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An N, Gao Z, Li W, Cao F, Wang W, Xu W, Wang C, Xiang M, Gao Y, Wang D, Yu D, Ning X. Source localization comparison and combination of OPM-MEG and fMRI to detect sensorimotor cortex responses. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2024; 254:108292. [PMID: 38936152 DOI: 10.1016/j.cmpb.2024.108292] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/26/2023] [Revised: 04/29/2024] [Accepted: 06/16/2024] [Indexed: 06/29/2024]
Abstract
BACKGROUND AND OBJECTIVES The exploration of various neuroimaging techniques have become focal points within the field of neuroscience research. Magnetoencephalography based on optically pumped magnetometers (OPM-MEG) has shown significant potential to be the next generation of functional neuroimaging with the advantages of high signal intensity and flexible sensor arrangement. In this study, we constructed a 31-channel OPM-MEG system and performed a preliminary comparison of the temporal and spatial relationship between magnetic responses measured by OPM-MEG and blood-oxygen-level-dependent signals detected by functional magnetic resonance imaging (fMRI) during a grasping task. METHODS For OPM-MEG, the β-band (15-30 Hz) oscillatory activities can be reliably detected across multiple subjects and multiple session runs. To effectively localize the inhibitory oscillatory activities, a source power-spectrum ratio-based imaging method was proposed. This approach was compared with conventional source imaging methods, such as minimum norm-type and beamformer methods, and was applied in OPM-MEG source analysis. Subsequently, the spatial and temporal responses at the source-level between OPM-MEG and fMRI were analyzed. RESULTS The effectiveness of the proposed method was confirmed through simulations compared to benchmark methods. Our demonstration revealed an average spatial separation of 10.57 ± 4.41 mm between the localization results of OPM-MEG and fMRI across four subjects. Furthermore, the fMRI-constrained OPM-MEG localization results indicated a more focused imaging extent. CONCLUSIONS Taken together, the performance exhibited by OPM-MEG positions it as a potential instrument for functional surgery assessment.
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Affiliation(s)
- Nan An
- Key Laboratory of Ultra-Weak Magnetic Field Measurement Technology, Ministry of Education, School of Instrumentation and Optoelectronic Engineering, Beihang University, Beijing, 100191, China; Hangzhou Institute of Extremely-weak Magnetic Field Major National Science and Technology Infrastructure, Hangzhou, 310051, China
| | - Zhenfeng Gao
- Key Laboratory of Ultra-Weak Magnetic Field Measurement Technology, Ministry of Education, School of Instrumentation and Optoelectronic Engineering, Beihang University, Beijing, 100191, China; Hangzhou Institute of Extremely-weak Magnetic Field Major National Science and Technology Infrastructure, Hangzhou, 310051, China; Zhejiang Provincial Key Laboratory of Ultra-Weak Magnetic-Field Space and Applied Technology, Hangzhou Innovation Institute, Beihang University, Hangzhou, 310051, China
| | - Wen Li
- Key Laboratory of Ultra-Weak Magnetic Field Measurement Technology, Ministry of Education, School of Instrumentation and Optoelectronic Engineering, Beihang University, Beijing, 100191, China; Hangzhou Institute of Extremely-weak Magnetic Field Major National Science and Technology Infrastructure, Hangzhou, 310051, China; Zhejiang Provincial Key Laboratory of Ultra-Weak Magnetic-Field Space and Applied Technology, Hangzhou Innovation Institute, Beihang University, Hangzhou, 310051, China
| | - Fuzhi Cao
- Key Laboratory of Ultra-Weak Magnetic Field Measurement Technology, Ministry of Education, School of Instrumentation and Optoelectronic Engineering, Beihang University, Beijing, 100191, China; Hangzhou Institute of Extremely-weak Magnetic Field Major National Science and Technology Infrastructure, Hangzhou, 310051, China; School of Engineering Medicine, 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.
| | - Wenli Wang
- Key Laboratory of Ultra-Weak Magnetic Field Measurement Technology, Ministry of Education, School of Instrumentation and Optoelectronic Engineering, Beihang University, Beijing, 100191, China; Hangzhou Institute of Extremely-weak Magnetic Field Major National Science and Technology Infrastructure, Hangzhou, 310051, China; Zhejiang Provincial Key Laboratory of Ultra-Weak Magnetic-Field Space and Applied Technology, Hangzhou Innovation Institute, Beihang University, Hangzhou, 310051, China
| | - Weinan Xu
- Key Laboratory of Ultra-Weak Magnetic Field Measurement Technology, Ministry of Education, School of Instrumentation and Optoelectronic Engineering, Beihang University, Beijing, 100191, China; Hangzhou Institute of Extremely-weak Magnetic Field Major National Science and Technology Infrastructure, Hangzhou, 310051, China; Zhejiang Provincial Key Laboratory of Ultra-Weak Magnetic-Field Space and Applied Technology, Hangzhou Innovation Institute, Beihang University, Hangzhou, 310051, China
| | - Chunhui Wang
- Key Laboratory of Ultra-Weak Magnetic Field Measurement Technology, Ministry of Education, School of Instrumentation and Optoelectronic Engineering, Beihang University, Beijing, 100191, China; Hangzhou Institute of Extremely-weak Magnetic Field Major National Science and Technology Infrastructure, Hangzhou, 310051, China; Zhejiang Provincial Key Laboratory of Ultra-Weak Magnetic-Field Space and Applied Technology, Hangzhou Innovation Institute, Beihang University, Hangzhou, 310051, China
| | - Min Xiang
- Key Laboratory of Ultra-Weak Magnetic Field Measurement Technology, Ministry of Education, School of Instrumentation and Optoelectronic Engineering, Beihang University, Beijing, 100191, China; Hangzhou Institute of Extremely-weak Magnetic Field Major National Science and Technology Infrastructure, Hangzhou, 310051, 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
| | - Yang Gao
- Key Laboratory of Ultra-Weak Magnetic Field Measurement Technology, Ministry of Education, School of Instrumentation and Optoelectronic Engineering, Beihang University, Beijing, 100191, China; Hangzhou Institute of Extremely-weak Magnetic Field Major National Science and Technology Infrastructure, Hangzhou, 310051, China
| | - Dawei Wang
- Shandong Key Laboratory: Magnetic Field-free Medicine & Functional Imaging, Qilu hospital of Shandong University, Jinan, 250014, China
| | - Dexin Yu
- Shandong Key Laboratory: Magnetic Field-free Medicine & Functional Imaging, Qilu hospital of Shandong University, Jinan, 250014, China
| | - Xiaolin Ning
- Key Laboratory of Ultra-Weak Magnetic Field Measurement Technology, Ministry of Education, School of Instrumentation and Optoelectronic Engineering, Beihang University, Beijing, 100191, China; Hangzhou Institute of Extremely-weak Magnetic Field Major National Science and Technology Infrastructure, Hangzhou, 310051, 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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Brickwedde M, Anders P, Kühn AA, Lofredi R, Holtkamp M, Kaindl AM, Grent-'t-Jong T, Krüger P, Sander T, Uhlhaas PJ. Applications of OPM-MEG for translational neuroscience: a perspective. Transl Psychiatry 2024; 14:341. [PMID: 39181883 PMCID: PMC11344782 DOI: 10.1038/s41398-024-03047-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/12/2023] [Revised: 06/25/2024] [Accepted: 08/01/2024] [Indexed: 08/27/2024] Open
