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.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Increased proximity to the scalp can improve sensitivity and spatial resolution beyond that achieved using cryogenic MEG.
“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]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
A Mathematical Theory of Communication
Shannon, C. E. (1948) · Bell System Technical Journal · doi:10.1002/j.1538-7305.1948.tb01338.x · Cited by 88,486 · see citing works
A Mathematical Theory of Communication
Shannon, C. E. (1948) · Bell System Technical Journal · doi:10.1002/j.1538-7305.1948.tb00917.x · Cited by 49,574 · see citing works
Cortical Surface-Based Analysis
Dale, A. M., Fischl, B., & Sereno, M. I. (1999) · NeuroImage · doi:10.1006/nimg.1998.0395 · Cited by 10,910 · cited 1× · see citing works
“FreeSurfer software (Dale et al., 1999; Fischl et al., 1999a; Fischl, 2012) was used to segment the cortical mantles from individual MRIs.”
Fischl, B. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2012.01.021 · Cited by 9,526 · cited 1× · see citing works
“FreeSurfer software (Dale et al., 1999; Fischl et al., 1999a; Fischl, 2012) was used to segment the cortical mantles from individual MRIs.”
Cortical Surface-Based Analysis
Fischl, B., Sereno, M. I., & Dale, A. M. (1999) · NeuroImage · doi:10.1006/nimg.1998.0396 · Cited by 6,147 · cited 2× · see citing works
“FreeSurfer software (Dale et al., 1999; Fischl et al., 1999a; Fischl, 2012) was used to segment the cortical mantles from individual MRIs.”
Hämäläinen, M., Hari, R., Ilmoniemi, R. J., Knuutila, J., & Lounasmaa, O. V. (1993) · Reviews of Modern Physics · doi:10.1103/revmodphys.65.413 · Cited by 4,684 · cited 2× · see citing works
“2.3 Minimum-norm estimate Minimum-l2-norm estimator (Dale and Sereno, 1993; Hämäläinen and Ilmoniemi, 1994) can be used to estimate underlying sources from measured data.”
InfluentialA hybrid approach to the skull stripping problem in MRI
Ségonne, F., Dale, A. M., Busa, E., Glessner, M., Salat, D. H., Hahn, H., & Fischl, B. R. (2004) · NeuroImage · doi:10.1016/j.neuroimage.2004.03.032 · Cited by 2,227 · cited 2× · see citing works
“For each subject, we used the watershed algorithm (Ségonne et al., 2004) implemented in FreeSurfer and MNE software (Gramfort et al., 2014) to segment the brain, skull and scalp compartments.”
Dale, A. M., & Sereno, M. I. (1993) · Journal of Cognitive Neuroscience · doi:10.1162/jocn.1993.5.2.162 · Cited by 2,003 · cited 2× · see citing works
“2.3 Minimum-norm estimate Minimum-l2-norm estimator (Dale and Sereno, 1993; Hämäläinen and Ilmoniemi, 1994) can be used to estimate underlying sources from measured data.”
InfluentialInterpreting magnetic fields of the brain: minimum norm estimates
Hämäläinen, M. S., & Ilmoniemi, R. J. (1994) · Medical & Biological Engineering & Computing · doi:10.1007/bf02512476 · Cited by 1,995 · cited 2× · see citing works
“2.3 Minimum-norm estimate Minimum-l2-norm estimator (Dale and Sereno, 1993; Hämäläinen and Ilmoniemi, 1994) can be used to estimate underlying sources from measured data.”
InfluentialMNE software for processing MEG and EEG data
Gramfort, A., Luessi, M., Larson, E., Engemann, D. A., Strohmeier, D., Brodbeck, C. J., Parkkonen, L. T., & Hämäläinen, M. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.10.027 · Cited by 1,924 · cited 1× · see citing works
“, 2004) implemented in FreeSurfer and MNE software (Gramfort et al., 2014) to segment the brain, skull and scalp compartments.”
Self-citationBudker, D., & Romalis, M. V. (2007) · Nature Physics · doi:10.1038/nphys566 · Cited by 1,923 · cited 1× · see citing works
“Alternative sensors such as optically-pumped, or atomic, magnetometers (OPMs) (Budker and Kimball, 2013; Budker and Romalis, 2007) and high-Tc SQUIDs (Öisjöen et al., 2012) have recently reached sensitivities required for detecting neuromagnetic fields.”
Gross, K. S., Brandner, D. D., Martinez, L. A., Olive, M. F., Meisel, R. L., & Mermelstein, P. G. (2016) · PLoS ONE · doi:10.1371/journal.pone.0162755 · Cited by 1,610 · see citing works
High-Sensitivity Atomic Magnetometer Unaffected by Spin-Exchange Relaxation
Allred, J. C., Lyman, R. N., Kornack, T. W., & Romalis, M. V. (2002) · Physical Review Letters · doi:10.1103/physrevlett.89.130801 · Cited by 1,049 · cited 2× · see citing works
“Particularly OPMs operating in the spin-exchange relaxation-free (SERF) regime (Allred et al., 2002) could become a feasible, noncryogenic alternative to SQUIDs for neuromagnetic measurements as the combined dimensions and sensitivies of the SERF-OPMs are approaching those of SQUIDs (∼4–6 cm(2) and ∼3 − 5 fT/ Hz ).”
Source connectivity analysis with MEG and EEG
Schoffelen, J., & Groß, J. (2009) · Human Brain Mapping · doi:10.1002/hbm.20745 · Cited by 854 · see citing works
EEG and MEG: forward solutions for inverse methods
Mosher, J. C., Leahy, R. M., & Lewis, P. S. (1999) · IEEE Transactions on Biomedical Engineering · doi:10.1109/10.748978 · Cited by 845 · cited 1× · see citing works
“We also compared the topographies obtained with a linear collocation (LC) (De Munck, 1992) and LG BEM (Mosher et al., 1999) across the subjects.”
Considerations of quasi-stationarity in electrophysiological systems
Plonsey, R., & Heppner, D. B. (1967) · Bulletin of Mathematical Biology · doi:10.1007/bf02476917 · Cited by 623 · cited 2× · see citing works
“2.1 Physics When bioelectromagnetic fields are modeled in the macroscopic scale, the time-dependent terms in Maxwell’s equations can be omitted (Plonsey and Heppner, 1967).”
InfluentialA sensor-weighted overlapping-sphere head model and exhaustive head model comparison for MEG
Huang, M., Mosher, J. C., & Leahy, R. M. (1999) · Physics in Medicine and Biology · doi:10.1088/0031-9155/44/2/010 · Cited by 615 · cited 1× · see citing works
“The authors computed the magnetic field with local-spheres head model (Huang et al., 1999) in a single head geometry.”
Lin, F., Witzel, T., Ahlfors, S. P., Stufflebeam, S. M., Belliveau, J. W., & Hämäläinen, M. (2006) · NeuroImage · doi:10.1016/j.neuroimage.2005.11.054 · Cited by 506 · see citing works
A common formalism for the Integral formulations of the forward EEG problem
Kybic, J., Clerc, M., Abboud, T., Faugeras, O. D., Keriven, R., & Papadopoulo, T. (2005) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2004.837363 · Cited by 424 · cited 2× · see citing works
“Thus, the field computation for normal-component-measuring OPMs could potentially be done with a LC BEM, which is computationally lighter than the more accurate solvers such as LG BEM or symmetric BEM (Kybic et al., 2005).”
