HAL : hal-00507957, version 2

DOI : 10.1109/TBME.2010.2099227

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IEEE Transactions on Biomedical Engineering 58, 4 (2011) 884-893

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v1 (02-08-2010)

v2 (04-04-2011)

Directed Differential Connectivity Graph of Interictal Epileptiform Discharges

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

(04/2011)

In this paper, we study temporal couplings between interictal events of spatially remote regions in order to localize the leading epileptic regions from intracerebral electroencephalogram (iEEG). We aim to assess whether quantitative epileptic graph analysis during interictal period may be helpful to predict the seizure onset zone of ictal iEEG. Using wavelet transform, cross-correlation coefficient, and multiple hypothesis test, we propose a differential connectivity graph (DCG) to represent the connections that change significantly between epileptic and non-epileptic states as defined by the interictal events. Post-processings based on mutual information and multi-objective optimization are proposed to localize the leading epileptic regions through DCG. The suggested approach is applied on iEEG recordings of five patients suffering from focal epilepsy. Quantitative comparisons of the proposed epileptic regions within ictal onset zones detected by visual inspection and using electrically stimulated seizures, reveal good performance of the present method.

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 - Grenoble Institute of Technology
2 :	Control and Intelligent Processing Center of Excellence - University of Tehran (CIPCE)
	University of Tehran
3 :	Grenoble Institut des Neurosciences (GIN)
	INSERM : U836 – Université Joseph Fourier - Grenoble I – CHU Grenoble – CEA : DSV/IRTSV

Domaine

:

Informatique/Traitement du signal et de l'image Sciences de l'ingénieur/Traitement du signal et de l'image

Mots Clés : Epilepsy – functional connectivity graph – intracerebral EEG – permutation-based multiple hypothesis test – wavelet cross-correlation coefficient.

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Contributeur : Ladan Amini <>

Soumis le : Lundi 4 Avril 2011, 14:52:18

Dernière modification le : Vendredi 15 Avril 2011, 14:32:28