Source modelling in magnetoencephalography (MEG) infers the spatial origins of electrophysiological signals in the brain. Typically, this requires an anatomical MRI scan of the subject’s head, from which models of the magnetic fields generated by the brain (the forward model) are derived. Wearable MEG—based on optically pumped magnetometers (OPMs)—enables MEG measurement from participants who struggle to cope with conventional scanning environments (e.g., children), enabling study of novel cohorts. However, its value is limited if an MRI scan is still required for source modelling. Here we describe a method of warping template MRIs to 3D structured-light scans of the head, to generate “pseudo-MRIs”. We apply our method to data from 20 participants during a sensory task, measuring induced (beta band) responses and whole-brain functional connectivity. Results show that the group average locations of peak task-induced beta modulation were separated by 2.75 mm, when comparing real- and pseudo-MRI approaches. Group averaged time–frequency spectra were also highly correlated (Pearson correlation 0.99) as were functional connectome matrices (0.87) and global connectivity (0.98). In sum, our results demonstrate that source-localised OPM-MEG data, modelled with and without an individual MRI scan, can be comparable. While individual MRI scans remain the “gold standard” for OPM-MEG modelling, our method will be useful for future studies where MRI data capture is challenging.

Optically pumped magnetometers (OPMs) have emerged as a viable alternative to superconducting quantum interference devices (SQUIDs) to measure the magnetic fields generated by brain activity. Magnetoencephalography (MEG) systems based on OPMs offer potential advantages over conventional systems. However, there remains a pressing need for techniques and studies that demonstrate equivalence between emergent OPM-based instruments and the established conventional MEG standard. Here, we seek to demonstrate similarities between a 192-channel (64-triaxial sensor) OPM-based system and a 275-channel SQUID-based system, when measuring data during a sensory task designed elicit induced oscillatory (beta-band) and evoked responses as well as subtle attentional effects. We reasoned that in addition to measuring these primary responses (which are stable across individuals), neural fingerprinting (i.e., demonstrating that an individual’s OPM-MEG data can be identified from a group, by matching to their SQUID data) would determine whether subtle but repeatable differences between individuals are also measurable across OPM and SQUID-based platforms. Our results showed (1) that primary responses are measurable using both systems with correlations of 0.96 (beta responses) and 0.97 (evoked responses) at the group level; (2) both systems captured significant attentional modulation of the beta rhythm; and (3) fingerprinting was successful in 15 of 15 people using OPM-MEG, 14 of 15 people using SQUID-MEG, and 15 of 15 people when examining cross-platform data. Overall, our results confirm that the two MEG platforms capture similar information on brain function. This is an important step towards proving equivalence between OPMs and SQUIDs, which in turn is required if OPMs are to replace SQUIDs for clinical evaluations.

Optically-pumped magnetometers (OPMs) are compact and lightweight sensors that can measure magnetic fields generated by current flow in neuronal assemblies in the brain. Such sensors enable construction of magnetoencephalography (MEG) instrumentation, with significant advantages over conventional MEG devices, including adaptability to head size, enhanced movement tolerance, lower complexity, and improved data quality. However, realising the potential of OPMs depends on our ability to perform system calibration—which means finding sensor locations, orientations, and the relationship between the sensor output and magnetic field (termed sensor gain). Such calibration is complex in OPM-MEG since, for example, OPM placement can change from subject to subject (unlike in conventional MEG where sensor locations/orientations are fixed). Here, we present two methods for calibration, both based on generating well-characterised magnetic fields across a sensor array. Our first device (the HALO) is a head mounted system that generates dipole-like fields from a set of coils. Our second (the matrix coil (MC)) generates fields using coils embedded in the walls of a magnetically shielded room. Our results show that both methods offer an accurate means to calibrate an OPM array (e.g., sensor locations within 2 mm of the ground truth) and that the calibrations produced by the two methods agree strongly with each other: reconstructed positions, orientations, and gains differ on average by 2.0 mm; 1.2° and 1.3% between HALO and MC. When applied to data from human MEG experiments, both methods offer improved signal-to-noise ratio after beamforming, suggesting that they give calibration parameters closer to the ground truth than presumed physical sensor coordinates and orientations. Both techniques are practical and easy to integrate into real-world MEG applications. This advances the field significantly closer to the routine use of OPMs for MEG recording.

