Data‐driven model optimization for optically pumped magnetometer sensor arrays

Duque‐Muñoz, Leonardo; Tierney, Tim M.; Meyer, Sofie S.; Boto, Elena; Holmes, Niall; Roberts, Gillian; Leggett, James; Vargas‐Bonilla, J. F.; Bowtell, Richard; Brookes, Matthew J.; López, Jose D.; Barnes, Gareth R.

Abstract

© 2019 The Authors. Human Brain Mapping published by Wiley Periodicals, Inc. Optically pumped magnetometers (OPMs) have reached sensitivity levels that make them viable portable alternatives to traditional superconducting technology for magnetoencephalography (MEG). OPMs do not require cryogenic cooling and can therefore be placed directly on the scalp surface. Unlike cryogenic systems, based on a well-characterised fixed arrays essentially linear in applied flux, OPM devices, based on different physical principles, present new modelling challenges. Here, we outline an empirical Bayesian framework that can be used to compare between and optimise sensor arrays. We perturb the sensor geometry (via simulation) and with analytic model comparison methods estimate the true sensor geometry. The width of these perturbation curves allows us to compare different MEG systems. We test this technique using simulated and real data from SQUID and OPM recordings using head-casts and scanner-casts. Finally, we show that given knowledge of underlying brain anatomy, it is possible to estimate the true sensor geometry from the OPM data themselves using a model comparison framework. This implies that the requirement for accurate knowledge of the sensor positions and orientations a priori may be relaxed. As this procedure uses the cortical manifold as spatial support there is no co-registration procedure or reliance on scalp landmarks.

Citation

Duque‐Muñoz, L., Tierney, T. M., Meyer, S. S., Boto, E., Holmes, N., Roberts, G., …Barnes, G. R. (2019). Data‐driven model optimization for optically pumped magnetometer sensor arrays. Human Brain Mapping, 40(15), 4357-4369. https://doi.org/10.1002/hbm.24707

• Journal Article Type: Article
• Acceptance Date: Jun 24, 2019
• Online Publication Date: Jul 11, 2019
• Publication Date: Oct 15, 2019
• Deposit Date: Jul 15, 2019
• Publicly Available Date: Jul 15, 2019
• Journal: Human Brain Mapping
• Print ISSN: 1065-9471
• Electronic ISSN: 1097-0193
• Publisher: Wiley
• Peer Reviewed: Peer Reviewed
• Volume: 40
• Issue: 15
• Pages: 4357-4369
• DOI: https://doi.org/10.1002/hbm.24707
• Keywords: Anatomy; Radiological and Ultrasound Technology; Radiology Nuclear Medicine and imaging; Neurology; Clinical Neurology
• Public URL: https://nottingham-repository.worktribe.com/output/2307743
• Publisher URL: https://onlinelibrary.wiley.com/doi/full/10.1002/hbm.24707
• Additional Information: Received: 2019-01-15; Accepted: 2019-06-24; Published: 2019-07-11