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Yuan Z, Lin S, Liu Y, Tang J, Long T, Zhai Y. Gradient phase and amplitude errors in atomic magnetic gradiometers for biomagnetic imaging systems. iScience 2024; 27:109250. [PMID: 38439975 PMCID: PMC10910274 DOI: 10.1016/j.isci.2024.109250] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2023] [Revised: 01/30/2024] [Accepted: 02/13/2024] [Indexed: 03/06/2024] Open
Abstract
The cross-axis projection error (CAPE) caused by residual magnetic fields has recently attracted widespread attention. In this study, we propose a more specific theoretical model and expand the CAPE in gradient measurements. We first report that differences in relaxation rate and residual magnetic field between optically pumped magnetometers (OPMs) introduce a significant error term in the output of OPM gradiometers, referred to as the gradient phase error. Furthermore, when the longitudinal field compensation is inadequate, the interaxial response interference of a single OPM is prominent, resulting in an amplitude distortion of the signal. This is further amplified in the gradiometer configuration, introducing the gradient amplitude error. Our experiments demonstrated that the efficacy of mitigating common-mode noise of OPM gradiometers was significantly impaired when existing the gradient errors. In addition, a simulation with a magnetoencephalography (MEG) system illustrated an induced source localization error of exceeding 2 cm, severely compromising the localization accuracy of OPM-MEG systems.
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Affiliation(s)
- Ziqi Yuan
- Key Laboratory of Ultra-Weak Magnetic Field Measurement Technology, Ministry of Education, School of Instrumentation and Optoelectronic Engineering, Beihang University, Beijing 100191, China
- Zhejiang Provincial Key Laboratory of Ultra-Weak Magnetic-Field Space and Applied Technology, Hangzhou Innovation Institute, Beihang University, Hangzhou 310051, China
| | - Shudong Lin
- Key Laboratory of Ultra-Weak Magnetic Field Measurement Technology, Ministry of Education, School of Instrumentation and Optoelectronic Engineering, Beihang University, Beijing 100191, China
- Zhejiang Provincial Key Laboratory of Ultra-Weak Magnetic-Field Space and Applied Technology, Hangzhou Innovation Institute, Beihang University, Hangzhou 310051, China
| | - Ying Liu
- Key Laboratory of Ultra-Weak Magnetic Field Measurement Technology, Ministry of Education, School of Instrumentation and Optoelectronic Engineering, Beihang University, Beijing 100191, China
- Zhejiang Provincial Key Laboratory of Ultra-Weak Magnetic-Field Space and Applied Technology, Hangzhou Innovation Institute, Beihang University, Hangzhou 310051, China
- Hefei National Laboratory, Hefei 230088, China
| | - Junjian Tang
- Key Laboratory of Ultra-Weak Magnetic Field Measurement Technology, Ministry of Education, School of Instrumentation and Optoelectronic Engineering, Beihang University, Beijing 100191, China
- Zhejiang Provincial Key Laboratory of Ultra-Weak Magnetic-Field Space and Applied Technology, Hangzhou Innovation Institute, Beihang University, Hangzhou 310051, China
- School of Physics, Beihang University, Beijing 100191, China
| | - Tengyue Long
- Key Laboratory of Ultra-Weak Magnetic Field Measurement Technology, Ministry of Education, School of Instrumentation and Optoelectronic Engineering, Beihang University, Beijing 100191, China
- Zhejiang Provincial Key Laboratory of Ultra-Weak Magnetic-Field Space and Applied Technology, Hangzhou Innovation Institute, Beihang University, Hangzhou 310051, China
| | - Yueyang Zhai
- Key Laboratory of Ultra-Weak Magnetic Field Measurement Technology, Ministry of Education, School of Instrumentation and Optoelectronic Engineering, Beihang University, Beijing 100191, China
- Zhejiang Provincial Key Laboratory of Ultra-Weak Magnetic-Field Space and Applied Technology, Hangzhou Innovation Institute, Beihang University, Hangzhou 310051, China
- Hefei National Laboratory, Hefei 230088, China
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Feys O, De Tiège X. From cryogenic to on-scalp magnetoencephalography for the evaluation of paediatric epilepsy. Dev Med Child Neurol 2024; 66:298-306. [PMID: 37421175 DOI: 10.1111/dmcn.15689] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/15/2023] [Revised: 05/28/2023] [Accepted: 06/02/2023] [Indexed: 07/09/2023]
