Biology subjects

Barnes, G. R.

Publications and source records attributed to Barnes, G. R..

At least 19 recordsLinked to original sources

bioRxiv2026

Modular Arrays for High Precision Wearable MEG

Optically pumped magnetometers (OPMs) can be used for magnetoencephalography (MEG) with equivalent or improved signal to noise ratio, relative to cryogenic MEG, when sensors are placed close to the scalp. OPM-based MEG can also be used in mobile contexts if sensors are placed in lightweight, wearable arrays. Individually tailored, rigid helmets known as scannercasts are currently the only method capable of achieving on-scalp, mobile recordings with high precision. However, these scannercasts are expensive to produce, require structural imaging in advance of the experiment, and can incur lengthy downtime while sensors are transferred between scannercasts. Here, we introduce a solution to these challenges that retains the advantages of scannercasts. We provide detailed steps for constructing a modular, cap-based design, suitable for all head sizes. Using simulations, we compare the leadfield power of this array against an idealised array and a commercially available mobile solution. We then validate our proposed solution empirically, in five participants, and provide a complete data preparation and analysis pipeline. Our design expands the accessibility of OPM-based MEG, and increases participant throughput to levels comparable to other imaging modalities. Crucially, it removes the trade-off between signal quality, mobility and practicality, promoting the unique potential of OPM-based MEG as a tool for studying naturalistic behaviour, and clinical assessment with high precision.

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bioRxiv2026

Magnetoencephalography Without a Shielded Room

Magnetoencephalography (MEG) offers non-invasive neuroimaging with high temporal and spatial precision - but its adoption is hampered by the prohibitive cost and infrastructure burden of a magnetically shielded room. We have overcome that burden and present a lightweight, low-cost, multichannel magnetoencephalography system that can image brain activity without needing a magnetically shielded room. The multichannel nature of the system facilitates not just detection but also localization of brain signals that are over 300 million times smaller than environmental interference, without requiring passive shielding. Our system weighs less than 75kg, more than 100 times lighter than a typical shielded room. This is made possible through low-cost active shielding and software-based spatial filtering. We also show that the signal to noise ratio of our in-vivo recordings is comparable to what can be obtained from a conventional cryogenically-cooled MEG system sited within a shielded room. This demonstration is a crucial step towards democratizing magnetoencephalography and making it a globally accessible neuroimaging technology for healthcare and discovery research.

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bioRxiv2025

Beyond deep versus superficial: true laminar inference with MEG

Neural dynamics at the laminar level are critical for cortical computation. However, in humans, non-invasive methods to probe such dynamics have been limited to coarse distinctions between deep and superficial layers. Here, we present a multilayer magnetoencephalography source reconstruction framework and evaluate the conditions under which depth-resolved laminar inference may be feasible. Using simulations, we systematically assess the limits of magnetoencephalography depth resolution, showing that laminar discrimination depends on sufficiently high signal-to-noise ratio, precise co-registration, and accurate specification of cortical column orientation. We demonstrate that regional variations in cortical anatomy influence reconstruction fidelity, with lead-field separability emerging as a key determinant. We then apply this framework to empirical data from three independent datasets and find laminar activation patterns that align with canonical feedforward and feedback motifs in visual and sensorimotor circuits, supporting the plausibility of laminar inference under favorable conditions and offering opportunities to bridge invasive electrophysiology and human neuroimaging.

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bioRxiv2024

Volume conductor models for magnetospinography

The recent development of small, wearable, magnetic field sensors allow for the investigation of biomagnetic fields with a flexibility previously unavailable. We carry out forward computations to describe how current flow in the spinal cord and thorax gives rise to measurable magnetic fields outside the torso. We compare various open-access volume conductor models, in order to select the most parsimonious and accurate descriptor of the magnetic fields due to source current in the spinal cord. We find that fields produced due to current flow along the superior-inferior axis of the cord are relatively insensitive to the choice of volume conductor model. However, fields produced by current flow in predominantly left-right or anterior-posterior direction are significantly attenuated by the presence of bone in the forward model. Furthermore, volume conductors with bone demonstrate larger differences in field topographies for nearby sources compared to bone-free models. These findings suggest that precise modelling of spinal cord location and surrounding vertebrae will be important a-priori knowledge going forward.