Abstract
Magnetoencephalography (MEG) allows the non-invasive measurement of brain activity at millisecond precision combined with localization of the underlying generators. So far, MEG-systems consisted of superconducting quantum interference devices (SQUIDS), which suffer from several limitations. Recent technological advances, however, have enabled the development of novel MEG-systems based on optically pumped magnetometers (OPMs), offering several advantages over conventional SQUID-MEG systems. Considering potential improvements in the measurement of neuronal signals as well as reduced operating costs, the application of OPM-MEG systems for clinical neuroscience and diagnostic settings is highly promising. Here we provide an overview of the current state-of-the art of OPM-MEG and its unique potential for translational neuroscience. First, we discuss the technological features of OPMs and benchmark OPM-MEG against SQUID-MEG and electroencephalography (EEG), followed by a summary of pioneering studies of OPMs in healthy populations. Key applications of OPM-MEG for the investigation of psychiatric and neurological conditions are then reviewed. Specifically, we suggest novel applications of OPM-MEG for the identification of biomarkers and circuit deficits in schizophrenia, dementias, movement disorders, epilepsy, and neurodevelopmental syndromes (autism spectrum disorder and attention deficit hyperactivity disorder). Finally, we give an outlook of OPM-MEG for translational neuroscience with a focus on remaining methodological and technical challenges.
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Affiliation(s)
- Marion Brickwedde
- Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität Berlin, and Berlin Institute of Health, Department of Child and Adolescent Psychiatry, 13353, Berlin, Germany.
- Physikalisch-Technische Bundesanstalt, Berlin, Germany.
| | - Paul Anders
- Physikalisch-Technische Bundesanstalt, Berlin, Germany
| | - Andrea A Kühn
- Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität Berlin, and Berlin Institute of Health, Sektion für Bewegungsstörungen und Neuromodulation, Klinik für Neurologie und Experimentelle Neurologie, 10117, Berlin, Germany
- Bernstein Center for Computational Neuroscience, Humboldt-Universität, Berlin, Germany
- NeuroCure, Exzellenzcluster, Charité-Universitätsmedizin Berlin, Berlin, Germany
- DZNE, German center for neurodegenerative diseases, Berlin, Germany
- Berlin School of Mind and Brain, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Roxanne Lofredi
- Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität Berlin, and Berlin Institute of Health, Sektion für Bewegungsstörungen und Neuromodulation, Klinik für Neurologie und Experimentelle Neurologie, 10117, Berlin, Germany
- Berlin Institute of Health, Berlin, Germany
| | - Martin Holtkamp
- Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität Berlin, and Berlin Institute of Health, Department of Neurology, Epilepsy-Center Berlin-Brandenburg, 10117, Berlin, Germany
| | - Angela M Kaindl
- Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität Berlin, and Berlin Institute of Health, Department of Pediatric Neurology, 13353, Berlin, Germany
- Charité- Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität Berlin, and Berlin Institute of Health, Center for Chronically Sick Children, 13353, Berlin, Germany
- Charité- Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität Berlin, and Berlin Institute of Health, Institute of Cell Biology and Neurobiology, 10117, Berlin, Germany
| | - Tineke Grent-'t-Jong
- Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität Berlin, and Berlin Institute of Health, Department of Child and Adolescent Psychiatry, 13353, Berlin, Germany
- Institute for Neuroscience and Psychology, Glasgow University, Scotland, United Kingdom
| | - Peter Krüger
- Physikalisch-Technische Bundesanstalt, Berlin, Germany
| | | | - Peter J Uhlhaas
- Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität Berlin, and Berlin Institute of Health, Department of Child and Adolescent Psychiatry, 13353, Berlin, Germany
- Institute for Neuroscience and Psychology, Glasgow University, Scotland, United Kingdom
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Wang R, Fu K, Zhao R, Wang D, Yang Z, Bin W, Gao Y, Ning X. Expanding the clinical application of OPM-MEG using an effective automatic suppression method for the dental brace metal artifact. Neuroimage 2024; 296:120661. [PMID: 38838840 DOI: 10.1016/j.neuroimage.2024.120661] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/01/2024] [Revised: 05/19/2024] [Accepted: 05/30/2024] [Indexed: 06/07/2024] Open
Abstract
Optically pumped magnetometer magnetoencephalography (OPM-MEG) holds significant promise for clinical functional brain imaging due to its superior spatiotemporal resolution. However, effectively suppressing metallic artifacts, particularly from devices such as orthodontic braces and vagal nerve stimulators remains a major challenge, hindering the wider clinical application of wearable OPM-MEG devices. A comprehensive analysis of metal artifact characteristics from time, frequency, and time-frequency perspectives was conducted for the first time using an OPM-MEG device in clinical medicine. This study focused on patients with metal orthodontics, examining the modulation of metal artifacts by breath and head movement, the incomplete regular sub-Gaussian distribution, and the high absolute power ratio in the 0.5-8 Hz band. The existing metal artifact suppression algorithms applied to SQUID-MEG, such as fast independent component analysis (FastICA), information maximization (Infomax), and algorithms for multiple unknown signal extraction (AMUSE), exhibit limited efficacy. Consequently, this study introduced the second-order blind identification (SOBI) algorithm, which utilized multiple time delays for the component separation of OPM-MEG measurement signals. We modified the time delays of the SOBI method to improve its efficacy in separating artifact components, particularly those in the ultralow frequency range. This approach employs the frequency-domain absolute power ratio, root mean square (RMS) value, and mutual information methods to automate the artifact component screening process. The effectiveness of this method was validated through simulation experiments involving four subjects in both resting and evoked experiments. In addition, the proposed method was also validated by the actual OPM-MEG evoked experiments of three subjects. Comparative analyses were conducted against the FastICA, Infomax, and AMUSE algorithms. Evaluation metrics included normalized mean square error, normalized delta band power error, RMS error, and signal-to-noise ratio, demonstrating that the proposed method provides optimal suppression of metal artifacts. This advancement holds promise for enhancing data quality and expanding the clinical applications of OPM-MEG.
