Abstract #3664

Best Practice EEG-MRI: The Utility of Retrospective Synchronization and PCA for the Removal of Gradient Artefacts.

Hendrik Mandelkow¹, Daniel Brandeis², Peter Boesiger¹

¹Inst. for Biomedical Engineering, ETH Zurich, Zurich, Switzerland; ²2) Dept. of Child and Adolescent Psychiatry, University of Zurich, Zurich, Switzerland

We present a new software synchronization method for removing the notorious MRI gradient artefact (MGA) from EEG data recorded during MRI. Furthermore, we propose new methods for quantifying and comparing the performance of different post-processing algorithms for EEG-fMRI data. Comparisons based on in-vivo data as well as simulations of the MGA show that the retrospective synchronisation algorithm can substitute hardware synchronisation as well as other post-processing methods such as slice timing correction and PCA. This insight points toward an optimal recording and post-processing strategy for EEG-fMRI experiments.