High-frequency oscillations and seizure generation in neocortical epilepsy.
Academic Article
Overview
abstract
Neocortical seizures are often poorly localized, explosive and widespread at onset, making them poorly amenable to epilepsy surgery in the absence of associated focal brain lesions. We describe, for the first time in an unselected group of patients with neocortical epilepsy, the finding that high-frequency (60-100 Hz) epileptiform oscillations are highly localized in the seizure onset zone, both before and temporally removed from seizure onset. These findings were observed in all six patients with neocortical epilepsy out of 23 consecutive patients implanted with intracranial electrodes for pre-surgical evaluation during the study period. The majority of seizures (62%) in these patients were anticipated by an increase in high-frequency activity in the 20 min prior to neocortical seizure onset. Contrary to observations in normal brain, high-frequency activity was strongly modulated by behavioural state, and was maximal during slow-wave sleep, which may explain the propensity for neocortical onset seizures to begin during sleep. These findings point to an important role for neuromodulatory circuits, probably involving the thalamus, in mechanisms underlying seizure generation in neocortical epilepsy. These findings demonstrate that high-frequency epileptiform oscillations may prove clinically useful in localizing the seizure onset zone in neocortical epilepsy, for identifying periods of increased probability of seizure onset, and in elucidating mechanisms underlying neocortical ictogenesis. Confirmation that prolonged bursts of high-frequency activity may predict focal onset neocortical seizures will require prospective validation on continuous, prolonged recordings in a larger number of patients. Importantly, the results show that the dynamic range utilized in current clinical practice for localization of epileptogenic brain largely ignores fundamental oscillations that are signatures of an epileptogenic brain. It may prove that many currently available clinical EEG systems and EEG analysis methods utilize a dynamic range that discards clinically important information.
