Acquisition of typical EEG waveforms during fMRI: SSVEP, LRP, and frontal theta

www.elsevier.com/locate/ynimg NeuroImage 24 (2005) 1012 – 1024

Acquisition of typical EEG waveforms during fMRI: SSVEP, LRP, and frontal theta Gebhard Sammer,* Carlo Blecker, Helge Gebhardt, Peter Kirsch, Rudolf Stark, and Dieter Vaitl Bender Institute of Neuroimaging, University of Giessen, Otto-Behaghel-Str. 10F, D-35394 Giessen, Germany Received 10 April 2004; revised 27 September 2004; accepted 26 October 2004 Available online 13 December 2004 Recent work has demonstrated the feasibility of simultaneous electroencephalography (EEG) and functional magnetic resonance imaging (fMRI). Virtually no systematic comparisons between EEG recorded inside and outside the MR scanner have been conducted, and it is unknown if different kinds of frequency mix, topography, and domainspecific processing are uniformly recordable within the scanner environment. The aim of the study was to investigate several typical EEG waveforms in the same subjects inside the magnet during fMRI and outside the MR examination room. We examined whether uniform artifact subtraction allows the extraction of these different EEG waveforms inside the scanner during EPI scanning to the same extent as outside the scanner. Three well-established experiments were conducted, eliciting steady state visual evoked potentials (SSVEP), lateralized readiness potentials (LRP), and frontal theta enhancement induced by mental addition. All waveforms could be extracted from the EEG recorded during fMRI. Substantially no differences in these waveforms of interest were found between gradient-switching and intermediate epochs during fMRI (only the SSVEP-experiment was designed for a comparison of gradient—with intermediate epochs), or between waveforms recorded inside the scanner during EPI scanning and outside the MR examination room (all experiments). However, non-specific amplitude differences were found between inside and outside recorded EEG at lateral electrodes, which were not in any interaction with the effects of interest. The source of these differences requires further exploration. The high concordance of activation patterns with published results demonstrates that EPI-images could be acquired during EEG recording without significant distortion. D 2004 Elsevier Inc. All rights reserved. Keywords: Electroencephalography (EEG); Functional MRI (fMRI); Visual evoked potential; Readiness potential; Frontal theta

* Corresponding author. Fax: +49 641 9926099. E-mail address: [email protected] (G. Sammer). Available online on ScienceDirect (www.sciencedirect.com). 1053-8119/$ - see front matter D 2004 Elsevier Inc. All rights reserved. doi:10.1016/j.neuroimage.2004.10.026

Introduction The combination of the electroencephalogram (EEG) and functional magnetic resonance images (fMRI) is a potentially powerful approach in multi-modal brain research. Because the two methods are sensitive to different temporal and spatial properties of brain function, they have the potential to complement one another. The low time resolution of BOLD-sampling blurs interpretations of the functional specificity of a BOLD-activated brain structure. Peaks and latencies of event-related potentials (ERPs) provide additional functional information at high time resolution. They can be utilized to describe functional fMRI-activations more precisely. On the other hand, the spatial resolution of EEG is poor and the localization of sources for measured voltage distributions difficult. Estimation of cortical generators was shown to benefit from the use of spatial fMRI-constraints (Babiloni et al., 2003; Bonmassar et al., 2001). Recording EEG and fMRI simultaneously is of advantage if task repetition is supposed to induce additional processes, for example, memory, practice, subjective probability of stimulus occurrence, or other well known influences on repeated task performance. Only simultaneously recorded EEG and fMRI can ensure that the same composition of processes is represented in fMRI and EEG. So far, only a few studies have been carried out on simultaneously acquired EEG and fMRI. Goldman et al. (2000) recorded EEG between periods of gradient-induced noise and showed increased power in the alpha band (8–12 Hz) when the subject’s eyes were closed. After recording EEG with a specific sampling protocol (dstepping stone samplingT) and the application of a gradient artifact subtraction method, Anami et al. (2003) retrieved alpha activity by inspection during eyes open/closed periods. Laufs et al. (2003) correlated the alpha power time course with the BOLD signals. In this study, the EEG measured during gradient switching was used for analysis as well. Using the MR gradient artifact subtraction technique and pulse artifact subtraction method which have been proposed by Allen et al. (1998, 2000), the authors concluded that artifact subtraction works for the spectral frequency analysis approach. Salek-Haddadi et al. (2003a,b) demonstrated the identification of epileptiform events in EEG continuously recorded during imaging. Be´ nar et al. (2003) compared the effectiveness of scanning artifact removal methods

G. Sammer et al. / NeuroImage 24 (2005) 1012–1024

and for reducing the ballistocardiographic artifact in epileptic patients having interictal epileptiform discharges. They found that EPI-artifact subtraction (without using a triggering signal from the scanner, and sampling the EEG at a rate of 1 kHz) left less distortion than using a FFT filter, as it has been suggested by Hoffmann et al. (2000). Nevertheless, Be´nar et al. (2003) reported about larger remaining imaging artifacts in the EEG, limiting the detection of epileptiform waves in some patients. In the same study, the ballistocardiographic artifact could be eliminated satisfactorily using both PCA and ICA, but also without any correction, the epileptiform discharges in the EEG were preserved. Because this is in distinction to most of the literature (cp. Allen et al., 1998; Bonmassar et al., 2002; Goldman et al., 2000), Be´nar et al. attribute their results to the successful use of head restraints and electrode-wiring inside the scanner, but they limited this finding to epileptic EEG. Event-related potentials were recorded by Kruggel et al. (2000). They compared checkerboard visual evoked potentials (VEP) inside a 3T magnet with and without fMRI scanning to published reference data. Latencies of the P2 and N3 corresponded to these reference data outside a MR scanner. In a subsequent study (Kruggel et al., 2002), event-related potentials (ERPs) were computed on onsets of Kaniza figures and nonKaniza figures (figures composed of the same elements as Kanizafigures but they were arranged in such a way that prevented the illusion). Again ERPs were computed from MR-gradient-free epochs. MR-gradient artifact epochs were excluded from analysis. The ERPs were shown to vary with experimental conditions (Gestalt perception and target processing). Bonmassar et al. (2001) demonstrated the acquisition of 4 Hz checkerboard VEPs during fMRI scanning. Epochs for VEP averaging were scheduled between epochs of gradient switching to avoid gradient artifacts. Other studies showing the feasibility of simultaneous EEG and fMRI recordings were published by Goldman et al. (2002), Hoffmann et al. (2000), Lazeyras et al. (2002), without EEGanalysis, Lemieux et al. (2001), and Salek-Haddadi et al., 2002. Although some studies have been performed on simultaneous EEG/fMRI recording, this area is still in its early stages. The main sources of artifacts in the EEG are identified: movements in the magnetic field, cardioballistic artifacts and HF-gradient artifacts. An influence of the magnetic field itself on the EEG, similar to the effect on the T-wave of the electrocardiogram (Wendt et al., 1988), has not been reported so far. Significant progress was made for the development of artifact-reduction methods. However, it is still unknown which effects remaining artifacts have on signalextraction. Moreover, it is not known if different aspects of the EEG, for example, frequency-mix, topography, and domainspecific processing (e.g., motor, visual, cognitive) are uniformly recordable within the scanner environment. Accordingly, the aim of the study was to investigate several typical EEG waveforms in the same subject inside and outside the magnet. EEG was measured during fMRI scanning—including periods of gradient switching— and outside the MR examination room in the same subjects using identical technical EEG-equipment. We investigated if the application of artifact subtraction methods allows the extraction of typical waveforms to the same extent as outside the scanner. Three well-established experiments were conducted in order to elicit a variety of EEG waveforms. In the first experiment, steady state visual-evoked potentials (SSVEP) were elicited by watching a rapid sequence of flashes. Mu¨ller (1997) showed that SSVEPs could be elicited with all stimulation frequencies. SSVEPs are sinusoidal in form and the waveform represents the stimulation