Microfabricated alkali atom vapor cells
Liew, L., Knappe, S. A., Moreland, J., Robinson, H. G., Hollberg, L. W., & Kitching, J. E. (2004) · Applied Physics Letters · doi:10.1063/1.1691490 · Cited by 373 · cited 2× · see citing works
“Thus, compared to the state-of-the-art OPMs, our hypothetical OPMs are optimistic in design; however, we anticipate that the distance between the vapor cell and the outer surface of the sensor will shrink in the next generation OPMs due to advances in sensor packaging and in the utilization of microfabrication (Liew e…”
Monte Carlo simulation studies of EEG and MEG localization accuracy
Liu, A. K., Dale, A. M., & Belliveau, J. W. (2002) · Human Brain Mapping · doi:10.1002/hbm.10024 · Cited by 348 · cited 1× · see citing works
“To evaluate the differences between the arrays in linear distributedsource estimation, we used metrics derived from the resolution matrix (Hauk et al., 2011; Liu et al., 2002; Molins et al., 2008; de Peralta Menendez et al., 1997; Stenroos and Hauk, 2013).”
A compact, high performance atomic magnetometer for biomedical applications
Shah, V. K., & Wakai, R. T. (2013) · Physics in Medicine and Biology · doi:10.1088/0031-9155/58/22/8153 · Cited by 322 · cited 2× · see citing works
“We assumed a noise level of 6 fT/ for the OPM sensor based on the work by Shah and Wakai (2013) who reported such a field resolution for their sensor in optimal conditions.”
Geselowitz, D. A. (1970) · IEEE Transactions on Magnetics · doi:10.1109/tmag.1970.1066765 · Cited by 317 · cited 1× · see citing works
“When the conducting region is modeled to consist of piecewise homogeneous regions, the magnetic field is given by the Geselowitz formula; (Geselowitz, 1970) where Bp(r) and Bv(r) are the magnetic fields due to primary and volume currents, μ0 is the permeability of free space, and , and are the…”
A guideline for head volume conductor modeling in EEG and MEG
Vorwerk, J., Cho, J., Rampp, S., Hamer, H. M., Knösche, T. R., & Wolters, C. H. (2014) · NeuroImage · doi:10.1016/j.neuroimage.2014.06.040 · Cited by 307 · cited 1× · see citing works
“The effect of common volume-conductor-model errors and simplifications on both nOPM and tOPM could be assessed by comparing geometrically correct and erroneous simplified models to more detailed reference models (Stenroos et al., 2014; Stenroos and Nummenmaa, 2016; Vorwerk et al., 2014).”
Distributed current estimates using cortical orientation constraints
Lin, F., Belliveau, J. W., Dale, A. M., & Hämäläinen, M. (2005) · Human Brain Mapping · doi:10.1002/hbm.20155 · Cited by 291 · cited 3× · see citing works
“The regularization parameter has been suggested to be chosen as (Lin et al., 2006a,b) where Nc is the number of sensors, SNR is the estimated signal-to-noise ratio, tr(·) is trace of a matrix and L is the whitened lead-field matrix: .”
(2013) · doi:10.1017/cbo9780511846380 · Cited by 286 · see citing works
Goldenholz, D. M., Ahlfors, S. P., Hämäläinen, M., Sharon, D., Ishitobi, M., Vaina, L. M., & Stufflebeam, S. M. (2008) · Human Brain Mapping · doi:10.1002/hbm.20571 · Cited by 266 · cited 3× · see citing works
“For each subject, we used the watershed algorithm (Ségonne et al., 2004) implemented in FreeSurfer and MNE software (Gramfort et al., 2014) to segment the brain, skull and scalp compartments.”
Magnetoencephalography with a two-color pump-probe, fiber-coupled atomic magnetometer
Johnson, C., Schwindt, P. D. D., & Weisend, M. P. (2010) · Applied Physics Letters · doi:10.1063/1.3522648 · Cited by 210 · see citing works
de Munck, J. C. (1992) · IEEE Transactions on Biomedical Engineering · doi:10.1109/10.256433 · Cited by 194 · cited 1× · see citing works
“We also compared the topographies obtained with a linear collocation (LC) (De Munck, 1992) and LG BEM (Mosher et al., 1999) across the subjects.”
On the Potential of a New Generation of Magnetometers for MEG: A Beamformer Simulation Study
Boto, E., Bowtell, R., Krüger, P., Fromhold, T. M., Morris, P. G., Meyer, S. S., Barnes, G. R., & Brookes, M. J. (2016) · PLOS ONE · doi:10.1371/journal.pone.0157655 · Cited by 194 · see citing works
Quantification of the benefit from integrating MEG and EEG data in minimum ℓ2-norm estimation
Molins, A., Stufflebeam, S. M., Brown, E. N., & Hämäläinen, M. S. (2008) · NeuroImage · doi:10.1016/j.neuroimage.2008.05.064 · Cited by 192 · cited 2× · see citing works
“To evaluate the differences between the arrays in linear distributed-source estimation, we used metrics derived from the resolution matrix (Hauk et al., 2011; Liu et al., 2002; Molins et al., 2008; de Peralta Menendez et al., 1997; Stenroos and Hauk, 2013).”
Hauk, O., Wakeman, D. G., & Henson, R. N. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2010.09.053 · Cited by 191 · cited 1× · see citing works
“To evaluate the differences between the arrays in linear distributed-source estimation, we used metrics derived from the resolution matrix (Hauk et al., 2011; Liu et al., 2002; Molins et al., 2008; de Peralta Menendez et al., 1997; Stenroos and Hauk, 2013).”
Alem, O., Sander, T. H., Mhaskar, R. R., LeBlanc, J., Eswaran, H., Steinhoff, U., Okada, Y. C., Kitching, J. E., Trahms, L., & Knappe, S. A. (2015) · Physics in Medicine and Biology · doi:10.1088/0031-9155/60/12/4797 · Cited by 185 · see citing works
A low-power, high-sensitivity micromachined optical magnetometer
Mhaskar, R. R., Knappe, S. A., & Kitching, J. E. (2012) · Applied Physics Letters · doi:10.1063/1.4770361 · Cited by 176 · see citing works
Comparison of three-shell and simplified volume conductor models in magnetoencephalography
Stenroos, M., Hunold, A., & Haueisen, J. (2014) · NeuroImage · doi:10.1016/j.neuroimage.2014.01.006 · Cited by 123 · see citing works
Self-citationStenroos, M., Mäntynen, V., & Nenonen, J. (2007) · Computer Methods and Programs in Biomedicine · doi:10.1016/j.cmpb.2007.09.004 · Cited by 122 · see citing works
Self-citationA random dipole model for spontaneous brain activity
de Munck, J. C., Vijn, P. C. M., & da Silva, F. H. L. (1992) · IEEE Transactions on Biomedical Engineering · doi:10.1109/10.148387 · Cited by 103 · cited 1× · see citing works
“In addition, we investigated the overlap of the sensor lead fields as a function of the sensor distance (de Munck et al., 1992): for each sensor in the array, we calculated the distances and lead-field correlations between that sensor and all other sensors in the array.”
Bioelectromagnetic forward problem: isolated source approach revis(it)ed
Stenroos, M., & Sarvas, J. (2012) · Physics in Medicine and Biology · doi:10.1088/0031-9155/57/11/3517 · Cited by 92 · cited 2× · see citing works
“For each subject, the lead-field matrix L was computed using a linear Galerkin BEM formulated with Isolated Source Approach (ISA) (Stenroos and Sarvas, 2012).”
InfluentialSelf-citationÖisjöen, F., Schneiderman, J. F., Figueras, G. A., Chukharkin, M. L., Kalabukhov, A., Hedström, A., Elam, M., & Winkler, D. (2012) · Applied Physics Letters · doi:10.1063/1.3698152 · Cited by 69 · cited 7× · see citing works
“The aim of this study was to assess the possible benefits of on-scalp MEG arrays that can be constructed using novel magnetic field sensors, e.g., optically-pumped magnetometers (OPMs) or high-Tc SQUIDs.”
