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A 90‐channel triaxial magnetoencephalography system using optically pumped magnetometers.

Authors :
Rea, Molly
Boto, Elena
Holmes, Niall
Hill, Ryan
Osborne, James
Rhodes, Natalie
Leggett, James
Rier, Lukas
Bowtell, Richard
Shah, Vishal
Brookes, Matthew J.
Source :
Annals of the New York Academy of Sciences. Nov2022, Vol. 1517 Issue 1, p107-124. 18p. 5 Color Photographs, 2 Graphs.
Publication Year :
2022

Abstract

Magnetoencephalography (MEG) measures the small magnetic fields generated by current flow in neural networks, providing a noninvasive metric of brain function. MEG is well established as a powerful neuroscientific and clinical tool. However, current instrumentation is hampered by cumbersome cryogenic field‐sensing technologies. In contrast, MEG using optically pumped magnetometers (OPM‐MEG) employs small, lightweight, noncryogenic sensors that provide data with higher sensitivity and spatial resolution, a natural scanning environment (including participant movement), and adaptability to any age. However, OPM‐MEG is new and the optimum way to design a system is unknown. Here, we construct a novel, 90‐channel triaxial OPM‐MEG system and use it to map motor function during a naturalistic handwriting task. Results show that high‐precision magnetic field control reduced background fields to ∼200 pT, enabling free participant movement. Our triaxial array offered twice the total measured signal and better interference rejection compared to a conventional (single‐axis) design. We mapped neural oscillatory activity to the sensorimotor network, demonstrating significant differences in motor network activity and connectivity for left‐handed versus right‐handed handwriting. Repeatability across scans showed that we can map electrophysiological activity with an accuracy ∼4 mm. Overall, our study introduces a novel triaxial OPM‐MEG design and confirms its potential for high‐performance functional neuroimaging. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
00778923
Volume :
1517
Issue :
1
Database :
Academic Search Index
Journal :
Annals of the New York Academy of Sciences
Publication Type :
Academic Journal
Accession number :
160284854
Full Text :
https://doi.org/10.1111/nyas.14890