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Measuring MEG closer to the brain: Performance of on-scalp sensor arrays
Open accessPublished version of a preprint
Abstract
Optically-pumped magnetometers (OPMs) have recently reached sensitivity levels required for magnetoencephalography (MEG). OPMs do not need cryogenics and can thus be placed within millimetres from the scalp into an array that adapts to the individual head size and shape, thereby reducing the distance from cortical sources to the sensors. Here, we quantified the improvement in recording MEG with hypothetical on-scalp OPM arrays compared to a 306-channel state-of-the-art SQUID array (102 magnetometers and 204 planar gradiometers). We simulated OPM arrays that measured either normal (nOPM; 102 sensors), tangential (tOPM; 204 sensors), or all components (aOPM; 306 sensors) of the magnetic field. We built forward models based on magnetic resonance images of 10 adult heads; we employed a three-compartment boundary element model and distributed current dipoles evenly across the cortical mantle. Compared to the SQUID magnetometers, nOPM and tOPM yielded 7.5 and 5.3 times higher signal power, while the correlations between the field patterns of source dipoles were reduced by factors of 2.8 and 3.6, respectively. Values of the field-pattern correlations were similar across nOPM, tOPM and SQUID gradiometers. Volume currents reduced the signals of primary currents on average by 10%, 72% and 15% in nOPM, tOPM and SQUID magnetometers, respectively. The information capacities of the OPM arrays were clearly higher than that of the SQUID array. The dipole-localization accuracies of the arrays were similar while the minimum-norm-based point-spread functions were on average 2.4 and 2.5 times more spread for the SQUID array compared to nOPM and tOPM arrays, respectively.
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“Increased proximity to the scalp can improve sensitivity and spatial resolution beyond that which is achieved using a cryogenic MEG [26,27].”
From Naturalistic Hyperscanning with Wearable Magnetoencephalography (2023) · cites this paper as [27]
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OMMR: Co-registration toolbox of OPM-MEG and MRI
Cao, F., An, N., Xu, W., Wang, W., Li, W., Wang, C., Yang, Y., Xiang, M., Gao, Y., & Ning, X. (2022) · Frontiers in Neuroscience · doi:10.3389/fnins.2022.984036 · Cited by 23
“This results in lower cost and higher signal strength for OPM-MEG (Iivanainen et al., 2017; Boto et al., 2018).”
BackgroundMiniature Coil Array for Passive Magnetocardiography in Non-Shielded Environments
Zhu, K., Shah, A. M., Berkow, J., & Kiourti, A. (2021) · IEEE Journal of Electromagnetics, RF and Microwaves in Medicine and Biology · doi:10.1109/jerm.2020.3019891 · Cited by 22
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Hardware-Based Interference Suppression Techniques for OPM-MEG: A Review
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“MEG can operate at room temperature, so its sensors can be quite close to the scalp, which improves the signal-to-noise ratio (SNR) of the measured signals [6], [7].”
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Towards an Objective Evaluation of EEG/MEG Source Estimation Methods: The Linear Tool KitPreprint
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“(Boto et al., 2018; Iivanainen et al., 2017; Tierney et al., 2019).”
Self-citationA fully integrated whole-head helium OPM MEG: a performance assessment compared to cryogenic MEG
Bonnet, M., Schwartz, D., Gutteling, T. P., Daligault, S., & Labyt, É. (2025) · Frontiers in Medical Technology · doi:10.3389/fmedt.2025.1548260 · Cited by 20
“This advantage of OPM MEG was also reported in several papers (7, 34).”
Optimising the sensing volume of OPM sensors for MEG source reconstruction
Bezsudnova, Y., Koponen, L. M., Barontini, G., Jensen, O. B., & Kowalczyk, A. (2022) · NeuroImage · doi:10.1016/j.neuroimage.2022.119747 · Cited by 21
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BackgroundMethodInfluentialDesign of locally arranged sensor arrays in wearable OPM-MEG based on sensor volume constraints
Wang, W., Cao, F., An, N., Wen, L., Xu, W., Wang, C., Gao, Z., Yu, D., Gao, Y., & Ning, X. (2024) · Measurement · doi:10.1016/j.measurement.2024.114373 · Cited by 21
Optimal Design of Self-Shielded Biplanar Coil Assembly With Miniaturized Structure
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“Numerous studies have investigated miniature multichannel OPM systems [6], [7], [8], [9], [10], [11], [12], [13], [14], [15].”
