Interactions between epileptic network and brain function: non-linear dynamic analysis of the intracranial EEG.

Recent advances in the non-linear dynamics analysis have made it possible t o identify hidden recurrences in EEG signals that could be missed by more t raditional linear techniques such as power spectrum or coherence analysis. This is particularly true for epileptic EEG recordings either in animals or in humans as epileptic phenomena are usually concomitant with the emergenc e a strong non-linear EEG behavior. Non-linear dynamical analysis technique s quantify the relations between EEG signals. The literature concerning the spatiotemporal characteristics of the epileptic processes during seizures and interictal periods is reviewed. Our attention has been mainly focused o n the interdependences between brain structures or on the dynamical changes of one particular brain region during intracranial recordings. These data could explain in part the dysfunctioning of the cerebral cortex induced by epileptic activities and provide an insight into the spatio-temporal organi zation of the epileptic network. Futhermore, by tracking the time variation of non-linear indices, one can anticipate the occurrence of seizures in te mporal lobe epilepsies. All this information could contribute to improve de finitions of the epileptogenic zone in partial epilepsy and also open the w ay to preventive interventions.