Localization of epileptogenic zones in Lennox-Gastaut syndrome using frequency domain source imaging of intracranial electroencephalography: a preliminary investigation

Although intracranial electroencephalography (iEEG) has been widely used to localize epileptogenic zones in epilepsy, visual inspection of iEEG recordings does not always result in a favorable surgical outcome, especially in secondary generalized epilepsy such as Lennox-Gastaut syndrome (LGS). Various computational iEEG analysis methods have recently been introduced to confirm the visual inspection results. Of these methods, high gamma oscillation in iEEG has attracted interest because a series of studies have reported a close relationship between epileptogenic zones and cortical areas with high gamma oscillation. Meanwhile, frequency domain source imaging of EEG and MEG oscillations has proven to be a useful auxiliary tool for identifying rough locations of epileptogenic zones. To the best of our knowledge, however, frequency domain source imaging of high gamma iEEG oscillations has not been studied. In this study, we investigated whether the iEEG-based frequency domain source imaging of high gamma oscillation (60-100 Hz) would be a useful supplementary tool for identifying epileptogenic zones in patients with secondary generalized epilepsy. The method was applied to three successfully operated on LGS patients, whose iEEG contained some ictal events with distinct high gamma oscillations before seizure onset. The resultant cortical source distributions were compared with surgical resection areas and with high gamma spectral power distributions on the intracranial sensor plane. While the results of the sensor-level analyses contained many spurious activities, the results of frequency domain source imaging coincided better with the surgical resection areas, suggesting that the frequency domain source imaging of iEEG high gamma oscillations might help enhance the accuracy of pre-surgical evaluations of patients with secondary generalized epilepsy.This work was supported in part by the KRISS-WCL project (Development of Measurement Technology for Cognitive Process) and in part by the Public Welfare and Safety Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology (no 2011-0027859)