BackgroundDetermining sensor geometry and gain in a wearable MEG system
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“To this end, OPMs have been introduced as an on-scalp MEG sensor detecting the magnetic field within approximately 5 mm from the scalp and, potentially, enabling higher spatial resolution than that obtained by SQUIDs [22,23].”
Self-citationHigh-Precision Magnetic Field Control of Active Magnetic Compensation System Based on MFAC-RBFNN
Li, Y., Cui, P., Li, H., Yang, Z., & Liu, X. (2024) · IEEE Transactions on Instrumentation and Measurement · doi:10.1109/tim.2024.3394482 · Cited by 17
“…of biomagnetic signals in the human body and their susceptibility to magnetic field disturbances [3], MEG measurements based on OPM are usually performed in magnetic shielding rooms (MSRs), where the extremely weak magnetic field environment can improve the signal-to-noise ratio of the signal [4].”
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“It is interesting to apply these results to on-scalp MEG as it is envisaged by the use of optically pumped magnetometers [20, 21] or high-Tc SQUIDs [22].”
BackgroundBrain‐wide network analysis of resting‐state neuromagnetic data
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Estimates of cortical column orientation improve MEG source inversion
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“These sensors can be worn on the head and permit long-duration recordings without head-to-sensor movement, with accurate knowledge of each sensor’s position with respect to the brain (Boto et al., 2018, 2017; Holmes et al., 2018; Iivanainen et al., 2019, 2017; Knappe et al., 2014).”
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Combining OPM and lesion mapping data for epilepsy surgery planning: a simulation study
Mellor, S., Timms, R. C., O’Neill, G. C., Tierney, T. M., Spedden, M. E., Spitzer, H., Ripart, M., Whitaker, K. J., Napolitano, A., Palma, L. D., et al. (2024) · Scientific Reports · doi:10.1038/s41598-024-51857-3 · Cited by 12
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Yttrium-Iron Garnet Magnetometer in MEG: Advance towards Multi-Channel Arrays
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Wireless optically pumped magnetometer MEG
Cheng, H., He, K., Li, C., Ma, X., Zheng, F., Xu, W., Liao, P., Yang, R., Li, D., Qin, L., et al. (2024) · NeuroImage · doi:10.1016/j.neuroimage.2024.120864 · Cited by 11
“This close proximity not only provides stronger signals but also enhances spatial resolution in identifying the source of brain activity (Iivanainen et al., 2017; Qin and Gao, 2021).”
Wang, X., Teng, P., Meng, Q., Jiang, Y., Wu, J., Li, T., Wang, M., Guan, Y., Zhou, J., Sheng, J., et al. (2024) · Journal of Neural Engineering · doi:10.1088/1741-2552/ad9680 · Cited by 14
“By reducing the distance between sensors and brain activity sources, OPM-MEG enhances sensitivity for detecting the brain’s weak magnetic fields [11, 12].”
Robotic Hand Exoskeletons for Rehabilitation and Assistance: A State-of-the-Art
Chen, B., Wu, Y., Ni, X., Qin, L.-Y., & Li, E. (2024) · Journal of Medical Devices · doi:10.1115/1.4067350 · Cited by 13
Optimizing magnetometers arrays and analysis pipelines for multivariate pattern analysis
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“Second, the sensors can be arranged in an array that better captures the spatial characteristics of the brain signal (Beltrachini et al., 2021; Iivanainen et al., 2017; Brookes et al., 2021).”
