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Anticipating epileptic seizures in real time by a nonlinear analysis of similarity between EEG recordings

Van Quyen, M Le1,2; Martinerie, J1; Baulac, M1; Varela, F1

Computatonal Neuroscience

IN a previous publication we showed that non-linear analysis can extract spatio-temporal changes of brain electrical activity prior to epileptic seizures. Here we describe a new method to analyze this long-term nonstationarity in the EEG by a measure of dynamical similarity between different parts of the time series. We apply this method to the study of a group of patients with temporal lobe epilepsy recorded intracranially during transitions to seizure. We show that the method, which can be implemented on a personal computer, can track in real time spatio-temporal changes in brain dynamics several minutes prior to seizure.

1Laboratoire de Neurosciences Cognitives et Imagerie Cérébrale (CNRS UPR 640) and Unité D'epileptologie, Hôpital de la Salpêtrière, 47 Blvd. De L'hoôpital, 75651 Paris Cedex 13, France

2Corresponding Author: M. Le Van Quyen

Received 12 April 1999; accepted 17 May 1999

ACKNOWLEDGEMENTS: The support of Human Science Program (RG-92/97) and the Ligue Francaise Contre I'Epilepsie is gratefully acknowledged. We also thank Claude Adam for his help in providing the data used in this study.

© 1999 Lippincott Williams & Wilkins, Inc.