InfluentialStenroos, M., & Nummenmaa, A. R. (2016) · PLoS ONE · doi:10.1371/journal.pone.0159595 · Cited by 68 · cited 1× · see citing works
“The effect of common volume-conductor-model errors and simplifications on both nOPM and tOPM could be assessed by comparing geometrically correct and erroneous simplified models to more detailed reference models (Stenroos et al., 2014; Stenroos and Nummenmaa, 2016; Vorwerk et al., 2014).”
Self-citationStenroos, M., & Hauk, O. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.04.086 · Cited by 62 · cited 2× · see citing works
“To evaluate the differences between the arrays in linear distributed-source estimation, we used metrics derived from the resolution matrix (Hauk et al., 2011; Liu et al., 2002; Molins et al., 2008; de Peralta Menendez et al., 1997; Stenroos and Hauk, 2013).”
Self-citationSchneiderman, J. F. (2013) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2013.10.007 · Cited by 56 · cited 1× · see citing works
“Previously, the performance of various MEG arrays has been assessed by computing the total information Itot conveyed by the array (Kemppainen and Ilmoniemi, 1989; Nenonen et al., 2004; Schneiderman, 2014).”
Channel Capacity of Multichannel Magnetometers
Kemppainen, P., & Ilmoniemi, R. J. (1989) · Springer eBooks · doi:10.1007/978-1-4613-0581-1_141 · Cited by 37 · cited 3× · see citing works
“To complete forward model -based metrics and quantify the performance of the array with a single number, we calculated the total information conveyed by the array (Kemppainen and Ilmoniemi, 1989).”
Sensory mapping in a congenitally deaf subject: MEG and fRMI studies of cross-modal non-plasticity
Hickok, G. S., Poeppel, D., Clark, K., Buxton, R. B., Rowley, H. A., & Roberts, T. P. L. (1997) · Human Brain Mapping · doi:10.1002/(sici)1097-0193(1997)5:6 · Cited by 32 · see citing works
Information Content in Single-Component Versus Three-Component Cardiomagnetic Fields
Arturi, C. M., Rienzo, L. D., & Haueisen, J. (2004) · IEEE Transactions on Magnetics · doi:10.1109/tmag.2004.824891 · Cited by 26 · cited 1× · see citing works
“Similar observations have been made for cardiomagnetic fields (Arturi et al., 2004).”
Radial and tangential components of dipolar sources and their magnetic fields
de Munck, J. C., & Daffertshofer, A. (2012) · Clinical Neurophysiology · doi:10.1016/j.clinph.2012.01.001 · Cited by 3 · cited 1× · see citing works
“…indicate that the normal and tangential components carry independent information as the information capacity of the aOPM is higher than the information capacities of its sub-arrays nOPM and tOPM, indicating that these measurements are not redundant; see also de Munck and Daffertshofer (2012).”
High-resolution intersubject averaging and a coordinate system for the cortical surface
Fischl, B., Sereno, M. I., Tootell, R. B. H., & Dale, A. M. (1999) · Human Brain Mapping · doi:10.1002/(sici)1097-0193(1999)8:4
Flagged first, then by citations
Research works printed but not linked: 1
- Nenonen J Kajola M Simola J Ahonen A Total information of multichannel MEG sensor arrays Proceedings of the 14th International Conference on Biomagnetism (Biomag2004) 2004 630 631
Cited by
Sorted by citations
Brookes, M. J., Leggett, J., Rea, M., Hill, R. M., Holmes, N., Boto, E., & Bowtell, R. W. (2022) · Trends in Neurosciences · doi:10.1016/j.tins.2022.05.008 · Cited by 425 · see citing works
“Simulations [12,13] show that this effect provides a four- to fivefold signal enhancement in many cortical areas.”
BackgroundOptically pumped magnetometers: from quantum origins to multi-channel magnetoencephalography
Tierney, T. M., Holmes, N., Mellor, S., López, J. D., Roberts, G., Hill, R. M., Boto, E., Leggett, J., Shah, V., Brookes, M. J., et al. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2019.05.063 · Cited by 400 · see citing works
“…advances in sensors, additional neuroscientific motivation for OPMs came from simulation studies examining issues such as improvements in SNR, spatial resolution and the requirements necessary for accurate source reconstruction (Boto et al., 2016a; Iivanainen et al., 2017a; Zetter et al., 2017).”
BackgroundMulti-Channel Whole-Head OPM-MEG: Helmet Design and a Comparison with a Conventional System
Hill, R. M., Boto, E., Rea, M., Holmes, N., Leggett, J., Coles, L. A., Papastavrou, M., Everton, S. K., Hunt, B. A. E., Sims, D., et al. (2020) · NeuroImage · doi:10.1016/j.neuroimage.2020.116995 · Cited by 285 · see citing works
Ultrasensitive Magnetic Field Sensors for Biomedical Applications
Murzin, D., Mapps, D. J., Levada, K., Belyaev, V., Omelyanchik, A., Panina, L., & Rodionova, V. (2020) · Sensors · doi:10.3390/s20061569 · Cited by 277 · see citing works
On-scalp MEG system utilizing an actively shielded array of optically-pumped magnetometers
Iivanainen, J., Zetter, R., Grön, M., Hakkarainen, K., & Parkkonen, L. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2019.03.022 · Cited by 269 · see citing works
Self-citationHolmes, N., Leggett, J., Boto, E., Roberts, G., Hill, R. M., Tierney, T. M., Shah, V., Barnes, G. R., Brookes, M. J., & Bowtell, R. (2018) · NeuroImage · doi:10.1016/j.neuroimage.2018.07.028 · Cited by 250 · see citing works
“Simulation studies (Boto et al., 2016; Iivanainen et al., 2017) have demonstrated the gains in performance which could be achieved using OPM-based MEG systems.”
MethodBoto, E., Shah, V., Hill, R. M., Rhodes, N., Osborne, J., Doyle, C., Holmes, N., Rea, M., Leggett, J., Bowtell, R. W., et al. (2022) · NeuroImage · doi:10.1016/j.neuroimage.2022.119027 · Cited by 187 · see citing works
“3) Triaxial sensors provide three times more measurements; tangential fields are known to be weaker than radial fields (Iivanainen et al., 2017) and so this does not”
BackgroundA 20-channel magnetoencephalography system based on optically pumped magnetometers
Borna, A., Carter, T. R., Goldberg, J. D., Colombo, A. P., Jau, Y.-Y., Berry, C., McKay, J., Stephen, J., Weisend, M., & Schwindt, P. D. D. (2017) · Physics in Medicine and Biology · doi:10.1088/1361-6560/aa93d1 · Cited by 179 · see citing works
“Two recent simulation studies also demonstrate the distinct advantages of moving the sensors closer to the brain [4, 5].”
BackgroundIFCN-endorsed practical guidelines for clinical magnetoencephalography (MEG)
Hari, R., Baillet, S., Barnes, G. R., Burgess, R. C., Forss, N., Groß, J., Hämäläinen, M., Jensen, O. B., Kakigi, R., Mauguı̀ere, F., et al. (2018) · Clinical Neurophysiology · doi:10.1016/j.clinph.2018.03.042 · Cited by 170 · see citing works
“Moreover, they can be placed closer to the brain than the low-temperature SQUIDs, thereby providing better spatial resolution (Iivanainen et al., 2017), as long as their higher noise does not compromise this advantage.”
