Concordance between distributed EEG source localization and simultaneous EEG-fMRI studies of epileptic spikes.
In order to analyze where epileptic spikes are generated, we assessed the level of concordance between EEG source localization using distributed source models and simultaneous EEG-fMRI which measures the hemodynamic correlates of EEG activity. Data to be compared were first estimated on the same cortical surface and two comparison strategies were used: (1) MEM-concordance: a comparison between EEG sources localized with the Maximum Entropy on the Mean (MEM) method and fMRI clusters showing a significant hemodynamic response. Minimal geodesic distances between local extrema and overlap measurements between spatial extents of EEG sources and fMRI clusters were used to quantify MEM-concordance. (2) fMRI-relevance: estimation of the fMRI-relevance index alpha quantifying if sources located in an fMRI cluster could explain some scalp EEG data, when this fMRI cluster was used to constrain the EEG inverse problem. Combining MEM-concordance and fMRI-relevance (alpha) indexes, each fMRI cluster showing a significant hemodynamic response (p<0.05 corrected) was classified according to its concordance with EEG data. Nine patients with focal epilepsy who underwent EEG-fMRI examination followed by EEG recording outside the scanner were selected for this study. Among the 62 fMRI clusters analyzed (7 patients), 15 (24%) found in 6 patients were highly concordant with EEG according to both MEM-concordance and fMRI-relevance. EEG concordance was found for 5 clusters (8%) according to alpha only, suggesting sources missed by the MEM. No concordance with EEG was found for 30 clusters (48%) and for 10 clusters (16%) alpha was significantly negative, suggesting EEG-fMRI discordance. We proposed two complementary strategies to assess and classify EEG-fMRI concordance. We showed that for most patients, part of the hemodynamic response to spikes was highly concordant with EEG sources, whereas other fMRI clusters in response to the same spikes were found distant or discordant with EEG sources.
Grova
C
C
Montreal Neurological Institute, McGill University, 3801 University Street, EEG Department, Room 009d, Montreal, Quebec, Canada H3A 2B4. christophe.grova@mail.mcgill.ca
Daunizeau
J
J
Kobayashi
E
E
Bagshaw
A P
AP
Lina
J-M
JM
Dubeau
F
F
Gotman
J
J
D000465:Algorithms; D001499:Bayes Theorem; D002540:Cerebral Cortex / Q000473:pathology / Q000503:physiopathology; D016000:Cluster Analysis; D003627:Data Interpretation, Statistical; D004569:Electroencephalography / Q000379:methods* / Q000706:statistics & numerical data; D019277:Entropy; D004827:Epilepsy / Q000175:diagnosis*; D006801:Humans; D008279:Magnetic Resonance Imaging / Q000379:methods* / Q000706:statistics & numerical data; D010100:Oxygen / Q000097:blood; D013017:Sound Localization / Q000502:physiology
D010100:Oxygen