Rhodes, N., Rier, L., Boto, E., Hill, R. M., & Brookes, M. J. (2025) · Imaging Neuroscience · doi:10.1162/imag.a.8 · Cited by 11
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“B. WEARABLE PEDIATRIC SERF-MEG INSTRUMENT However, it is the fixed and ‘one-size-fits-all’ configuration of SQUID-MEG that limits its application in developmental studies and diagnosis, since it is unrealistic to expect children with disorders to stay peacefully motionless with their heads in a half-enclosed hollow sp…”
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Sensor array design of optically pumped magnetometers for accurately estimating source currents
Takeda, Y., Gomi, T., Umebayashi, R., Tomita, S., Suzuki, K., Hiroe, N., Saikawa, J., Munaka, T., & Yamashita, O. (2023) · NeuroImage · doi:10.1016/j.neuroimage.2023.120257 · Cited by 13
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“…normal temperature operation, and easy configuration specific sensor layout close to the target brain regions for more precise measurement [6], [7], OPM-MEG can obtain higher signal amplitude, reconstruction accuracy, spatial resolution than SQUID-MEG [8], [9], and has the potential of…”
BackgroundZhao, R., Wang, R., Gao, Y., & Ning, X. (2024) · Biomedical Signal Processing and Control · doi:10.1016/j.bspc.2024.106236 · Cited by 10
A minimum assumption approach to MEG sensor array design
Zhdanov, A. V., Nurminen, J., Iivanainen, J., & Taulu, S. (2023) · Physics in Medicine and Biology · doi:10.1088/1361-6560/ace306 · Cited by 10
Self-citationOptically Pumped Magnetometers for Practical MEG-Based Brain-Computer Interfacing
Wittevrongel, B., Holmes, N., Boto, E., Hill, R., Rea, M., Libert, A., Khachatryan, E., Bowtell, R., Brookes, M. J., & Van Hulle, M. M. (2021) · SpringerBriefs in Electrical and Computer Engineering · doi:10.1007/978-3-030-79287-9_4 · Cited by 9
Decoding N400m Evoked Component: A Tutorial on Multivariate Pattern Analysis for OP-MEG Data
Wu, H., Wang, R., Ma, Y., Liang, X., Liu, C., Yu, D., An, N., & Ning, X. (2024) · Bioengineering · doi:10.3390/bioengineering11060609 · Cited by 9
“…in BCI and cognitive neuroscience has different aims [25,26] and OP-MEG is superior over SQUID-MEG in channel information capacity and SNR [15,27] with a smaller number of channels, we provide a tutorial introduction using an OP-MEG N400 evoked response data with statistical inference across…”
MethodWu, H., Cui, P., Tian, P., Zhang, H., & Zhao, X. (2024) · Measurement · doi:10.1016/j.measurement.2024.115548 · Cited by 9
Superconducting Quantum Magnetometers for Brain Investigations
Bonavolontà, C., Vettoliere, A., Sorrentino, P., & Granata, C. (2025) · Sensors · doi:10.3390/s25154625 · Cited by 12
“Even if the tangential components are smaller than the radial components [75,76], they still contain useful information.”
Niu, Y., & Ye, C. (2023) · IEEE Sensors Journal · doi:10.1109/jsen.2023.3299690 · Cited by 9
“in the spin-exchange relaxation-free (SERF) regime [7], [11].”
A Multivariate analysis on evoked components of Chinese semantic congruity: an OP-MEG study with EEG
Wu, H., Liang, X., Wang, R., Ma, Y., Gao, Y., & Ning, X. (2024) · Cerebral Cortex · doi:10.1093/cercor/bhae108 · Cited by 10
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“This is because the SQUID sensor was located farther from the signal source owing to the thickness of the vacuum layer in the cryostat, whereas the MR sensor was located closer to the signal source [7], [19].”
BackgroundMEG-Based Detection of Voluntary Eye Fixations Used to Control a Computer
Ovchinnikova, A. O., Vasilyev, A. N., Zubarev, I., Kozyrskiy, B. L., & Shishkin, S. L. (2021) · Frontiers in Neuroscience · doi:10.3389/fnins.2021.619591 · Cited by 9
“…to operate, making the system portable and less expensive while providing superior spatial resolution (Boto et al., 2016, 2017, 2018, 2019, 2020; Borna et al., 2017, 2020; Iivanainen et al., 2017, 2019; Hill et al., 2019, 2020; Limes et al., 2020; Zhang R. et al., 2020; Zhang X. et al., 2020).”