BackgroundHolmes, N., Tierney, T. M., Leggett, J., Boto, E., Mellor, S., Roberts, G., Hill, R. M., Shah, V., Barnes, G. R., Brookes, M. J., et al. (2019) · Scientific Reports · doi:10.1038/s41598-019-50697-w · Cited by 163 · see citing works
Magnetoencephalography in Cognitive Neuroscience: A Primer
Groß, J. (2019) · Neuron · doi:10.1016/j.neuron.2019.07.001 · Cited by 160 · see citing works
“The reduced distance between sensors and the brain leads to a significant increase in signal power, by a factor of 5–7, compared to SQUIDs (Iivanainen et al., 2017).”
BackgroundNon-Invasive Functional-Brain-Imaging with an OPM-based Magnetoencephalography System
Borna, A., Carter, T. R., Colombo, A. P., Jau, Y.-Y., McKay, J., Weisend, M., Taulu, S., Stephen, J. M., & Schwindt, P. D. D. (2020) · PLOS ONE · doi:10.1371/journal.pone.0227684 · Cited by 158 · see citing works
“7 have been reported in simulations consisting of dipolar brain sources and MEG sensors that are brought from the SQUID-related measurement distance onto the scalp [33].”
BackgroundTheoretical advantages of a triaxial optically pumped magnetometer magnetoencephalography system
Brookes, M. J., Boto, E., Rea, M., Shah, V., Osborne, J., Holmes, N., Hill, R. M., Leggett, J., Rhodes, N., & Bowtell, R. W. (2021) · NeuroImage · doi:10.1016/j.neuroimage.2021.118025 · Cited by 151 · see citing works
“(r12 is similar to the lead field correlation metric used in a previous study (Iivanainen et al., 2017).”
BackgroundResultInfluentialTowards OPM-MEG in a Virtual Reality Environment
Roberts, G., Holmes, N., Alexander, N., Boto, E., Leggett, J., Hill, R. M., Shah, V., Rea, M., Vaughan, R., Maguire, E. A., et al. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2019.06.010 · Cited by 128 · see citing works
“Since the external surface of these sensors is approximately at body temperature, they can be brought within ~6-8 mm of the scalp surface, leading to a significant increase in the measurable signal (Boto et al., 2016; Iivanainen et al., 2017).”
BackgroundWearable neuroimaging: Combining and contrasting magnetoencephalography and electroencephalography
Boto, E., Seedat, Z. A., Holmes, N., Leggett, J., Hill, R. M., Roberts, G., Shah, V., Fromhold, T. M., Mullinger, K. J., Tierney, T. M., et al. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2019.116099 · Cited by 136 · see citing works
“With scalpmounting, the sensing volume is positioned only millimetres from the scalp surface and the measured magnetic field is consequently higher compared to superconducting sensors (which are located further away), providing increased sensitivity (Boto et al., 2017, 2016; Iivanainen et al., 2017).”
BackgroundMeasuring functional connectivity with wearable MEG
Boto, E., Hill, R. M., Rea, M., Holmes, N., Seedat, Z. A., Leggett, J., Shah, V., Osborne, J., Bowtell, R. W., & Brookes, M. J. (2021) · NeuroImage · doi:10.1016/j.neuroimage.2021.117815 · Cited by 125 · see citing works
“Finally, because OPM sensors can get closer 13 to the brain, we can capture better data with higher sensitivity and spatial resolution (Boto et 14 al., 2019, 2016; Iivanainen et al., 2017).”
Borna, A., Iivanainen, J., Carter, T. R., McKay, J., Taulu, S., Stephen, J., & Schwindt, P. D. D. (2022) · NeuroImage · doi:10.1016/j.neuroimage.2021.118818 · Cited by 120 · see citing works
Self-citationPrecision magnetic field modelling and control for wearable magnetoencephalography
Rea, M., Holmes, N., Hill, R. M., Boto, E., Leggett, J., Edwards, L. J., Woolger, D., Dawson, E., Shah, V., Osborne, J., et al. (2021) · NeuroImage · doi:10.1016/j.neuroimage.2021.118401 · Cited by 121 · see citing works
“This, in turn, limits spatial resolution ( Boto et al., 016 ; Iivanainen et al., 2017 ).”
BackgroundInterference suppression techniques for OPM-based MEG: Opportunities and challenges
Seymour, R. A., Alexander, N., Mellor, S., O’Neill, G. C., Tierney, T. M., Barnes, G. R., & Maguire, E. A. (2021) · NeuroImage · doi:10.1016/j.neuroimage.2021.118834 · Cited by 123 · see citing works
“Detailed simulation work has shown that compared to radialnly oriented sensors, dual-axis and triaxial arrays of OPMs can theoetically measure neuromagnetic fields with greater information content nd increased signal amplitude ( Iivanainen et al., 2017 ).”
BackgroundA 90-Channel Triaxial Magnetoencephalography System Using Optically Pumped Magnetometers
Rea, M., Boto, E., Holmes, N., Hill, R., Osborne, J., Rhodes, N., Leggett, J., Rier, L., Bowtell, R., Shah, V., et al. (2022) · Annals of the New York Academy of Sciences · doi:10.1111/nyas.14890 · Cited by 102 · see citing works
Sensitive magnetometry in challenging environments
Fu, K. C., Iwata, G. Z., Wickenbrock, A., & Budker, D. (2020) · AVS Quantum Science · doi:10.1116/5.0025186 · Cited by 112 · see citing works
Using OPMs to measure neural activity in standing, mobile participants
Seymour, R. A., Alexander, N., Mellor, S., O'Neill, G. C., Tierney, T. M., Barnes, G. R., & Maguire, E. A. (2021) · NeuroImage · doi:10.1016/j.neuroimage.2021.118604 · Cited by 102 · see citing works
Potential of on‐scalp MEG: Robust detection of human visual gamma‐band responses
Iivanainen, J., Zetter, R., & Parkkonen, L. T. (2019) · Human Brain Mapping · doi:10.1002/hbm.24795 · Cited by 96 · see citing works
“OPMs, in contrast to SQUIDs, can be placed in very close proximity to the scalp, considerably boosting both spatial resolution and sensitivity to neural sources (Boto et al., 2016; Iivanainen et al., 2017).”
InfluentialSelf-citationAn integrated full-head OPM-MEG system based on 128 zero-field sensors
Alem, O., Hughes, K. J., Buard, I., Cheung, T., Maydew, T., Griesshammer, A., Holloway, K., Park, A., Lechuga, V., Coolidge, C., et al. (2023) · Frontiers in Neuroscience · doi:10.3389/fnins.2023.1190310 · Cited by 98 · see citing works
“4 times more spread for a cryogenic MEG (Iivanainen et al., 2017).”
BackgroundOptical Co-Registration of MRI and On-Scalp MEG
Zetter, R., Iivanainen, J., & Parkkonen, L. (2019) · Scientific Reports · doi:10.1038/s41598-019-41763-4 · Cited by 93 · see citing works
“Accurate co-registration is particularly important in on-scalp MEG [7] due to its high spatial resolution [2], [3].”
BackgroundSelf-citationFaley, M. I., Dammers, J., Maslennikov, Y. V., Schneiderman, J. F., Winkler, D., Koshelets, V. P., Shah, N. J., & Dunin‐Borkowski, R. E. (2017) · Superconductor Science and Technology · doi:10.1088/1361-6668/aa73ad · Cited by 91 · see citing works
“Theoretical studies [7, 8] have shown that atomic magnetometers can provide a higher SNR and potentially replace SQUIDs in MEG systems.”
BackgroundTowards an objective evaluation of EEG/MEG source estimation methods – The linear approach
Hauk, O., Stenroos, M., & Treder, M. S. (2022) · NeuroImage · doi:10.1016/j.neuroimage.2022.119177 · Cited by 92 · see citing works
“rather than the peak to compute localization error, or spatial extent has been evaluated using measures of area (Iivanainen et al., 2017).”
