Evidence map›Paper›PMID 36403733›Full record

ArticleNeuroImage2022

Optimising the sensing volume of OPM sensors for MEG source reconstruction.

Yulia Bezsudnova, Lari M Koponen, Giovanni Barontini, Ole Jensen, Anna U Kowalczyk

Abstract read
In one paragraph

Article in NeuroImage, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
–field-weighted citation impact
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

10 citing papers in PubMed.

  1. Spatial-Jitter Model for Magnetoencephalography Sensor Arrays.IEEE transactions on medical imaging · 2026
    Article
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  3. Article
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  5. Article
  6. Article
  7. Review
  8. Article
  9. Article
  10. How far neuroscience is from understanding brains.Frontiers in systems neuroscience · 2023
    Article
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

5 authors.

Yulia BezsudnovaSchool of Physics and Astronomy, University of Birmingham, Edgbaston, Birmingham, B15 2TT, United Kingdom.
Lari M KoponenCentre for Human Brain Health, School of Psychology, University of Birmingham, Edgbaston, Birmingham, B15 2SA, United Kingdom.
Giovanni BarontiniSchool of Physics and Astronomy, University of Birmingham, Edgbaston, Birmingham, B15 2TT, United Kingdom; Centre for Human Brain Health, School of Psychology, University of Birmingham, Edgbaston, Birmingham, B15 2SA, United Kingdom.
Ole JensenCentre for Human Brain Health, School of Psychology, University of Birmingham, Edgbaston, Birmingham, B15 2SA, United Kingdom.
Anna U KowalczykCentre for Human Brain Health, School of Psychology, University of Birmingham, Edgbaston, Birmingham, B15 2SA, United Kingdom. Electronic address: a.u.kowalczyk@bham.ac.uk.

Funding

Wellcome Trust 207550Wellcome Trust 207550/Z/17/Z
6 · The paper itself

Abstract

Magnetoencephalography (MEG) based on optically pumped magnetometers (OPMs) has been hailed as the future of electrophysiological recordings from the human brain. In this work, we investigate how the dimensions of the sensing volume (the vapour cell) affect the performance of both a single OPM-MEG sensor and a multi-sensor OPM-MEG system. We consider a realistic noise model that accounts for background brain activity and residual noise. By using source reconstruction metrics such as localization accuracy and time-course reconstruction accuracy, we demonstrate that the best overall sensitivity and reconstruction accuracy are achieved with cells that are significantly longer and wider that those of the majority of current commercial OPM sensors. Our work provides useful tools to optimise the cell dimensions of OPM sensors in a wide range of environments.

Indexed as

Brain MappingMagnetoencephalographyBrainHumansMagnetoencephalographyOptically pumped magnetometersOptimisationQuantum sensorsSensing volumeSource reconstruction

Identifiers

PMID36403733
PMCPMC7615061

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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.