1013

frequency or its harmonic frequency (with slow stimulation rates). With constant stimulus intensity for all frequencies, the SSVEP amplitude decreases with higher stimulation frequencies. Estimation of equivalent current dipoles from magnetoencephalographic steady state visual-evoked fields (SSVEFs) were localized in the posterior occipital cortex near the calcarine fissure for 6.0 and 11.9 Hz SSVEF responses (Mu¨ller, 1997). In the second experiment, readiness potentials (cf. Kornhuber and Deecke, 1965) were recorded. The readiness potential is part of the movement-related slow negativity, which occurs in the S1(warning stimulus)–S2(imperative stimulus)–R(Response) paradigm. It is mostly related to the S2-related negativity. The readiness potential (RP) consists of at least two components, an early (RP1) and a late (RP2) readiness potential. The RP1 principal generator is located in the mesial prefrontal cortex and supplementary motor area (SMA); the RP2 principal generator is the primary motor cortex (Deecke et al., 1998). The response-locked lateralized readiness potential (LRP) is a specific case of the RP2. It is computed by subtracting the ERP above the cortex ipsilateral to the side of motor response from the contralaterally recorded ERP. These difference waveforms are averaged across left hand and right hand motor-responses. The LRP is considered to represent response preparation or activation (Coles, 1989). Recently, Masaki et al. (2004) proposed that the LRP starts after the completion of response-hand selection and at the beginning of motor programming. Studying fMRI, Dehaene et al. (1998) used the time course of motor-cortex voxel activation to compute a lateralized bold response (LBR), which was higher with the certainty of the side of the required motor response. In a third experiment, the EEG theta-frequency band was studied. There is numerous published work showing that theta band activity in the human EEG is associated with working memory engagement (e.g., Gevins et al., 1997), especially over the frontal midline (Inanga, 1998). Mental arithmetic calculations are an appropriate method to induce working memory processes in order to increase EEG theta power. Klimesch et al. (2001) proposed that theta activity reflects the encoding of new information into working memory. Imaging studies on mental arithmetic tasks have described a pattern of activation, including structures of the prefrontal and the parietal cortex (Burbaud et al., 1995; Dehaene et al., 1999). In our study, frontal theta in relation to mental arithmetic was compared to a baseline task, usually showing significantly less activation in the EEG-theta frequency range. The EEG waveforms associated with the paradigms mentioned above represent a range of typical EEG characteristics. They differ in scalp-topography (occipital, central lateralized, frontal), characteristic frequency (stimulus-induced, slow potential, typical EEGfrequency band), and prominent components in the waveforms (sinusoidal oscillations, negative peak, power in frequency domain), and they represent activity in different cognitive or behavioral domains (visual perception, motor preparation, thinking). Each subject performed the three experiments twice, inside the magnet during fMRI EPI scanning and outside the MR examination room. fMRI was acquired throughout the experiments. It has been shown that MR images can be acquired during EEG without significant distortion (Krakow et al., 2000). Most of the combined EEG/fMRI studies using simultaneous recordings were focused on the detection of epileptic EEG phenomena, showing that filtering methods enable to detect many of the epileptic events in the EEG (cp. Be´nar et al., 2003). In this study, the attempt is made to detect several EEG standard waveforms, that is, event-related potentials

1014

G. Sammer et al. / NeuroImage 24 (2005) 1012–1024

and spectral compositions of the ongoing EEG, in the same subjects using subtraction-filtering techniques. Be´nar et al. (2003) pointed to the fact that feasibility reports in laboratories where the methods were developed might not fully apply to other MR sites. Particularly, specific technical equipment could limit the replication of findings. Thus, feasibility studies in different laboratories contribute to the development of generally applicable simultaneous EEG-fMRI recording and analysis protocols.

Method Subjects Twenty healthy subjects took part in the study. All were students of the University of Giessen, where the study was performed. Half of the subjects were male, and mean age was 25.4 (range 20.3–39.6 years). Subjects were paid for their participation (EUR 25, ). All subjects gave written informed consent.

Experiment III, mental arithmetic, frontal theta Subjects performed 16 mental arithmetic tasks. Each task consisted of 10 subsequently displayed numbers (range 0–20, selected by a random dput and take backT procedure), which had to be added by the subjects. Each number was presented for 500 ms. The interval between two numbers was 1500 ms, during this epoch, a fixation mark was displayed. Mental addition lasted for 20 s followed by the display of three numbers. Subjects were instructed to indicate by an appropriate button press, which of the numbers was the correct sum of the previous addition task. The display of the three numbers was terminated by the subject’s button press or after 1300 ms. For motivational reasons, within these 1300 ms, a feedback word was given for the subjects indicating if the response has been right or wrong. Usually such a task enhances theta-activity over frontal leads. For comparison reasons, eight reference trials were implemented. Instead of numbers, 10 zeros were presented during the addition period, three zeros were subsequently displayed. Timing and task were the same as for the mental arithmetic task. The numbers were different for the task repetition inside/outside the scanner.

