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Optimization of OPM-MEG layouts with a limited number of sensors
ID
Marhl, Urban
(
Author
),
ID
Hren, Rok
(
Author
),
ID
Sander, Tilmann
(
Author
),
ID
Jazbinšek, Vojko
(
Author
)
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https://www.mdpi.com/1424-8220/25/9/2706
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Abstract
Magnetoencephalography (MEG) is a non-invasive neuroimaging technique that measures weak magnetic fields generated by neural electrical activity in the brain. Traditional MEG systems use superconducting quantum interference device (SQUID) sensors, which require cryogenic cooling and employ a dense array of sensors to capture magnetic field maps (MFMs) around the head. Recent advancements have introduced optically pumped magnetometers (OPMs) as a promising alternative. Unlike SQUIDs, OPMs do not require cooling and can be placed closer to regions of interest (ROIs). This study aims to optimize the layout of OPM-MEG sensors, maximizing information capture with a limited number of sensors. We applied a sequential selection algorithm (SSA), originally developed for body surface potential mapping in electrocardiography, which requires a large database of full-head MFMs. While modern OPM-MEG systems offer full-head coverage, expected future clinical use will benefit from simplified procedures, where handling a lower number of sensors is easier and more efficient. To explore this, we converted full-head SQUID-MEG measurements of auditory-evoked fields (AEFs) into OPM-MEG layouts with 80 sensor sites. System conversion was done by calculating a current distribution on the brain surface using minimum norm estimation (MNE). We evaluated the SSA’s performance under different protocols, for example, using measurements of single or combined OPM components. We assessed the quality of estimated MFMs using metrics, such as the correlation coefficient (CC), root-mean-square error, and relative error. Additionally, we performed source localization for the highest auditory response (M100) by fitting equivalent current dipoles. Our results show that the first 15 to 20 optimally selected sensors (CC > 0.95, localization error < 1 mm) capture most of the information contained in full-head MFMs. Our main finding is that for event-related fields, such as AEFs, which primarily originate from focal sources, a significantly smaller number of sensors than currently used in conventional MEG systems is sufficient to extract relevant information.
Language:
English
Keywords:
magnetoencephalography
,
optically pumped magnetometers
,
magnetic field
,
neuroimaging
,
sensors
,
optimization
Work type:
Article
Typology:
1.01 - Original Scientific Article
Organization:
FMF - Faculty of Mathematics and Physics
Publication status:
Published
Publication version:
Version of Record
Year:
2025
Number of pages:
24 str.
Numbering:
Vol. 25, iss. 9, art. no. 2706
PID:
20.500.12556/RUL-168805
UDC:
537:616.8
ISSN on article:
1424-8220
DOI:
10.3390/s25092706
COBISS.SI-ID:
234231299
Publication date in RUL:
25.04.2025
Views:
373
Downloads:
109
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Record is a part of a journal
Title:
Sensors
Shortened title:
Sensors
Publisher:
MDPI
ISSN:
1424-8220
COBISS.SI-ID:
10176278
Licences
License:
CC BY 4.0, Creative Commons Attribution 4.0 International
Link:
http://creativecommons.org/licenses/by/4.0/
Description:
This is the standard Creative Commons license that gives others maximum freedom to do what they want with the work as long as they credit the author.
Secondary language
Language:
Slovenian
Keywords:
magnetoencefalografija
,
optični magnetometri
,
magnetno polje
,
nevroslikanje
,
senzorji
,
optimizacija
Projects
Funder:
ARIS - Slovenian Research and Innovation Agency
Project number:
P2-0348-2022
Name:
Nove slikovno-analitske metode
Funder:
ARIS - Slovenian Research and Innovation Agency
Project number:
N1-0283-2023
Name:
Napredno mapiranje nevrovaskularne sklopitve z združenima tehnikama bližnje infrardeče spektroskopije in magnetoencefalografije na osnovi optičnih magnetometrov
Funder:
ARIS - Slovenian Research and Innovation Agency
Project number:
BI-DE/23-24-005-2023
Name:
Prilagodljivi merski sistemi na osnovi OPM
Funder:
DAAD - Deutscher Akademischer Austauschdienst
Project number:
57570963
Funder:
DFG - Deutsche Forschungsgemeinschaft
Project number:
505063244
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