Adaptive multipole models of optically pumped magnetometer data.

Multipole expansions have been used extensively in the Magnetoencephalography (MEG) literature for mitigating environmental interference and modelling brain signal. However, their application to Optically Pumped Magnetometer (OPM) data is challenging due to the wide variety of existing OPM sensor and array designs. We therefore explore how such multipole models can be adapted to provide stable models of brain signal and interference across OPM systems. Firstly, we demonstrate how prolate spheroidal (rather than spherical) harmonics can provide a compact representation of brain signal when sampling on the scalp surface with as few as 100 channels. We then introduce a type of orthogonal projection incorporating this basis set. The Adaptive Multipole Models (AMM), which provides robust interference rejection across systems, even in the presence of spatially structured nonlinearity errors (shielding factor is the reciprocal of the maximum fractional nonlinearity error). Furthermore, this projection is always stable, as it is an orthogonal projection, and will only ever decrease the white noise in the data. However, for array designs that are suboptimal for spatially separating brain signal and interference, this method can remove brain signal components. We contrast these properties with the more typically used multipole expansion, Signal Space Separation (SSS), which never reduces brain signal amplitude but is less robust to the effect of sensor nonlinearity errors on interference rejection and can increase noise in the data if the system is sub-optimally designed (as it is an oblique projection). We conclude with an empirical example utilizing AMM to maximize signal to noise ratio (SNR) for the stimulus locked neuronal response to a flickering visual checkerboard in a 128-channel OPM system and demonstrate up to 40 dB software shielding in real data.

Moving magnetoencephalography towards real-world applications with a wearable system.

Imaging human brain function with techniques such as magnetoencephalography typically requires a subject to perform tasks while their head remains still within a restrictive scanner. This artificial environment makes the technique inaccessible to many people, and limits the experimental questions that can be addressed. For example, it has been difficult to apply neuroimaging to investigation of the neural substrates of cognitive development in babies and children, or to study processes in adults that require unconstrained head movement (such as spatial navigation). Here we describe a magnetoencephalography system that can be worn like a helmet, allowing free and natural movement during scanning. This is possible owing to the integration of quantum sensors, which do not rely on superconducting technology, with a system for nulling background magnetic fields. We demonstrate human electrophysiological measurement at millisecond resolution while subjects make natural movements, including head nodding, stretching, drinking and playing a ball game. Our results compare well to those of the current state-of-the-art, even when subjects make large head movements. The system opens up new possibilities for scanning any subject or patient group, with myriad applications such as characterization of the neurodevelopmental connectome, imaging subjects moving naturally in a virtual environment and investigating the pathophysiology of movement disorders.

Real-time, model-based magnetic field correction for moving, wearable MEG.

Most neuroimaging techniques require the participant to remain still for reliable recordings to be made. Optically pumped magnetometer (OPM) based magnetoencephalography (OP-MEG) however, is a neuroimaging technique which can be used to measure neural signals during large participant movement (approximately 1 m) within a magnetically shielded room (MSR) (Boto et al., 2018; Seymour et al., 2021). Nevertheless, environmental magnetic fields vary both spatially and temporally and OPMs can only operate within a limited magnetic field range, which constrains participant movement. Here we implement real-time updates to electromagnetic coils mounted on-board of the OPMs, to cancel out the changing background magnetic fields. The coil currents were chosen based on a continually updating harmonic model of the background magnetic field, effectively implementing homogeneous field correction (HFC) in real-time (Tierney et al., 2021). During a stationary, empty room recording, we show an improvement in very low frequency noise of 24 dB. In an auditory paradigm, during participant movement of up to 2 m within a magnetically shielded room, introduction of the real-time correction more than doubled the proportion of trials in which no sensor saturated recorded outside of a 50 cm radius from the optimally-shielded centre of the room. The main advantage of such model-based (rather than direct) feedback is that it could allow one to correct field components along unmeasured OPM axes, potentially mitigating sensor gain and calibration issues (Borna et al., 2022).

Spherical harmonic based noise rejection and neuronal sampling with multi-axis OPMs.

