Optimising the sensing volume of OPM sensors for MEG source reconstruction

Autor: Yulia Bezsudnova, Lari M. Koponen, Giovanni Barontini, Ole Jensen, Anna U. Kowalczyk
Jazyk: angličtina
Rok vydání: 2022
Předmět:
Zdroj: NeuroImage, Vol 264, Iss , Pp 119747- (2022)
Druh dokumentu: article
ISSN: 1095-9572
DOI: 10.1016/j.neuroimage.2022.119747
Popis: 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.
Databáze: Directory of Open Access Journals