Investigating the effect of modifying the EEG cap lead configuration on the gradient artifact in simultaneous EEG-fMRI

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.

[1]  Masato Yumoto,et al.  Stepping stone sampling for retrieving artifact-free electroencephalogram during functional magnetic resonance imaging , 2003, NeuroImage.

[2]  Tobias U. Hauser,et al.  The feedback-related negativity (FRN) revisited: New insights into the localization, meaning and network organization , 2014, NeuroImage.

[3]  Tom Eichele,et al.  Removal of MRI Artifacts from EEG Recordings , 2010 .

[4]  Stephen D. Mayhew,et al.  Spontaneous EEG alpha oscillation interacts with positive and negative BOLD responses in the visual–auditory cortices and default-mode network , 2013, NeuroImage.

[5]  Gabriel Curio,et al.  Ultrahigh-frequency EEG during fMRI: Pushing the limits of imaging-artifact correction , 2009, NeuroImage.

[6]  Richard Bowtell,et al.  Best current practice for obtaining high quality EEG data during simultaneous FMRI. , 2013, Journal of visualized experiments : JoVE.

[7]  Arno Villringer,et al.  Visual evoked potentials recovered from fMRI scan periods , 2005, Human brain mapping.

[8]  Karen J. Mullinger,et al.  Identifying the sources of the pulse artefact in EEG recordings made inside an MR scanner , 2013, NeuroImage.

[9]  Karen J. Mullinger,et al.  Reducing the gradient artefact in simultaneous EEG-fMRI by adjusting the subject's axial position , 2011, NeuroImage.

[10]  Nadim Joni Shah,et al.  Attention to Detail: Why Considering Task Demands Is Essential for Single-Trial Analysis of BOLD Correlates of the Visual P1 and N1 , 2014, Journal of Cognitive Neuroscience.

[11]  S. Debener,et al.  Properties of the ballistocardiogram artefact as revealed by EEG recordings at 1.5, 3 and 7 T static magnetic field strength. , 2008, International journal of psychophysiology : official journal of the International Organization of Psychophysiology.

[12]  Richard Bowtell,et al.  Simultaneous EEG–fMRI: evaluating the effect of the cabling configuration on the gradient artefact , 2015, Physics in medicine and biology.

[13]  Daniel Brandeis,et al.  Synchronization facilitates removal of MRI artefacts from concurrent EEG recordings and increases usable bandwidth , 2006, NeuroImage.

[14]  Juliana Yordanova,et al.  Simultaneous EEG and fMRI Reveals a Causally Connected Subcortical-Cortical Network during Reward Anticipation , 2013, The Journal of Neuroscience.

[15]  Matthew J. Brookes,et al.  Understanding gradient artefacts in simultaneous EEG/fMRI , 2009, NeuroImage.

[16]  P. Sajda,et al.  Simultaneous EEG-fMRI Reveals Temporal Evolution of Coupling between Supramodal Cortical Attention Networks and the Brainstem , 2013, The Journal of Neuroscience.

[17]  M. Roth,et al.  Single‐trial analysis of oddball event‐related potentials in simultaneous EEG‐fMRI , 2007, Human brain mapping.

[18]  Kenneth Hugdahl,et al.  Realignment parameter-informed artefact correction for simultaneous EEG–fMRI recordings , 2009, NeuroImage.

[19]  S. Francis,et al.  Theta power during encoding predicts subsequent‐memory performance and default mode network deactivation , 2013, Human brain mapping.

[20]  Karen J Mullinger,et al.  Improved artifact correction for combined electroencephalography/functional MRI by means of synchronization and use of vectorcardiogram recordings , 2008, Journal of magnetic resonance imaging : JMRI.

[21]  EEG signatures of auditory activity correlate with simultaneously recorded fMRI responses in humans , 2010, NeuroImage.

[22]  Stephen D. Mayhew,et al.  Poststimulus undershoots in cerebral blood flow and BOLD fMRI responses are modulated by poststimulus neuronal activity , 2013, Proceedings of the National Academy of Sciences.

[23]  Robert Turner,et al.  A Method for Removing Imaging Artifact from Continuous EEG Recorded during Functional MRI , 2000, NeuroImage.

[24]  Winston X. Yan,et al.  Physical modeling of pulse artefact sources in simultaneous EEG/fMRI , 2009, Human brain mapping.

[25]  Catie Chang,et al.  Development, validation, and comparison of ICA-based gradient artifact reduction algorithms for simultaneous EEG-spiral in/out and echo-planar fMRI recordings , 2009, NeuroImage.

[26]  Karen J. Mullinger,et al.  A novel method of minimizing EEG artefacts during simultaneous fMRI: a simulation study , 2013 .