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Affiliation(s)
- Ruonan Wang
- School of Instrumentation Science and Optoelectronic Engineering, Beihang University, Beijing 100191, China; Key Laboratory of Ultra-Weak Magnetic Field Measurement Technology, Ministry of Education, School of Instrumentation and Optoelectronic Engineering, Beihang University, Beijing 100191, China; Institute of Large-scale Scientific Facility and Centre for Zero Magnetic Field Science, Beihang University, Hangzhou 310051, China.
| | - Kaiwen Fu
- School of Instrumentation Science and Optoelectronic Engineering, Beihang University, Beijing 100191, China; Key Laboratory of Ultra-Weak Magnetic Field Measurement Technology, Ministry of Education, School of Instrumentation and Optoelectronic Engineering, Beihang University, Beijing 100191, China; Institute of Large-scale Scientific Facility and Centre for Zero Magnetic Field Science, Beihang University, Hangzhou 310051, China.
| | - Ruochen Zhao
- School of Instrumentation Science and Optoelectronic Engineering, Beihang University, Beijing 100191, China; Key Laboratory of Ultra-Weak Magnetic Field Measurement Technology, Ministry of Education, School of Instrumentation and Optoelectronic Engineering, Beihang University, Beijing 100191, China; Institute of Large-scale Scientific Facility and Centre for Zero Magnetic Field Science, Beihang University, Hangzhou 310051, China.
| | - Dawei Wang
- Department of Radiology, Qilu Hospital of Shandong University, Jinan 250012, China; National Innovation Platform for industry-Education Integration in Medicine-Engineering Interdisciplinary, Shandong Key Laboratory for Magnetic Field-free Medicine and Functional Imaging, Shandong University, Research Institute of Shandong University, Jinan, 250014, China.
| | - Zhimin Yang
- State Key Laboratory of Traditional Chinese Medicine Syndrome/Health Construction Center, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, 510120, China.
| | - Wei Bin
- State Key Laboratory of Traditional Chinese Medicine Syndrome/Health Construction Center, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, 510120, China.
| | - Yang Gao
- Key Laboratory of Ultra-Weak Magnetic Field Measurement Technology, Ministry of Education, School of Instrumentation and Optoelectronic Engineering, Beihang University, Beijing 100191, China; Institute of Large-scale Scientific Facility and Centre for Zero Magnetic Field Science, Beihang University, Hangzhou 310051, China; National Institute of Extremely-Weak Magnetic Field Infrastructure, Hangzhou 310051, China.
| | - Xiaolin Ning
- School of Instrumentation Science and Optoelectronic Engineering, Beihang University, Beijing 100191, China; Key Laboratory of Ultra-Weak Magnetic Field Measurement Technology, Ministry of Education, School of Instrumentation and Optoelectronic Engineering, Beihang University, Beijing 100191, China; National Innovation Platform for industry-Education Integration in Medicine-Engineering Interdisciplinary, Shandong Key Laboratory for Magnetic Field-free Medicine and Functional Imaging, Shandong University, Research Institute of Shandong University, Jinan, 250014, China; National Institute of Extremely-Weak Magnetic Field Infrastructure, Hangzhou 310051, China.
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4
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Wu H, Wang R, Ma Y, Liang X, Liu C, Yu D, An N, Ning X. Decoding N400m Evoked Component: A Tutorial on Multivariate Pattern Analysis for OP-MEG Data. Bioengineering (Basel) 2024; 11:609. [PMID: 38927845 PMCID: PMC11200846 DOI: 10.3390/bioengineering11060609] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2024] [Revised: 05/26/2024] [Accepted: 06/11/2024] [Indexed: 06/28/2024] Open
Abstract
Multivariate pattern analysis (MVPA) has played an extensive role in interpreting brain activity, which has been applied in studies with modalities such as functional Magnetic Resonance Imaging (fMRI), Magnetoencephalography (MEG) and Electroencephalography (EEG). The advent of wearable MEG systems based on optically pumped magnetometers (OPMs), i.e., OP-MEG, has broadened the application of bio-magnetism in the realm of neuroscience. Nonetheless, it also raises challenges in temporal decoding analysis due to the unique attributes of OP-MEG itself. The efficacy of decoding performance utilizing multimodal fusion, such as MEG-EEG, also remains to be elucidated. In this regard, we investigated the impact of several factors, such as processing methods, models and modalities, on the decoding outcomes of OP-MEG. Our findings indicate that the number of averaged trials, dimensionality reduction (DR) methods, and the number of cross-validation folds significantly affect the decoding performance of OP-MEG data. Additionally, decoding results vary across modalities and fusion strategy. In contrast, decoder type, resampling frequency, and sliding window length exert marginal effects. Furthermore, we introduced mutual information (MI) to investigate how information loss due to OP-MEG data processing affect decoding accuracy. Our study offers insights for linear decoding research using OP-MEG and expand its application in the fields of cognitive neuroscience.
