How reliable are fMRI–EEG studies of epilepsy? A nonparametric approach to analysis validation and optimization

• Published in: NeuroImage (Orlando, Fla.) Vol. 24; no. 1; pp. 192 - 199
• Main Authors: Waites, Anthony B., Shaw, Marnie E., Briellmann, Regula S., Labate, Angelo, Abbott, David F., Jackson, Graeme D.
• Format: Journal Article
• Language: English
• Published: United States Elsevier Inc 2005; Elsevier Limited
• Subjects: Analysis of Variance; Brain; Cerebral Cortex - physiopathology; Child; Computer Simulation; Electroencephalography; Electroencephalography - statistics & numerical data; Epilepsy; Epilepsy, Absence - diagnosis; Epilepsy, Absence - physiopathology; Epilepsy, Generalized - diagnosis; Epilepsy, Generalized - physiopathology; Evoked Potentials - physiology; Female; fMRI; Humans; Image Enhancement; Image Processing, Computer-Assisted - statistics & numerical data; Magnetic Resonance Imaging - statistics & numerical data; Mathematical Computing; Methods; NMR; Nuclear magnetic resonance; Optimization; Oxygen - blood; Reference Values; Reproducibility of Results; Statistics as Topic; Statistics, Nonparametric; Studies; fMRI; Epilepsy; Electroencephalography
• ISSN: 1053-8119; 1095-9572
• DOI: 10.1016/j.neuroimage.2004.09.005

Simultaneously acquired functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) data hold great promise for localizing the spatial source of epileptiform events detected in the EEG trace. Despite a number of studies applying this method, there has been no independent and systematic validation of the approach. The present study uses a nonparametric method to show that interictal discharges lead to a blood oxygen level dependent (BOLD) response that is significantly different to that obtained by examining random ‘events’. We also use this approach to examine the optimization of analysis strategy for detecting these BOLD responses. Two patients with frequent epileptiform events and a healthy control were studied. The fMRI data for each patient were analyzed using a model derived from the timings of the epileptiform events detected on EEG during fMRI scanning. Twenty sets of random pseudoevents were used to generate a null distribution representing the level of chance correlation between the EEG events and fMRI data. The same pseudoevents were applied to control data. We demonstrate that it is possible to detect blood oxygen level-dependent (BOLD) changes related to interictal discharges with specific and independent knowledge about the reliability of this activation. Biologically generated events complicate the fMRI–EEG experiment. Our proposed validation examines whether identified events have an associated BOLD response beyond chance and allows optimization of analysis strategies. This is an important step beyond standard analysis. It informs clinical interpretation because it permits assessment of the reliability of the connection between interictal EEG events and the BOLD response to those events.