3. Dynamic effective connectivity of epileptic networks determined with high density EEG source analysis

• Published in: Clinical neurophysiology 2012-10, Vol.123 (10), p.e109-e109
• Main Authors: Plomp, G, Tyrand, R, Astolfi, L, He, B, Seeck, M, Michel, C.M, Vulliemoz, S
• Format: Article
• Language: English
• Subjects: Neurology
• ISSN: 1388-2457; 1872-8952
• DOI: 10.1016/j.clinph.2012.03.067

Introduction Analyzing the dynamic behaviour of epileptic networks could help to better understand the way pathologic neural activity propagates, and leads to spikes, seizures, and their electro-clinical and cognitive manifestations, with implications for epilepsy surgery candidates. Methods In 6 patients with temporal lobe epilepsy we studied effective connectivity of large-scale cortical networks at high temporal resolution around interictal spikes, recorded with high density (256 channels) EEG. The cortical electric source activity was obtained for 90 cortical regions of interest (ROI) using a distributed inverse solution. Multivariate, time-varying (millisecond resolution), and frequency-resolved (1–50 Hz) Granger causality analysis (Partial Directed Coherence) was applied to the source signal for all ROIs. In all patients subsequent intracranial recording or surgical resection was used for validation. Results Information flow occurred predominantly in the theta and beta bands. The key driving structures where located in the anterior and medial temporal regions, with peak information transfer before the spike maximum. We found fast-varying connectivity patterns between the antero-medial and lateral temporal lobe and basal frontal lobe, but also transient transfer towards the contralateral temporal lobe. In two patients with a multifocal irritative zone, we found evidence of connectivity from the main anterior temporal driver towards the secondary spike focus remote from the epileptogenic zone. Conclusion EEG-based time-varying effective connectivity of epileptic spikes provides a clear characterization of the epileptic networks that is concordant with invasive electro-clinical findings. This could have major clinical implications for tailoring resective, disconnective, and functional surgery.