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Wang R, Wu H, Liang X, Cao F, Xiang M, Gao Y, Ning X. Optimization of Signal Space Separation for Optically Pumped Magnetometer in Magnetoencephalography. Brain Topogr 2023; 36:350-370. [PMID: 37046041 DOI: 10.1007/s10548-023-00957-w] [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: 12/12/2022] [Accepted: 03/30/2023] [Indexed: 04/14/2023]
Abstract
Magnetoencephalography (MEG) is a noninvasive functional neuroimaging modality but highly susceptible to environmental interference. Signal space separation (SSS) is a method for improving the SNR to separate the MEG signals from external interference. The origin and truncation values of SSS significantly affect the SSS performance. The origin value fluctuates with respect to the helmet array, and determining the truncation values using the traversal method is time-consuming; thus, this method is inappropriate for optically pumped magnetometer (OPM) systems with flexible array designs. Herein, an automatic optimization method for the SSS parameters is proposed. Virtual sources are set inside and outside the brain to simulate the signals of interest and interference, respectively, via forward model, with the sensor array as prior information. The objective function is determined as the error between the signals from simulated sources inside the brain and the SSS reconstructed signals; thus, the optimized parameters are solved inversely by minimizing the objective function. To validate the proposed method, a simulation analysis and MEG auditory-evoked experiments were conducted. For an OPM sensor array, this method can precisely determine the optimized origin and truncation values of the SSS simultaneously, and the auditory-evoked component, for example, N100, can be accurately located in the temporal cortex. The proposed optimization procedure outperforms the traditional method with regard to the computation time and accuracy, simplifying the SSS process in signal preprocessing and enhancing the performance of SSS denoising.
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Affiliation(s)
- Ruonan Wang
- Key Laboratory of Ultra-Weak Magnetic Field Measurement Technology, Ministry of Education, School of Instrumentation and Optoelectronic Engineering, Beihang University, Beijing, 100191, China
| | - Huanqi Wu
- Key Laboratory of Ultra-Weak Magnetic Field Measurement Technology, Ministry of Education, School of Instrumentation and Optoelectronic Engineering, Beihang University, Beijing, 100191, China
| | - Xiaoyu Liang
- Key Laboratory of Ultra-Weak Magnetic Field Measurement Technology, Ministry of Education, School of Instrumentation and Optoelectronic Engineering, Beihang University, Beijing, 100191, 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
| | - 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
- Zhejiang Provincial Key Laboratory of Ultra-Weak Magnetic-Field Space and Applied Technology, Hangzhou Innovation Institute, Beihang University, Hangzhou, 310051, China
| | - Yang Gao
- 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.
| | - 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.
- Zhejiang Provincial Key Laboratory of Ultra-Weak Magnetic-Field Space and Applied Technology, Hangzhou Innovation Institute, Beihang University, Hangzhou, 310051, China.
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Westin K, Pfeiffer C, Andersen LM, Ruffieux S, Cooray G, Kalaboukhov A, Winkler D, Ingvar M, Schneiderman J, Lundqvist D. Detection of interictal epileptiform discharges: A comparison of on-scalp MEG and conventional MEG measurements. Clin Neurophysiol 2020; 131:1711-1720. [DOI: 10.1016/j.clinph.2020.03.041] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2019] [Revised: 03/06/2020] [Accepted: 03/30/2020] [Indexed: 10/24/2022]
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Pfeiffer C, Ruffieux S, Jonsson L, Chukharkin ML, Kalaboukhov A, Xie M, Winkler D, Schneiderman JF. A 7-Channel High-${T}_\text{c}$ SQUID-Based On-Scalp MEG System. IEEE Trans Biomed Eng 2020; 67:1483-1489. [DOI: 10.1109/tbme.2019.2938688] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
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Abstract
Optically pumped magnetometers (OPMs) operating in the spin-exchange relaxation-free regime are emerging as alternative sensors to superconducting quantum interference devices (SQUIDs) for magnetoencephalography (MEG). As the number of OPMs in a single imaging system increases to rival SQUID MEG systems, cross-talk between nearby sensors limits the measurement accuracy. We experimentally demonstrate a coil geometry, which generates an order of magnitude less cross-talk (less than 0.5%) than a Helmholtz coil (8%). The new coil design is simple and compact, requiring two coaxial coil pairs that add 1 mm to the 6 mm radius and is driven by a single current driver. The new design maintains a magnetic field homogeneity over the volume of the magnetometer of more than 94%, which is sufficient for the zero-field OPM to operate in a 200 nT ambient field environment. Our result increases the feasibility of high-spatial resolution OPM-based bio-magnetic imaging technology due to the reduction of cross-talk at high sensor density.
