Evidence map›Paper›PMID 37177460›Full record

ArticleSensors (Basel, Switzerland)2023

Yttrium-Iron Garnet Magnetometer in MEG: Advance towards Multi-Channel Arrays.

Ekaterina Skidchenko, Anna Butorina, Maxim Ostras, Petr Vetoshko, Alexey Kuzmichev, Nikolay Yavich, Mikhail Malovichko, Nikolay Koshev

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

8 authors.

Ekaterina SkidchenkoCNBR, Skolkovo Institute of Science and Technology, 121205 Moscow, Russia.ORCID 0000-0003-0945-2436
Anna ButorinaCNBR, Skolkovo Institute of Science and Technology, 121205 Moscow, Russia.
Maxim OstrasM-Granat, Russian Quantum Center, 121205 Moscow, Russia.
Petr VetoshkoM-Granat, Russian Quantum Center, 121205 Moscow, Russia.ORCID 0000-0002-0561-1850
Alexey KuzmichevM-Granat, Russian Quantum Center, 121205 Moscow, Russia.
Nikolay YavichCNBR, Skolkovo Institute of Science and Technology, 121205 Moscow, Russia.ORCID 0000-0002-8913-7710
Mikhail MalovichkoComputational Geophysics Lab, Moscow Institute of Physics and Technology, 141701 Dolgoprudny, Russia.
Nikolay KoshevCNBR, Skolkovo Institute of Science and Technology, 121205 Moscow, Russia.

Funding

Russian Science Foundation 22-71-10120
6 · The paper itself

Abstract

Recently, a new kind of sensor applicable in magnetoencephalography (MEG) has been presented: a solid-state yttrium-iron garnet magnetometer (YIGM). The feasibility of yttrium-iron garnet magnetometers (YIGMs) was demonstrated in an alpha-rhythm registration experiment. In this paper, we propose the analysis of lead-field matrices for different possible multi-channel on-scalp sensor layouts using YIGMs with respect to information theory. Real noise levels of the new sensor were used to compute signal-to-noise ratio (SNR) and total information capacity (TiC), and compared with corresponding metrics that can be obtained with well-established MEG systems based on superconducting quantum interference devices (SQUIDs) and optically pumped magnetometers (OPMs). The results showed that due to YIGMs' proximity to the subject's scalp, they outperform SQUIDs and OPMs at their respective noise levels in terms of SNR and TiC. However, the current noise levels of YIGM sensors are unfortunately insufficient for constructing a multichannel YIG-MEG system. This simulation study provides insight into the direction for further development of YIGM sensors to create a multi-channel MEG system, namely, by decreasing the noise levels of sensors.

Indexed as

gradiometersmagnetometersMEGOPMssimulationSNRSQUIDYIGM

Identifiers

PMID37177460
PMCPMC10181089

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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.