Experiment I, steady state visual-evoked potentials Data recording: EEG Flashes were presented once at 4.7 Hz and alternatively at a rate of 18.8 Hz. The presentation rates were set to these frequencies in order to prevent interference with HF gradient artifacts in the EEG signal. Switching a black computer screen to white each 106 ms for the 4.7 Hz rate and each 26 ms for the 18.8 Hz stimulation rate produced flashes. Six 4.7 -Hz flash series and twelve 18.8 Hz series were presented in a pseudo-randomized order, identical for each subject. The inter-flash-series interval was set to 2.5 s or 4.5 s represented by a black screen. With this timing, the co-occurrence or separation of stimulation with gradient switching was controlled. Six of the twelve 18.8 Hz (=1620 ms duration each) flash-series occurred during gradient switching; the remaining six series during intermediate periods. Each 4.7 Hz flash-series lasted 6420 ms. Thus, each series covered two repetition times (TRs) of fMRI scanning. To be able to compare the EEG recorded during gradient switching to intermediately recorded EEG, the flashes 1 to 8 and the flashes 23 to 29 were presented during gradient switching, flashes 9 to 22 and 30 occurred during intermediate periods. Experiment II, lateralized readiness potential Readiness potentials were elicited by displaying an arrow (S1) pointing towards right or left. The direction of the arrow indicated which hand had to be used for the response to a forthcoming imperative stimulus (S2). The imperative stimulus was represented by an dXT, which appeared 1500 or 2000 ms after the cueing arrow on the screen. Subjects were instructed to respond quickly by pressing a button with the index finger of the required hand. In all, 160 trials had to be performed, 80 right side responses and 80 for the left hand. The S1–S2 interval was 1500 ms for one half of the trials, and 2000 ms for the remaining trials. The inter-trial interval (S1–S1) was 4611 ms. Arrows remained visible for 500 ms. The imperative stimulus remained on the screen until a button was pressed. If no button was pressed, the dXT disappeared 300 ms prior to the onset of the next trial. The sequence of right, left, 1500 and 2000 ms trials was pseudo-randomized, and the same for each subject.

The EEG-equipment, recording procedure, electrodes, electrode montage, amplifier and amplifier setting were the same inside and outside the scanner. Electrodes were not removed between the inside/outside takes. EEG was recorded from 29 electrodes (10–20 system, plus FC1, FC2, CP1, CP2, FC5, FC6, CP5, CP6, TP9, TP10 [frontocentral, centro-parietal and temporoparietal positions]). The sintered Ag/AgCl ring electrodes were attached using the dBrainCapT electrode-cap (Falk-Minow Services, Herrsching-Breitbrunn, Germany), which is part of the MRcompatible EEG recording system dBrainAmp-MRT (Brainproducts, Munich, Germany). An electrode located between Fz and Cz was used as reference electrode during recording. Electrode impedance was kept below 5 kV. In addition, vertical EOG was recorded using one channel. The remaining two channels of the 32 channel-system were used for recording the electrocardiogram (ECG) to control for heartbeat artifacts in the EEG. Within the scanner-tube, the subjects laid in supine position. A head clamp, which is part of the head coil basement, fixed the head. Via a mirror, which was attached to the head-coil, the subjects could watch a backlight screen, where the visual stimuli were projected from the back by a LCD-projector. The projector was located outside the scanner-room. Special lenses allow projecting through a wave-guide. The helium-pump of the MR scanner was switched off to prevent artifacts in the EEG due to pump-induced movements of the subjects. Outside the magnet, the session took place in the scannercontrol room. The subjects rested on a bed in supine position as they did within the scanner. Via a pillar-mounted mirror, subjects could watch a computer screen. In both situations, inside and outside the scanner, the mirror reduced the viewing angle to 188. A BrainAmp-MR 32-channel amplifier (Brainproducts) was used to amplify the EEG-signals. Sampling rate was 5 kHz. Filters were set to 0.016–250 Hz. Several triggers were recorded together with the biological signals including stimulation, responses, and the volume trigger, indicating the onset of the gradient for the first slice measurement of a volume.

G. Sammer et al. / NeuroImage 24 (2005) 1012–1024

1015

The BOLD response was measured using a 1.5 Siemens Symphony whole body scanner with Quantum gradients. Functional scans were obtained by using a single-shot T2*-weighted gradientecho planar imaging (EPI) sequence (TR = 4.5 s, TA = 81 ms, TE = 59 ms, flip angle = 908, and slice thickness = 6 mm). In-plane resolution was 3  3 mm, the acquisition matrix consisted of 64  64 pixels; consequently, the field of view was 192  192 mm; The setup kept 2880 ms windows between the acquisitions of subsequent volumes for gradient-artifact EEG recording (paused acquisition: 81 ms (TA)  20 (slices) + 2880 ms (pause) = 4500 = TR). Twenty axial slices were acquired interleaved to cover the major part of the brain. An anatomical MRI was acquired using a T1-weighted, threedimensional MPR sequence. This whole brain 3D-image was used for control of the normalizing procedure and for documentation purpose.

and the waveform represents the stimulation frequency Mqller (1997). Accordingly, the hypothesis was that the stimulation frequency or its harmonic frequency for the slow stimulation rate determined the average waveform of the SSVEP at posterior electrodes. For both occipital electrodes, O1 and O2, the amplitude spectra of the average waveforms were computed. Amplitudes and frequency indicated by the maximum peak of the entire spectrum, and the highest amplitudes within the frequency ranges of 3–6.9 Hz, 7–11.9 Hz, 12–14.9 Hz, and 15–23 Hz were written out for statistical analysis. This set of values was available for each experimental condition, that is, inside the scanner during EPI scanning and outside the MR examination room, with and without gradient switching during SSVEP recording (this was a dummy condition for EEG recorded outside the magnet). Repeated measurement analyses were computed using the factors (number of levels in brackets) electrode (2), during EPI scanning-outside the MR examination room (2), and gradient–no gradient switching (2).

Data analysis

Experiment II, lateralized readiness potential

EEG preprocessing, artifact rejection First step of EEG preprocessing was the application of the offline MRI artifact correction method, which is implemented in BrainVision software (BrainProducts). The method was described by Allen et al. (1998, 2000). The MR scanner volume-marker was used for scanner artifact detection. EEG-was averaged for an epoch of 2000 ms, starting 200 ms prior to the marker-onset and covering the time for the measurement of one entire volume, which consisted of 20 slices. The average was subtracted from the EEG. Data were low-pass filtered (cutoff at 70 Hz) and downsampled to 256 Hz. In a second step pulse artifacts were reduced in the data. A template match procedure was used, identifying pulse artifacts by the correlation between a template and one ECG channel; the template was manually selected from the data set before. Ten pulse intervals were averaged. The average was subtracted from the data, at least reducing the artifact amplitude. The time delay between pulse detection and correction in the EEG data was set to 0.21 s according to Allen et al. (2000). Next step was to re-reference the data to an average-reference and to pass the EEG through appropriate filters. Band-pass filters were 2 Hz/12 dB–12 Hz/48 dB (slow flickering) and 12 Hz/12 dB–25 Hz/48 dB (fast flickering) for experiment I (SSVEP), 0.016 Hz/12 dB–15 Hz/ 48 dB for experiment II (LRP), and 2.5 Hz/24 dB–18 Hz/48 dB for experiment III (FTh). After segmentation of the data, an ocular correction (Gratton et al., 1983; implemented in BrainVision) and blink detection were performed. Finally, the segments were visually inspected for remaining artifacts.

