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Session: Neurophysiology: Clinical Neurophysiology
Session starts: Thursday 24 January, 13:30
Presentation starts: 14:00
Room: Lamoraalzaal

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Pauly Ossenblok (Dr.)
Petra van Houdt (Ir)
Albert Colon (Drs)
Paul Boon (Prof. dr.)
Jan de Munck (Dr)

Abstract:
EEG-correlated functional MRI (EEG-fMRI) has proven its application as a noninvasive technique for the pre-operative work-up of epilepsy surgery candidates. EEG-fMRI investigates the correlation between the occurrence of interictal epileptic discharges in the EEG (IEDs) and blood oxygenation level-dependent (BOLD) changes using a general linear model framework (GLM). However, this approach highly depends on the number of IEDs present in the EEG [1], which might not occur during the limited time of scanning or might not be visible at the scalp. In order to increase the ability to identify the epileptic network based on fMRI, we explored the feasibility of independent component analysis (ICA), a data-driven fMRI approach without the use of EEG. As a proof-of-concept study fMRI data were selected of seven patients from a previous EEG-fMRI study [2] for whom the results of the standard GLM approach were validated with the gold standard (i.e. invasive EEG recordings and surgical outcome). The fMRI data of these patients were divided into two epochs, one during which IEDs were present in the simultaneously recorded EEG (with IEDs) and a second one during which no IEDs were present (without IEDs). Both epochs were analyzed with ICA yielding a large number of independent components (ICs). To select the component related to epileptic activity, the spatial overlap was calculated for each IC with the resection area of a post-operative MRI and with the EEG-fMRI correlation pattern. The IC that showed a high degree of overlap with both was identified as the epileptic component (ICE). Furthermore, as a clinical application, EEG-fMRI data were acquired before and after withdrawal of anti-epileptic drugs (AEDs) in patients with localization-related epilepsy who are candidates for epilepsy surgery (n=5). For all patients of the proof-of-concept study an ICE could be selected both in the data with IEDs and without IEDs. For the patients in the clinical study, no IEDs were present in the EEG data recorded while taking AEDs. However, using the a priori information based on the standard GLM approach in combination with the ICA results we were able to identify the ICE for the fMRI data acquired in both conditions, with and without AED administration. This study shows that ICA enables the identification of the ICE of patients with localization-related epilepsy. These components can also be identified when no IEDs are present in the EEG. This could indicate the existence of a patient-specific epileptic resting-state network, similar to the existence of large scale resting-state networks in healthy volunteers [3], providing promising information for the clinical application of fMRI in the presurgical work-up of patients with epilepsy. REFERENCES [1] P. van Houdt, J. de Munck, M. Zijlmans, G. Huiskamp, F. Leijten, P. Boon, P. Ossenblok. “Comparison of analytical strategies for EEG-correlated fMRI data in patients with epilepsy”, Magn Reson Imaging Vol. 28, pp.1078-86 (2010). [2] P. van Houdt, P. Ossenblok, A. Colon, P. Boon, J. de Munck. “A framework to integrate EEG-correlated fMRI and intracerebral recordings”, Neuroimage, Vol. 60(4), pp. 2042-53 (2012). [3] C. Beckmann, M. DeLuca, J. Devlin, S. Smith. “Investigations into resting-state connectivity using independent component analysis”, Philos Trans R Soc Lond B Biol Sci, Vol. 360, pp. 1001-13 (2005).