In this study we explore the interference rejection and spatial sampling properties of multi-axis Optically Pumped Magnetometer (OPM) data. We use both vector spherical harmonics and eigenspectra to quantify how well an array can separate neuronal signal from environmental interference while adequately sampling the entire cortex. We found that triaxial OPMs have superb noise rejection properties allowing for very high orders of interference (L=6) to be accounted for while minimally affecting the neural space (2dB attenuation for a 60-sensor triaxial system). We show that at least 11th order (143 spatial degrees of freedom) irregular solid harmonics or 95 eigenvectors of the lead field are needed to model the neural space for OPM data (regardless of number of axes measured). This can be adequately sampled with 75-100 equidistant triaxial sensors (225-300 channels) or 200 equidistant radial channels. In other words, ordering the same number of channels in triaxial (rather than purely radial) configuration may give significant advantages not only in terms of external noise rejection but also by minimizing cost, weight and cross-talk.

Interference suppression techniques for OPM-based MEG: Opportunities and challenges.

One of the primary technical challenges facing magnetoencephalography (MEG) is that the magnitude of neuromagnetic fields is several orders of magnitude lower than interfering signals. Recently, a new type of sensor has been developed - the optically pumped magnetometer (OPM). These sensors can be placed directly on the scalp and move with the head during participant movement, making them wearable. This opens up a range of exciting experimental and clinical opportunities for OPM-based MEG experiments, including paediatric studies, and the incorporation of naturalistic movements into neuroimaging paradigms. However, OPMs face some unique challenges in terms of interference suppression, especially in situations involving mobile participants, and when OPMs are integrated with electrical equipment required for naturalistic paradigms, such as motion capture systems. Here we briefly review various hardware solutions for OPM interference suppression. We then outline several signal processing strategies aimed at increasing the signal from neuromagnetic sources. These include regression-based strategies, temporal filtering and spatial filtering approaches. The focus is on the practical application of these signal processing algorithms to OPM data. In a similar vein, we include two worked-through experiments using OPM data collected from a whole-head sensor array. These tutorial-style examples illustrate how the steps for suppressing external interference can be implemented, including the associated data and code so that researchers can try the pipelines for themselves. With the popularity of OPM-based MEG rising, there will be an increasing need to deal with interference suppression. We hope this practical paper provides a resource for OPM-based MEG researchers to build upon.

The Role of Hippocampal-Ventromedial Prefrontal Cortex Neural Dynamics in Building Mental Representations.

The hippocampus and ventromedial prefrontal cortex (vmPFC) play key roles in numerous cognitive domains including mind-wandering, episodic memory, and imagining the future. Perspectives differ on precisely how they support these diverse functions, but there is general agreement that it involves constructing representations composed of numerous elements. Visual scenes have been deployed extensively in cognitive neuroscience because they are paradigmatic multielement stimuli. However, it remains unclear whether scenes, rather than other types of multifeature stimuli, preferentially engage hippocampus and vmPFC. Here, we leveraged the high temporal resolution of magnetoencephalography to test participants as they gradually built scene imagery from three successive auditorily presented object descriptions and an imagined 3-D space. This was contrasted with constructing mental images of nonscene arrays that were composed of three objects and an imagined 2-D space. The scene and array stimuli were, therefore, highly matched, and this paradigm permitted a closer examination of step-by-step mental construction than has been undertaken previously. We observed modulation of theta power in our two regions of interest-anterior hippocampus during the initial stage and vmPFC during the first two stages, of scene relative to array construction. Moreover, the scene-specific anterior hippocampal activity during the first construction stage was driven by the vmPFC, with mutual entrainment between the two brain regions thereafter. These findings suggest that hippocampal and vmPFC neural activity is especially tuned to scene representations during the earliest stage of their formation, with implications for theories of how these brain areas enable cognitive functions such as episodic memory.

Laminar dynamics of high amplitude beta bursts in human motor cortex.

