Noise Reduction and Localization Accuracy in a Mobile Magnetoencephalography System

Bardouille, Timothy; Smith, Vanessa; Vajda, Elias; Leslie, Carson Drake; Holmes, Niall

Abstract

Magnetoencephalography (MEG) non-invasively provides important information about human brain electrophysiology. The growing use of optically pumped magnetometers (OPM) for MEG, as opposed to fixed arrays of cryogenic sensors, has opened the door for innovation in system design and use cases. For example, cryogenic MEG systems are housed in large, shielded rooms to provide sufficient space for the system dewar. Here, we investigate the performance of OPM recordings inside of a cylindrical shield with a 1 × 2 m2 footprint. The efficacy of shielding was measured in terms of field attenuation and isotropy, and the value of post hoc noise reduction algorithms was also investigated. Localization accuracy was quantified for 104 OPM sensors mounted on a fixed helmet array based on simulations and recordings from a bespoke current dipole phantom. Passive shielding attenuated the vector field magnitude to 50.0 nT at direct current (DC), to 16.7 pT/√Hz at power line, and to 71 fT/√Hz (median) in the 10–200 Hz range. Post hoc noise reduction provided an additional 5–15 dB attenuation. Substantial field isotropy remained in the volume encompassing the sensor array. The consistency of the isotropy over months suggests that a field nulling solution could be readily applied. A current dipole phantom generating source activity at an appropriate magnitude for the human brain generated field fluctuations on the order of 0.5–1 pT. Phantom signals were localized with 3 mm localization accuracy, and no significant bias in localization was observed, which is in line with performance for cryogenic and OPM MEG systems. This validation of the performance of a small footprint MEG system opens the door for lower-cost MEG installations in terms of raw materials and facility space, as well as mobile imaging systems (e.g., truck-based). Such implementations are relevant for global adoption of MEG outside of highly resourced research and clinical institutions.

Citation

Bardouille, T., Smith, V., Vajda, E., Leslie, C. D., & Holmes, N. (2024). Noise Reduction and Localization Accuracy in a Mobile Magnetoencephalography System. Sensors, 24(11), Article 3503. https://doi.org/10.3390/s24113503

• Journal Article Type: Article
• Acceptance Date: May 21, 2024
• Online Publication Date: May 29, 2024
• Publication Date: May 29, 2024
• Deposit Date: Jul 29, 2024
• Publicly Available Date: Jul 29, 2024
• Journal: Sensors
• Print ISSN: 1424-8220
• Electronic ISSN: 1424-8220
• Publisher: MDPI
• Peer Reviewed: Peer Reviewed
• Volume: 24
• Issue: 11
• Article Number: 3503
• DOI: https://doi.org/10.3390/s24113503
• Public URL: https://nottingham-repository.worktribe.com/output/35999828
• Publisher URL: https://www.mdpi.com/1424-8220/24/11/3503