Real-time, model-based magnetic field correction for moving, wearable MEG
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 (appro...
| Main Authors: | , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2023-09-01
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| Series: | NeuroImage |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1053811923004032 |
| _version_ | 1827866637024362496 |
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| author | Stephanie Mellor Tim M. Tierney Robert A. Seymour Ryan C. Timms George C. O'Neill Nicholas Alexander Meaghan E. Spedden Heather Payne Gareth R. Barnes |
| author_facet | Stephanie Mellor Tim M. Tierney Robert A. Seymour Ryan C. Timms George C. O'Neill Nicholas Alexander Meaghan E. Spedden Heather Payne Gareth R. Barnes |
| author_sort | Stephanie Mellor |
| collection | DOAJ |
| description | 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). |
| first_indexed | 2024-03-12T15:08:20Z |
| format | Article |
| id | doaj.art-8d7e0428e2e64e84a814effc352e02bd |
| institution | Directory Open Access Journal |
| issn | 1095-9572 |
| language | English |
| last_indexed | 2024-03-12T15:08:20Z |
| publishDate | 2023-09-01 |
| publisher | Elsevier |
| record_format | Article |
| series | NeuroImage |
| spelling | doaj.art-8d7e0428e2e64e84a814effc352e02bd2023-08-12T04:33:45ZengElsevierNeuroImage1095-95722023-09-01278120252Real-time, model-based magnetic field correction for moving, wearable MEGStephanie Mellor0Tim M. Tierney1Robert A. Seymour2Ryan C. Timms3George C. O'Neill4Nicholas Alexander5Meaghan E. Spedden6Heather Payne7Gareth R. Barnes8Corresponding author.; Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London WC1N 3AR, UKWellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London WC1N 3AR, UKWellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London WC1N 3AR, UKWellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London WC1N 3AR, UKWellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London WC1N 3AR, UKWellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London WC1N 3AR, UKWellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London WC1N 3AR, UKWellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London WC1N 3AR, UKWellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London WC1N 3AR, UKMost 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).http://www.sciencedirect.com/science/article/pii/S1053811923004032MagnetoencephalographyMEGOptically pumped magnetometerMagnetic field correctionWalking OP-MEGAuditory evoked field |
| spellingShingle | Stephanie Mellor Tim M. Tierney Robert A. Seymour Ryan C. Timms George C. O'Neill Nicholas Alexander Meaghan E. Spedden Heather Payne Gareth R. Barnes Real-time, model-based magnetic field correction for moving, wearable MEG NeuroImage Magnetoencephalography MEG Optically pumped magnetometer Magnetic field correction Walking OP-MEG Auditory evoked field |
| title | Real-time, model-based magnetic field correction for moving, wearable MEG |
| title_full | Real-time, model-based magnetic field correction for moving, wearable MEG |
| title_fullStr | Real-time, model-based magnetic field correction for moving, wearable MEG |
| title_full_unstemmed | Real-time, model-based magnetic field correction for moving, wearable MEG |
| title_short | Real-time, model-based magnetic field correction for moving, wearable MEG |
| title_sort | real time model based magnetic field correction for moving wearable meg |
| topic | Magnetoencephalography MEG Optically pumped magnetometer Magnetic field correction Walking OP-MEG Auditory evoked field |
| url | http://www.sciencedirect.com/science/article/pii/S1053811923004032 |
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