Abstract
Magnetoencephalography (MEG) is a neurophysiological technique based on the detection of brain magnetic fields. Whole-head MEG systems typically house a few hundred sensors requiring cryogenic cooling in a rigid one-size-fits-all (commonly adult-sized) helmet to keep a thermal insulation space. This leads to an increased brain-to-sensor distance in children, because of their smaller head circumference, and decreased signal-to-noise ratio. MEG allows detection and localization of interictal and ictal epileptiform discharges, and pathological high frequency oscillations, as a part of the presurgical assessment of children with refractory focal epilepsy, where electroencephalography is not contributive. MEG can also map the eloquent cortex before surgical resection. MEG also provides insights into the physiopathology of both generalized and focal epilepsy. On-scalp recordings based on cryogenic-free sensors have demonstrated their use in the field of childhood focal epilepsy and should become a reference technique for diagnosing epilepsy in the paediatric population. WHAT THIS PAPER ADDS: Magnetoencephalography (MEG) contributes to the diagnosis and understanding of paediatric epilepsy. On-scalp MEG recordings demonstrate some advantages over cryogenic MEG.
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Affiliation(s)
- Odile Feys
- Department of Neurology, Université libre de Bruxelles, Hôpital Universitaire de Bruxelles, Hôpital Erasme, Bruxelles, Belgium
- Laboratoire de Neuroanatomie et Neuroimagerie Translationnelles, Université libre de Bruxelles, ULB Neuroscience Institute, Bruxelles, Belgium
| | - Xavier De Tiège
- Laboratoire de Neuroanatomie et Neuroimagerie Translationnelles, Université libre de Bruxelles, ULB Neuroscience Institute, Bruxelles, Belgium
- Department of Translational Neuroimaging, Université libre de Bruxelles, Hôpital Universitaire de Bruxelles, Hôpital Erasme, Bruxelles, Belgium
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Tierney TM, Seedat Z, St Pier K, Mellor S, Barnes GR. Adaptive multipole models of optically pumped magnetometer data. Hum Brain Mapp 2024; 45:e26596. [PMID: 38433646 PMCID: PMC10910270 DOI: 10.1002/hbm.26596] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2023] [Revised: 12/14/2023] [Accepted: 12/29/2023] [Indexed: 03/05/2024] Open
Abstract
Multipole expansions have been used extensively in the Magnetoencephalography (MEG) literature for mitigating environmental interference and modelling brain signal. However, their application to Optically Pumped Magnetometer (OPM) data is challenging due to the wide variety of existing OPM sensor and array designs. We therefore explore how such multipole models can be adapted to provide stable models of brain signal and interference across OPM systems. Firstly, we demonstrate how prolate spheroidal (rather than spherical) harmonics can provide a compact representation of brain signal when sampling on the scalp surface with as few as 100 channels. We then introduce a type of orthogonal projection incorporating this basis set. The Adaptive Multipole Models (AMM), which provides robust interference rejection across systems, even in the presence of spatially structured nonlinearity errors (shielding factor is the reciprocal of the maximum fractional nonlinearity error). Furthermore, this projection is always stable, as it is an orthogonal projection, and will only ever decrease the white noise in the data. However, for array designs that are suboptimal for spatially separating brain signal and interference, this method can remove brain signal components. We contrast these properties with the more typically used multipole expansion, Signal Space Separation (SSS), which never reduces brain signal amplitude but is less robust to the effect of sensor nonlinearity errors on interference rejection and can increase noise in the data if the system is sub-optimally designed (as it is an oblique projection). We conclude with an empirical example utilizing AMM to maximize signal to noise ratio (SNR) for the stimulus locked neuronal response to a flickering visual checkerboard in a 128-channel OPM system and demonstrate up to 40 dB software shielding in real data.
