Reference Layer Artefact Subtraction (RLAS): A Novel Method of Minimizing EEG Artefacts During Simultaneous fMRI.

Muhammad E.H. Chowdhury¹, Karen J. Mullinger¹, Richard W. Bowtell¹

Large artefacts due to switched gradients, cardiac pulsation and head movement compromise EEG data quality during simultaneous EEG-fMRI. Artefacts are often corrected using average artefact subtraction (AAS), but small movements significantly hinder the performance of AAS. Here we attenuate the artefacts by subtracting the signal from a reference layer, which has a similar conductivity to tissue and carries a set of electrodes and leads that precisely overlay those attached to the scalp. In experiments on a phantom and human subject undergoing small movements, we demonstrate that Reference Layer Artefact Subtraction (RLAS) outperforms AAS in reduction of gradient and movement artefacts.