Glyn S. Spencer1, Karen J. Mullinger1, Andrew Peters1, Richard Bowtell1
1SPMMRC, School of Physics and Astronomy, University of Nottingham, Nottingham, Nottinghamshire, United Kingdom
The EEG gradient artefact (GA) is formed from a linear superposition of individual artefacts generated by the orthogonal gradients. Variations in position of the head and/or EEG leads scale the relative weighting of the artefact contribution from the different gradient channels. Here we verify this concept and use it to introduce a novel GA correction method, which is based on a gradient model fit (GMF). Our results show that GMF performs better than conventional GA correction methods at high frequency when subject movement occurs, potentially providing a more robust method for GA correction when investigating gamma (30-150Hz) frequency neuronal activity.