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Affiliation(s)
- Huanqi Wu
- Key Laboratory of Ultra-Weak Magnetic Field Measurement Technology, Ministry of Education, School of Instrumentation and Optoelectronic Engineering, Beihang University, 37 Xueyuan Rd., Haidian Dist., Beijing 100083, China; (H.W.); (R.W.); (Y.M.); (X.L.); (C.L.)
- Hangzhou Institute of National Extremely-Weak Magnetic Field Infrastructure, 465 Binan Rd., Binjiang Dist., Hangzhou 310000, China
| | - Ruonan Wang
- Key Laboratory of Ultra-Weak Magnetic Field Measurement Technology, Ministry of Education, School of Instrumentation and Optoelectronic Engineering, Beihang University, 37 Xueyuan Rd., Haidian Dist., Beijing 100083, China; (H.W.); (R.W.); (Y.M.); (X.L.); (C.L.)
- Hangzhou Institute of National Extremely-Weak Magnetic Field Infrastructure, 465 Binan Rd., Binjiang Dist., Hangzhou 310000, China
| | - Yuyu Ma
- Key Laboratory of Ultra-Weak Magnetic Field Measurement Technology, Ministry of Education, School of Instrumentation and Optoelectronic Engineering, Beihang University, 37 Xueyuan Rd., Haidian Dist., Beijing 100083, China; (H.W.); (R.W.); (Y.M.); (X.L.); (C.L.)
- Hangzhou Institute of National Extremely-Weak Magnetic Field Infrastructure, 465 Binan Rd., Binjiang Dist., Hangzhou 310000, China
| | - Xiaoyu Liang
- Key Laboratory of Ultra-Weak Magnetic Field Measurement Technology, Ministry of Education, School of Instrumentation and Optoelectronic Engineering, Beihang University, 37 Xueyuan Rd., Haidian Dist., Beijing 100083, China; (H.W.); (R.W.); (Y.M.); (X.L.); (C.L.)
- Hangzhou Institute of National Extremely-Weak Magnetic Field Infrastructure, 465 Binan Rd., Binjiang Dist., Hangzhou 310000, China
| | - Changzeng Liu
- Key Laboratory of Ultra-Weak Magnetic Field Measurement Technology, Ministry of Education, School of Instrumentation and Optoelectronic Engineering, Beihang University, 37 Xueyuan Rd., Haidian Dist., Beijing 100083, China; (H.W.); (R.W.); (Y.M.); (X.L.); (C.L.)
- Hangzhou Institute of National Extremely-Weak Magnetic Field Infrastructure, 465 Binan Rd., Binjiang Dist., Hangzhou 310000, China
| | - Dexin Yu
- Shandong Key Laboratory for Magnetic Field-Free Medicine and Functional Imaging, Institute of Magnetic Field-Free Medicine and Functional Imaging, Shandong University, 27 South Shanda Rd., Licheng Dist., Jinan 250100, China;
| | - Nan An
- Hangzhou Institute of National Extremely-Weak Magnetic Field Infrastructure, 465 Binan Rd., Binjiang Dist., Hangzhou 310000, China
| | - Xiaolin Ning
- Key Laboratory of Ultra-Weak Magnetic Field Measurement Technology, Ministry of Education, School of Instrumentation and Optoelectronic Engineering, Beihang University, 37 Xueyuan Rd., Haidian Dist., Beijing 100083, China; (H.W.); (R.W.); (Y.M.); (X.L.); (C.L.)
- Hangzhou Institute of National Extremely-Weak Magnetic Field Infrastructure, 465 Binan Rd., Binjiang Dist., Hangzhou 310000, China
- Shandong Key Laboratory for Magnetic Field-Free Medicine and Functional Imaging, Institute of Magnetic Field-Free Medicine and Functional Imaging, Shandong University, 27 South Shanda Rd., Licheng Dist., Jinan 250100, China;
- Hefei National Laboratory, Gaoxin Dist., Hefei 230093, China
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Mutanen TP, Ilmoniemi I, Atti I, Metsomaa J, Ilmoniemi RJ. A simulation study: comparing independent component analysis and signal-space projection - source-informed reconstruction for rejecting muscle artifacts evoked by transcranial magnetic stimulation. Front Hum Neurosci 2024; 18:1324958. [PMID: 38784523 PMCID: PMC11112076 DOI: 10.3389/fnhum.2024.1324958] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2023] [Accepted: 04/02/2024] [Indexed: 05/25/2024] Open
Abstract
Introduction The combination of transcranial magnetic stimulation (TMS) and electroencephalography (EEG) allows researchers to explore cortico-cortical connections. To study effective connections, the first few tens of milliseconds of the TMS-evoked potentials are the most critical. Yet, TMS-evoked artifacts complicate the interpretation of early-latency data. Data-processing strategies like independent component analysis (ICA) and the combined signal-space projection-source-informed reconstruction approach (SSP-SIR) are designed to mitigate artifacts, but their objective assessment is challenging because the true neuronal EEG responses under large-amplitude artifacts are generally unknown. Through simulations, we quantified how the spatiotemporal properties of the artifacts affect the cleaning performances of ICA and SSP-SIR. Methods We simulated TMS-induced muscle artifacts and superposed them on pre-processed TMS-EEG data, serving as the ground truth. The simulated muscle artifacts were varied both in terms of their topography and temporal profiles. The signals were then cleaned using ICA and SSP-SIR, and subsequent comparisons were made with the ground truth data. Results ICA performed better when the artifact time courses were highly variable across the trials, whereas the effectiveness of SSP-SIR depended on the congruence between the artifact and neuronal topographies, with the performance of SSP-SIR being better when difference between topographies was larger. Overall, SSP-SIR performed better than ICA across the tested conditions. Based on these simulations, SSP-SIR appears to be more effective in suppressing TMS-evoked muscle artifacts. These artifacts are shown to be highly time-locked to the TMS pulse and manifest in topographies that differ substantially from the patterns of neuronal potentials. Discussion Selecting between ICA and SSP-SIR should be guided by the characteristics of the artifacts. SSP-SIR might be better equipped for suppressing time-locked artifacts, provided that their topographies are sufficiently different from the neuronal potential patterns of interest, and that the SSP-SIR algorithm can successfully find those artifact topographies from the high-pass-filtered data. ICA remains a powerful tool for rejecting artifacts that are not strongly time locked to the TMS pulse.
