Directed epileptic network from scalp and intracranial EEG of epileptic patients

Abstract : We proposed recently the computation of epileptic connectivity graphs based on wavelet correlation coefficients between EEG signals. The suspected epileptiform electrodes are recognized using the clustering of the topological properties of the graph that can be useful for pre-surgical studies. Here, we present a method for comparing epileptic networks estimated from scalp and intracranial EEG (IEEG) in partial epilepsy patients. The results are presented for a patient with left temporal epilepsy. Good spatial correspondence between the IEEG and the scalp EEG epileptic graphs is obtained. These results are consistent with the patient's clinical diagnosis.
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Ladan Amini, Christian Jutten, Sophie Achard, Olivier David, Hamid Soltanian-Zadeh, et al.. Directed epileptic network from scalp and intracranial EEG of epileptic patients. IEEE International Workshop on Machine Learning for Signal Processing (MLSP 2009), Sep 2009, Grenoble, France. 6 p. ⟨hal-00424212⟩

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