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Abstract #0145

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

SUMMA25Muhammad E.H. Chowdhury1, Karen J. Mullinger1, Richard W. Bowtell1

1SPMMRC, School of Physics and Astronomy, University of Nottingham, Nottingham, Nottinghamshire, United Kingdom

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.