Best practice EEG-MRI: The utility of retrospective synchronization and PCA for the removal of gradient artefacts

INTRODUCTION The EEG recorded during MRI inside the scanner is obstructed by the all but inevitable MRI gradient artefact (MGA) originating from the electromagnetic interference of the two measurements. Post-processing algorithms based on average artefact subtraction (AAS) have proven to be instrumental and efficient in removing the MGA [1-3]. However, the residual MGA after AAS still limits the quality and usable bandwidth of the EEG data despite further reduction through slice timing correction (STC), principal component analysis (PCA), and adaptive noise cancellation (ANC). We recently demonstrated that the residual MGA can largely be avoided by means of hardware synchronisation, which ensures that the TR of the MRI sequence matches exactly a multiple of the EEG sampling interval [4]. Here we present a new software synchronisation method, which substitutes hardware synchronisation and makes post-processing beyond AAS dispensable. The effectiveness of the retrospective synchronisation algorithm (Resync) is demonstrated by comparison to some of the aforementioned techniques. For this purpose we also developed a method for simulating the MGA and we propose new concepts for quantifying and comparing the performance of post-processing algorithms for EEG-MRI data.