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Affiliation(s)
- Tuomas Petteri Mutanen
- Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, Espoo, Finland
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Iivanainen J, Carter TR, Trumbo MCS, McKay J, Taulu S, Wang J, Stephen JM, Schwindt PDD, Borna A. Single-trial classification of evoked responses to auditory tones using OPM- and SQUID-MEG. J Neural Eng 2023; 20:056032. [PMID: 37748476 DOI: 10.1088/1741-2552/acfcd9] [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: 06/12/2023] [Accepted: 09/25/2023] [Indexed: 09/27/2023]
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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Affiliation(s)
- Joonas Iivanainen
- Sandia National Laboratories, Albuquerque, NM 87185, United States of America
| | - Tony R Carter
- Sandia National Laboratories, Albuquerque, NM 87185, United States of America
| | - Michael C S Trumbo
- Sandia National Laboratories, Albuquerque, NM 87185, United States of America
| | - Jim McKay
- Candoo Systems Inc, Port Coquitlam, BC, Canada
| | - Samu Taulu
- University of Washington, Seattle, WA, United States of America
| | - Jun Wang
- Department of Speech, Language, and Hearing Sciences, The University of Texas at Austin, Austin, TX, United States of America
- Department of Neurology, The University of Texas at Austin, Austin, TX, United States of America
| | - Julia M Stephen
- The Mind Research Network a Division of Lovelace Biomedical Research Institute, Albuquerque, NM 87106, United States of America
| | - Peter D D Schwindt
- Sandia National Laboratories, Albuquerque, NM 87185, United States of America
| | - Amir Borna
- Sandia National Laboratories, Albuquerque, NM 87185, United States of America
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Holmes N, Rea M, Hill RM, Leggett J, Edwards LJ, Hobson PJ, Boto E, Tierney TM, Rier L, Rivero GR, Shah V, Osborne J, Fromhold TM, Glover P, Brookes MJ, Bowtell R. Enabling ambulatory movement in wearable magnetoencephalography with matrix coil active magnetic shielding. Neuroimage 2023; 274:120157. [PMID: 37149237 PMCID: PMC10465235 DOI: 10.1016/j.neuroimage.2023.120157] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2023] [Revised: 04/13/2023] [Accepted: 05/03/2023] [Indexed: 05/08/2023] Open
Abstract
The ability to collect high-quality neuroimaging data during ambulatory participant movement would enable a wealth of neuroscientific paradigms. Wearable magnetoencephalography (MEG) based on optically pumped magnetometers (OPMs) has the potential to allow participant movement during a scan. However, the strict zero magnetic field requirement of OPMs means that systems must be operated inside a magnetically shielded room (MSR) and also require active shielding using electromagnetic coils to cancel residual fields and field changes (due to external sources and sensor movements) that would otherwise prevent accurate neuronal source reconstructions. Existing active shielding systems only compensate fields over small, fixed regions and do not allow ambulatory movement. Here we describe the matrix coil, a new type of active shielding system for OPM-MEG which is formed from 48 square unit coils arranged on two planes which can compensate magnetic fields in regions that can be flexibly placed between the planes. Through the integration of optical tracking with OPM data acquisition, field changes induced by participant movement are cancelled with low latency (25 ms). High-quality MEG source data were collected despite the presence of large (65 cm translations and 270° rotations) ambulatory participant movements.
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Affiliation(s)
- Niall Holmes
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham NG7 2RD, UK; Cerca Magnetics Limited, Unit 2 Castlebridge Office Village, Kirtley Drive, Nottingham NG7 1LD, UK.