BackgroundYan, B., Peng, Y., Zhang, Y., Zhang, Y., Zhang, H., Cao, Y., Sun, C. K., & Ding, M. (2025) · NeuroImage · doi:10.1016/j.neuroimage.2025.121262 · Cited by 8
“…benchmarked OPM-MEG systems against SQUID-MEG systems using methodologies such as beamformer (Boto et al., 2016), Minimum Norm Estimation (MNE) (Iivanainen et al., 2017), and the Cram ´ er-Rao Bound (CRB) (Beltrachini et al., 2021) to investigate the performance differences between a SQUID-MEG…”
Real-Time Localization of OPMs in a Flexible Array During MEG Recordings
Gu, W., He, K., Ma, X., Li, D., Pang, W., Sheng, J., & Gao, J. (2023) · IEEE Transactions on Instrumentation and Measurement · doi:10.1109/tim.2023.3346516 · Cited by 8
“Consequently, OPM-MEG has the potential to provide higher SNR, resulting in higher spatial resolution and deeper insights into the brain [12], [13].”
BackgroundHämäläinen, M., & Lundqvist, D. (2019) · Springer eBooks · doi:10.1007/978-3-030-00087-5_81 · Cited by 8
A visual encoding model links magnetoencephalography signals to neural synchrony in human cortex
Kupers, E. R., Benson, N. C., & Winawer, J. A. (2021) · NeuroImage · doi:10.1016/j.neuroimage.2021.118655 · Cited by 10
A 7-channel high- T c SQUID-based on-scalp MEG systemPreprint
Pfeiffer, C., Ruffieux, S., Jönsson, L., Chukharkin, M. L., Kalaboukhov, A., Xie, M., Winkler, D., & Schneiderman, J. F. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/534107 · Cited by 8
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“These advantages have led to the increased use of OPMs in detecting biomagnetic fields, including applications in MEG [10], [11], [12] and magnetocardiography (MCG) [13].”
BackgroundPotential of 4 He OPM‐MEG for detecting interictal epileptic activity: A comparison with SQUID‐MEG
Schwartz, D., Badier, J., Gutteling, T. P., Daligault, S., Labyt, É., Bonini, F., & Jung, J. (2025) · Epilepsia Open · doi:10.1002/epi4.70139 · Cited by 7
“8,9 Lightweight and flexible, OPMs can be integrated into adaptable motion-tolerant headsets, enabling recordings during seizures or natural head movements, particularly in children, 10 and potentially enhancing the detection of interictal epileptiform discharges (IEDs).”
Helbling, S. (2024) · Imaging Neuroscience · doi:10.1162/imag_a_00410 · Cited by 8
Repairbads: An automatic and adaptive method to repair bad channels and segments for OPM-MEG
Wang, F., Yu-jie, M., Gao, T., Tao, Y., Wang, R., Zhao, R., Cao, F., Gao, Y., & Ning, X. (2025) · NeuroImage · doi:10.1016/j.neuroimage.2024.120996 · Cited by 7
Magnetically shielded high-resolution visual stimulation for OPM-MEG applications
Anders, P., Brickwedde, M., Voigt, J., Grent-‘t-Jong, T., Krüger, P., Haueisen, J., Uhlhaas, P. J., & Sander-Thoemmes, T. (2025) · Biomedical Physics & Engineering Express · doi:10.1088/2057-1976/adb1eb · Cited by 7
Optimal configuration of on-scalp OPMs with fixed channel counts
Schoffelen, J., Cheung, T., Knappe, S. A., & Oostenveld, R. (2025) · Imaging Neuroscience · doi:10.1162/imag.a.22 · Cited by 7
“Monoaxial arrays that measure the component of the magnetic field normal to the head surface are inherently most sensitive to signals that originate from the brain ( Hughett & Miyauchi, 2000; Iivanainen et al., 2017).”
