Abstract
EEG data recorded during simultaneous fMRI are contaminated by large voltages generated by time-varying magnetic field gradients. Correction of the resulting gradient artifact (GA) generally involves low-pass filtering to attenuate the high-frequency voltage fluctuations of the GA, followed by subtraction of a GA template produced by averaging over repeats of the artifact waveforms. This average artifact subtraction (AAS) process relies on the EEG amplifier having a large enough dynamic range to characterize the artifact voltages and on invariance of the artifact waveform over repeated image acquisitions. Saturation of the amplifiers and changes in subject position can leave unwanted residual GA after AAS. Previous modeling work suggested that modifying the lead layout and the exit position of the cable bundle on the EEG cap could reduce the GA amplitude. Here, we used simulations and experiments to evaluate the effect of modifying the lead paths on the magnitude of the GA and on the residual artifact after AAS. The modeling work showed that for wire paths following great circles, the smallest overall GA occurs when the leads converge at electrode Cz. The performance of this new cap design was compared with a standard cap in experiments on a spherical agar phantom and human subjects. Using gradient pulses applied separately along the three Cartesian axes, we found that the GA due to the foot-head gradient was most significantly reduced relative to a standard cap for the phantom, whereas the anterior-posterior GA was most attenuated for human subjects. In addition, there was an overall 37% reduction in the RMS GA amplitude produced by a standard EPI sequence when comparing the two caps on the phantom. In contrast, the subjects showed an 11% increase in the average RMS of the GA. This work shows that the optimal design reduces the GA on a spherical phantom however; these gains are not translated to human subjects, probably due to the differences in geometry.
Highlights
Electroencephalography (EEG) data recorded simultaneously with functional Magnetic Resonance Imaging acquisition is becoming a widely used technique for studying brain function (e.g., Mayhew et al, 2013; Mullinger et al, 2013c; Walz et al, 2013; Warbrick et al, 2014)
SIMULATION Figure 3 shows that changing the lead paths by moving the cable bundle position along the midline produces a decrease in the range of the gradient artifact (GA) for the FH gradient, but little change for the RL
We show that for the FH gradient, varying the lead paths and the convergence point of the cable bundle reduces the amplitude of the induced artifact, and changes the spatial pattern to give an anterior-posterior (Figure 4C) rather than right-left (Figures 4A,B) GA pattern of variation
Summary
Electroencephalography (EEG) data recorded simultaneously with functional Magnetic Resonance Imaging (fMRI) acquisition is becoming a widely used technique for studying brain function (e.g., Mayhew et al, 2013; Mullinger et al, 2013c; Walz et al, 2013; Warbrick et al, 2014). Combined EEG-fMRI opens up opportunities for developing a better understanding of brain function and of the origin of the haemodynamic signals measured in fMRI The promise of this technique, combined with the commercial availability of MR-compatible EEG systems, means that simultaneous EEG-fMRI is being used by neuroscientists in answering numerous research questions (e.g., Plichta et al, 2013; Walz et al, 2013; White et al, 2013; Hauser et al, 2014). The other dominant artifacts are the pulse artifact, linked to the subject’s cardiac cycle (Debener et al, 2008; Mullinger et al, 2013b), and motion artifacts, caused by movement of the EEG equipment in the MR scanner due to subject motion or vibration (Eichele et al, 2010) These artifacts severely corrupt the EEG data and without post-processing methods render it impossible to investigate the neuronal EEG signals of interest. Correction of EEG artifacts is essential when combining EEG and fMRI data which have been acquired simultaneously
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