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Peer-reviewedCC BY 4.0Imaging Neuroscience

The dual future of OPM-MEG: Clinical translation and naturalistic neuroscience

8 affiliations
  1. 1School of Chinese as a Second Language, Peking University, Beijing, China
  2. 2Centre for Mental Health & Brain Sciences, Swinburne University of Technology, Hawthorn, VIC, Australia
  3. 3Centre for Cognitive and Brain Sciences, University of Macau, Macau SAR, China
  4. 4Changping Laboratory, Beijing, China
  5. 5Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China
  6. 6Laboratory of Medical Physics and Engineering, School of Physics, Peking University, Beijing, China
  7. 7McGovern Institute of Brain Research, Peking University, Beijing, China
  8. 8National Biomedical Imaging Center, Peking University, Beijing, China

Abstract

Optically pumped magnetometer magnetoencephalography (OPM-MEG) has moved beyond proof of principle. The decisive question is no longer whether cryogen-free sensors can detect neuromagnetic fields from the human brain with sufficient sensitivity, but whether complete systems can deliver clinical decision value and interpretable recordings during more naturalistic behaviour. Here we argue that OPM-MEG is developing along two partly overlapping trajectories. One is clinical translation, where usefulness depends more on reliable workflows, calibrated source localisation, auditable quality control, and empirical evidence for improved diagnostic or treatment decisions. The other is naturalistic neuroscience, where wearable measurement can connect neural dynamics to movement, action, and social behaviour without conflating neural activity with movement-related artefacts. Both trajectories depend on a shared engineering stack including magnetic field control, dense spatial sampling, accurate calibration, integrated electronics, artefact suppression, participant comfort, and synchronised behavioural measurement. The next stage of OPM-MEG should be evaluated by clinical utility in specific patient groups, statistically identifiable neural dynamics in behaviourally rich settings, and sufficient system detail for replication across systems and sites.

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BibTeX
@article{qin2026dual,
  title = {{The dual future of OPM-MEG: Clinical translation and naturalistic neuroscience}},
  author = {Lang Qin and Miao Cao and Zhen Yuan and Bingjiang Lyu and Jia-Hong Gao},
  journal = {Imaging Neuroscience},
  year = {2026},
  month = oct,
  doi = {10.1162/imag.a.1436},
  url = {https://doi.org/10.1162/imag.a.1436},
  note = {CC BY 4.0},
}
RIS
TY  - JOUR
TI  - The dual future of OPM-MEG: Clinical translation and naturalistic neuroscience
AU  - Lang Qin
AU  - Miao Cao
AU  - Zhen Yuan
AU  - Bingjiang Lyu
AU  - Jia-Hong Gao
PY  - 2026
DA  - 2026/10/29
JO  - Imaging Neuroscience
DO  - 10.1162/imag.a.1436
UR  - https://doi.org/10.1162/imag.a.1436
AB  - Optically pumped magnetometer magnetoencephalography (OPM-MEG) has moved beyond proof of principle. The decisive question is no longer whether cryogen-free sensors can detect neuromagnetic fields from the human brain with sufficient sensitivity, but whether complete systems can deliver clinical decision value and interpretable recordings during more naturalistic behaviour. Here we argue that OPM-MEG is developing along two partly overlapping trajectories. One is clinical translation, where usefulness depends more on reliable workflows, calibrated source localisation, auditable quality control, and empirical evidence for improved diagnostic or treatment decisions. The other is naturalistic neuroscience, where wearable measurement can connect neural dynamics to movement, action, and social behaviour without conflating neural activity with movement-related artefacts. Both trajectories depend on a shared engineering stack including magnetic field control, dense spatial sampling, accurate calibration, integrated electronics, artefact suppression, participant comfort, and synchronised behavioural measurement. The next stage of OPM-MEG should be evaluated by clinical utility in specific patient groups, statistically identifiable neural dynamics in behaviourally rich settings, and sufficient system detail for replication across systems and sites.
SN  - 2837-6056
ER  -