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Affiliation(s)
- Tim M. Tierney
- Department of Imaging NeuroscienceUCL Queen Square Institute of Neurology, University College LondonLondonUK
| | | | - Kelly St Pier
- Diagnostic Suite, Young Epilepsy, St Piers LaneSurreyUK
| | - Stephanie Mellor
- Department of Imaging NeuroscienceUCL Queen Square Institute of Neurology, University College LondonLondonUK
| | - Gareth R. Barnes
- Department of Imaging NeuroscienceUCL Queen Square Institute of Neurology, University College LondonLondonUK
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Mellor S, Tierney TM, Seymour RA, Timms RC, O'Neill GC, Alexander N, Spedden ME, Payne H, Barnes GR. Real-time, model-based magnetic field correction for moving, wearable MEG. Neuroimage 2023; 278:120252. [PMID: 37437702 PMCID: PMC11157691 DOI: 10.1016/j.neuroimage.2023.120252] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2023] [Revised: 06/04/2023] [Accepted: 06/25/2023] [Indexed: 07/14/2023] Open
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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Affiliation(s)
- Stephanie Mellor
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London WC1N 3AR, UK.
| | - Tim M Tierney
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London WC1N 3AR, UK
| | - Robert A Seymour
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London WC1N 3AR, UK
| | - Ryan C Timms
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London WC1N 3AR, UK
| | - George C O'Neill
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London WC1N 3AR, UK
| | - Nicholas Alexander
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London WC1N 3AR, UK
| | - Meaghan E Spedden
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London WC1N 3AR, UK
| | - Heather Payne
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London WC1N 3AR, UK
| | - Gareth R Barnes
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London WC1N 3AR, UK
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Alem O, Hughes KJ, Buard I, Cheung TP, Maydew T, Griesshammer A, Holloway K, Park A, Lechuga V, Coolidge C, Gerginov M, Quigg E, Seames A, Kronberg E, Teale P, Knappe S. An integrated full-head OPM-MEG system based on 128 zero-field sensors. Front Neurosci 2023; 17:1190310. [PMID: 37389367 PMCID: PMC10303922 DOI: 10.3389/fnins.2023.1190310] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2023] [Accepted: 05/24/2023] [Indexed: 07/01/2023] Open
Abstract
Compact optically-pumped magnetometers (OPMs) are now commercially available with noise floors reaching 10 fT/Hz1/2. However, to be used effectively for magnetoencephalography (MEG), dense arrays of these sensors are required to operate as an integrated turn-key system. In this study, we present the HEDscan, a 128-sensor OPM MEG system by FieldLine Medical, and evaluate its sensor performance with regard to bandwidth, linearity, and crosstalk. We report results from cross-validation studies with conventional cryogenic MEG, the Magnes 3,600 WH Biomagnetometer by 4-D Neuroimaging. Our results show high signal amplitudes captured by the OPM-MEG system during a standard auditory paradigm, where short tones at 1000 Hz were presented to the left ear of six healthy adult volunteers. We validate these findings through an event-related beamformer analysis, which is in line with existing literature results.
