Mellor, Stephanie;
Tierney, Tim M;
Seymour, Robert A;
Timms, Ryan C;
O'Neill, George C;
Alexander, Nicholas;
Spedden, Meaghan E;
... Barnes, Gareth R; + view all
(2023)
Real-time, model-based magnetic field correction for moving, wearable MEG.
NeuroImage
10.1016/j.neuroimage.2023.120252.
(In press).
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Mellor_Real-time, model-based magnetic field correction for moving, wearable MEG_Pre-proof.pdf - Accepted Version Download (3MB) | Preview |
Abstract
Most neuroimaging techniques require the participant to remain still for reliable recordings to be made. Optically pumped magnetometer (OPM) based magnetoencephalography (OP-MEG) however, is a neuroimaging technique which can be used to measure neural signals during large participant movement (approximately 1 m) within a magnetically shielded room (MSR) (Boto et al., 2018; Seymour et al., 2021). Nevertheless, environmental magnetic fields vary both spatially and temporally and OPMs can only operate within a limited magnetic field range, which constrains participant movement. Here we implement real-time updates to electromagnetic coils mounted on-board of the OPMs, to cancel out the changing background magnetic fields. The coil currents were chosen based on a continually updating harmonic model of the background magnetic field, effectively implementing homogeneous field correction (HFC) in real-time (Tierney et al., 2021). During a stationary, empty room recording, we show an improvement in very low frequency noise of 24 dB. In an auditory paradigm, during participant movement of up to 2 m within a magnetically shielded room, introduction of the real-time correction more than doubled the proportion of trials in which no sensor saturated recorded outside of a 50 cm radius from the optimally-shielded centre of the room. The main advantage of such model-based (rather than direct) feedback is that it could allow one to correct field components along unmeasured OPM axes, potentially mitigating sensor gain and calibration issues (Borna et al., 2022).
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