The DOI matches its Crossref record; 32 of the 32 references it cites were found in a registry or an index.
SQUID sensor array configurations for magnetoencephalography applications
Open accessAbstract
Electrophysiological activity in the human brain generates a small magnetic field from the spatial superposition of individual neuronal source currents. At a distance of about 15 mm from the scalp, the observed field is of the order of 10 −13 to 10 −12 T peak-to-peak. This measurement process is termed magnetoencephalography (MEG). In order to minimize instrumental noise, the MEG is usually detected using superconducting flux transformers, coupled to SQUID (superconducting quantum interference device) sensors. Since MEG signals are also measured in the presence of significant environmental magnetic noise, flux transformers must be designed to strongly attenuate environmental noise, maintain low instrumental noise and maximize signals from the brain. Furthermore, the flux transformers must adequately sample spatial field variations if the brain activity is to be imaged. The flux transformer optimization for maximum brain signal-to-noise ratio (SNR) requires analysis of the spatial and temporal properties of brain activity, the environmental noise and how these signals are coupled to the flux transformer. Flux transformers that maximize SNR can detect the smallest brain signals and have the best ability to spatially separate dipolar sources. An optimal flux transformer design is a synthetic higher-order gradiometer based on relatively short-baseline first-order radial gradiometer primary sensors.
Overview
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
Verification
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?
The cited source says what the claim attributes to it.
In the citing paper
“Mapping of internal current sources from externally measured magnetic fields is attempted by solving the forward or inverse problem [7,17].”
From Biomagnetism using SQUIDs: status and perspectives (2006) · cites this paper as [7]
The check wasn’t confident either way, so it gives no verdict — never disputed.
In the citing paper
“To obtain an approximate solution of the inverse problem, various variants of the minimum norm technique are usually employed [7,16,19].”
From Biomagnetism using SQUIDs: status and perspectives (2006) · cites this paper as [7]
Experimental — accuracy not yet measured
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
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
Possible new effects in superconductive tunnelling
Josephson, B. D. (1962) · Physics Letters · doi:10.1016/0031-9163(62)91369-0 · Cited by 4,143
Van Veen, B. D., Van Drongelen, W., Yuchtman, M., & Suzuki, A. (1997) · IEEE Transactions on Biomedical Engineering · doi:10.1109/10.623056 · Cited by 2,561
Basic mathematical and electromagnetic concepts of the biomagnetic inverse problem.
Sarvas, J. (1987) · Physics in Medicine and Biology · doi:10.1088/0031-9155/32/1/004 · Cited by 1,945
Signal-space projection method for separating MEG or EEG into components
Uusitalo, M. A., & Ilmoniemi, R. J. (1997) · Medical & Biological Engineering & Computing · doi:10.1007/bf02534144 · Cited by 938
Magnetoencephalography: Evidence of Magnetic Fields Produced by Alpha-Rhythm Currents
Cohen, D. (1968) · Science · doi:10.1126/science.161.3843.784 · Cited by 750
Quantum Interference Effects in Josephson Tunneling
Jaklevic, R. C., Lambe, J., Silver, A. H., & Mercereau, J. E. (1964) · Physical Review Letters · doi:10.1103/physrevlett.12.159 · Cited by 520
Tesche, C. D., Uusitalo, M. A., Ilmoniemi, R. J., Huotilainen, M., Kajola, M., & Salonen, O. L. M. (1995) · Electroencephalography and Clinical Neurophysiology · doi:10.1016/0013-4694(95)00064-6 · Cited by 356
Williamson, S. J., & Kaufman, L. (1981) · Journal of Magnetism and Magnetic Materials · doi:10.1016/0304-8853(81)90078-0 · Cited by 328
A new interpretation of the generators of BAEP waves I-V: results of a spatio-temporal dipole model.
Scherg, M., & von Cramon, D. (1985) · Electroencephalography and Clinical Neurophysiology · doi:10.1016/0168-5597(85)90006-1 · Cited by 308
Flagged first, then by citations
Research works printed but not linked: 2
- Huang M, 1997, NeuroImage, 5, S441
- Buchanan D S, 1998, 11, 44
Cited by
Sorted by citations
Boto, E., Meyer, S. S., Shah, V., Alem, O., Knappe, S., Kruger, P., Fromhold, T. M., Lim, M., Glover, P. M., Morris, P. G., et al. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2017.01.034 · Cited by 471
Hillebrand, A., Barnes, G. R., Bosboom, J. L., Berendse, H. W., & Stam, C. J. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2011.11.005 · Cited by 416
Multi-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
Biomagnetism using SQUIDs: status and perspectives
Sternickel, K., & Braginski, A. I. (2006) · Superconductor Science and Technology · doi:10.1088/0953-2048/19/3/024 · Cited by 180
Emotional Automaticity Is a Matter of Timing
Luo, Q., Holroyd, T., Majestic, C., Cheng, X., Schechter, J., & Blair, R. J. (2010) · The Journal of Neuroscience · doi:10.1523/jneurosci.bc-5668-09.2010 · Cited by 118
Metadata
- Authors
- Vrba, J., & Robinson, S. E.
- ORCID
- Venue
- Superconductor Science and Technology
- Publisher
- IOP Publishing
- Published
- 2002-08-13
- Volume
- 15
- Issue
- 9
- Pages
- R51-R89
- ISSN
- 0953-2048 (ISSN-L)
- OpenAlex
- W1995444235
- Cited by
- 126
- References
- 32
- Citations by year
- 2026: 8 · 2025: 11 · 2024: 7 · 2023: 10 · 2022: 6 · 2021: 7 · 2020: 9 · 2019: 12 · 2018: 2 · 2017: 4 · 2016: 6 · 2015: 3 · 2014: 5 · 2013: 2 · 2012: 3
- FWCI
- 0.70
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Superconductor Science and Technology (publishedVersion)
- Topics
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Magnetic Field Sensors Techniques
- Physical Sciences › Physics and Astronomy › Atomic and Molecular Physics, and Optics › Atomic and Subatomic Physics Research
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Superconducting Materials and Applications
- Keywords
- magnetoencephalography, signal-to-noise ratio, brain magnetic fields
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
