Evidence map›Paper›PMID 33303793›Full record

ArticleScientific reports2020

Pragmatic spatial sampling for wearable MEG arrays.

Tim M Tierney, Stephanie Mellor, George C O'Neill, Niall Holmes, Elena Boto, Gillian Roberts, Ryan M Hill, James Leggett, Richard Bowtell, Matthew J Brookes and 1 more

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed
3.2field-weighted citation impact, top 7% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

25 citing papers in PubMed, 41 citations in OpenAlex.

  1. Spatial-Jitter Model for Magnetoencephalography Sensor Arrays.IEEE transactions on medical imaging · 2026
    Article
  2. Article
  3. Enhanced Neural Decoding With Optically Pumped Magnetometer MEG Using Multivariate Pattern Analysis.IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society · 2026
    Article
  4. Article
  5. SPM-30 years and beyond.Cerebral cortex (New York, N.Y. : 1991) · 2025
    Review
  6. Article
  7. Article
  8. Determining sensor geometry and gain in a wearable MEG system.Imaging neuroscience (Cambridge, Mass.) · 2025
    Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Review
  14. Article
  15. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors at 3 institutions in 1 country.

Tim M TierneyWellcome Centre for Human Neuroimaging, UCL Institute of Neurology, London, WC1N 3AR, UK. tim.tierney.12@ucl.ac.uk.
Stephanie MellorWellcome Centre for Human Neuroimaging, UCL Institute of Neurology, London, WC1N 3AR, UK.
George C O'NeillWellcome Centre for Human Neuroimaging, UCL Institute of Neurology, London, WC1N 3AR, UK.
Niall HolmesSir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, NG7 2RD, UK.
Elena BotoSir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, NG7 2RD, UK.
Gillian RobertsSir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, NG7 2RD, UK.
Ryan M HillSir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, NG7 2RD, UK.
James LeggettSir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, NG7 2RD, UK.
Richard BowtellSir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, NG7 2RD, UK.
Matthew J BrookesSir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, NG7 2RD, UK.
Gareth R BarnesWellcome Centre for Human Neuroimaging, UCL Institute of Neurology, London, WC1N 3AR, UK.
University of Nottingham · GBWellcome Centre for Human Neuroimaging · GBUniversity College London · GB

Funding

Biotechnology and Biological Sciences Research Council BB/M009645/1Medical Research Council MR/K005464/1Medical Research Council MR/K6010/86010/1Wellcome Trust 203147/Z/16/ZWellcome Trust 203257/B/16/ZWellcome Trust 203257/Z/16/Z
6 · The paper itself

Abstract

Several new technologies have emerged promising new Magnetoencephalography (MEG) systems in which the sensors can be placed close to the scalp. One such technology, Optically Pumped MEG (OP-MEG) allows for a scalp mounted system that provides measurements within millimetres of the scalp surface. A question that arises in developing on-scalp systems is: how many sensors are necessary to achieve adequate performance/spatial discrimination? There are many factors to consider in answering this question such as the signal to noise ratio (SNR), the locations and depths of the sources, density of spatial sampling, sensor gain errors (due to interference, subject movement, cross-talk, etc.) and, of course, the desired spatial discrimination. In this paper, we provide simulations which show the impact these factors have on designing sensor arrays for wearable MEG. While OP-MEG has the potential to provide high information content at dense spatial samplings, we find that adequate spatial discrimination of sources (< 1 cm) can be achieved with relatively few sensors (< 100) at coarse spatial samplings (~ 30 mm) at high SNR. After this point approximately 50 more sensors are required for every 1 mm improvement in spatial discrimination. Comparable discrimination for traditional cryogenic systems require more channels by these same metrics. We also show that sensor gain errors have the greatest impact on discrimination between deep sources at high SNR. Finally, we also examine the limitation that aliasing due to undersampling has on the effective SNR of on-scalp sensors.

Identifiers

PMID33303793
PMCPMC7729945
OpenAlexW3111071107

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.