Motor cortical activity in the beta frequency range is one of the strongest and most studied movement-related neural signals. At the single trial level, beta band activity is often characterized by transient, high amplitude, bursting events rather than slowly modulating oscillations. The timing of these bursting events is tightly linked to behavior, suggesting a more dynamic functional role for beta activity than previously believed. However, the neural mechanisms underlying beta bursts in sensorimotor circuits are poorly understood. To address this, we here leverage and extend recent developments in high precision MEG for temporally resolved laminar analysis of burst activity, combined with a neocortical circuit model that simulates the biophysical generators of the electrical currents which drive beta bursts. This approach pinpoints the generation of beta bursts in human motor cortex to distinct excitatory synaptic inputs to deep and superficial cortical layers, which drive current flow in opposite directions. These laminar dynamics of beta bursts in motor cortex align with prior invasive animal recordings within the somatosensory cortex, and suggest a conserved mechanism for somatosensory and motor cortical beta bursts. More generally, we demonstrate the ability for uncovering the laminar dynamics of event-related neural signals in human non-invasive recordings. This provides important constraints to theories about the functional role of burst activity for movement control in health and disease, and crucial links between macro-scale phenomena measured in humans and micro-circuit activity recorded from animal models.

Using OPMs to measure neural activity in standing, mobile participants.

Optically pumped magnetometer-based magnetoencephalography (OP-MEG) can be used to measure neuromagnetic fields while participants move in a magnetically shielded room. Head movements in previous OP-MEG studies have been up to 20 cm translation and ∼30° rotation in a sitting position. While this represents a step-change over stationary MEG systems, naturalistic head movement is likely to exceed these limits, particularly when participants are standing up. In this proof-of-concept study, we sought to push the movement limits of OP-MEG even further. Using a 90 channel (45-sensor) whole-head OP-MEG system and concurrent motion capture, we recorded auditory evoked fields while participants were: (i) sitting still, (ii) standing up and still, and (iii) standing up and making large natural head movements continuously throughout the recording - maximum translation 120 cm, maximum rotation 198°. Following pre-processing, movement artefacts were substantially reduced but not eliminated. However, upon utilisation of a beamformer, the M100 event-related field localised to primary auditory regions. Furthermore, the event-related fields from auditory cortex were remarkably consistent across the three conditions. These results suggest that a wide range of movement is possible with current OP-MEG systems. This in turn underscores the exciting potential of OP-MEG for recording neural activity during naturalistic paradigms that involve movement (e.g. navigation), and for scanning populations who are difficult to study with stationary MEG (e.g. young children).

Modelling optically pumped magnetometer interference in MEG as a spatially homogeneous magnetic field.

Here we propose that much of the magnetic interference observed when using optically pumped magnetometers for MEG experiments can be modeled as a spatially homogeneous magnetic field. We show that this approximation reduces sensor level variance and substantially improves statistical power. This model does not require knowledge of the underlying neuroanatomy nor the sensor positions. It only needs information about the sensor orientation. Due to the model's low rank there is little risk of removing substantial neural signal. However, we provide a framework to assess this risk for any sensor number, design or subject neuroanatomy. We find that the risk of unintentionally removing neural signal is reduced when multi-axis recordings are performed. We validated the method using a binaural auditory evoked response paradigm and demonstrated that removing the homogeneous magnetic field increases sensor level SNR by a factor of 3. Considering the model's simplicity and efficacy, we suggest that this homogeneous field correction can be a powerful preprocessing step for arrays of optically pumped magnetometers.

Mouth magnetoencephalography: A unique perspective on the human hippocampus.

Traditional magnetoencephalographic (MEG) brain imaging scanners consist of a rigid sensor array surrounding the head; this means that they are maximally sensitive to superficial brain structures. New technology based on optical pumping means that we can now consider more flexible and creative sensor placement. Here we explored the magnetic fields generated by a model of the human hippocampus not only across scalp but also at the roof of the mouth. We found that simulated hippocampal sources gave rise to dipolar field patterns with one scalp surface field extremum at the temporal lobe and a corresponding maximum or minimum at the roof of the mouth. We then constructed a fitted dental mould to accommodate an Optically Pumped Magnetometer (OPM). We collected data using a previously validated hippocampal-dependant task to test the empirical utility of a mouth-based sensor, with an accompanying array of left and right temporal lobe OPMs. We found that the mouth sensor showed the greatest task-related theta power change. We found that this sensor had a mild effect on the reconstructed power in the hippocampus (~10% change) but that coherence images between the mouth sensor and reconstructed source images showed a global maximum in the right hippocampus. We conclude that augmenting a scalp-based MEG array with sensors in the mouth shows unique promise for both basic scientists and clinicians interested in interrogating the hippocampus.

vmPFC Drives Hippocampal Processing during Autobiographical Memory Recall Regardless of Remoteness.

