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Intracranial-EEG Based Classification and Localization of Epileptiform Activity in a Large Cohort of Adults with Drug-Resistant Epilepsy

Yost, S. W.; Campbell, J. M.; Sun, W.; Findlay, M.; Soule, C.; Mahler, K.; Soule, S.; Rahimpour, S.; Shofty, B.

2025-12-04 neurology
10.64898/2025.11.30.25340505 medRxiv
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ObjectiveTo characterize the type and distribution of epileptiform activity across anatomical regions and functional networks in a large cohort of patients with drug-resistant epilepsy (DRE) undergoing intracranial electroencephalography (iEEG). MethodsWe retrospectively reviewed iEEG recordings from 93 patients with DRE who underwent stereoelectroencephalography at our institution between 2019 and 2025. Epileptiform activity was classified as "ictal", "interictal", or "ictal spread" based on visual inspection and clinical correlation. Electrode coordinates were localized to anatomical regions using the Brainnetome Atlas and to functional networks using the DU15NET-Consensus Atlas. The distribution of epileptiform activity across regions and networks was compared with global baselines using Chi-square tests with false discovery rate correction. ResultsInterictal discharges were the most prevalent type of epileptiform activity (median 9.5% of contacts per patient), followed by ictal (6.0%) and ictal spread (2.1%). Temporal regions exhibited an increased prevalence of all types of epileptiform activity compared to the global baseline, whereas frontal regions showed marked reductions, despite dense sampling. At the network level, epileptiform activity was overrepresented in Default Network-A and underrepresented in the Salience/Parietal Memory Network. SignificanceEpileptiform activity shows consistent, non-uniform patterns across both anatomical regions and functional networks. These findings reinforce the central role of the temporal lobe and associative networks in epileptogenesis and support the view of epilepsy as a disorder of distributed brain networks. Mapping epileptiform activity in a network framework may enhance biomarker development and inform circuit-based surgical and neuromodulatory treatment strategies.

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