Diagnosing Epilepsy with Normal Interictal EEG Using Dynamic Network Models.

Objective: Whereas a scalp electroencephalogram (EEG) is important for diagnosing epilepsy, a single routine EEG is limited in its diagnostic value. Only a small percentage of routine EEGs show interictal epileptiform discharges (IEDs) and overall misdiagnosis rates of epilepsy are 20% to 30%. We aim to demonstrate how network properties in EEG recordings can be used to improve the speed and accuracy differentiating epilepsy from mimics, such as functional seizures - even in the absence of IEDs.

The effect of epilepsy surgery on tonic-clonic seizures.

Objective: Epilepsy surgery outcomes tend to be judged by the percentage in seizure reduction without considering the effect on specific seizure types, particularly tonic-clonic seizures, which produce the greatest morbidity and mortality. We assess how often focal to bilateral tonic-clonic seizures (BTCS) stop and how often they appear de novo after epilepsy surgery.

Methods: Analysis of a prospectively maintained epilepsy surgery database between 1986 and 2022 that characterizes the burden of BTCS after resective epilepsy surgery.

Multicentre analysis of seizure outcome predicted by removal of high frequency oscillations.

In drug-resistant focal epilepsy, planning surgical resection may involve presurgical intracranial EEG recordings (iEEG) to detect seizures and other iEEG patterns to improve postsurgical seizure outcome. We hypothesized that resection of tissue generating interictal high frequency oscillations (HFOs, 80-500 Hz) in the iEEG predicts surgical outcome. Eight international epilepsy centres recorded iEEG during the patients' pre-surgical evaluation.