Abstract
Wearable magnetoencephalography based on optically pumped magnetometers (OPM-MEG) offers non-invasive and high-fidelity measurement of human brain electrophysiology. The flexibility of OPM-MEG also means it can be deployed in participants of all ages and permits scanning during movement. However, the magnetic fields generated by neuronal currents - which form the basis of the OPM-MEG signal - are much smaller than environmental fields, and this means measurements are highly sensitive to interference. Further, OPMs have a low dynamic range, and should be operated in near-zero background field. Scanners must therefore be housed in specialised magnetically shielded rooms (MSRs), formed from multiple layers of shielding material. The MSR is a critical component, and current OPM-optimised shields are large (>3 m in height), heavy (>10,000 kg) and expensive (with up to 5 layers of material). This restricts the uptake of OPM-MEG technology. Here, we show that the application of the Maxwell filtering techniques signal space separation (SSS) and its spatiotemporal extension (tSSS) to OPM-MEG data can isolate small signals of interest measured in the presence of large interference. We compare phantom recordings and MEG data from a participant performing a motor task in a state-of-the-art 5-layer MSR, to similar data collected in a lightly shielded room: application of tSSS to data recorded in the lightly shielded room allowed accurate localisation of a dipole source in the phantom and neuronal sources in the brain. Our results point to future deployment of OPM-MEG in lighter, cheaper and easier-to-site MSRs which could catalyse widespread adoption of the technology.