Modeling of intracerebral interictal epileptic discharges: Evidence for network interactions. Issue 6 (June 2018)

• Record Type: Journal Article
• Authors: Meesters, Stephan; Ossenblok, Pauly; Colon, Albert; Wagner, Louis; Schijns, Olaf; Boon, Paul; Florack, Luc; Fuster, Andrea
• Is Part Of: Clinical neurophysiology. Volume 129:Issue 6(2018:Jun.)
• Page Start: 1276
• Page End: 1290
• Publication Date: 2018-06
• Subjects: SEEG stereo-electroencephalography -- IED interictal epileptic discharges -- GLM General Linear Model -- ICA Independent Component Analysis -- SOZ seizure onset zone; Stereo-electroencephalography -- Analysis framework -- Interictal epileptic discharges -- Spatiotemporal network interaction -- Epilepsy surgery; Neurophysiology -- Periodicals; Electroencephalography -- Periodicals; Electromyography -- Periodicals; Neurology -- Periodicals; 612.8
• DOI: 10.1016/j.clinph.2018.03.021
• Languages: English
• ISSNs: 1388-2457

Abstract

Highlights: A framework is introduced to model network interactions underlying interictal epileptic discharges. Interdependency of brain areas is assessed by independent component analysis of synchronized spikes. It is concluded that a network approach is promising in the case of complex epilepsies. Abstract: Objective: The interictal epileptic discharges (IEDs) occurring in stereotactic EEG (SEEG) recordings are in general abundant compared to ictal discharges, but difficult to interpret due to complex underlying network interactions. A framework is developed to model these network interactions. Methods: To identify the synchronized neuronal activity underlying the IEDs, the variation in correlation over time of the SEEG signals is related to the occurrence of IEDs using the general linear model. The interdependency is assessed of the brain areas that reflect highly synchronized neural activity by applying independent component analysis, followed by cluster analysis of the spatial distributions of the independent components. The spatiotemporal interactions of the spike clusters reveal the leading or lagging of brain areas. Results: The analysis framework was evaluated for five successfully operated patients, showing that the spike cluster that was related to the MRI-visible brain lesions coincided with the seizure onset zone. The additional value of the framework was demonstrated for two more patients, who were MRI-negative and for whom surgery was not successful. Conclusions: A network approach is promising in case of complex epilepsies. Significance: Analysis of IEDs is considered a valuable addition to routine review of SEEG recordings, with the potential to increase the success rate of epilepsy surgery.