How reliable are fMRI–EEG studies of epilepsy? A nonparametric approach to analysis validation and optimization Anthony B. Waites, a Marnie E. Shaw, a Regula S. Briellmann, a Angelo Labate, a David F. Abbott, a and Graeme D. Jackson a,b, * a Brain Research Institute, Austin Health, Heidelberg West, Australia b Department of Medicine and Radiology, The University of Melbourne, Parkville, Australia Received 6 April 2004; revised 18 June 2004; accepted 7 September 2004 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 deventsT. 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. D 2004 Elsevier Inc. All rights reserved. Keywords: fMRI; Electroencephalography; Epilepsy Introduction Scalp electroencephalography (EEG) gives good temporal information about interictal epileptiform discharges (IED), while functional magnetic resonance imaging (fMRI) can identify blood oxygen level dependent (BOLD)-associated neuronal activity with high spatial resolution (Logothetis, 2002, 2003; Ogawa et al., 1990). EEG that is simultaneous with fMRI scanning gives high- resolution information spatially and temporally, providing a powerful tool for the study of the neural substrates active during generation of interictal discharges. The simplest way to combine EEG and fMRI is to use dspike- triggered fMRIT, which simply activates the MRI when an epileptiform event is seen. While this has contributed greatly to our understanding of activated areas during epileptiform activity (Archer et al., 2003a,b,c; Baudewig et al., 2001; Jager et al., 2002; Krakow et al., 1999, 2001a,b; Lazeyras et al., 2000; Seeck et al., 1998; Symms et al., 1999; Warach et al., 1996), it has the disadvantage that it only collects a single acquisition per event, not the whole hemodynamic response. Also, no EEG information is acquired during the time when the fMRI image is obtained. Technical developments have enabled simultaneous acquisition of EEG and fMRI data (Allen et al., 2000; Bonmassar et al., 2002; Jay et al., 1993; Lemieux et al., 2001). Gradient artefact is eliminated using filters (Hoffmann et al., 2000) or by avoiding measurement during gradient switching (Anami et al., 2003). Pulse artefact can be ameliorated using an adaptive subtraction method (Allen et al., 1998; Bonmassar et al., 2002). The combined effect of these correction methods leads to an EEG signal that is of sufficient quality to reliably identify interictal epileptiform discharges, allowing dspike-related fMRI–EEGT data sets to be acquired (Benar et al., 2002; Iannetti et al., 2002; Lemieux et al., 2001). Despite the importance of these data, there has been little work done on objectively validating the method. The factors that influence the success of a particular fMRI–EEG investigation remain poorly understood. For example, the number of spikes required for obtaining a significant BOLD response varies 1053-8119/$ - see front matter D 2004 Elsevier Inc. All rights reserved. doi:10.1016/j.neuroimage.2004.09.005 * Corresponding author. Brain Research Institute, Ground Floor, Neurosciences Building, Austin Health, Heidelberg West, Victoria, 3081, Australia. Fax: +61 3 9496 2980. E-mail address: BRI@brain.org.au (G.D. Jackson). Available online on ScienceDirect (www.sciencedirect.com.) www.elsevier.com/locate/ynimg NeuroImage 24 (2005) 192 – 199