Abstracts

RATIONALE: An important issue in epileptology is whether specific features can be extracted from the EEG that are predictive of an impending seizure. Much research has been done on this topic lately, and different univariate measures from nonlinear time-series analyses have been used. In this study we use a bivariate measure to determine the phase synchronization in intracranial EEG recordings from up to now 15 patients suffering from different types of focal epilepsy. We evaluate the merit of this measure to distinguish between interictal and preictal states. METHODS: Using a moving-window technique an average of 10 EEG segments per patient recorded from bilateral intrahippocampal depth electrodes were analyzed. Instantaneous phases of the EEG signals were determined by means of the Hilbert Transformation and the mean phase coherence was used as a measure for phase synchronization. Phase coherence values of adjacent electrode contacts were evaluated in terms of level and variation for interictal and preictal recordings. RESULTS: In the majority of the patients analyzed, distinct differences between interictal and preictal states were revealed. In contrast to interictal states which were characterized by high and constant values of the mean phase coherence, low values were observed before an impending seizure. In most cases, these states of decreased synchronization started hours before the actual seizures. CONCLUSIONS: Findings indicate that the analysis of phase synchronization might offer the possibility of distinguishing a preictal from an interictal state thus rendering helpful information for an actual prediction of seizures. Specific changes in brain dynamics traced by the mean phase coherence appear to be different from those traced by other measures, possibly making measures for phase synchronization a valuable addition to EEG analysis techniques. Supported by the Deutsche Forschungsgemeinschaft