UCL Discovery
UCL home » Library Services » Electronic resources » UCL Discovery

Modelling optically pumped magnetometer interference in MEG as a spatially homogeneous magnetic field

Tierney, TM; Alexander, N; Mellor, S; Holmes, N; Seymour, R; O'Neill, GC; Maguire, EA; (2021) Modelling optically pumped magnetometer interference in MEG as a spatially homogeneous magnetic field. NeuroImage , 244 , Article 118484. 10.1016/j.neuroimage.2021.118484. Green open access

[thumbnail of 1-s2.0-S1053811921007576-main.pdf]
Preview
Text
1-s2.0-S1053811921007576-main.pdf - Published Version

Download (2MB) | Preview

Abstract

Here we propose that much of the magnetic interference observed when using optically pumped magnetometers for MEG experiments can be modeled as a spatially homogeneous magnetic field. We show that this approximation reduces sensor level variance and substantially improves statistical power. This model does not require knowledge of the underlying neuroanatomy nor the sensor positions. It only needs information about the sensor orientation. Due to the model's low rank there is little risk of removing substantial neural signal. However, we provide a framework to assess this risk for any sensor number, design or subject neuroanatomy. We find that the risk of unintentionally removing neural signal is reduced when multi-axis recordings are performed. We validated the method using a binaural auditory evoked response paradigm and demonstrated that removing the homogeneous magnetic field increases sensor level SNR by a factor of 3. Considering the model's simplicity and efficacy, we suggest that this homogeneous field correction can be a powerful preprocessing step for arrays of optically pumped magnetometers.

Type: Article
Title: Modelling optically pumped magnetometer interference in MEG as a spatially homogeneous magnetic field
Open access status: An open access version is available from UCL Discovery
DOI: 10.1016/j.neuroimage.2021.118484
Publisher version: https://doi.org/10.1016/j.neuroimage.2021.118484
Language: English
Additional information: Copyright © 2021 Published by Elsevier Inc. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology > Imaging Neuroscience
URI: https://discovery.ucl.ac.uk/id/eprint/10134967
Downloads since deposit
168Downloads
Download activity - last month
Download activity - last 12 months
Downloads by country - last 12 months

Archive Staff Only

View Item View Item