OPM-MEG reveals dynamics of beta bursts underlying attentional processes in sensory cortex
Rivero, G., Tanner, Z., Rier, L., Hill, R. M., Shah, V., Rea, M., Doyle, C., Osborne, J., Bobela, D., Morris, P. G., et al. (2025) · Scientific Reports · doi:10.1038/s41598-025-08037-8 · Cited by 8
“OPMs do not require cryogenics, and can therefore be placed closer to the head (improving signal strength and spatial specificity) 32,40–42 .”
Quantum optical magnetic field sensor for neurodiagnostic systems of a new generation
Petrenko, M. V., Pazgalev, A. S., & Vershovskii, A. K. (2022) · Quantum Electronics · doi:10.1070/qel17978 · Cited by 7
Imaging human cortical responses to intraneural microstimulation using magnetoencephalography
O’Neill, G. C., Watkins, R. H., Ackerley, R., Barratt, E. L., Sengupta, A., Asghar, M., Panchuelo, R. M. S., Brookes, M. J., Glover, P. M., Wessberg, J., et al. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2019.01.017 · Cited by 8
“, 2018, 2017), and since they provide of the order of 5–8 fold improvement in SNR over the central gyri and have sensors which move with the head, these will potentially provide flexibility for combined single-unit INMSwithout compromising on spatial specificity (Boto et al., 2016; Iivanainen et al., 2017).”
BackgroundSpatial sampling of MEG and EEG revisited: From spatial-frequency spectra to model-informed samplingPreprint
Iivanainen, J., Mäkinen, A. J., Zetter, R., Stenroos, M., Ilmoniemi, R. J., & Parkkonen, L. T. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2006.02919 · Cited by 7
“Simulations have shown that the closer proximity of the sensors to the brain improves spatial resolution of MEG and increases information about neuronal currents (Schneiderman, 2014; Boto et al., 2016; Iivanainen et al., 2017; Riaz et al., 2017).”
BackgroundMethodInfluentialSelf-citationPetrenko, M., & Vershovskii, A. (2022) · Sensors · doi:10.3390/s22249862 · Cited by 6
Han, S., Wu, Y., Xiao, L., Jin, Z., & Chen, J. (2025) · Superconductor Science and Technology · doi:10.1088/1361-6668/ada82d · Cited by 6
“…giant magnetoresistance (GMR), or tunnel magnetoresistance (TMR), these sensors still suffer from inherent issues such as relatively large noise and low sensitivity, resulting in the magnetic field resolution lagging behind magnetic sensors like SQUIDs and optically pumped magnetometers [7–13].”
Dynamic field nulling method for magnetically shielded room based on Smith predictor assisted GADRC
Zhao, J., Zhang, W., Sun, J., & Zhang, H. (2025) · Sensors and Actuators A Physical · doi:10.1016/j.sna.2025.116394 · Cited by 6
Modulation crosstalk effect analysis on single-beam SERF atomic magnetic gradiometer
Chen, T., Zheng, Z., Zhang, J., Chen, Z., Chen, W., Ou, Z., Yue, H., & Liu, Y. (2025) · Measurement · doi:10.1016/j.measurement.2025.117782 · Cited by 6
Xu, X., Zhai, Y., Zhao, B., Zhang, Y., Yue, Z., & Tang, J. (2025) · IEEE Transactions on Instrumentation and Measurement · doi:10.1109/tim.2025.3612562 · Cited by 6
“Most notably, OPMs operated in the spin-exchange relaxation-free (SERF) regime have achieved remarkable sensitivity on the order of sub-fT / Hz 1 / 2 [9], [10], surpassing the performance of traditional superconducting quantum interference devices (SQUIDs) [11], [12], [13].”
