Sparse Differential Connectivity Graph of Scalp EEG for Epileptic Patients

Abstract : The aim of the work is to integrate the information modulation of the inter-relations between EEG scalp measurements of two brain states in a connectivity graph. We present a sparse differential connectivity graph (SDCG) to distinguish the effectively modulated connections between epileptiform and non-epileptiform states of the brain from all the common connections created by noise, artifact, unwanted background activities and their related volume conduction effect. The proposed method is applied on real epileptic EEG data. Clustering the extracted features from SDCG may present valuable information about the epileptiform focus and their relations.
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Submitted on : Tuesday, January 19, 2010 - 1:11:59 PM
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Ladan Amini, Sophie Achard, Christian Jutten, Hamid Soltanian-Zadeh, Gholam Ali Hossein-Zadeh, et al.. Sparse Differential Connectivity Graph of Scalp EEG for Epileptic Patients. 17th European Symposium on Artificial Neural Networks (ESANN 2009), Apr 2009, Bruges, Belgium. ⟨hal-00448557⟩

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