BackgroundMethodResultInfluentialSelf-citationMouth magnetoencephalography: A unique perspective on the human hippocampus
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) · NeuroImage · doi:10.1016/j.neuroimage.2020.117443 · Cited by 84 · see citing works
Nardelli, N. V., Perry, A. R., Krzyzewski, S., & Knappe, S. A. (2020) · EPJ Quantum Technology · doi:10.1140/epjqt/s40507-020-00086-4 · Cited by 86 · see citing works
Measurement of Frontal Midline Theta Oscillations using OPM-MEG
Rhodes, N., Rea, M., Boto, E., Rier, L., Shah, V., Hill, R. M., Osborne, J., Doyle, C., Holmes, N., Coleman, S. C., et al. (2023) · NeuroImage · doi:10.1016/j.neuroimage.2023.120024 · Cited by 87 · see citing works
Magnetoencephalography with a Cs-based high-sensitivity compact atomic magnetometer
Sheng, J., Wan, S., Sun, Y., Dou, R., Guo, Y., Wei, K., He, K., Qin, J., & Gao, J. (2017) · Review of Scientific Instruments · doi:10.1063/1.5001730 · Cited by 80 · see citing works
Reducing crosstalk in optically-pumped magnetometer arrays
Nardelli, N. V., Krzyzewski, S., & Knappe, S. A. (2019) · Physics in Medicine and Biology · doi:10.1088/1361-6560/ab4c06 · Cited by 80 · see citing works
“Recent studies simulating whole-head MEG systems with on-scalp sensors promise greatly increased spatial resolution compared to the current SQUID-based MEG systems (Luessi et al 2014, Boto et al 2016, Iivanainen et al 2017).”
Using OPM-MEG in contrasting magnetic environments
Hill, R. M., Devasagayam, J., Holmes, N., Boto, E., Shah, V., Osborne, J., Safar, K., Worcester, F., Mariani, C., Dawson, E., et al. (2022) · NeuroImage · doi:10.1016/j.neuroimage.2022.119084 · Cited by 80 · see citing works
Imaging the human hippocampus with optically-pumped magnetoencephalography
Barry, D. N., Tierney, T. M., Holmes, N., Boto, E., Roberts, G., Leggett, J., Bowtell, R. W., Brookes, M. J., Barnes, G. R., & Maguire, E. A. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2019.116192 · Cited by 71 · see citing works
Laminar dynamics of high amplitude beta bursts in human motor cortex
Bonaiuto, J. J., Little, S., Neymotin, S. A., Jones, S. R., Barnes, G. R., & Bestmann, S. (2021) · NeuroImage · doi:10.1016/j.neuroimage.2021.118479 · Cited by 76 · see citing works
“…layers, and higher SNR data afforded by cryogen- ree MEG sensors (optically-pumped magnetometers; OPMs; Boto et al., 016, 2018; Holmes et al., 2018; Iivanainen et al., 2017, 2019; Knappe t al., 2014 ), may be able to use an approach similar to current source ensity methods ( Pettersen et al.,…”
MethodOptically pumped magnetoencephalography in epilepsy
Vivekananda, U., Mellor, S., Tierney, T. M., Holmes, N., Boto, E., Leggett, J., Roberts, G., Hill, R. M., Vladimir Litvak, A., Brookes, M. J., et al. (2020) · Annals of Clinical and Translational Neurology · doi:10.1002/acn3.50995 · Cited by 72 · see citing works
Jodko-Władzińska, A., Wildner, K., Pałko, T., & Władziński, M. (2020) · Sensors · doi:10.3390/s20164563 · Cited by 74 · see citing works
“Flexible optical and electrical wiring of OPMs, together with a small size sensor head, enable minimizing the sensor-signal source distance, which leads to higher amplitudes of received signal [27,28].”
BackgroundMagnetoencephalography With Optically Pumped4He Magnetometers at Ambient Temperature
Labyt, É., Corsi, M., Fourcault, W., Laloy, A. P., Bertrand, F., Lenouvel, F., Cauffet, G., Prado, M. L., Berger, F. R., & Morales, S. (2018) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2018.2856367 · Cited by 72 · see citing works
“This result well agrees with a recent work [53] quantifying the improvement in recording MEG with simulated on-scalp OPM arrays compared to a 306-channels SQUID array such as Vectorview Neuromag MEG machine used in our study.”
ResultOptically Pumped Magnetometers Recent Advances and Applications in Biomagnetism: A Review
Zhao, B., Li, L., Zhang, Y., Tang, J., Liu, Y., & Zhai, Y. (2023) · IEEE Sensors Journal · doi:10.1109/jsen.2023.3297109 · Cited by 70 · see citing works
“[25], [26], [27], [28], [29], [30], [33], [34], [35], [36], [37], [38], [39], [40], and magnetomyography (MMG) [41].”
Manyukhina, V. O., Prokofyev, A. O., Galuta, I. A., Goiaeva, D. E., Obukhova, T. S., Schneiderman, J. F., Altukhov, D., Stroganova, T. A., & Orekhova, E. V. (2022) · Molecular Autism · doi:10.1186/s13229-022-00498-2 · Cited by 75 · see citing works
“Thirdly, the new and rapidly developing technology of ‘on-scalp’ MEG (65-67) may help to obtain equally high-quality data in all parts of the head, including the frontal areas, which are typically positioned furthest away from the sensors in ‘conventional’ MEG systems.”
BackgroundNann, M., Cordella, F., Trigili, E., Lauretti, C., Bravi, M., Miccinilli, S., Catalan, J. M., Badesa, F. J., Crea, S., Bressi, F., et al. (2020) · IEEE Systems Journal · doi:10.1109/jsyst.2020.3021485 · Cited by 69 · see citing works
“quantum sensors [34], [35], may overcome the current constraint of limited spatial resolution when recording brain oscillatory activity noninvasively.”
BackgroundZhang, G., Huang, S.-J., Xu, F., Hu, Z., & Lin, Q. (2019) · Optics Express · doi:10.1364/oe.27.000597 · Cited by 64 · see citing works
He, K., Wan, S., Sheng, J., Liu, D., Wang, C., Li, D., Qin, L., Luo, S., Qin, J., & Gao, J. (2019) · Review of Scientific Instruments · doi:10.1063/1.5066250 · Cited by 63 · see citing works
Transforming and comparing data between standard SQUID and OPM-MEG systems
Marhl, U., Jodko-Władzińska, A., Brühl, R., Sander, T. H., & Jazbinšek, V. (2022) · PLoS ONE · doi:10.1371/journal.pone.0262669 · Cited by 64 · see citing works
Long, T., Song, X., Han, B., Suo, Y., & Jia, L. (2023) · IEEE Transactions on Instrumentation and Measurement · doi:10.1109/tim.2023.3331425 · Cited by 62 · see citing works
“As a result, the OPM achieves an enhanced signal strength, typically offering a three-to fivefold improvement by reducing the distance between the sensor and the subject’s brain [19], [20].”
BackgroundScalp attached tangential magnetoencephalography using tunnel magneto-resistive sensors
Kanno, A., Nakasato, N., Oogane, M., Fujiwara, K., Nakano, T., Arimoto, T., Matsuzaki, H., & Ando, Y. (2022) · Scientific Reports · doi:10.1038/s41598-022-10155-6 · Cited by 62 · see citing works
Ru, X., He, K., Lyu, B., Li, D., Xu, W., Gu, W., Ma, X., Liu, J., Li, C., Li, T., et al. (2022) · NeuroImage · doi:10.1016/j.neuroimage.2022.119420 · Cited by 56 · see citing works
Characterizing hippocampal dynamics with MEG: A systematic review and evidence‐based guidelines
Ruzich, E., Crespo‐García, M., Dalal, S. S., & Schneiderman, J. F. (2018) · Human Brain Mapping · doi:10.1002/hbm.24445 · Cited by 54 · see citing works
“These systems, still in development, are demonstrated to have comparable or better SNRs to classic MEG, and suggest their potential utility to measure a broader range of brain activity from deeper structures (Boto et al., 2016; Boto et al., 2018; Iivanainen et al., 2017; Öisjöen et al., 2012; Schneiderman, 2014).”