Towards a 384-channel magnetoencephalography system based on optically pumped magnetometers
Schofield, H., Hill, R. M., Rier, L., Kennett, E., Rivero, G. R., Gibson, J. M., Tyler, A. J., Tanner, Z., Worcester, F., Hayward, T., et al. (2025) · Imaging Neuroscience · doi:10.1162/imag.a.1042 · Cited by 11
“First, as sensors move closer to the head, field patterns become more focal ( Boto et al., 2016; Iivanainen et al., 2017; Tierney et al., 2022); if the density of sensors is insufficient, then the largest magnetic fields can be missed (i.e., the field pattern is spatially aliased).”
Effects of head modeling errors on the spatial frequency representation of MEG
Yeo, W.-J., Larson, E., Iivanainen, J., Borna, A., McKay, J., Stephen, J. M., Schwindt, P. D. D., & Taulu, S. (2023) · Physics in Medicine and Biology · doi:10.1088/1361-6560/accc06 · Cited by 6
Self-citationLong, T., Song, X., Wu, Z., Suo, Y., Jia, L., Qi, S., Duan, Z., & Han, B. (2024) · Measurement · doi:10.1016/j.measurement.2024.114711 · Cited by 6
Wang, R., Fu, K., Zhao, R., Wang, D., Yang, Z., Bin, W., Gao, Y., & Ning, X. (2024) · NeuroImage · doi:10.1016/j.neuroimage.2024.120661 · Cited by 6
“This is because the radial component measured by the sensor is known to reflect the MEG signal better than the tangential component [41, 42].”
Source imaging method based on diagonal covariance bases and its applications to OPM-MEG
Li, W., Cao, F., An, N., Wang, W., Wang, C., Xu, W., Yu, D., Xiang, M., & Ning, X. (2024) · NeuroImage · doi:10.1016/j.neuroimage.2024.120851 · Cited by 6
“Traditional imaging methods, such as the minimum norm estimate (MNE), typically adopt the 𝐿 2 -norm constraint (Hämäläinen and Ilmoniemi, 1994).”
MethodOptimization of OPM-MEG Layouts with a Limited Number of Sensors
Marhl, U., Hren, R., Sander, T. H., & Jazbinšek, V. (2025) · Sensors · doi:10.3390/s25092706 · Cited by 6
Realistic three-layer head phantom for optically pumped magnetometer-based magnetoencephalography
Cao, F., Gao, Z., Qi, S., Chen, K. L., Xiang, M., An, N., & Ning, X. (2023) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2023.107318 · Cited by 6
A visual encoding model links magnetoencephalography signals to neural synchrony in human cortexPreprint
Kupers, E. R., Benson, N. C., & Winawer, J. A. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.04.19.049197 · Cited by 7
Weiss, B., Dreyer, F. R., Fonteneau, E., van Casteren, M., & Hauk, O. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.07.09.451139 · Cited by 6
Razorenova, A. M., Butorina, A. V., Skidchenko, E., Ostras, M., Ossadtchi, A. E., & Koshev, N. (2025) · IEEE Transactions on Instrumentation and Measurement · doi:10.1109/tim.2025.3544372 · Cited by 5
“These metrics are presented in various simulation studies on MEG (see [7], [10], [24]).”
Fedosov, N., Medvedeva, D., Shevtsov, O., & Ossadtchi, A. E. (2025) · Journal of Neural Engineering · doi:10.1088/1741-2552/aded35 · Cited by 7
“Additionally, we investigated the effect of using magnetic field components of different orientation on the classification accuracy and demonstrated that, for most subjects, the radial axis is significantly more informative than the tangential axis, see figure 18, see Iivanainen et al (2017).”
Light-noise suppression method for the single-beam optically-pumped magnetometer arrays
Suo, Y., Song, X., Wu, Z., Yuan, Z., Jia, L., & Long, T. (2023) · Optics Express · doi:10.1364/oe.489172 · Cited by 5
Source Extent Estimation in OPM-MEG: A Two-Stage Champagne Approach
Li, W., Cao, F., An, N., Wang, W., Wang, C., Xu, W., Gao, Y., & Ning, X. (2024) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2024.3462415 · Cited by 4
“Furthermore, OPM-MEG sensors can be flexibly arranged closer to the scalp, resulting in higher-intensity MEG signals [12].”
