Preictal State Detection in Intracranial EEG Recordings from Epilepsy Patients Using the Linear Cross Correlation Function.
Abstract number :
1.119
Submission category :
Year :
2001
Submission ID :
1946
Source :
www.aesnet.org
Presentation date :
12/1/2001 12:00:00 AM
Published date :
Dec 1, 2001, 06:00 AM
Authors :
F. Mormann, Dept. of Epileptology, University of Bonn, Bonn, Germany; K. Lehnertz, PhD, Dept. of Epileptology, University of Bonn, Bonn, Germany; R.G. Andrzejak, Dept. of Epileptology, University of Bonn, Bonn, Germany; T. Kreuz, John-von-Neumann Institut
RATIONALE: An important issue in epileptology is the question whether epileptic seizures can be anticipated. Recent studies have shown that certain measures derived from the theory of nonlinear time series analysis are to some extend capable of extracting information from the EEG that allows the definition of a preictal state and its distinction from the interictal state. In particular, we have shown a significant loss of phase synchronization to be a characteristic feature of the preictal state. In this study we evaluate the merit of the cross correlation function as a linear measure to distinguish between interictal and preictal states.
METHODS: 23 EEG recordings containing spontaneously occurring seizures were selected from 16 patients suffering from different types of focal epilepsy. In addition, 61 EEG recordings from the interictal state were selected from the same group of patients to serve as controls and reference states. Data were recorded from bilateral intrahippocampal depth electrodes and were analyzed using a moving-window technique. As a measure for synchronization/similarity, the maximum of the normalized cross correlation function was used. Cross correlation values of adjacent electrode contacts were evaluated and the criterion for the detection of a preictal state was defined as a drop of the time profiles below the interictal mean by more than 3 standard deviations.
RESULTS: In 19 out of the 23 seizure recordings, a preictal state could successfully be detected. In terms of patients, preictal state detection was successful in 13 out of the 16 patients. In all of the interictal recordings there was not a single false positive detection. Duration of detected preictal states ranged from several minutes to more than 3 hours.
CONCLUSIONS: Findings indicate that apart from measures derived from the theory of nonlinear time series analysis, linear measures such as the well-known cross correlation function appear to be capable of distinguishing preictal from interictal states thus rendering helpful information with regard to an actual prediction or even prevention of seizures.
Support: Deutsche Forschungsgemeinschaft