| | - Molly Rea
- Cerca Magnetics Limited, Unit 2 Castlebridge Office Village, Kirtley Drive, Nottingham NG7 1LD, UK; Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham NG7 2RD, UK
| | - Ryan M Hill
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham NG7 2RD, UK; Cerca Magnetics Limited, Unit 2 Castlebridge Office Village, Kirtley Drive, Nottingham NG7 1LD, UK
| | - James Leggett
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham NG7 2RD, UK
| | - Lucy J Edwards
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham NG7 2RD, UK
| | - Peter J Hobson
- School of Physics and Astronomy, University of Nottingham, University Park, Nottingham NG7 2RD, UK
| | - Elena Boto
- Cerca Magnetics Limited, Unit 2 Castlebridge Office Village, Kirtley Drive, Nottingham NG7 1LD, UK; Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham NG7 2RD, UK
| | - Tim M Tierney
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London WC1N 3AR, UK
| | - Lukas Rier
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham NG7 2RD, UK
| | - Gonzalo Reina Rivero
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham NG7 2RD, UK; Cerca Magnetics Limited, Unit 2 Castlebridge Office Village, Kirtley Drive, Nottingham NG7 1LD, UK
| | - Vishal Shah
- QuSpin Inc., 331 South 104th Street, Suite 130, Louisville, CO 80027, USA
| | - James Osborne
- QuSpin Inc., 331 South 104th Street, Suite 130, Louisville, CO 80027, USA
| | - T Mark Fromhold
- School of Physics and Astronomy, University of Nottingham, University Park, Nottingham NG7 2RD, UK
| | - Paul Glover
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham NG7 2RD, UK
| | - Matthew J Brookes
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham NG7 2RD, UK; Cerca Magnetics Limited, Unit 2 Castlebridge Office Village, Kirtley Drive, Nottingham NG7 1LD, UK
| | - Richard Bowtell
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham NG7 2RD, UK
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8
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Xiang J, Yu X, Bonnette S, Anand M, Riehm CD, Schlink B, Diekfuss JA, Myer GD, Jiang Y. Improved Biomagnetic Signal-To-Noise Ratio and Source Localization Using Optically Pumped Magnetometers with Synthetic Gradiometers. Brain Sci 2023; 13:663. [PMID: 37190628 PMCID: PMC10136792 DOI: 10.3390/brainsci13040663] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2023] [Revised: 04/10/2023] [Accepted: 04/13/2023] [Indexed: 05/17/2023] Open
Abstract
Optically pumped magnetometers (OPMs) can capture brain activity but are susceptible to magnetic noise. The objective of this study was to evaluate a novel methodology used to reduce magnetic noise in OPM measurements. A portable magnetoencephalography (MEG) prototype was developed with OPMs. The OPMs were divided into primary sensors and reference sensors. For each primary sensor, a synthetic gradiometer (SG) was constructed by computing a secondary sensor that simulated noise with signals from the reference sensors. MEG data from a phantom with known source signals and six human participants were used to assess the efficacy of the SGs. Magnetic noise in the OPM data appeared predominantly in a low frequency range (<4 Hz) and varied among OPMs. The SGs significantly reduced magnetic noise (p < 0.01), enhanced the signal-to-noise ratio (SNR) (p < 0.001) and improved the accuracy of source localization (p < 0.02). The SGs precisely revealed movement-evoked magnetic fields in MEG data recorded from human participants. SGs provided an effective method to enhance SNR and improve the accuracy of source localization by suppressing noise. Software-simulated SGs may provide new opportunities regarding the use of OPM measurements in various clinical and research applications, especially those in which movement is relevant.
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Affiliation(s)
- Jing Xiang
- MEG Center, Division of Neurology, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH 45229, USA
| | - Xiaoqian Yu
- Laureate Institute for Brain Research, 6655 S Yale Ave., Tulsa, OK 74136, USA
| | - Scott Bonnette
- Division of Sports Medicine, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH 45229, USA
| | - Manish Anand
- Emory Sport Performance and Research Center (SPARC), Emory University, Flowery Branch, GA 30542, USA
- Emory Sports Medicine Center, Emory Healthcare, Atlanta, GA 30329, USA
- Department of Orthopaedics, Emory University School of Medicine, Atlanta, GA 45267, USA
| | - Christopher D. Riehm
- Emory Sport Performance and Research Center (SPARC), Emory University, Flowery Branch, GA 30542, USA
- Emory Sports Medicine Center, Emory Healthcare, Atlanta, GA 30329, USA
- Department of Orthopaedics, Emory University School of Medicine, Atlanta, GA 45267, USA
| | - Bryan Schlink
- Emory Sport Performance and Research Center (SPARC), Emory University, Flowery Branch, GA 30542, USA
| | - Jed A. Diekfuss
- Emory Sport Performance and Research Center (SPARC), Emory University, Flowery Branch, GA 30542, USA
- Emory Sports Medicine Center, Emory Healthcare, Atlanta, GA 30329, USA
- Department of Orthopaedics, Emory University School of Medicine, Atlanta, GA 45267, USA
| | - Gregory D. Myer
- Emory Sport Performance and Research Center (SPARC), Emory University, Flowery Branch, GA 30542, USA
- Emory Sports Medicine Center, Emory Healthcare, Atlanta, GA 30329, USA
- Department of Orthopaedics, Emory University School of Medicine, Atlanta, GA 45267, USA
- The Micheli Center for Sports Injury Prevention, Waltham, MA 02453, USA
| | - Yang Jiang
- Department of Behavioral Science, University of Kentucky College of Medicine, Lexington, KY 40536, USA
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9
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Everaert K, Sander T, Körber R, Löwa N, Van Waeyenberge B, Leliaert J, Wiekhorst F. Monitoring magnetic nanoparticle clustering and immobilization with thermal noise magnetometry using optically pumped magnetometers. NANOSCALE ADVANCES 2023; 5:2341-2351. [PMID: 37056624 PMCID: PMC10089116 DOI: 10.1039/d3na00016h] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/08/2023] [Accepted: 03/15/2023] [Indexed: 06/19/2023]
Abstract
Thermal noise magnetometry (TNM) is a recently developed magnetic characterization technique where thermally induced fluctuations in magnetization are measured to gain insight into nanomagnetic structures like magnetic nanoparticles (MNPs). Due to the stochastic nature of the method, its signal amplitude scales with the square of the volume of the individual fluctuators, which makes the method therefore extra attractive to study MNP clustering and aggregation processes. Until now, TNM signals have exclusively been detected by using a superconducting quantum interference device (SQUID) sensor. In contrast, we present here a tabletop setup using optically pumped magnetometers (OPMs) in a compact magnetic shield, as a flexible alternative. The agreement between results obtained with both measurement systems is shown for different commercially available MNP samples. We argue that the OPM setup with low complexity complements the SQUID setup with high sensitivity and bandwidth. Furthermore, the OPM tabletop setup is well suited to monitor aggregation processes because of its excellent sensitivity in lower frequencies. As a proof of concept, we show the changes in the noise spectrum for three different MNP immobilization and clustering processes. From our results, we conclude that the tabletop setup offers a flexible and widely adoptable measurement unit to monitor the immobilization, aggregation, and clustering of MNPs for different applications, including interactions of the particles with biological systems and the long-term stability of magnetic samples.