Beyond sensitivity: what are the enabling opportunities of OPM-MEG?
Roberts, T. P. L., Birnbaum, C., Bloy, L., & Gaetz, W. C. (2025) · Frontiers in Medical Technology · doi:10.3389/fmedt.2025.1515548 · Cited by 5
“…within a rigid helmet, OPM sensors can be placed much closer to the surface of the head, with corresponding gain in magnetic fi eld sensitivity (15); (ii) weight/ rigidity/movement, removing the constraint for a dewar fi lled with liquid helium, the constraints of fi xed-position helmet are…”
Hauk, O., Jackson, R. L., & Rahimi, S. V. (2023) · Language Cognition and Neuroscience · doi:10.1080/23273798.2023.2226268 · Cited by 5
“Recent developments with non-cryogenic on-scalp sensors (e.g. ‘ OPMs ’ ) promise a signi fi cant improvement of spatial resolution of future MEG systems (Boto et al., 2018; Iivanainen et al., 2017).”
AI for brain-computer interfaces
Haslacher, D., Akmazoglu, T. B., van Beinum, A., Starke, G., Buthut, M., & Soekadar, S. R. (2024) · Developments in neuroethics and bioethics · doi:10.1016/bs.dnb.2024.02.003 · Cited by 8
Optically Pumped Magnetometers for MEG
Knappe, S. A., Sander, T. H., & Trahms, L. (2019) · Springer eBooks · doi:10.1007/978-3-030-00087-5_49 · Cited by 5
Microfabricated optically-pumped magnetometers for imaging applications
Knappe, S. A., Hughes, J. V., & Alem, O. (2023) · Optical and Quantum Sensing and Precision Metrology II · doi:10.1117/12.2657353 · Cited by 5
“It has also been predicted that this can lead to high reconstruction accuracy [44-47].”
BackgroundOPM-MEG bad channel identification method based on the improved box-isolation forest algorithm
Wang, R., Jia, Z., Zhao, R., Gao, Y., & Ning, X. (2023) · Measurement · doi:10.1016/j.measurement.2023.113948 · Cited by 5
Sampling theory for spatial field sensing: Application to electro- and magnetoencephalographyPreprint
Iivanainen, J., Mäkinen, A., Zetter, R., Stenroos, M., Ilmoniemi, R. J., & Parkkonen, L. T. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1912.05401 · Cited by 7
“Simulations have shown that the closer proximity of the sensors to the brain improves spatial resolution of MEG and increases information about neuronal currents (Schneiderman, 2014; Boto et al., 2016; Iivanainen et al., 2017; Riaz et al., 2017).”
BackgroundMethodInfluentialSelf-citationMouth magnetoencephalography: A unique perspective on the human hippocampusPreprint
Tierney, T. M., Levy, A. D., Barry, D. N., Meyer, S. S., Shigihara, Y., Everatt, M., Mellor, S., López, J. D., Bestmann, S., Holmes, N., et al. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.03.19.998641 · Cited by 5
Using OPMs to measure neural activity in standing, mobile participantsPreprint
Seymour, R. A., Alexander, N., Mellor, S., O’Neill, G. C., Tierney, T. M., Barnes, G. R., & Maguire, E. A. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.05.26.445793 · Cited by 5
Li, W., An, N., Cao, F.-Z., Wang, W., Wang, C., Xu, W., Gao, Y., & Ning, X.-L. (2024) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2024.3467377 · Cited by 1
“Additionally, the flexibility of OPM-MEG allows sensors to be positioned closer to the scalp [8], resulting in increased signal intensity.”
