Characterization of a flexible cap for simultaneous OPM-MEG and EEG measurements

Objective.Combining magnetoencephalography (MEG) and electroencephalography (EEG) can lead to more accurate source reconstruction results. Previous efforts of simultaneous EEG and MEG using optically pumped magnetometers (OPM-MEG) used a two-layer setup, where a helmet or cap with mounted OPMs was worn on top of an EEG cap, resulting in decreased OPM signal amplitudes. This is inevitable for rigid OPM-MEG helmets used by most research groups, which are often heavy and need fixation, require time-consuming customization or do not adapt to different head shapes, diminishing the advantages of OPM-MEG. In this study, we therefore aimed to create a flexible cap that enables fully integrated simultaneous OPM-MEG and EEG measurements, which are suitable for source reconstruction and yield the same signal quality as each individual modality.Approach.We integrated OPM mounts into a commercial EEG cap and implemented a sensor localization pipeline based on co-registering the known OPM mount geometry to 3D scans of participants wearing the cap. In a multi-paradigm experiment with five volunteers, we investigated how much OPMs shift during an experiment due to head movements of the participant. We also compared signal-to-noise ratios and artifact strengths between single-modality and multimodal measurements.Main results.The distribution of changes in OPM positions and orientations are within acceptable limits for source reconstruction as published in a simulation study. Occipital OPMs experienced larger shifts. No systematic difference in signal-to-noise ratios or artifact strengths between single-modality and multimodal acquisition could be observed, indicating no signal degradation due to the presence of the other modality.Significance.Measuring simultaneous OPM-MEG and EEG using a flexible cap could improve source reconstruction results and help to bring OPM-MEG to clinical settings due to easier comparison and verification with the established EEG, which is relevant for presurgical epilepsy evaluation.