Our ability to recall past experiences, autobiographical memories (AMs), is crucial to cognition, endowing us with a sense of self and underwriting our capacity for autonomy. Traditional views assume that the hippocampus orchestrates event recall, whereas recent accounts propose that the ventromedial prefrontal cortex (vmPFC) instigates and coordinates hippocampal-dependent processes. Here we sought to characterize the dynamic interplay between the hippocampus and vmPFC during AM recall to adjudicate between these perspectives. Leveraging the high temporal resolution of magnetoencephalography, we found that the left hippocampus and the vmPFC showed the greatest power changes during AM retrieval. Moreover, responses in the vmPFC preceded activity in the hippocampus during initiation of AM recall, except during retrieval of the most recent AMs. The vmPFC drove hippocampal activity during recall initiation and also as AMs unfolded over subsequent seconds, and this effect was evident regardless of AM age. These results recast the positions of the hippocampus and the vmPFC in the AM retrieval hierarchy, with implications for theoretical accounts of memory processing and systems-level consolidation.

The Neural Dynamics of Novel Scene Imagery.

Retrieval of long-term episodic memories is characterized by synchronized neural activity between hippocampus and ventromedial prefrontal cortex (vmPFC), with additional evidence that vmPFC activity leads that of the hippocampus. It has been proposed that the mental generation of scene imagery is a crucial component of episodic memory processing. If this is the case, then a comparable interaction between the two brain regions should exist during the construction of novel scene imagery. To address this question, we leveraged the high temporal resolution of MEG to investigate the construction of novel mental imagery. We tasked male and female humans with imagining scenes and single isolated objects in response to one-word cues. We performed source-level power, coherence, and causality analyses to characterize the underlying interregional interactions. Both scene and object imagination resulted in theta power changes in the anterior hippocampus. However, higher theta coherence was observed between the hippocampus and vmPFC in the scene compared with the object condition. This interregional theta coherence also predicted whether imagined scenes were subsequently remembered. Dynamic causal modeling of this interaction revealed that vmPFC drove activity in hippocampus during novel scene construction. Additionally, theta power changes in the vmPFC preceded those observed in the hippocampus. These results constitute the first evidence in humans that episodic memory retrieval and scene imagination rely on similar vmPFC-hippocampus neural dynamics. Furthermore, they provide support for theories emphasizing similarities between both cognitive processes and perspectives that propose the vmPFC guides the construction of context-relevant representations in the hippocampus.SIGNIFICANCE STATEMENT Episodic memory retrieval is characterized by a dialog between hippocampus and ventromedial prefrontal cortex (vmPFC). It has been proposed that the mental generation of scene imagery is a crucial component of episodic memory processing. An ensuing prediction would be of a comparable interaction between the two brain regions during the construction of novel scene imagery. Here, we leveraged the high temporal resolution of MEG and combined it with a scene imagination task. We found that a hippocampal-vmPFC dialog existed and that it took the form of vmPFC driving the hippocampus. We conclude that episodic memory and scene imagination share fundamental neural dynamics and the process of constructing vivid, spatially coherent, contextually appropriate scene imagery is strongly modulated by vmPFC.

Estimates of cortical column orientation improve MEG source inversion.