The lateralized readiness potential (LRP) can be computed from the late readiness potential, a late steeper negative slope, about 500 ms prior to the onset of movement. The LRP is defined as LRP = 0.5 [meanleft hand response(C4V–C3V) + meanright hand response(C3V–C4V)] (De Jong et al., 1995; Coles et al., 1988). Usually, electrodes are placed over motor cortex (M1, indicated by Vin the formula) or at C3/C4 according to the international 10–20 system. For this study, LRPs were computed from C3 and C4. The area covered by the LRP (range was from 200 ms until the motor response) was taken for statistical analysis. The same measures were computed for the fronto-central electrodes FC1 and FC2 and the centro-parietal leads CP1 and CP2. Comparisons were calculated between electrodes and recording location (during EPI scanning-outside the MR examination room).

Data recording fMRI

Averaging and statistical analysis The last step was averaging of the artifact-corrected segments in the time (exp. I, II) or frequency domain (exp. III). Averaging was performed for each experimental condition. Experiment I, steady state visual-evoked potential For each subject, EEG-epochs were averaged separately for those parts including gradient switching and the intermediate periods. The length of epochs was 1600 ms for the 4.7 Hz-series and 320 ms for the 18.8 Hz-series. SSVEPs are sinusoidal in form

Experiment III, mental arithmetic, frontal theta For the present study, the increase in frontal theta with mental arithmetic processing was of interest. The area between 3.0 and 6.5 Hz of the power-spectrum was calculated for F3, Fz, F4, and for P3, P4 as well. Repeated measurement analysis of variance was computed including the factors (level of factors in brackets) electrodes (2, without Fz), anterior–posterior electrodes (2), during EPI scanning—outside the MR examination room (2). fMRI data analysis FMRI data were analyzed using SPM2 (Wellcome Institute of Neurology at University College London, UK. http://www.fil.ion. ucl.ac.uk/spm). The first five images were discarded. Images were preprocessed including slice time correction, movement correction, normalization, and smoothing (FWHM = 8 mm). At the 1st level, general linear models were applied to the data of each subject. For experiment I (SSVEP), regressors were determined by the onset and duration of the flash-series. Because of the small number of stimuli distributed over a small number of volumes, no further conditions were included in the model. For experiment II (LRP) regressors were S1-onsets left, right, S2-onsets left, right, and onset of button presses. For experiment III (FTh), regressors were blocks of mental arithmetic performance and blocks of reference-task processing. For all experiments, the movement parameters

1016

G. Sammer et al. / NeuroImage 24 (2005) 1012–1024

computed during the realignment procedure were included in the models. The contrasts of interest were brought to the 2nd level. At the 2nd level one-sample t tests and F tests were computed. All results reported here are height thresholded at P value = 0.05, adjusted to control for the family-wise error (FWE).

Results Experiment I (SSVEP) The histograms of the maximum peak in the spectra of the SSVEP are shown in Fig. 1 for 4.7 Hz flash-stimulation and in Fig. 2 for 18.8 Hz flash-stimulation. For the 4.7-Hz flash-series, the maximum peak was either near the stimulation frequency of 4.7 Hz or at the first harmonic frequency (9.4 Hz). For the 18.8-Hz flashseries, the maximum peak always was in the corresponding frequency band. The ANOVA of the highest peak in the frequency range between 3 and 7 Hz revealed a slightly slower average frequency during EPI scanning (4.25 Hz) than outside the magnet (4.68 Hz) ( F(1,14) = 22,22, P = 0.0003). The amplitude of the corresponding frequency was smaller during EPI scanning (1.48) than outside the magnet (1.79) ( F(1,14) = 6,24, P = 0.026). Table 1 shows the peak frequencies and their amplitudes. The first harmonic frequency averaged at 9.38 Hz (SD = 0.08), showing no effects of any factors. However, the amplitude of this peak was smaller during EPI scanning (1.86) than outside the magnet (2.25)( F(1,19) = 11.05, P = 0.004). Contrary to the results for the 4.7-Hz condition, there was no difference between inside

the scanner and outside recordings with respect to the peak frequency in the 18.8 Hz data. Again, the amplitude of the frequency-peak was smaller during EPI scanning (1,36) than outside the magnet (1,61) ( F(1,8) = 6.59, P = 0.033). Table 1 shows the peak-frequencies and their amplitudes. The grand average separated for stimulation condition, recording location, and recording epoch (during gradient switching and in-between) is shown in Figs. 3 and 4. The fMRI results (Fig. 5) showed a cluster of activation in the occipital lobe. Peaks were located in the left (0, 90, 4, T = 8.00) and right (4, 74, 14, T = 11.62) calcarine sulcus and the left ( 8, 66, 2, T = 12.46) and right (12, 68, 2, T = 11.31) occipital/ lingual gyrus. Experiment II (LRP) The lateralized readiness potential clearly showed a voltage negativity prior to the button press. The LRP peaked 68 ms on the average before the motor response. The peak was negative in voltage indicating appropriate motor preparation. The waveforms C3/C4, FC1/FC2, and CP1/CP are shown in Fig. 6. The grand average shows the typical negative deflection at the central electrodes. The repeated measurement ANOVA of the area measures did not reveal a significant effect for the factor inside during EPI scanning/outside the magnet ( F(1,38) = 0.13, P = 0.71). The correlation between inside and outside the magnet recorded waveforms ( 1000 ms to motor response) was r[C3/ C4] = 0.36, r[FC1/FC2] = 0.30, and r[CP1/CP2] = 0.35 (Fisher’s Z-transformed). In Fig. 7, the waveforms are overlaid for all subjects. It can be seen that especially the potential following the

Fig. 1. Histograms of the maximum value in the amplitude spectra for the 4.7-Hz SSVEPs. (0 T) Outside the MR examination room, (1.5 T) inside the magnet during EPI scanning. The rows in the plot represent SSVEPs recorded during gradients and intermediate epochs. Exact boundaries of categories are b3, b5.9, b8.9, b11.9, b23 Hz.

G. Sammer et al. / NeuroImage 24 (2005) 1012–1024

1017

Fig. 2. Histograms of the maximum value in the amplitude-spectra for the 18.8 Hz SSVEPs. (0 T) outside the MR examination room, (1.5 T) inside the magnet during EPI scanning. The rows in the plot represent SSVEPs recorded during gradients and intermediate epochs. Exact boundaries of categories are b3, b5.9, b8.9, b11.9, b23 Hz.

contralaterally as well. Activation peaks were at right (8 20 52, F = 34.89) and left ( 6 22 50, F = 49.07) SMA. In addition the left ( 14 15 30, F = 82.94) and right (14 50 26, F = 53.76) anterior cerebellum was activated.

motor response shows greater amplitudes inside the magnet than outside. These waves are due to even slight button-press-related movements. They were not in the focus of artifact reduction for the LRP-computation and that is why they survived artifact detection procedures. Correlating the inside waveforms showing higher oscillatory amplitudes with outside less oscillating waveforms explains the relative weakness of the correlations. The fMRI data (Fig. 8) showed the expected contralateral activation in sensory and motor areas. Voxel level tests revealed peaks of activation at right (42 24 50, F = 152.49) and left ( 38 28 64, F = 85.48) postcentral gyrus. As seen in similar experiments, the supplementary motor area (SMA) was activated

