Single-trial classification of evoked responses to auditory tones using OPM- and SQUID-MEG

Iivanainen, Joonas; Carter, Tony R.; Trumbo, Michael C. S.; McKay, Jim; Taulu, Samu; Wang, Jun; Stephen, Julia M.; Schwindt, Peter D. D.; Borna, Amir

doi:10.1088/1741-2552/acfcd9

Single-trial classification of evoked responses to auditory tones using OPM- and SQUID-MEG

Journal Article · Fri Oct 06 00:00:00 EDT 2023 · Journal of Neural Engineering

DOI:https://doi.org/10.1088/1741-2552/acfcd9· OSTI ID:2007979

; Carter, Tony R.; Trumbo, Michael C. S.; McKay, Jim; Taulu, Samu; ; Stephen, Julia M.; Schwindt, Peter D. D.; Borna, Amir

Abstract

Objective. Optically pumped magnetometers (OPMs) are emerging as a near-room-temperature alternative to superconducting quantum interference devices (SQUIDs) for magnetoencephalography (MEG). In contrast to SQUIDs, OPMs can be placed in a close proximity to subject’s scalp potentially increasing the signal-to-noise ratio and spatial resolution of MEG. However, experimental demonstrations of these suggested benefits are still scarce. Here, to compare a 24-channel OPM-MEG system to a commercial whole-head SQUID system in a data-driven way, we quantified their performance in classifying single-trial evoked responses. Approach. We measured evoked responses to three auditory tones in six participants using both OPM- and SQUID-MEG systems. We performed pairwise temporal classification of the single-trial responses with linear discriminant analysis as well as multiclass classification with both EEGNet convolutional neural network and xDAWN decoding. Main results. OPMs provided higher classification accuracies than SQUIDs having a similar coverage of the left hemisphere of the participant. However, the SQUID sensors covering the whole helmet had classification scores larger than those of OPMs for two of the tone pairs, demonstrating the benefits of a whole-head measurement. Significance. The results demonstrate that the current OPM-MEG system provides high-quality data about the brain with room for improvement for high bandwidth non-invasive brain–computer interfacing.

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Sponsoring Organization:: USDOE

OSTI ID:: 2007979

Alternate ID(s):: OSTI ID: 2005010

Journal Information:: Journal of Neural Engineering, Journal Name: Journal of Neural Engineering Journal Issue: 5 Vol. 20; ISSN 1741-2560

Publisher:: IOP PublishingCopyright Statement

Country of Publication:: United Kingdom

Language:: English

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