BackgroundApplications of OPM-MEG for translational neuroscience: a perspective
Brickwedde, M., Anders, P., Kühn, A. A., Lofredi, R., Holtkamp, M., Kaindl, A. M., Grent-‘t-Jong, T., Krüger, P., Sander, T. H., & Uhlhaas, P. J. (2024) · Translational Psychiatry · doi:10.1038/s41398-024-03047-y · Cited by 59 · see citing works
Requirements for Coregistration Accuracy in On-Scalp MEG
Zetter, R., Iivanainen, J., Stenroos, M., & Parkkonen, L. T. (2018) · Brain Topography · doi:10.1007/s10548-018-0656-5 · Cited by 57 · see citing works
“Since sensitivity and spatial resolution are related to the distance between the sources and the sensors, the need of cryogenics eventually results in a considerable loss of signal amplitude and spatial resolution (Boto et al., 2016; Iivanainen et al., 2017).”
BackgroundMethodInfluentialSelf-citationOptimal design of on‐scalp electromagnetic sensor arrays for brain source localisation
Beltrachini, L., von Ellenrieder, N., Eichardt, R., & Haueisen, J. (2021) · Human Brain Mapping · doi:10.1002/hbm.25586 · Cited by 53 · see citing works
Spherical harmonic based noise rejection and neuronal sampling with multi-axis OPMs
Tierney, T. M., Mellor, S., O’Neill, G. C., Timms, R. C., & Barnes, G. R. (2022) · NeuroImage · doi:10.1016/j.neuroimage.2022.119338 · Cited by 55 · see citing works
“With regards to limitations we have not explored the implications of important effects such as volume currents which can be larger for tangential measurements (Iivanainen et al., 2017) or the impact of different forward models (Stenroos et al.”
BackgroundHillebrand, A., Holmes, N., Sijsma, N., O’Neill, G. C., Tierney, T. M., Liberton, N., Stam, A. H., van Klink, N. E. C., Stam, C. J., Bowtell, R. W., et al. (2023) · Scientific Reports · doi:10.1038/s41598-023-31111-y · Cited by 57 · see citing works
Gutteling, T. P., Bonnefond, M., Clausner, T., Daligault, S., Romain, R., Mitryukovskiy, S. I., Fourcault, W., Josselin, V., Prado, M. L., Palacios-Laloy, A., et al. (2023) · Sensors · doi:10.3390/s23052801 · Cited by 50 · see citing works
Magnetic Source Imaging Using a Pulsed Optically Pumped Magnetometer Array
Borna, A., Carter, T. R., DeRego, P., James, C. D., & Schwindt, P. D. D. (2018) · IEEE Transactions on Instrumentation and Measurement · doi:10.1109/tim.2018.2851458 · Cited by 51 · see citing works
Naturalistic Hyperscanning with Wearable Magnetoencephalography
Holmes, N., Rea, M., Hill, R. M., Boto, E., Leggett, J., Edwards, L. J., Rhodes, N., Shah, V., Osborne, J., Fromhold, T. M., et al. (2023) · Sensors · doi:10.3390/s23125454 · Cited by 52 · see citing works
“Increased proximity to the scalp can improve sensitivity and spatial resolution beyond that which is achieved using a cryogenic MEG [26,27].”
BackgroundMethodPragmatic spatial sampling for wearable MEG arrays
Tierney, T. M., Mellor, S., O’Neill, G. C., Holmes, N., Boto, E., Roberts, G., Hill, R. M., Leggett, J., Bowtell, R. W., Brookes, M. J., et al. (2020) · Scientific Reports · doi:10.1038/s41598-020-77589-8 · Cited by 48 · see citing works
Spatial sampling of MEG and EEG based on generalized spatial-frequency analysis and optimal design
Iivanainen, J., Mäkinen, A. J., Zetter, R., Stenroos, M., Ilmoniemi, R. J., & Parkkonen, L. T. (2021) · NeuroImage · doi:10.1016/j.neuroimage.2021.118747 · Cited by 52 · see citing works
“In contrast, magnetic field is a vector field, and the orthog512 onal field components may each provide additional information about the neural sources (Iivanainen et al., 2017).”
BackgroundMethodInfluentialSelf-citationNugent, A. C., Benitez Andonegui, A., Holroyd, T., & Robinson, S. E. (2022) · Neuroimage: Reports · doi:10.1016/j.ynirp.2022.100093 · Cited by 41 · see citing works
“The simplest simulation involves measuring signal to noise; simulating a single dipole predicts a ten-fold increase in SNR for an on-scalp whole head system compared to a traditional axial gradiometer SQUID MEG system (Iivanainen et al., 2017).”
MethodMiniature Biplanar Coils for Alkali-Metal-Vapor Magnetometry
Tayler, M. C. D., Mouloudakis, K., Zetter, R., Hunter, D., Lucivero, V. G., Bodenstedt, S., Parkkonen, L. T., & Mitchell, M. W. (2022) · Physical Review Applied · doi:10.1103/physrevapplied.18.014036 · Cited by 45 · see citing works
Self-citationPratt, E. J., Ledbetter, M. P., Jiménez-Martínez, R., Shapiro, B., Solon, A. J., Iwata, G. Z., Garber, S., Gormley, J., Decker, D., Delgadillo, D., et al. (2021) · Optical and Quantum Sensing and Precision Metrology · doi:10.1117/12.2581794 · Cited by 43 · see citing works
Schofield, H., Hill, R. M., Feys, O., Holmes, N., Osborne, J., Doyle, C., Bobela, D., Corvilain, P., Wens, V., Rier, L., et al. (2024) · Imaging Neuroscience · doi:10.1162/imag_a_00283 · Cited by 47 · see citing works
“…cryogenic devices, as a thermally insulating gap is no longer required); this improves signal amplitude significantly ( Boto et al., 2016, 2017; Iivanainen et al., 2017, 2019, 2020) and theoretical calculations suggest this can offer improved spatial resolution (higher than conventional MEG…”
BackgroundEvaluation of realistic layouts for next generation on-scalp MEG: spatial information density maps
Riaz, B., Pfeiffer, C., & Schneiderman, J. F. (2017) · Scientific Reports · doi:10.1038/s41598-017-07046-6 · Cited by 39 · see citing works
Integrated Giant Magnetoresistance Technology for Approachable Weak Biomagnetic Signal Detections
Shen, H., Hu, L., & Fu, X. H. (2018) · Sensors · doi:10.3390/s18010148 · Cited by 42 · see citing works
“improve temporal and spatial resolutions, since the signal magnitude will be greater with the reduced distance between sensor and tissues [58,59].”
BackgroundPractical real-time MEG-based neural interfacing with optically pumped magnetometers
Wittevrongel, B., Holmes, N., Boto, E., Hill, R. M., Rea, M., Libert, A., Khachatryan, E., Hulle, M. M. V., Bowtell, R. W., & Brookes, M. J. (2021) · BMC Biology · doi:10.1186/s12915-021-01073-6 · Cited by 43 · see citing works
Exploring the limits of MEG spatial resolution with multipolar expansions
Wens, V. (2023) · NeuroImage · doi:10.1016/j.neuroimage.2023.119953 · Cited by 41 · see citing works
Schofield, H., Boto, E., Shah, V., Hill, R. M., Osborne, J., Rea, M., Doyle, C., Holmes, N., Bowtell, R. W., Woolger, D., et al. (2022) · Contemporary Physics · doi:10.1080/00107514.2023.2182950 · Cited by 41 · see citing works
“Sensor proximity is important due to the inverse square law and simulations suggest that scalp-based measurement offers 4–5 times higher signal strength from most cortical sources, compared to SQUID based measurements [29,30].”