Experiment III (FTh) The ANOVA showed significant main effects for mental arithmetic ( F(1,18) = 13.7, P = 0.002), electrodes ( F(4,72) = 8.3, P = 0.000), and inside/outside the scanner F(1,18) = 24.6, P = 0.000). The results reveal increased theta at all (F3, Fz, F4, P3, P4) locations and under both conditions (during EPI scanning

Table 1 Mean peak frequencies and their amplitudes (in brackets) in the SSVEP-spectra of the low stimulation frequency (4.7 Hz; search range 3 b = f b 6.9 Hz), its harmonic frequency (9.4 Hz; search range 7 b = f b 11.9 Hz), and the high stimulation frequency (18.8 Hz; search range 15 b = f b 23 Hz). N = 20 (0 T) outside the MR examination room

(1.5 T) inside MR during EPI scanning

O1

O2

O1

O2

4.7 Hz SSVEP: stimulation frequency Gradientsa 4.6 (1.85) 4.6 (1.76) Intermediatea

4.6 (1.72) 4.7 (1.84)

4.1 (1.50) 4.1 (1.49)

4.4 (1.46) 4.3 (1.47)

4.7 Hz SSVEP: harmonic frequency Gradientsa Intermediatea

9.3 (2.14) 9.4 (2.25)

9.3 (2.21) 9.4 (2.38)

9.3 (1.81) 9.3 (2.06)

9.5 (1.61) 9.4 (1.93)

18.8 Hz SSVEP: stimulation frequency Gradientsa 18.1 (1.58) Intermediatea 18.8 (1.43)

18.6 (1.88) 18.8 (1.53)

18.4 (1.49) 18.5 (1.25)

18.8 (1.46) 18.6 (1.21)

a

For comparison reasons, gradient and intermediate epochs under the 0 T condition refer to the homologous epochs of the scans under the 1.5 T condition.

1018

G. Sammer et al. / NeuroImage 24 (2005) 1012–1024

Fig. 3. Grand average for 4.7 Hz flash-sequences. Column (0 T) consists of potentials recorded outside the MR examination room, (1.5 T) shows potentials recorded inside the magnet during EPI scanning. In plots (i) and (v) SSVEPs at each electrode were superimposed. Waveforms show SSVEPs derived from gradient* epochs. Analogously, (ii) and (vv) display the waveforms extracted from intermediate* epochs. The grand averages for O1 and O2 are displayed separately; gradient* epochs and intermediate* epochs are superimposed. In each plot, pairs of vertical dotted lines mark the exact duration of a single 4.7-Hz period (=212 ms). (*) For comparison reasons, gradient and intermediate epochs under the 0 T condition refer to the homologous epochs of the scans under the 1.5 T condition.

and outside the MR examination room) for the mental arithmetic performance. While subjects performed the mental arithmetic task, the spectral power in the theta frequency band was enhanced compared to performing the reference-baseline task. In addition, a decrease in power in the slow alpha band could be seen during mental arithmetic. The effects of electrodes and the factor inside/outside are due to differences in overall amplitude. Never effects between the mental task and reference task were concerned by those general differences (no interaction of factors). There was more power in the EEG-theta band at frontal electrodes (F3, F4) compared to the parietal electrodes (P3, P4). Theta power was increased inside the magnet during EPI scanning at these four electrodes (F3, F4, P3, P4). However, no difference was found for the frontal midline EEG at Fz. The power spectra are displayed in Figs. 9 and 10. The fMRI analysis (Fig. 11) revealed a set of activated structures. The activation-pattern included left ( 32, 58, 50, T = 11.74) and right (40, 42, 42, T = 9.72) inferior parietal, left frontal superior ( 18, 0, 56, T = 18.52), left inferior frontal ( 30, 10, 26, T = 9.64), left thalamus ( 12, 10, 12, T = 10.08), right

angular gyrus/intraparietal sulcus (34, 62, 46, T = 9.26), right midfrontal (34, 36, 22, T = 8.62), and the left ( 6, 10, 48, T = 7.74) SMA. This activation pattern was in high correlation with the results reported by Menon et al. (2000) investigating a similar task.

Discussion Recording EEG during EPI scanning is still in its early stage. Distortions of the EEG by MR gradients and cardioballistic artifacts can be reduced markedly, as it recently has been shown mostly with epileptiform EEG. However, it remained unclear if any of the proposed artifact reduction methods can be used in a generalized manner: for the investigation of event-related potentials and EEG-frequency-spectra, or to study EEG recorded during motor, visual, or cognitive tasks. The aim of the study was to investigate if several typical standard EEG waveforms can be derived from EEG recorded during functional MR-EPI scanning by artifact subtraction. It was investigated whether artifact subtraction can preserve multiple typical characteristics of the EEG (SSVEP,

G. Sammer et al. / NeuroImage 24 (2005) 1012–1024

1019

Fig. 4. Grand average for 18.8 Hz flash-sequences. Column (0 T) consists of potentials recorded outside the MR examination room, (1.5 T) shows potentials recorded inside the magnet during EPI scanning. In plots (i) and (v), SSVEPs at each electrode were superimposed. Waveforms show SSVEPs derived from gradient* epochs. Analogously, (ii) and (vv) display the waveforms extracted from intermediate* epochs. The grand averages for O1 and O2 are displayed separately; gradient* epochs and intermediate* epochs are superimposed. In each plot, pairs of vertical dotted lines mark the exact duration of a single 18.8 Hz period (=53 ms). (*) For comparison reasons, gradient and intermediate epochs under the 0 T condition refer to the homologous epochs of the scans under the 1.5 T condition.

