ArticleHuman brain mapping2019
Data-driven model optimization for optically pumped magnetometer sensor arrays.
Article in Human brain mapping, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed, 25 citations in OpenAlex.
- Ambulation improves memory for rotated scenes.Memory & cognition · 2026Article
- SPM-30 years and beyond.Cerebral cortex (New York, N.Y. : 1991) · 2025Review
- Volume conductor models for magnetospinography.Scientific reports · 2025Article
- Inferring laminar origins of MEG signals with optically pumped magnetometers (OPMs): A simulation study.Imaging neuroscience (Cambridge, Mass.) · 2025Article
- A fully integrated whole-head helium OPM MEG: a performance assessment compared to cryogenic MEG.Frontiers in medical technology · 2025Article
- Article
- On-scalp magnetocorticography with optically pumped magnetometers: Simulated performance in resolving simultaneous sources.Neuroimage. Reports · 2022Article
- Imaging somatosensory cortex responses measured by OPM-MEG: Variational free energy-based spatial smoothing estimation approach.iScience · 2022Article
- OMMR: Co-registration toolbox of OPM-MEG and MRI.Frontiers in neuroscience · 2022Article
- Optimal design of on-scalp electromagnetic sensor arrays for brain source localisation.Human brain mapping · 2021Article
- Bridging M/EEG Source Imaging and Independent Component Analysis Frameworks Using Biologically Inspired Sparsity Priors.Neural computation · 2021Article
- The integration of social and neural synchrony: a case for ecologically valid research using MEG neuroimaging.Social cognitive and affective neuroscience · 2021Review
- Data-driven model optimization for optically pumped magnetometer sensor arrays.Human brain mapping · 2019Article
- Channel gain calibrated signal space projection using variational Bayesian estimation for optically pumped magnetometers.Imaging neuroscience (Cambridge, Mass.)Article
Corrections and comments
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Authors and funding
12 authors at 3 institutions in 2 countries.
Funding
Abstract
Optically pumped magnetometers (OPMs) have reached sensitivity levels that make them viable portable alternatives to traditional superconducting technology for magnetoencephalography (MEG). OPMs do not require cryogenic cooling and can therefore be placed directly on the scalp surface. Unlike cryogenic systems, based on a well-characterised fixed arrays essentially linear in applied flux, OPM devices, based on different physical principles, present new modelling challenges. Here, we outline an empirical Bayesian framework that can be used to compare between and optimise sensor arrays. We perturb the sensor geometry (via simulation) and with analytic model comparison methods estimate the true sensor geometry. The width of these perturbation curves allows us to compare different MEG systems. We test this technique using simulated and real data from SQUID and OPM recordings using head-casts and scanner-casts. Finally, we show that given knowledge of underlying brain anatomy, it is possible to estimate the true sensor geometry from the OPM data themselves using a model comparison framework. This implies that the requirement for accurate knowledge of the sensor positions and orientations a priori may be relaxed. As this procedure uses the cortical manifold as spatial support there is no co-registration procedure or reliance on scalp landmarks.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.