Validation of a combined cylindrical shield and partial-coverage mobile OPM system for detecting neuromagnetic sensorimotor responses in humans
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".