Refined signal space separation methods for on-scalp MEG systems

Objective.The reliability of biomagnetic measurements is improved by data processing techniques like the signal space separation (SSS) method, which transforms multichannel signals into device-independent channels with separate components for internal biomagnetic and external interference signals based on sensor geometry. Newer on-scalp sensors, such as optically-pumped magnetometers (OPMs), have recently been deployed in magnetoencephalography (MEG) systems, bringing a need for refined SSS variants to capture the potentially improved spatial resolution provided by the on-scalp sensors. Standard single-origin SSS may fail to capture the full brain-space when the sensors are on scalp. In this paper, we propose potential solutions to this problem including novel multi-origin SSS (mSSS). With multiple optimized origins and radii used together, the basis can span the brain-space without encroaching on the sensor space. Other adaptations to SSS include vector spheroidal harmonics, which create signal space expansions using ellipsoidal geometry to model the brain-space. This adaptation is further modified to combine an interior spheroidal with exterior single-SSS.Approach.Focusing on two-origin mSSS, the spheroidal constructions and the single-origin SSS are investigated with simulated data from an internal current dipole source coupled with an external interference signal with geometry from the 432-channel Kernel Flux OPM system, the 306-channel MEGIN/Elekta Neuromag SQUID system, and the 192-Channel Triaxial QuSpin OPM system. Finally, each variant is used to process collected data including auditory evoked data measured at the University of Washington with the Kernel Flux OPM system, previously recorded empty-room data collected in a lightly-shielded magnetically shielded room with 192-channel third generation triaxial QuSpin Zero Field Magnetometers, and publicly available single-subject audiovisual data collected with an 86-Channel dual-axis QuSpin OPM system at the University College London.Main results.The mSSS method has comparable or better stability to the SSS method in all sensor geometries and reconstructs interior simulated signals while successfully suppressing exterior interference, and performs better in simulated cases with variably placed on-scalp MEG systems. Additionally, results with Kernel and QuSpin data show the mSSS basis provides a lower noise floor than other SSS variants and had the best performance with on-scalp systems, even with low-channel-count OPM systems.Significance.With on-scalp MEG systems becoming more widely available, the MEG community needs updated data analysis techniques. mSSS is a straightforward and robust modification to the SSS method which functions for novel on-scalp sensor systems without needing drastic modification to the underlying mathematical method.