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Affiliation(s)
- Katrijn Everaert
- Department of Biosignals, Physikalisch-Technische Bundesanstalt Abbestraße 2-12 10587 Berlin Germany
- Ghent University, Department of Solid State Sciences Krijgslaan 281/S1 9000 Gent Belgium
| | - Tilmann Sander
- Department of Biosignals, Physikalisch-Technische Bundesanstalt Abbestraße 2-12 10587 Berlin Germany
| | - Rainer Körber
- Department of Biosignals, Physikalisch-Technische Bundesanstalt Abbestraße 2-12 10587 Berlin Germany
| | - Norbert Löwa
- Department of Biosignals, Physikalisch-Technische Bundesanstalt Abbestraße 2-12 10587 Berlin Germany
| | - Bartel Van Waeyenberge
- Ghent University, Department of Solid State Sciences Krijgslaan 281/S1 9000 Gent Belgium
| | - Jonathan Leliaert
- Ghent University, Department of Solid State Sciences Krijgslaan 281/S1 9000 Gent Belgium
| | - Frank Wiekhorst
- Department of Biosignals, Physikalisch-Technische Bundesanstalt Abbestraße 2-12 10587 Berlin Germany
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10
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Hillebrand A, Holmes N, Sijsma N, O'Neill GC, Tierney TM, Liberton N, Stam AH, van Klink N, Stam CJ, Bowtell R, Brookes MJ, Barnes GR. Non-invasive measurements of ictal and interictal epileptiform activity using optically pumped magnetometers. Sci Rep 2023; 13:4623. [PMID: 36944674 PMCID: PMC10030968 DOI: 10.1038/s41598-023-31111-y] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2022] [Accepted: 03/06/2023] [Indexed: 03/23/2023] Open
Abstract
Magneto- and electroencephalography (MEG/EEG) are important techniques for the diagnosis and pre-surgical evaluation of epilepsy. Yet, in current cryogen-based MEG systems the sensors are offset from the scalp, which limits the signal-to-noise ratio (SNR) and thereby the sensitivity to activity from deep structures such as the hippocampus. This effect is amplified in children, for whom adult-sized fixed-helmet systems are typically too big. Moreover, ictal recordings with fixed-helmet systems are problematic because of limited movement tolerance and/or logistical considerations. Optically Pumped Magnetometers (OPMs) can be placed directly on the scalp, thereby improving SNR and enabling recordings during seizures. We aimed to demonstrate the performance of OPMs in a clinical population. Seven patients with challenging cases of epilepsy underwent MEG recordings using a 12-channel OPM-system and a 306-channel cryogen-based whole-head system: three adults with known deep or weak (low SNR) sources of interictal epileptiform discharges (IEDs), along with three children with focal epilepsy and one adult with frequent seizures. The consistency of the recorded IEDs across the two systems was assessed. In one patient the OPMs detected IEDs that were not found with the SQUID-system, and in two patients no IEDs were found with either system. For the other patients the OPM data were remarkably consistent with the data from the cryogenic system, noting that these were recorded in different sessions, with comparable SNRs and IED-yields overall. Importantly, the wearability of OPMs enabled the recording of seizure activity in a patient with hyperkinetic movements during the seizure. The observed ictal onset and semiology were in agreement with previous video- and stereo-EEG recordings. The relatively affordable technology, in combination with reduced running and maintenance costs, means that OPM-based MEG could be used more widely than current MEG systems, and may become an affordable alternative to scalp EEG, with the potential benefits of increased spatial accuracy, reduced sensitivity to volume conduction/field spread, and increased sensitivity to deep sources. Wearable MEG thus provides an unprecedented opportunity for epilepsy, and given its patient-friendliness, we envisage that it will not only be used for presurgical evaluation of epilepsy patients, but also for diagnosis after a first seizure.
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Affiliation(s)
- Arjan Hillebrand
- Department of Clinical Neurophysiology and Magnetoencephalography Center, Amsterdam UMC Location Vrije Universiteit Amsterdam, De Boelelaan 1117, 1081HV, Amsterdam, The Netherlands.
- Brain Imaging, Amsterdam Neuroscience, Amsterdam, The Netherlands.
- Systems and Network Neurosciences, Amsterdam Neuroscience, Amsterdam, The Netherlands.
