seizure event, epileptiform activities were classified into two categories according to their time-frequency diagrams (multiband and non-multiband epileptiform activities). The center of the SOZ was regarded as the recording site with the largest amplitude of epileptiform activities. Using the spatial-phase-based analysis, we analyzed the propagation pattern during the seizure event and extracted the ETWs. The sources of ETWs were traced by the intersection of spatial-phase-gradient.<i>Main results</i>. The ETW proportion of multiband epileptiform activities was 62.7%±8.3%, significantly higher than those in non-multiband epileptiform activities (53.8%±9.0%). ETWs with stable propagation patterns gave rise to a concentrated source tracing outcome. The single-band signal (component of the multiband activities) had a more stable ETW propagation pattern than both the multiband and non-multiband activities. The source tracing results of the single-band signals clustered around the SOZ center and remained stable even when the SOZ center was out of coverage (removing half of the recording sites, among which the SOZ center was included).<i>Significance</i>. The proposed framework enables ETW extraction from epileptiform activities and can trace ETW sources even when the sources are out of coverage. Therefore, the proposed framework may prove clinically valuable in cases with sparse intracranial recordings, addressing the limitation of traditional SOZ localization methods.