LRP, and enhancement of frontal theta by mental arithmetic). Recent studies showed that the removal of imaging and pulse artifacts by subtraction was applicable for epileptiform discharges (Allen et al., 2000), and alpha-EEG (Laufs et al., 2003). Motion inside a magnetic field is a serious source of EEG distortion (Allen et al., 1998; Bonmassar et al., 2002). Particularly, ballistocardiac movements of the head, which hardly can be avoided, distort the EEG not only in the heartbeat frequency but in several other frequencies depending on multiple factors, for example, the shape of the pulse-artifact and of the electrode wiring within the scannertube. Be´nar et al. (2003) found that the immobilization of the patient’s head and electric wires by using a vacuum pillow works well to avoid serious movement artifacts. However, comparing different methods (ICA, PCA, no correction), they concluded that removing the ballistocardiographic artifacts was not absolutely necessary to identify epileptic events. However, the potentials of

event-related potentials and the amplitudes of ongoing EEG usually are much smaller than epileptiform discharges in the EEG. Thus, in the present study, an algorithm based on the method described by Allen et al. (1998) was applied for a subtraction of pulse artifacts. EEG war acquired during gradient switching as well as during intermediate periods between recordings of MR-volumes. The implementation of rapid flash series in combination with fMRIblock design allowed the comparison of gradient switching and intermediate periods during EPI scanning in experiment 1 (SSVEP). For the lateralized readiness potential and the mental arithmetic task, the underlying EEG epochs were an approximately balanced mix of gradient switching and intermediate periods. Changing the ratio of the epochs with and without gradient switching requires a large number of trials for averaging. In order to keep the MR scanning time within limits, such an approach was

1020

G. Sammer et al. / NeuroImage 24 (2005) 1012–1024

Fig. 5. Glass brain containing the SPM for the flash stimulation. 4.7 Hz and 18.8 Hz conditions were combined into a single regressor. Results are controlled for family-wise error (FWE) at P = 0.05. Activation was in the calcarine sulcus and the occipital/lingual gyrus.

discarded from the study. In all experiments, EEG recorded inside the magnet during EPI scanning was compared to EEG recorded outside the MR examination room. Each subject performed all task twice inside and outside the magnet. The steady state visual-evoked potential (SSVEP) was selected for investigation, because it consists of a clear frequency-structure and occipital topography. Beside epileptiform discharges, VEPs are the most frequently and successfully measured potential in the magnetic field of a MR scanner. An advantage of the SSVEP is that its power is concentrated almost exclusively at the stimulation frequency and its harmonics (Regan, 1989). Accordingly, the SSVEPs in our study consisted of the stimulation frequency in both stimulation conditions. As usually can be observed for slow frequency 4.7 Hz stimulation, the harmonic frequency (9.4 Hz) was a pronounced component in the signal. The fMRI results showed a cluster of activation in the occipital lobe with peaks located bilaterally in the calcarine sulcus and the occipital gyrus/lingual gyrus. This activation is in correspondence with magnetoencephalographic (MEG) findings of Mu¨ller (1997). He found correspondingly located current dipoles (ECDs) of the steady state visualevoked fields near the calcarine sulcus for 6 and 11.9 Hz flickering stimulation and in the lingual gyrus for 15.2 Hz flickering stimulation. Readiness potentials were included in our study for two reasons; the late component of the readiness potential is clearly lateralized and is strictly localized at specific electrodes. In addition, it is a small component usually not crossing 1.5–2 microvolts. Artifact subtraction has to prove its effectiveness on heavily corrupted EEG, as with gradients and pulse artifacts in the MR scanner, in order to extract such small deflections in the ERP. The lateralized readiness potential (LRP) reflects the differential engagement of the two hands. Preparation processes and response activation are indicated by the LRP. In this study, the LRP could easily be identified in the response-locked event-related potential. The LRPs did not differ between recordings during EPI scanning and outside the MR examination room. However, the inside/ outside correlation (r = 0.36) was not convincing. The attenuation of this correlation was probably caused by oscillations in the waveforms, which were not seen in the outside-recorded potentials. The source of these oscillations is unclear. They could be related to tiny movements during motor preparation. However, the movement parameters computed for the realignment of the functional MR-images did not reveal significant task correlated movements. Probably, MR-movement parameters are too coarse grained for the detection of movement artifacts in the EEG-time scale. The BOLD response was modeled on the cue-onsets (arrows). Due to the slowly changing BOLD signal and the

relatively short S1–S2 response duration of less 3 s, there was no difference between S1-locked, or response-locked regressor modeling. The corresponding statistical parametric map (SPM) showed the usually obtained result; strong motor cortex activation contralateral to the moved hand, and activation of the corresponding supplementary motor area (SMA). The same activation pattern was reported by Dehaene et al. (1998) in their investigation of overt motor responses. EEG-theta activity was chosen for the third experiment in this study. Contrary to the SSVEP, the frequency in the signal does not depend from stimulation frequency but it is generated as a result of cognitive processing. To our knowledge, theta-band activity has not previously been recorded in the MR scanner. There is good evidence that working memory processes enhance EEG-theta activity, at least over anterior areas of the brain. Mental arithmetic was used to induce working memory processes in the present study. Analysis of the EEG power-spectra revealed the expected increase in the theta frequency range compared to the reference task. This theta increase was evident for both frontal and parietal sites. Mental arithmetic performance has repeatedly been shown to

Fig. 6. Grand average of the lateralized readiness potential (LRP). Potentials are displayed for electrode pairs C3/C4, FC1/FC2, and CP1/ CP2. Solid lines represent LRPs measured inside the magnet during EPI scanning, dashed lines show LRPs recorded outside the MR examination room. The motor response (MR) and the peak of the LRP are indicated by a vertical lines.

G. Sammer et al. / NeuroImage 24 (2005) 1012–1024

1021

Fig. 7. The LRP average waveforms were superimposed for all subjects. Columns represent LRP recordings outside the MR examination room (0 T) and inside the magnet during EPI scanning (1.5 T). Rows contains the waveforms for the electrode pairs C3/C4, FC1/FC2, and CP1/CP2. The motor response (MR) is indicated by a vertical line.

involve parietal brain activity as well (Menon et al., 2000). Effects in the EEG-alpha band were not under consideration in this study. However, a decrease in the slow alpha-band with mental addition can also be seen in the spectra, even though not tested for statistical significance. There was no difference between recordings inside during EPI scanning and outside the MR examination room in relation to mental arithmetic processing. The fMRI activations pattern is nearly identical with the results described by Menon et al. (2000) with 3-operand mathematical processing, that is, subjects were presented 3-operand additions or subtractions and they had to judge if the displayed result was correct or not. In summary, all standard waveforms investigated in this study could be recorded inside the magnet during echo-planar-imaging. The effects of interest (i.e., frequency and amplitude of the SSVEP at occipital electrodes, latency, and amplitude of the LRP at central electrodes, increased theta power for mental addition compared to the reference task over frontal and parietal areas) did not differ from outside the MR examination room recorded

waveforms. The characteristic waveforms in EEG recorded during interleaved EPI scanning were preserved by the application of artifact subtraction techniques. As a result, all main

Fig. 8. Glass brain visualization of the SPM for the S1–S2 interval, between cue (arrow) and imperative stimulus (dXT). Values shown are controlled for family-wise error (FWE) at P = 0.05. Spots of activation were in the postcentral gyri and the SMA, contralaterally to the side of required response.

1022

G. Sammer et al. / NeuroImage 24 (2005) 1012–1024

Fig. 9. Outside the MR examination room (0 T): power-spectra showing the theta increase during mental addition (solid lines) at three frontal (F3, Fz, F4) and two parietal (P3, P4) electrodes. Spectra representing the reference task are displayed as dash-dot lines. The difference (mental addition) (reference task) is plotted below the spectra. The range of the EEG-theta band (3.5–7.5 Hz) is indicated by vertical dotted lines.