| | - Niall Holmes
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, NG7 2RD, UK
| | - Ndedi Sijsma
- Department of Clinical Neurophysiology and Magnetoencephalography Center, Amsterdam UMC Location Vrije Universiteit Amsterdam, De Boelelaan 1117, 1081HV, Amsterdam, The Netherlands
| | - George C O'Neill
- Wellcome Centre for Human Neuroimaging, Department of Imaging Neuroscience, UCL Queen Square Institute of Neurology, University College London, London, WC1N 3AR, UK
| | - Tim M Tierney
- Wellcome Centre for Human Neuroimaging, Department of Imaging Neuroscience, UCL Queen Square Institute of Neurology, University College London, London, WC1N 3AR, UK
| | - Niels Liberton
- Department of Medical Technology, 3D Innovation Lab, Amsterdam UMC Location Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Anine H Stam
- Department of Clinical Neurophysiology and Magnetoencephalography Center, Amsterdam UMC Location Vrije Universiteit Amsterdam, De Boelelaan 1117, 1081HV, Amsterdam, The Netherlands
| | - Nicole van Klink
- Department of Neurology and Neurosurgery, UMC Utrecht Brain Center, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX, Utrecht, The Netherlands
| | - Cornelis J Stam
- Department of Clinical Neurophysiology and Magnetoencephalography Center, Amsterdam UMC Location Vrije Universiteit Amsterdam, De Boelelaan 1117, 1081HV, Amsterdam, The Netherlands
- Brain Imaging, Amsterdam Neuroscience, Amsterdam, The Netherlands
- Neurodegeneration, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Richard Bowtell
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, NG7 2RD, UK
| | - Matthew J Brookes
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, NG7 2RD, UK
| | - Gareth R Barnes
- Wellcome Centre for Human Neuroimaging, Department of Imaging Neuroscience, UCL Queen Square Institute of Neurology, University College London, London, WC1N 3AR, UK
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11
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Petrenko M, Vershovskii A. Towards a Practical Implementation of a Single-Beam All-Optical Non-Zero-Field Magnetic Sensor for Magnetoencephalographic Complexes. SENSORS (BASEL, SWITZERLAND) 2022; 22:9862. [PMID: 36560230 PMCID: PMC9784752 DOI: 10.3390/s22249862] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/22/2022] [Revised: 12/02/2022] [Accepted: 12/12/2022] [Indexed: 06/17/2023]
Abstract
We present a single-beam all-optical two-channel magnetic sensor scheme developed for biological applications such as non-zero-field magnetoencephalography and magnetocardiography. The pumping, excitation and detection of magnetic resonance in two cells are performed using a single laser beam with time-modulated linear polarization: the linear polarization of the beam switches to orthogonal every half-cycle of the Larmor frequency. Light with such characteristics can be transmitted over a single-mode polarization-maintaining fiber without any loss in the quality of the polarization characteristics. We also present an algorithm for calculating optical elements in a sensor scheme, the results of measuring the parametric dependences of magnetic resonance in cells, and the results of direct testing of a sensor in a magnetic shield. We demonstrate sensitivity at the level of 20 fT/√Hz in one sensor channel in the frequency range of 80-200 Hz.
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12
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Bezsudnova Y, Koponen LM, Barontini G, Jensen O, Kowalczyk AU. Optimising the sensing volume of OPM sensors for MEG source reconstruction. Neuroimage 2022; 264:119747. [PMID: 36403733 PMCID: PMC7615061 DOI: 10.1016/j.neuroimage.2022.119747] [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: 06/07/2022] [Revised: 10/17/2022] [Accepted: 11/08/2022] [Indexed: 11/19/2022] Open
Abstract
Magnetoencephalography (MEG) based on optically pumped magnetometers (OPMs) has been hailed as the future of electrophysiological recordings from the human brain. In this work, we investigate how the dimensions of the sensing volume (the vapour cell) affect the performance of both a single OPM-MEG sensor and a multi-sensor OPM-MEG system. We consider a realistic noise model that accounts for background brain activity and residual noise. By using source reconstruction metrics such as localization accuracy and time-course reconstruction accuracy, we demonstrate that the best overall sensitivity and reconstruction accuracy are achieved with cells that are significantly longer and wider that those of the majority of current commercial OPM sensors. Our work provides useful tools to optimise the cell dimensions of OPM sensors in a wide range of environments.
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Affiliation(s)
- Yulia Bezsudnova
- School of Physics and Astronomy, University of Birmingham, Edgbaston, Birmingham, B15 2TT, United Kingdom
| | - Lari M Koponen
- Centre for Human Brain Health, School of Psychology, University of Birmingham, Edgbaston, Birmingham, B15 2SA, United Kingdom
| | - Giovanni Barontini
- School of Physics and Astronomy, University of Birmingham, Edgbaston, Birmingham, B15 2TT, United Kingdom; Centre for Human Brain Health, School of Psychology, University of Birmingham, Edgbaston, Birmingham, B15 2SA, United Kingdom
| | - Ole Jensen
- Centre for Human Brain Health, School of Psychology, University of Birmingham, Edgbaston, Birmingham, B15 2SA, United Kingdom
| | - Anna U Kowalczyk
- Centre for Human Brain Health, School of Psychology, University of Birmingham, Edgbaston, Birmingham, B15 2SA, United Kingdom.
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13
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Marhl U, Sander T, Jazbinšek V. Simulation Study of Different OPM-MEG Measurement Components. SENSORS 2022; 22:s22093184. [PMID: 35590874 PMCID: PMC9105726 DOI: 10.3390/s22093184] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/16/2022] [Revised: 04/15/2022] [Accepted: 04/20/2022] [Indexed: 02/04/2023]
Abstract
Magnetoencephalography (MEG) is a neuroimaging technique that measures the magnetic fields of the brain outside of the head. In the past, the most suitable magnetometer for MEG was the superconducting quantum interference device (SQUID), but in recent years, a new type has also been used, the optically pumped magnetometer (OPM). OPMs can be configured to measure multiple directions of magnetic field simultaneously. This work explored whether combining multiple directions of the magnetic field lowers the source localization error of brain sources under various conditions of noise. We simulated dipolar-like sources for multiple configurations of both SQUID- and OPM-MEG systems. To test the performance of a given layout, we calculated the average signal-to-noise ratio and the root mean square of the simulated magnetic field; furthermore, we evaluated the performance of the dipole fit. The results showed that the field direction normal to the scalp yields a higher signal-to-noise ratio and that ambient noise has a much lower impact on its localization error; therefore, this is the optimal choice for source localization when only one direction of magnetic field can be measured. For a low number of OPMs, combining multiple field directions greatly improves the source localization results. Lastly, we showed that MEG sensors that can be placed closer to the brain are more suitable for localizing deeper sources.
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Affiliation(s)
- Urban Marhl
- Faculty of Natural Sciences and Mathematics, University of Maribor, Koroška cesta 160, 2000 Maribor, Slovenia
- Department of Physics, Institute of Mathematics, Physics and Mechanics, Jadranska ulica 19, 1000 Ljubljana, Slovenia;
- Correspondence:
| | - Tilmann Sander
- Physikalisch-Technische Bundesanstalt, Abbestraße 2, 10587 Berlin, Germany;
| | - Vojko Jazbinšek
- Department of Physics, Institute of Mathematics, Physics and Mechanics, Jadranska ulica 19, 1000 Ljubljana, Slovenia;
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