Back

Validation of a combined cylindrical shield and partial-coverage mobile OPM system for detecting neuromagnetic sensorimotor responses in humans

Bailey, L. M.; Bardouille, T.

2025-06-12 neuroscience
10.1101/2025.06.10.657831 bioRxiv
Show abstract

Optically pumped magnetometers (OPMs) have emerged as a promising technology for neuromagnetic recording in humans. Current state-of-the-art OPM systems are housed in immobile magnetically-shielded rooms to reduce external electromagnetic noise, and typically comprise sensor arrays covering the entire head. Here we sought to validate a low-cost, mobile OPM system comprising a small cylindrical mu-metal shield and partial sensor coverage. Twelve participants underwent right-sided median nerve stimulation (MNS) and cued right-handed button-pressing intended to elicit ubiquitous sensorimotor responses: somatosensory-evoked fields (SEFs; comprising N20m, P35m and P60m components) and event-related (de)synchronisation (ERD/ERS) of oscillatory neuronal rhythms in the mu and beta frequency ranges. Following MNS, we observed robust N20m and P60m peaks, as well as the expected mu ERD and beta ERS effects. Moreover, we successfully localized these responses to expected cortical generators using distributed source modelling. SEFs and mu ERD were both maximal in left (i.e., contralateral to stimulation) primary somatosensory cortex (central sulcus, postcentral gyrus and sulcus), while beta ERS appeared more anteriorly, in the central sulcus and precentral gyrus. By contrast, results from the button-pressing paradigm were less conclusive--we observed beta ERS (but not mu/beta ERD), and an atypical distribution of the ERS effect over posterior ROIs. Overall, our findings provide proof-of-principle support for the use of our system in the context of passive (e.g., MNS) paradigms; its viability for cued movement tasks will require further development. Based on these results, we make recommendations for further developments in mobile and partial-coverage OPM.

Matching journals

The top 3 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.