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IEEE International Workshop on Machine Learning For Signal Processing, Grenoble, France, Grenoble : France (2009)

Directed Epileptic Network From Scalp And Intracranial EEG Of Epileptic Patients

Ladan Amini 1, 2, Christian Jutten 1, Sophie Achard 1, Olivier David 3, Hamid Soltanian-Zadeh 2, Gholam Ali Hossein-Zadeh 2, Philippe Kahane 3, Lorella Minotti 3, Laurent Vercueil 3

(09/2009)

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.

1 :	Grenoble Images Parole Signal Automatique (GIPSA-lab)
	CNRS : UMR5216 – Université Joseph Fourier - Grenoble I – Université Pierre Mendès-France - Grenoble II – Université Stendhal - Grenoble III – Institut Polytechnique de Grenoble
2 :	Control and Intelligent Processing Center of Excellence - University of Tehran (CIPCE)
	University of Tehran
3 :	Grenoble Institut des Neurosciences (GIN)
	INSERM : U836 – CEA – Université Joseph Fourier - Grenoble I – CHU Grenoble

Domaine

:

Informatique/Traitement du signal et de l'image

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Contributeur : Ladan Amini <>

Soumis le : Vendredi 5 Février 2010, 18:23:51

Dernière modification le : Vendredi 5 Février 2010, 21:05:43