School 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.
Neuroimage. 2022 Dec 1;264:119747. doi: 10.1016/j.neuroimage.2022.119747. Epub 2022 Nov 18.
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.
基于光泵磁强计(OPM)的脑磁图(MEG)被誉为未来人类大脑电生理记录的一种手段。在这项工作中,我们研究了传感体积(蒸气室)的尺寸如何影响单个 OPM-MEG 传感器和多传感器 OPM-MEG 系统的性能。我们考虑了一种现实的噪声模型,该模型考虑了背景脑活动和残余噪声。通过使用源重建指标,如定位准确性和时间过程重建准确性,我们证明,使用明显长于大多数当前商用 OPM 传感器的细胞可以获得最佳的整体灵敏度和重建准确性。我们的工作为在广泛的环境中优化 OPM 传感器的细胞尺寸提供了有用的工具。