The suppression of magnetic noise in a magnetic shielding unit for atomic sensor applications
Karabinaoğlu, M. S., Günay, E., Çakır, B., Caklı, B. M., & Sevim, M. H. (2025) · Sensors and Actuators A Physical · doi:10.1016/j.sna.2025.116833 · Cited by 4
Sasayama, T., Taue, S., & Yoshida, T. (2024) · AIP Advances · doi:10.1063/9.0000634 · Cited by 4
Zhao, J., Zhou, X., & Sun, J. (2024) · Electronics · doi:10.3390/electronics13163163 · Cited by 4
Tanner, Z., Rier, L., Fildes, J., Rivero, G., Schofield, H., Marani, C., Holmes, N., Hill, R. M., Shah, V., Doyle, C., et al. (2025) · Imaging Neuroscience · doi:10.1162/imag.a.10 · Cited by 7
“…al., 2004, 2007; V. Shah et al., 2007, 2020; V. K. Shah & Wakai, 2013) allow measurement of the MEG signal closer to the brain ( Boto et al., 2017; Iivanainen et al., 2017), enable sensor arrays that adapt to head size ( Corvilain et al., 2024; Feys et al., 2022; Hill et al., 2019; Rier et al.,…”
Zhao, R., Wang, R., Gao, Y., & Ning, X. (2024) · Bioengineering · doi:10.3390/bioengineering11050428 · Cited by 4
“…(OPMs) in recent years, wearable OPM-MEG systems [4,5] have not only overcome the disadvantages of traditional MEG devices [6] that need to operate at low temperatures and sensors that are fixed and far away from the subject’s body but have also acquired an improved level of signal sensitivity [7].”
BackgroundUsing Wearable MEG to Study the Neural Control of Human Stepping
Spedden, M. E., O’Neill, G. C., West, T. O., Tierney, T. M., Mellor, S., Alexander, N., Seymour, R. A., Lundbye‐Jensen, J., Nielsen, J. B., Farmer, S. F., et al. (2025) · Sensors · doi:10.3390/s25134160 · Cited by 5
“Unlike traditional MEG, OPM sensors do not require cryogenic cooling, allowing them to be placed close to the scalp [13] in wearable arrays [14], thereby improving signal strength.”
Global sensitivity of MEG source analysis to tissue conductivity uncertainties
Vorwerk, J., Höltershinken, M. B., Wolters, C. H., & Baumgarten, D. (2025) · NeuroImage · doi:10.1016/j.neuroimage.2025.121618 · Cited by 3
Gu, W., Li, D., & Gao, J. (2023) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2023.110010 · Cited by 4
Metadata
- Authors
- Iivanainen, J., Stenroos, M., & Parkkonen, L.
- Affiliations
- Aalto University (FI)
- Corresponding author
- Iivanainen, Joonas
- Venue
- NeuroImage
- Publisher
- Elsevier BV
- Published
- 2017-02
- Volume
- 147
- Pages
- 542-553
- ISSN
- 1053-8119 (ISSN-L)
- PMC
- PMC5432137
- OpenAlex
- W2949327983
- Cited by
- 296
- References
- 47
- Citations by year
- 2026: 28 · 2025: 49 · 2024: 39 · 2023: 40 · 2022: 36 · 2021: 30 · 2020: 25 · 2019: 32 · 2018: 10 · 2017: 7
- FWCI
- 7.72
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- NeuroImage (publishedVersion, cc-by-nc-nd)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Aaltodoc (Aalto University) (submittedVersion, cc-by-nc-nd)
- Funders
- National Institute of Neurological Disorders and Stroke
- Seventh Framework Programme (600730)
- National Institutes of Health (R01NS094604)
- Topics
- Physical Sciences › Physics and Astronomy › Atomic and Molecular Physics, and Optics › Atomic and Subatomic Physics Research
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Magnetic Field Sensors Techniques
- Life Sciences › Neuroscience › Cognitive Neuroscience › EEG and Brain-Computer Interfaces
- Keywords
- magnetoencephalography, optically pumped magnetometers, SQUID magnetometer, planar gradiometer, forward modeling, boundary element model, dipole source localization, point spread function, information capacity, volume currents, signal-to-noise ratio
- MeSH terms
- Adult, Brain, Female, Humans, Male, Models, Theoretical, Scalp, Signal Processing, Computer-Assisted, Magnetoencephalography
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