Directed differential connectivity graph of interictal epileptiform discharges

Abstract : In this paper, we study temporal couplings between interictal events of spatially remote regions in order to localize the leading epileptic regions from intracerebral EEG (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 nonepileptic states as defined by the interictal events. Postprocessings based on mutual information and multiobjective 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.
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IEEE Transactions on Biomedical Engineering, Institute of Electrical and Electronics Engineers, 2011, 58 (4), pp.884-93. 〈10.1109/TBME.2010.2099227〉
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Ladan Amini, Christian Jutten, Sophie Achard, Olivier David, Hamid Soltanian-Zadeh, et al.. Directed differential connectivity graph of interictal epileptiform discharges. IEEE Transactions on Biomedical Engineering, Institute of Electrical and Electronics Engineers, 2011, 58 (4), pp.884-93. 〈10.1109/TBME.2010.2099227〉. 〈inserm-00613113〉

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