BackgroundCichy, R. M., & Teng, S. (2017) · Philosophical Transactions of the Royal Society B Biological Sciences · doi:10.1098/rstb.2016.0108 · Cited by 38 · see citing works
Andersen, L. M., Oostenveld, R., Pfeiffer, C., Ruffieux, S., Jousmäki, V., Hämäläinen, M., Schneiderman, J. F., & Lundqvist, D. (2017) · PLoS ONE · doi:10.1371/journal.pone.0178602 · Cited by 38 · see citing works
“Simulations have indicated on-scalp MEG promises improved spatial precision in estimating the location of neural sources and better separation of source activations [16,17].”
BackgroundPeripheral Nerve Magnetoneurography With Optically Pumped Magnetometers
Bu, Y., Prince, J., Mojtahed, H., Kimball, D. F., Shah, V., Coleman, T. P., Sarkar, M., Rao, R., Huang, M., Schwindt, P. D. D., et al. (2022) · Frontiers in Physiology · doi:10.3389/fphys.2022.798376 · Cited by 36 · see citing works
The impact of improved MEG–MRI co-registration on MEG connectivity analysis
Chella, F., Marzetti, L., Stenroos, M., Parkkonen, L. T., Ilmoniemi, R. J., Romani, G. L., & Pizzella, V. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2019.04.061 · Cited by 37 · see citing works
“In conventional MEG devices, the dewar walls of the MEG helmet are approximately 2 cm thick (as reported in, e.g., Iivanainen et al., 2017); thus the head was reasonably close to the dewar surface, as recommended in real-world measurements.”
Self-citationMEG Sensor Selection for Neural Speech Decoding
Dash, D., Wisler, A. A., Ferrari, P., Davenport, E. M., Maldjian, J. A., & Wang, J. (2020) · IEEE Access · doi:10.1109/access.2020.3028831 · Cited by 38 · see citing works
“The OPM-MEG (on-scalp-MEG) system improves sensor-to-cortex proximity compared to the conventional MEG (in-helmet-MEG) systems thereby providing improved spatial resolution, higher signal magnitude, and better separation of source activations [54], [55].”
MethodAn, N., Cao, F., Wen, L., Wang, W., Xu, W., Wang, C., Xiang, M., Gao, Y., Sui, B., Liang, A., et al. (2022) · iScience · doi:10.1016/j.isci.2022.103752 · Cited by 35 · see citing works
“In particular, OPM-MEG has attracted the attention of researchers owing to its wearable and flexible sensor configuration (Boto et al., 2018; Iivanainen et al., 2017).”
BackgroundBoundary Element Fast Multipole Method for Enhanced Modeling of Neurophysiological Recordings
Makarov, S. N., Hämäläinen, M., Okada, Y. C., Noetscher, G. M., Ahveninen, J., & Nummenmaa, A. R. (2020) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2020.2999271 · Cited by 37 · see citing works
“The same is valid for more accurate MEG measurement techniques [20], [21].”
MethodA 7-Channel High-${T}_\text{c}$ SQUID-Based On-Scalp MEG System
Pfeiffer, C., Ruffieux, S., Jönsson, L., Chukharkin, M. L., Kalaboukhov, A., Xie, M., Winkler, D., & Schneiderman, J. F. (2019) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2019.2938688 · Cited by 41 · see citing works
Measuring the cortical tracking of speech with optically-pumped magnetometers
de Lange, P., Boto, E., Holmes, N., Hill, R. M., Bowtell, R. W., Wens, V., Tiège, X. D., Brookes, M. J., & Bourguignon, M. (2021) · NeuroImage · doi:10.1016/j.neuroimage.2021.117969 · Cited by 34 · see citing works
“expected (Boto et al., 2016; Iivanainen et al., 2017), these field patterns were more focal than those typically seen in SQUID–MEG or EEG studies.”
Concurrent spinal and brain imaging with optically pumped magnetometers
Mardell, L. C., Spedden, M. E., O’Neill, G. C., Tierney, T. M., Timms, R. C., Zich, C., Barnes, G. R., & Bestmann, S. (2024) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2024.110131 · Cited by 34 · see citing works
Evolution of MEG : A first MEG ‐feasible fluxgate magnetometer
Koshev, N., Butorina, A. V., Skidchenko, E., Kuzmichev, A. N., Ossadtchi, A. E., Ostras, M., Fedorov, M. V., & Vetoshko, P. M. (2021) · Human Brain Mapping · doi:10.1002/hbm.25582 · Cited by 32 · see citing works
“Also Iivanainen et al. (2017) show much higher total information capacity of the sensor array when sensors are located closer to the head surface.”
BackgroundWardle, S. G., & Baker, C. I. (2020) · F1000Research · doi:10.12688/f1000research.22296.1 · Cited by 32 · see citing works
Detection and analysis of cortical beta bursts in developmental EEG data
Rayson, H., Debnath, R., Alavizadeh, S., Fox, N. A., Ferrari, P. F., & Bonaiuto, J. J. (2022) · Developmental Cognitive Neuroscience · doi:10.1016/j.dcn.2022.101069 · Cited by 31 · see citing works
“…2018; Nakano et al., 2020; Pereira et al., 2018), and EEG alternatives such as newly developed, cryogen-free MEG sensors (Boto et al., 2018, 2017, 2016; Iivanainen et al., 2019, 2017; Knappe et al., 2014) which have to potential to allow acquisition of high SNR data from developmental populations.”
BackgroundOptical Co-Registration Method of Triaxial OPM-MEG and MRI
Cao, F., An, N., Xu, W., Wang, W., Li, W., Wang, C., Xiang, M., Gao, Y., & Ning, X. (2023) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2023.3263167 · Cited by 31 · see citing works
“Meanwhile, the addition of two tangential components has the potential to improve the sensitivity of OPM-MEG to the tangential and the volume source [15].”
Long, T., Song, X., Duan, Z., Suo, Y., Wu, Z., Jia, L., & Han, B. (2023) · IEEE Transactions on Instrumentation and Measurement · doi:10.1109/tim.2023.3341139 · Cited by 31 · see citing works
“This is attributed to the inverse square relationship between the amplitude of the magnetic field and the distance [13].”
BackgroundTest-retest reliability of the human connectome: An OPM-MEG study
Rier, L., Michelmann, S., Ritz, H., Shah, V., Hill, R. M., Osborne, J., Doyle, C., Holmes, N., Bowtell, R. W., Brookes, M. J., et al. (2023) · Imaging Neuroscience · doi:10.1162/imag_a_00020 · Cited by 31 · see citing works
“Improved data quality has been shown in both theory ( Boto et al., 2016; Iivanainen et al., 2017) and practice ( Boto et al., 2017), including during subject movement (e.g. Boto et al., 2018), though recording during active movement critically depends on background field control ( Holmes et al.,…”
BackgroundLocalizing on-scalp MEG sensors using an array of magnetic dipole coils
Pfeiffer, C., Andersen, L. M., Lundqvist, D., Hämäläinen, M., Schneiderman, J. F., & Oostenveld, R. (2018) · PLoS ONE · doi:10.1371/journal.pone.0191111 · Cited by 32 · see citing works
Calibration and Localization of Optically Pumped Magnetometers Using Electromagnetic Coils
Iivanainen, J., Borna, A., Zetter, R., Carter, T. R., Stephen, J. M., McKay, J., Parkkonen, L. T., Taulu, S., & Schwindt, P. D. D. (2022) · Sensors · doi:10.3390/s22083059 · Cited by 32 · see citing works
“In contrast to SQUIDs, which detect the field at least ~2 cm from the scalp, these optically pumped magnetometers (OPMs) can measure the magnetic field within millimeters from the scalp, increasing the signal magnitude and the spatial resolution of the measurement [9,10].”