Fig. 10. Inside the magnet during EPI scanning (1.5 T): power-spectra showing the theta increase during mental addition (solid lines) at three frontal (F3, Fz, F4) and two parietal (P3, P4) electrodes. Spectra representing the reference task are displayed as dash-dot lines. The difference (mental addition) (reference task) is plotted below the spectra. The range of the EEG-theta band (3.5–7.5 Hz) is indicated by vertical dotted lines.

G. Sammer et al. / NeuroImage 24 (2005) 1012–1024

Fig. 11. Glass brain showing the fMRI-brain activation for the mental addition task compared to a reference task. Values shown are controlled for family-wise error (FWE) at P = 0.05. The SPM revealed activated voxels bilaterally inferior parietal, left frontal superior, left frontal inferior, left thalamus, right angular gyrus/intraparietal sulcus, right midfrontal, and the left SMA.

hypotheses concerning the expected EEG-parameters were corroborated. In addition, we unexpectedly observed two kinds of EEG amplitude differences between EPI scanning and outside recordings. (1) Amplitudes were smaller during EPI scanning: in experiment 1 (SSVEP) during scanning, the peaks in the magnitude-spectra of the SSVEPs at the occipital electrodes of interest were slightly smaller for 4.7 and 18.8 Hz but not for 9.4 Hz. The small difference cannot easily be detected by visual inspection of the averaged SSVEP waveforms in Figs. 3 and 4. It is likely that (gradient, ballistocardiographic) artifacts caused small distortions of the periodical behavior of the SSVEP in the scanner, stealing some of the magnitude of the targeted peak and shifting the frequency of that peak to a slightly slower value than the stimulation frequency. (2) Amplitudes were larger during EPI scanning: In experiment 3 (FTh), the power in the frequency-band from 3.0 to 6.5 Hz was increased for EEG during EPI scanning at rather lateral electrodes (F3, F4, P3, P4) but not for the frontal midline lead. Similar effects can be seen in the plots overlaid for each subject for the SSVEPs (Figs. 3 and 4, v and vv vs. i and ii) and for the LRPs (Fig. 7). At these electrodes, the waveforms had bigger amplitudes inside the scanner during EPI scanning than outside. Recently, amplitude-related effects were found by others. Laufs et al. (2003) reported in all of the 10 subjects of their study slightly reduced amplitudes in the alpha-band for artifact-reduced gradientswitching epochs (8.2514 vs. 8.7260 AV2; similar variance). The authors attributed this difference to an attenuation of the signal due to the application of the artifact subtraction method and filtering. For this reason, the BrainVision-Analyzer software offers a recalibration of the concerned signal. The variance of the signal of gradient-switching periods is adjusted to the variance of the intermediate periods. It is questionable if the procedure takes the intended effect; changes in amplitude are not necessarily related to artifacts in the EEG but they can be caused by processing-specific changes in EEG amplitude. Laufs et al. (2003) did not give a note on the usage of recalibration. We decided to recalibrate the data because we analyzed epochs that covered both gradient-switching and intermediate periods. Hence, it remains difficult to explain those non-specific differences in amplitude between inside and outside recordings. The sequence of sessions outside the magnet and inside the magnet was balanced over subjects. So far, changes in electrode skin conductance cannot account for the inside–outside effect. On the one hand, in experiment 1 (SSVEP), the magnitude in the frequency of interest was smaller during EPI scanning, which

1023

supports the attenuation by artifact-subtraction hypothesis (ignoring recalibration by the way). On the other hand, the amplitudes of the averaged potentials in the time domain (SSVEP, LRP) show clearly higher amplitudes inside the magnet. Similarly, the power in the lower frequency range of experiment 3 (mental arithmetic task) is enhanced inside the magnet compared to outside. Noticeably, only more lateral electrodes (right or left from the midline) show this enhanced amplitudes. Therefore, it is not likely that gradient artifacts caused these oscillations. It has to be figured out, if tiny muscular artifacts, for example, caused by tiny jaw movements, or the orientation of the electrodes relative to the direction of the magnetic field, or simply insufficient removal of the cardiballistic artifact are associated with those undesired portions of the signals.

Conclusion This is the first time that several typical EEG-characteristics were studied under the condition of simultaneous functional MRImaging. It could be demonstrated that the correction by subtraction of gradient artifacts and cardioballistic distortions of the EEG, uniformly applied in all three experiments, preserved the typical characteristics of standard EEG waveforms. EEG waveforms could be extracted irrespective of topography and frequencycomposition. For effects of interest, neither significant differences were found between gradient-switching and intermediate epochs, nor for inside during EPI scanning/outside the MR examination room comparisons. However, non-specific EEG-amplitude differences were found in inside/outside comparisons, which were not in any interaction with the effects of interest. That effects require further explanation. The high correlation of activation patterns with published results demonstrates that EPI-images can be acquired during EEG recording without significant distortion.

References Allen, P.J., Polizzi, G., Krakow, K., Fish, D.R., Lemieux, L., 1998. Identification of EEG events in the MR scanner: the problem of pulse artifact and a method for its subtraction. NeuroImage 8, 229 – 239. Allen, P.J., Josephs, O., Turner, R., 2000. A method for removing imaging artifact from continuous EEG recorded during functional MRI. NeuroImage 12, 230 – 239. Anami, K., Mori, T., Tanaka, F., Kawagoe, Y., Okamoto, J., Yarita, M., Ohnishi, T., Yumoto, M., Matsuda, H., Saitoh, O., 2003. Stepping stone sampling for retrieving artifact-free electroencephalogram during functional magnetic resonance imaging. NeuroImage 19, 281 – 295. Babiloni, F., Babiloni, C., Carducci, F., Romani, G.L., Rossini, P.M., Angelone, L.M., Cincotti, F., 2003. Multimodal integration of highresolution EEG and functional magnetic resonance imaging data: a simulation study. NeuroImage 19, 1 – 15. Be´nar, Ch.-G., Aghakhani, Y., Wang, Y., Izenberg, A., Al-Asmi, A., Dubeau, F., Gotman, J., 2003. Quality of EEG in simultaneous EEGfMRI for epilepsy. Clin. Neurophysiol. 114, 569 – 580. Bonmassar, G., Schwartz, D.P., Liu, A.K., Kwong, K.K., Dale, A.M., Belliveau, J.W., 2001. Spatiotemporal brain imaging of visual-evoked activity using interleaved EEG and fMRI recordings. NeuroImage 13, 1035 – 1043. Bonmassar, G., Purdon, P.L., J77skel7inen, I.P., Chiappa, K., Solo, V., Brown, E.N., Belliveau, J.W., 2002. Motion and ballistocardiogram artifact removal for interleaved recording of EEG and EPs during MRI. NeuroImage 16, 1127 – 1141.