Determining the anatomical source of brain activity non-invasively measured from EEG or MEG sensors is challenging. In order to simplify the source localization problem, many techniques introduce the assumption that current sources lie on the cortical surface. Another common assumption is that this current flow is orthogonal to the cortical surface, thereby approximating the orientation of cortical columns. However, it is not clear which cortical surface to use to define the current source locations, and normal vectors computed from a single cortical surface may not be the best approximation to the orientation of cortical columns. We compared three different surface location priors and five different approaches for estimating dipole vector orientation, both in simulations and visual and motor evoked MEG responses. We show that models with source locations on the white matter surface and using methods based on establishing correspondences between white matter and pial cortical surfaces dramatically outperform models with source locations on the pial or combined pial/white surfaces and which use methods based on the geometry of a single cortical surface in fitting evoked visual and motor responses. These methods can be easily implemented and adopted in most M/EEG analysis pipelines, with the potential to significantly improve source localization of evoked responses.

Using optically pumped magnetometers to measure magnetoencephalographic signals in the human cerebellum.

KEY POINTS: The application of conventional cryogenic magnetoencephalography (MEG) to the study of cerebellar functions is highly limited because typical cryogenic sensor arrays are far away from the cerebellum and naturalistic movement is not allowed in the recording. A new generation of MEG using optically pumped magnetometers (OPMs) that can be worn on the head during movement has opened up an opportunity to image the cerebellar electrophysiological activity non-invasively. We use OPMs to record human cerebellar MEG signals elicited by air-puff stimulation to the eye. We demonstrate robust responses in the cerebellum. OPMs pave the way for studying the neurophysiology of the human cerebellum. ABSTRACT: We test the feasibility of an optically pumped magnetometer-based magnetoencephalographic (OP-MEG) system for the measurement of human cerebellar activity. This is to our knowledge the first study investigating the human cerebellar electrophysiology using optically pumped magnetometers. As a proof of principle, we use an air-puff stimulus to the eyeball in order to elicit cerebellar activity that is well characterized in non-human models. In three subjects, we observe an evoked component at approx. 50 ms post-stimulus, followed by a second component at approx. 85-115 ms post-stimulus. Source inversion localizes both components in the cerebellum, while control experiments exclude potential sources elsewhere. We also assess the induced oscillations, with time-frequency decompositions, and identify additional sources in the occipital lobe, a region expected to be active in our paradigm, and in the neck muscles. Neither of these contributes to the stimulus-evoked responses at 50-115 ms. We conclude that OP-MEG technology offers a promising way to advance the understanding of the information processing mechanisms in the human cerebellum.

Imaging the human hippocampus with optically-pumped magnetoencephalography.

Optically-pumped (OP) magnetometers allow magnetoencephalography (MEG) to be performed while a participant's head is unconstrained. To fully leverage this new technology, and in particular its capacity for mobility, the activity of deep brain structures which facilitate explorative behaviours such as navigation, must be detectable using OP-MEG. One such crucial brain region is the hippocampus. Here we had three healthy adult participants perform a hippocampal-dependent task - the imagination of novel scene imagery - while being scanned using OP-MEG. A conjunction analysis across these three participants revealed a significant change in theta power in the medial temporal lobe. The peak of this activated cluster was located in the anterior hippocampus. We repeated the experiment with the same participants in a conventional SQUID-MEG scanner and found similar engagement of the medial temporal lobe, also with a peak in the anterior hippocampus. These OP-MEG findings indicate exciting new opportunities for investigating the neural correlates of a range of crucial cognitive functions in naturalistic contexts including spatial navigation, episodic memory and social interactions.

Optically pumped magnetometers: From quantum origins to multi-channel magnetoencephalography.

Optically Pumped Magnetometers (OPMs) have emerged as a viable and wearable alternative to cryogenic, superconducting MEG systems. This new generation of sensors has the advantage of not requiring cryogenic cooling and as a result can be flexibly placed on any part of the body. The purpose of this review is to provide a neuroscience audience with the theoretical background needed to understand the physical basis for the signal observed by OPMs. Those already familiar with the physics of MRI and NMR should note that OPMs share much of the same theory as the operation of OPMs rely on magnetic resonance. This review establishes the physical basis for the signal equation for OPMs. We re-derive the equations defining the bounds on OPM performance and highlight the important trade-offs between quantities such as bandwidth, sensor size and sensitivity. These equations lead to a direct upper bound on the gain change due to cross-talk for a multi-channel OPM system.