BackgroundSelf-citationZahran, S., Mahmoudzadeh, M., Wallois, F., Betrouni, N., Derambure, P., Prado, M. L., Palacios-Laloy, A., & Labyt, É. (2022) · Sensors · doi:10.3390/s22083093 · Cited by 30 · see citing works
“Here, we only discuss the results obtained for the adult head model, for easier comparison with previous simulation studies of alkali OPMs and adult head models [14,15].”
BackgroundMethodResultInfluentialOn-scalp MEG SQUIDs are sensitive to early somatosensory activity unseen by conventional MEG
Andersen, L. M., Pfeiffer, C., Ruffieux, S., Riaz, B., Winkler, D., Schneiderman, J. F., & Lundqvist, D. (2020) · NeuroImage · doi:10.1016/j.neuroimage.2020.117157 · Cited by 28 · see citing works
Simulation Study of Different OPM-MEG Measurement Components
Marhl, U., Sander, T. H., & Jazbinšek, V. (2022) · Sensors · doi:10.3390/s22093184 · Cited by 29 · see citing works
“This was already shown in a couple of previous works [6,7], and it was also confirmed by our results in Tables 1 and 2, where we show that the OPM-MEG configurations have an RMSsignal around 2.”
BackgroundResultContactless measurements of retinal activity using optically pumped magnetometers
Westner, B. U., Lubell, J. I., Jensen, M., Hokland, S., & Dalal, S. S. (2021) · NeuroImage · doi:10.1016/j.neuroimage.2021.118528 · Cited by 28 · see citing works
“…can rather be placed ndividually and close to the scalp, which has yielded better signalo-noise ratio (SNR) for measurements of brain activity in simulations Boto et al., 2016; Iivanainen et al., 2017 ) and real recordings ( Boto t al., 2018; 2017; Hill et al., 2020; Iivanainen et al., 2020 ).”
BackgroundPfeiffer, C., Ruffieux, S., Andersen, L. M., Kalabukhov, A., Winkler, D., Oostenveld, R., Lundqvist, D., & Schneiderman, J. F. (2020) · NeuroImage · doi:10.1016/j.neuroimage.2020.116686 · Cited by 27 · see citing works
“At 3 closer proximity to the head –and thus to the neural sources– on-scalp MEG 4 should be able to measure weaker signals as well as capture higher spatial fre5 quencies compared to conventional MEG [1, 2].”
Simultaneous whole-head electrophysiological recordings using EEG and OPM-MEG
Seedat, Z. A., Pier, K. S., Holmes, N., Rea, M., Al-Hilaly, L., Tierney, T. M., Embury, C. M., Pardington, R., Mullinger, K. J., Cross, J. H., et al. (2024) · Imaging Neuroscience · doi:10.1162/imag_a_00179 · Cited by 26 · see citing works
“Because OPMs can get closer to the scalp than cryogenic sensors, they detect a signal that is less spatially diffuse and higher amplitude, bringing improved sensitivity and spatial resolution ( Borna et al., 2017; Boto et al., 2016; Iivanainen et al., 2017; Nugent et al., 2022).”
BackgroundHolmes, N., Bowtell, R. W., Brookes, M. J., & Taulu, S. (2023) · Sensors · doi:10.3390/s23146537 · Cited by 29 · see citing works
Hill, R. M., Schofield, H., Boto, E., Rier, L., Osborne, J., Doyle, C., Worcester, F., Hayward, T., Holmes, N., Bowtell, R. W., et al. (2024) · Imaging Neuroscience · doi:10.1162/imag_a_00112 · Cited by 26 · see citing works
“They also show experimental evidence of the high importance of expanding OPM-MEG systems to higher channel count (which has been highlighted by previous theory papers (e.g., Boto et al., 2016; Iivanainen et al., 2017).”
BackgroundResultTowards the Non-Zero Field Cesium Magnetic Sensor Array for Magnetoencephalography
Petrenko, M. V., Dmitriev, S. P., Pazgalev, A. S., Ossadtchi, A. E., & Vershovskii, A. K. (2021) · IEEE Sensors Journal · doi:10.1109/jsen.2021.3089455 · Cited by 24 · see citing works
Data‐driven model optimization for optically pumped magnetometer sensor arrays
Duque‐Muñoz, L., Tierney, T. M., Meyer, S. S., Boto, E., Holmes, N., Roberts, G., Leggett, J., Vargas‐Bonilla, J. F., Bowtell, R. W., Brookes, M. J., et al. (2019) · Human Brain Mapping · doi:10.1002/hbm.24707 · Cited by 24 · see citing works
“Additionally, we have measurements of magnetic fields tangential (rather than radial) to the cortical surface that we still have not used (Iivanainen et al., 2017).”
MethodEffects of Different Head Models in Wearable OPM-MEG
Cao, F., An, N., Wang, W., Xu, W., Li, W., Wang, C., Xiang, M., Gao, Y., & Ning, X. (2022) · IEEE Transactions on Instrumentation and Measurement · doi:10.1109/tim.2022.3192287 · Cited by 24 · see citing works
Single-trial classification of evoked responses to auditory tones using OPM- and SQUID-MEG
Iivanainen, J., Carter, T. R., Trumbo, M., McKay, J., Taulu, S., Wang, J., Stephen, J. M., Schwindt, P. D. D., & Borna, A. (2023) · Journal of Neural Engineering · doi:10.1088/1741-2552/acfcd9 · Cited by 24 · see citing works
“In contrast to SQUIDs, OPMs enable wearable sensor arrays detecting the field within millimeters from the scalp increasing the usability and spatial resolution of MEG (Iivanainen et al 2017, Boto et al 2018).”
Self-citationBadier, J., Schwartz, D., Bénar, C., Kanzari, K., Daligault, S., Romain, R., Mitryukovskiy, S. I., Fourcault, W., Josselin, V., Prado, M. L., et al. (2023) · eNeuro · doi:10.1523/eneuro.0222-23.2023 · Cited by 22 · see citing works
“The additional information offered by a vectorial measurement of the magnetic field, also reported in the present study, will be of interest to better characterize the spatiotemporal dynamics of epileptic activity and to interpret clinical data (Iivanainen et al., 2017; Zahran et al., 2022).”
BackgroundResultInfluentialNew Cognitive Neurotechnology Facilitates Studies of Cortical–Subcortical Interactions
Min, B., Hämäläinen, M., & Pantazis, D. (2020) · Trends in biotechnology · doi:10.1016/j.tibtech.2020.03.003 · Cited by 25 · see citing works
“This allows the OPMs to be placed within millimeters from the scalp, and the sensor array can be adapted to the size and shape of the subject’s head, substantially increasing spatial resolution [34, 35].”
BackgroundMethodTriaxial Vector Operation in Near-Zero Field of Atomic Magnetometer With Femtotesla Sensitivity
Lu, F., Lu, J., Li, B., Yan, Y., Zhang, S., Yin, K., Ye, M., & Han, B. (2022) · IEEE Transactions on Instrumentation and Measurement · doi:10.1109/tim.2022.3162282 · Cited by 23 · see citing works
- 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
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
