Epilepsy is a chronic neurological disorder characterized by recurrent seizures, affecting approximately 0.5–1% of the global population. For the 20–30% of patients whose seizures are refractory to medication, surgical intervention is often considered. The traditional pre-surgical evaluation relies on a combination of structural MRI, scalp electroencephalography (EEG), and neuropsychological testing to localize the epileptogenic zone and predict surgical outcomes. However, despite these assessments, about one-third of patients continue to experience seizures after surgery.
This technology provides a comprehensive, non-invasive system for mapping patient-specific brain networks in individuals with epilepsy, with a focus on identifying regions negatively correlated with the epileptogenic zone. What differentiates this technology is its ability to non-invasively and automatically model the negatively correlated epilepsy network. The integration of advanced data processing, source localization, and network modeling into a single workflow enables actionable insights for individualized surgical planning, filling a critical gap in epilepsy treatment and offering improved precision and accessibility over prior methods.
Mapped regions (green) represent seizure-free network