1024

G. Sammer et al. / NeuroImage 24 (2005) 1012–1024

Burbaud, P., Degreze, P., Lafon, P., Franconi, J.M., Bouligand, B., Bioulac, B., Caille, J.M., Allard, M., 1995. Lateralization of prefrontal activation during internal mental calculation: a functional magnetic resonance imaging study. J. Neurophysiol. 74, 2194 – 2200. Coles, M.G.H., 1989. Modern mind-brain reading: psychophysiology, physiology, and cognition. Psychophysiology 26, 251 – 269. Coles, M.G., Gratton, G., Donchin, E., 1988. Detecting early communication: using measures of movement-related potentials to illuminate human information processing. Biol. Psychol. 26, 69 – 89. De Jong, R., Coles, M.G., Logan, G.D., 1995. Strategies and mechanisms in nonselective and selective inhibitory motor control. J. Exp. Psychol. Hum. Percept. Perform. 21, 498 – 511. Deecke, L., Lang, W., Beisteiner, R., Uhl, T., Lindinger, G., Cui, R.Q., 1998. Experiments in movement using DC-EEG, MEG, SPECT and FMRI. Proceedings of the international symposium on brain mapping, Oiso/Japan, 13–15 September. Current Progress in Functional Brain Mapping—Science and Applications. Smith-Gordon and Co., London, pp. 53 – 60. Dehaene, S., Naccache, L., Le Clec’H, G., Koechlin, E., Mueller, M., Dehaene-Lambertz, G., van de Moortele, P.F., Le Bihan, D., 1998. Imaging unconscious semantic priming. Lett. from Nature 395, 597 – 600. Dehaene, E., Spelke, P., Pinel, R., Stanescu, S., Tsivkin, S., 1999. Sources of mathematical thinking: behavioral and brain-imaging evidence. Science 284, 970 – 974. Gevins, A., Smith, M.E., McEvoy, L., Yu, D., 1997. High-resolution EEG mapping of cortical activation related to working memory: effects of task difficulty, type of processing, and practice. Cereb. Cortex 7, 364 – 385. Goldman, R.I., Stern, J.M., Engel Jr., J., Cohen, M., 2000. Acquiring simultaneous EEG and functional MRI. Clin. Neurophysiol. 111, 1974 – 1980. Goldman, R.I., Stern, J.M., Engel Jr., J., Cohen, M.S., 2002. Simultaneous EEG and fMRI of the alpha rhythm. NeuroReport 13, 2487 – 2492. Gratton, G., Coles, M.G.H., Donchin, E., 1983. A new method for off-line removal of ocular artifact. Electroencephalogr. Clin. Neurophysiol. 55, 468 – 484. Hoffmann, A., J7ger, L., Werhahn, K.J., Jaschke, M., Noachtar, S., Reiser, M., 2000. Electroencephalography during functional echo-planar imaging: detection of epileptic spikes using post-processing methods. Magn. Reson. Med. 44, 791 – 798. Inanga, K., 1998. Frontal midline theta rhythm and mental activity. Psychiatry Clin. Neurosci. 52, 555 – 566. Klimesch, W., Doppelmayr, M., Wimmer, H., Schwaiger, J., Rohm, D., Gruber, W., Hutzler, F., 2001. Theta band power changes in normal and dyslexic children. Clin. Neurophysiol. 112, 1174 – 1185. Kornhuber, H.H., Deecke, L., 1965. Hirnpotential7nderungen bei Willkqrbewegungen und passiven Bewegungen des Menschen-Bereitschaft-

spotentiale und reafferente Potentiale (Brain-potential changes associated with voluntary and passive movements in humans: the Bereitschaftspotential and reafferent potentials). Pflqgers Arch. Gesamte Physiol. 284, 1 – 17. Krakow, K., Allen, P.J., Symms, M.R., Lemieux, L., Josephs, O., Fish, D.R., 2000. EEG recording during fMRI experiments: image quality. Hum. Brain Mapp. 10, 10 – 15. Kruggel, F., Wiggins, C.J., Hermann, C.S., von Cramon, D.Y., 2000. Recording of the event-related potentials during functional MRI at 3.0 Tesla field strength. Magn. Reson. Med. 44, 277 – 282. Kruggel, F., Herrmann, C.S., Wiggins, C.J., von Cramon, D.Y., 2002. Hemodynamic and electroencephalographic responses to illusory figures: recording of the evoked potentials during functional MRI. NeuroImage 14, 1327 – 1336. Laufs, H., Kleinschmidt, A., Beyerle, A., Eger, E., Salek-Haddadi, A., Preibisch, C., Krakow, K., 2003. EEG-correlated fMRI of human alpha activity. NeuroImage 19, 1463 – 1476. Lazeyras, F., Zimine, I., Blanke, O., Perrig, S.H., Seeck, M., 2002. Functional MRI with simultaneous EEG recording: feasibility and application to motor and visual activation. J. Magn. Reson. Imaging 13, 943 – 948. Lemieux, L., Salek-Haddadi, A., Josephs, O., Allen, P., Toms, N., Scott, C., Krakow, K., Turner, R., Fish, D.R., 2001. Event-related fMRI with simultaneous and continuous EEG: description of the method and initial case report. NeuroImage 14, 780 – 787. Masaki, H., Wild-Wall, N., Sangals, J., Sommer, W., 2004. The functional locus of the lateralized readiness potential. Psychophysiology 41, 220 – 230. Menon, V., Rivera, S.M., White, C.D., Glover, G.H., Reiss, A.L., 2000. Dissociating prefrontal and parietal cortex activation during arithmetic processing. NeuroImage 12, 357 – 365. Mqller, M.M., 1997. Oscillatory cortical activities in the human brain. Habilitation, University of Konstanz. Electronic publication, University of Konstanz, http://www.ub.uni-konstanz.de/kops/volltexte/2000/376/. Regan, D., 1989. Human Brain Electrophysiology: Evoked Potentials and Evoked Magnetic Fields in Science and Medicine. Elsevier, New York. Salek-Haddadi, A., Lemieux, L., Fish, D.R., 2002. Role of functional magnetic resonance imaging in the evaluation of patients with malformations caused by cortical development. Neurosurg. Clin. N. Am. 13, 63 – 69 (viii). Salek-Haddadi, A., Lemieux, L., Merschhemke, M., Diehl, B., Allen, P.J., Fish, D.R., 2003a. EEG quality during simultaneous functional MRI of interictal epileptiform discharges. Magn. Reson. Imaging 21, 1159 – 1166. Salek-Haddadi, A., Friston, K.J., Lemieux, L., Fish, D.R., 2003b. Studying spontaneous EEG activity with fMRI. Brain Res. Rev. 43, 110 – 133. Wendt, R.E., Rokey, R., Vick, G.W., Johnston, D.L., 1988. Electrocardiographic gating and monitoring in NMR imaging. Magn. Reson. Imaging 6, 89 – 95.