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Affiliation(s)
- Orang Alem
- FieldLine Medical, Boulder, CO, United States
- Paul M. Rady Department of Mechanical Engineering, University of Colorado Boulder, Boulder, CO, United States
- FieldLine Industries, Boulder, CO, United States
| | - K. Jeramy Hughes
- FieldLine Medical, Boulder, CO, United States
- Paul M. Rady Department of Mechanical Engineering, University of Colorado Boulder, Boulder, CO, United States
- FieldLine Industries, Boulder, CO, United States
| | - Isabelle Buard
- Anschutz Medical Campus, University of Colorado Denver, Denver, CO, United States
| | - Teresa P. Cheung
- FieldLine Medical, Boulder, CO, United States
- School of Engineering, Simon Fraser University, Burnaby, BC, Canada
- Surrey Memorial Hospital, Fraser Health Authority, Surrey, BC, Canada
| | | | | | | | - Aaron Park
- FieldLine Medical, Boulder, CO, United States
| | | | | | - Marja Gerginov
- Paul M. Rady Department of Mechanical Engineering, University of Colorado Boulder, Boulder, CO, United States
| | - Erik Quigg
- Paul M. Rady Department of Mechanical Engineering, University of Colorado Boulder, Boulder, CO, United States
| | - Alexander Seames
- Anschutz Medical Campus, University of Colorado Denver, Denver, CO, United States
| | - Eugene Kronberg
- Anschutz Medical Campus, University of Colorado Denver, Denver, CO, United States
| | - Peter Teale
- Anschutz Medical Campus, University of Colorado Denver, Denver, CO, United States
| | - Svenja Knappe
- FieldLine Medical, Boulder, CO, United States
- Paul M. Rady Department of Mechanical Engineering, University of Colorado Boulder, Boulder, CO, United States
- FieldLine Industries, Boulder, CO, United States
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Zhang C, Zhang J, Widmann M, Benke M, Kübler M, Dasari D, Klotz T, Gizzi L, Röhrle O, Brenner P, Wrachtrup J. Optimizing NV magnetometry for Magnetoneurography and Magnetomyography applications. Front Neurosci 2023; 16:1034391. [PMID: 36726853 PMCID: PMC9885266 DOI: 10.3389/fnins.2022.1034391] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2022] [Accepted: 12/28/2022] [Indexed: 01/13/2023] Open
Abstract
Magnetometers based on color centers in diamond are setting new frontiers for sensing capabilities due to their combined extraordinary performances in sensitivity, bandwidth, dynamic range, and spatial resolution, with stable operability in a wide range of conditions ranging from room to low temperatures. This has allowed for its wide range of applications, from biology and chemical studies to industrial applications. Among the many, sensing of bio-magnetic fields from muscular and neurophysiology has been one of the most attractive applications for NV magnetometry due to its compact and proximal sensing capability. Although SQUID magnetometers and optically pumped magnetometers (OPM) have made huge progress in Magnetomyography (MMG) and Magnetoneurography (MNG), exploring the same with NV magnetometry is scant at best. Given the room temperature operability and gradiometric applications of the NV magnetometer, it could be highly sensitive in the pT / Hz -range even without magnetic shielding, bringing it close to industrial applications. The presented work here elaborates on the performance metrics of these magnetometers to the state-of-the-art techniques by analyzing the sensitivity, dynamic range, and bandwidth, and discusses the potential benefits of using NV magnetometers for MMG and MNG applications.
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Affiliation(s)
- Chen Zhang
- Institute of Physics, University of Stuttgart, Stuttgart, Germany,Quantum Technology R&D Center, Beijing Automation Control Equipment Institute, Beijing, China,*Correspondence: Chen Zhang ✉
| | - Jixing Zhang
- Institute of Physics, University of Stuttgart, Stuttgart, Germany
| | - Matthias Widmann
- Institute of Physics, University of Stuttgart, Stuttgart, Germany
| | - Magnus Benke
- Institute of Physics, University of Stuttgart, Stuttgart, Germany
| | - Michael Kübler
- Institute of Physics, University of Stuttgart, Stuttgart, Germany
| | - Durga Dasari
- Institute of Physics, University of Stuttgart, Stuttgart, Germany
| | - Thomas Klotz
- Institute for Modelling and Simulation of Biomechanical Systems, University of Stuttgart, Stuttgart, Germany
| | - Leonardo Gizzi
- Institute for Modelling and Simulation of Biomechanical Systems, University of Stuttgart, Stuttgart, Germany,Department of Biomechatronic Systems, Fraunhofer Institute for Manufacturing Engineering and Automation IPA, Stuttgart, Germany
| | - Oliver Röhrle
- Institute for Modelling and Simulation of Biomechanical Systems, University of Stuttgart, Stuttgart, Germany
| | - Philipp Brenner
- ZEISS Innovation Hub @ KIT, Eggenstein-Leopoldshafen, Germany
| | - Jörg Wrachtrup
- Institute of Physics, University of Stuttgart, Stuttgart, Germany,Jörg Wrachtrup ✉
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