Wearable neuroimaging: Combining and contrasting magnetoencephalography and electroencephalography.

One of the most severe limitations of functional neuroimaging techniques, such as magnetoencephalography (MEG), is that participants must maintain a fixed head position during data acquisition. This imposes restrictions on the characteristics of the experimental cohorts that can be scanned and the experimental questions that can be addressed. For these reasons, the use of 'wearable' neuroimaging, in which participants can move freely during scanning, is attractive. The most successful example of wearable neuroimaging is electroencephalography (EEG), which employs lightweight and flexible instrumentation that makes it useable in almost any experimental setting. However, EEG has major technical limitations compared to MEG, and therefore the development of wearable MEG, or hybrid MEG/EEG systems, is a compelling prospect. In this paper, we combine and compare EEG and MEG measurements, the latter made using a new generation of optically-pumped magnetometers (OPMs). We show that these new second generation commercial OPMs, can be mounted on the scalp in an 'EEG-like' cap, enabling the acquisition of high fidelity electrophysiological measurements. We show that these sensors can be used in conjunction with conventional EEG electrodes, offering the potential for the development of hybrid MEG/EEG systems. We compare concurrently measured signals, showing that, whilst both modalities offer high quality data in stationary subjects, OPM-MEG measurements are less sensitive to artefacts produced when subjects move. Finally, we show using simulations that OPM-MEG offers a fundamentally better spatial specificity than EEG. The demonstrated technology holds the potential to revolutionise the utility of functional brain imaging, exploiting the flexibility of wearable systems to facilitate hitherto impractical experimental paradigms.

Towards OPM-MEG in a virtual reality environment.

Virtual reality (VR) provides an immersive environment in which a participant can experience a feeling of presence in a virtual world. Such environments generate strong emotional and physical responses and have been used for wide-ranging applications. The ability to collect functional neuroimaging data whilst a participant is immersed in VR would represent a step change for experimental paradigms; unfortunately, traditional brain imaging requires participants to remain still, limiting the scope of naturalistic interaction within VR. Recently however, a new type of magnetoencephalography (MEG) device has been developed, that employs scalp-mounted optically-pumped magnetometers (OPMs) to measure brain electrophysiology. Lightweight OPMs, coupled with precise control of the background magnetic field, enables participant movement during data acquisition. Here, we exploit this technology to acquire MEG data whilst a participant uses a virtual reality head-mounted display (VRHMD). We show that, despite increased magnetic interference from the VRHMD, we were able to measure modulation of alpha-band oscillations, and the visual evoked field. Moreover, in a VR experiment in which a participant had to move their head to look around a virtual wall and view a visual stimulus, we showed that the measured MEG signals map spatially in accordance with the known organisation of primary visual cortex. This technique could transform the type of neuroscientific experiment that can be undertaken using functional neuroimaging.

High-precision magnetoencephalography for reconstructing amygdalar and hippocampal oscillations during prediction of safety and threat.

Learning to associate neutral with aversive events in rodents is thought to depend on hippocampal and amygdala oscillations. In humans, oscillations underlying aversive learning are not well characterised, largely due to the technical difficulty of recording from these two structures. Here, we used high-precision magnetoencephalography (MEG) during human discriminant delay threat conditioning. We constructed generative anatomical models relating neural activity with recorded magnetic fields at the single-participant level, including the neocortex with or without the possibility of sources originating in the hippocampal and amygdalar structures. Models including neural activity in amygdala and hippocampus explained MEG data during threat conditioning better than exclusively neocortical models. We found that in both amygdala and hippocampus, theta oscillations during anticipation of an aversive event had lower power compared to safety, both during retrieval and extinction of aversive memories. At the same time, theta synchronisation between hippocampus and amygdala increased over repeated retrieval of aversive predictions, but not during safety. Our results suggest that high-precision MEG is sensitive to neural activity of the human amygdala and hippocampus during threat conditioning and shed light on the oscillation-mediated mechanisms underpinning retrieval and extinction of fear memories in humans.

Data-driven model optimization for optically pumped magnetometer sensor arrays.

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.