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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.
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“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]
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“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]
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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
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