Does seizure propagate within or across intrinsic brain networks? An intracranial EEG study

Background: Understanding the spatiotemporal propagation profiles of seizures is crucial for the preoperative assessment of epilepsy patients. The present study aimed to investigate whether seizures exhibit propagation patterns that align with intrinsic networks (INs).Methods: A quantitative analysis was conducted to examine ictal fast activity (IFA). The Epileptogenicity Index (EI) was employed to assess the epileptogenicity, spectral features, and temporal characteristics of IFA. Intra-network and inter-network comparisons were made regarding the IFA-related metrics. Additionally, the met-rics were correlated with Euclidean distance. Network connection maps were generated to visualize seizures originating from different INs, allowing for comparisons between distinct groups.Results: Data for 81 seizures in 43 subjects were captured using stereoelectroencephalography implantation. Three metrics were compared: EI, time involvement (TI), and energy ratio index (ERI). Intra-network channels exhibited higher EI, earlier involvement of IFA, and stronger high-frequency energy. These findings were further validated through subgroup analyses stratified by neuropathology, seizure type, and seizure origination lobe. Correlation analyses revealed a negative association between distance and both EI and ERI, while distance exhibited a positive correlation with TI. Seizures originating from different INs exhibited varying propagation characteristics.Conclusions: The study findings highlight the dominant role of intra-network dynamics over inter-network during seizure propagation. These results contribute to our understanding of seizure dynamics and their relationship with INs.

Automated summary

This study aims to investigate whether seizures exhibit propagation patterns that align with intrinsic networks (INs). Through quantitative analysis and network connection maps, the study found that seizures propagate more significantly within networks and exhibit different propagation characteristics between distinct networks.