Optimising the sensing volume of OPM sensors for MEG source reconstruction

•We present a model to optimise the sensing volume of OPM sensors for MEG applications in realistic conditions•We show how the optimal cell dimensions and number of sensors in the array depend on the environmental and brain noise•We find the optimal sensing dimensions both for SERF and NMOR OPM in a single sensor arrangement and in ∼70 sensor arrays•Our model can be used as a toolkit for optimising OPM-MEG systems in a wide range of experimental conditions 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.