Disruption of the balance between excitatory and inhibitory neurotransmission (E-I balance) is thought to underlie many neurodevelopmental disorders; however, its study is typically restricted to adults, animal models, and the lab-bench. Neurophysiological oscillations in the gamma frequency band relate closely to E-I balance, and a new technology—OPM-MEG—offers the possibility to measure such signals across the lifespan. We used OPM-MEG to measure gamma oscillations induced by visual stimulation in 101 participants, aged 2–34 years. We demonstrate a significantly changing spectrum with age, with low-amplitude broadband gamma oscillations in children and high-amplitude band limited oscillations in adults. We used a canonical cortical microcircuit to model these signals, revealing a significant decrease in the ratio of excitatory to inhibitory signalling with age in the superficial pyramidal neurons of the visual cortex. Our findings detail the first MEG metrics of gamma oscillations and their underlying generators from toddlerhood, providing a benchmark against which future studies can contextualise.

Magnetoencephalography (MEG) measures brain function via assessment of magnetic fields generated by neural currents. Conventional MEG uses superconducting sensors, which place significant limitations on performance, practicality, and deployment; however, the field has been revolutionised in recent years by the introduction of optically-pumped magnetometers (OPMs). OPMs enable measurement of the MEG signal without cryogenics, and consequently the conception of “OPM-MEG” systems which ostensibly allow increased sensitivity and resolution, lifespan compliance, free subject movement, and lower cost. However, OPM-MEG is in its infancy with existing limitations on both sensor and system design. Here, we report a new OPM-MEG design with miniaturised and integrated electronic control, a high level of portability, and improved sensor dynamic range. We show that this system produces equivalent measures compared with an established OPM-MEG instrument; specifically, when measuring task-induced beta-band, gamma-band, and evoked neuro-electrical responses, source localisations from the two systems were comparable and temporal correlation of measured brain responses was >0.7 at the individual level and >0.9 for groups. Using an electromagnetic phantom, we demonstrate improved dynamic range by running the system in background fields up to 8 nT. We show that the system is effective in gathering data during free movement (including a sitting-to-standing paradigm) and that it is compatible with simultaneous electroencephalography (EEG). Finally, we demonstrate portability by moving the system between two laboratories. Overall, our new system is shown to be a significant step forward for OPM-MEG and offers an attractive platform for next generation functional medical imaging.

The measurement of electrophysiology is of critical importance to our understanding of brain function. However, current non-invasive measurements—electroencephalography (EEG) and magnetoencephalography (MEG)—have limited sensitivity, particularly compared to invasive recordings. Optically-Pumped Magnetometers (OPMs) are a new type of magnetic field sensor which ostensibly promise MEG systems with higher sensitivity; however, the noise floor of current OPMs remains high compared to cryogenic instrumentation and this limits the achievable signal-to-noise ratio of OPM-MEG recordings. Here, we investigate how sensor array design affects sensitivity, and whether judicious sensor placement could compensate for the higher noise floor. Through theoretical analyses, simulations, and experiments, we use a beamformer framework to show that increasing the total signal measured by an OPM array—either by increasing the number of sensors and channels, or by optimising the placement of those sensors—affords a linearly proportional increase in signal-to-noise ratio (SNR) following beamformer reconstruction. Our experimental measurements confirm this finding, showing that by changing sensor locations in a 90-channel array, we could increase the SNR of visual gamma oscillations from 4.8 to 10.5. Using a 180-channel optimised OPM-array, we capture broadband gamma oscillations induced by a naturalistic visual paradigm, with an SNR of 3; a value that compares favourably to similar measures made using conventional MEG. Our findings show how an OPM-MEG array can be optimised to measure brain electrophysiology with the highest possible sensitivity. This is important for the design of future OPM-based instrumentation.

Magnetoencephalography with optically pumped magnetometers (OPM-MEG) offers a new way to record electrophysiological brain function, with significant advantages over conventional MEG, including adaptability to head shape/size, free movement during scanning, increased signal amplitude, and no reliance on cryogenics. However, OPM-MEG remains in its infancy, with significant questions to be answered regarding the optimal system design. Here, we present an open-source dataset acquired using a newly constructed OPM-MEG system with a triaxial sensor design, 168 channels, OPM-optimised magnetic shielding, and active background field control. We measure the test-retest reliability of the human connectome, which was computed using amplitude envelope correlation to measure whole-brain (parcellated) functional connectivity, in 10 individuals while they watch a 600 s move clip. Our results show high repeatability between experimental runs at the group level, with a correlation coefficient of 0.81 in the θ, 0.93 in α , and 0.94 in β frequency ranges. At the individual subject level, we found marked differences between individuals, but high within-subject robustness (correlations of 0.56 ± 0.25, 0.72 ± 0.15, and 0.78 ± 0.13 in α , θ, and β respectively). These results compare well to previous findings using conventional MEG and show that OPM-MEG is a viable way to robustly characterise connectivity.