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Affiliation(s)
- N V Nardelli
- University of Colorado Boulder, Boulder, CO 80309, United States of America
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Andersen LM, Oostenveld R, Pfeiffer C, Ruffieux S, Jousmäki V, Hämäläinen M, Schneiderman JF, Lundqvist D. Similarities and differences between on-scalp and conventional in-helmet magnetoencephalography recordings. PLoS One 2017; 12:e0178602. [PMID: 28742118 PMCID: PMC5524409 DOI: 10.1371/journal.pone.0178602] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2017] [Accepted: 05/16/2017] [Indexed: 11/19/2022] Open
Abstract
The development of new magnetic sensor technologies that promise sensitivities approaching that of conventional MEG technology while operating at far lower operating temperatures has catalysed the growing field of on-scalp MEG. The feasibility of on-scalp MEG has been demonstrated via benchmarking of new sensor technologies performing neuromagnetic recordings in close proximity to the head surface against state-of-the-art in-helmet MEG sensor technology. However, earlier work has provided little information about how these two approaches compare, or about the reliability of observed differences. Herein, we present such a comparison, based on recordings of the N20m component of the somatosensory evoked field as elicited by electric median nerve stimulation. As expected from the proximity differences between the on-scalp and in-helmet sensors, the magnitude of the N20m activation as recorded with the on-scalp sensor was higher than that of the in-helmet sensors. The dipole pattern of the on-scalp recordings was also more spatially confined than that of the conventional recordings. Our results furthermore revealed unexpected temporal differences in the peak of the N20m component. An analysis protocol was therefore developed for assessing the reliability of this observed difference. We used this protocol to examine our findings in terms of differences in sensor sensitivity between the two types of MEG recordings. The measurements and subsequent analysis raised attention to the fact that great care has to be taken in measuring the field close to the zero-line crossing of the dipolar field, since it is heavily dependent on the orientation of sensors. Taken together, our findings provide reliable evidence that on-scalp and in-helmet sensors measure neural sources in mostly similar ways.
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Affiliation(s)
- Lau M. Andersen
- NatMEG, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
- * E-mail:
| | - Robert Oostenveld
- NatMEG, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, HE Nijmegen, The Netherlands
| | - Christoph Pfeiffer
- Department of Microtechnology and Nanoscience—MC2, Chalmers University of Technology, Gothenburg, Sweden
| | - Silvia Ruffieux
- Department of Microtechnology and Nanoscience—MC2, Chalmers University of Technology, Gothenburg, Sweden
| | - Veikko Jousmäki
- NatMEG, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
- Department of Neuroscience and Biomedical Engineering, Aalto University, Aalto, Espoo, Finland
- Aalto NeuroImaging, Aalto University, Aalto, Espoo, Finland
| | - Matti Hämäläinen
- NatMEG, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
- Department of Neuroscience and Biomedical Engineering, Aalto University, Aalto, Espoo, Finland
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital/Harvard Medical School, Charlestown, MA, United States of America
- Harvard-MIT Division of Health Sciences and Technology, Cambridge, MA, United States of America
| | - Justin F. Schneiderman
- Institute of Neuroscience and Physiology, University of Gothenburg and MedTech West, Göteborg, Sweden
| | - Daniel Lundqvist
- NatMEG, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
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Xie M, Schneiderman JF, Chukharkin ML, Kalabukhov A, Riaz B, Lundqvist D, Whitmarsh S, Hamalainen M, Jousmaki V, Oostenveld R, Winkler D. Benchmarking for On-Scalp MEG Sensors. IEEE Trans Biomed Eng 2017; 64:1270-1276. [DOI: 10.1109/tbme.2016.2599177] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
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Poolos NP. Magnetoencephalography as a Noninvasive Probe of Brain Activity: The State of the Art. Neuroscientist 2016. [DOI: 10.1177/107385849500100303] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Magnetoencephalography (MEG) is a technique for visualizing brain electrical activity by noninvasive recording of associated magnetic fields. MEG has been used to study so matosensory mapping of the human cortex, waves of thalamocortical activation during wakefulness and sleep, and the localization of seizure foci in epilepsy patients. MEG tech niques are still in development, and its use as a tool for real-time imaging of brain electrical activity will depend on advances in the underlying technology. The Neuroscientist 1:127- 129, 1995
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