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bioRxiv2024

Non-invasive evidence for rhythmic interactions between the human brain, spinal cord, and muscle

Voluntary human movement relies on interactions between the spinal cord, brain, and sensory afferents. The integrative function of the spinal cord has proven particularly difficult to study directly and non-invasively in humans due to challenges in measuring spinal cord activity. Investigations of sensorimotor integration often rely on cortico-muscular coupling, which can capture interactions between the brain and muscle, but cannot reveal how the spinal cord mediates this communication. Here, we introduce a system for direct, non-invasive imaging of concurrent brain and cervical spinal cord activity in humans using optically-pumped magnetometers (OPMs). We used this system to study endogenous interactions between the brain, spinal cord, and muscle involved in sensorimotor control during simple maintained contraction. Participants (n=3) performed a hand contraction with real-time visual feedback while we recorded brain and spinal cord activity using OPMs and muscle activity using EMG. We first identify the part of the spinal cord exhibiting a peak in estimated current flow in the cervical region during contraction. We then demonstrate that rhythmic activity in the spinal cord exhibits significant coupling with both brain and muscle activity in the 5-35 Hz frequency range. These findings evidence the possibility of concurrent spatio-temporal imaging along the entire neuro-axis.

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bioRxiv2023

Adaptive multipole models of OPM 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. 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 40dB software shielding in real data.

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bioRxiv2023

Combining video telemetry and wearable MEG for naturalistic imaging

Neuroimaging studies have typically relied on rigorously controlled experimental paradigms to probe cognition, in which movement is restricted, primitive, an afterthought or merely used to indicate a subjects choice. Whilst powerful, these paradigms do not often resemble how we behave in everyday life, so a new generation of ecologically valid experiments are being developed. Magnetoencephalography (MEG) measures neural activity by sensing extracranial magnetic fields. It has recently been transformed from a large, static imaging modality to a wearable method where participants can move freely. This makes wearable MEG systems a prime candidate for naturalistic experiments going forward. However, these experiments will also require novel methods to capture and integrate information about complex behaviour executed during neuroimaging, and it is not yet clear how this could be achieved. Here we use video recordings of multi-limb dance moves, processed with open-source machine learning methods, to automatically identify analysis time windows of interest in concurrent wearable MEG data. In a first step, we compare a traditional, block-designed analysis of limb movements, where the times of interest are based on stimulus presentation, to an analysis pipeline based on hidden Markov model states derived from the video telemetry. Next, we show that it is possible to identify discrete modes of neuronal activity related to specific limbs and body posture by processing the participants choreographed movement in a dancing paradigm. This demonstrates the potential of combing video telemetry with mobile neuroimaging for future studies of complex and naturalistic behaviours.

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bioRxiv2023

Is high-frequency activity evidence of an anterior temporal lobe network or micro-saccades?

There is renewed interest in electrical activity that extends beyond the typical electrophysiological 100 Hz bandwidth. This activity, often in the anterior temporal lobe, has been attributed to processes ranging from memory consolidation to epileptiform activity. Here, using an open-access resting state magnetoencephalography (MEG) dataset (n = 89), and a second task-based MEG dataset, we could reliably localise high-frequency power to the temporal lobes across multiple bands up to 300-400 Hz. A functional connectivity analysis of this activity revealed a robust resting state bilateral network between the temporal lobes. However, we also found robust coherence in the 100-200 and 200-300 Hz bands between source reconstructed MEG data and the electrooculography (EOG) localised to within the temporal poles. Additional denoising schemes applied to the data could reduce power localisation to the temporal poles but the topography of the functional network did not drastically alter. Whilst it is clear that this network is biological and robust to established denoising methods, we cannot definitively rule yet on whether this is of neural or myogenic origin.

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bioRxiv2022

Neural activity in human eyeblink conditioning: an optically pumped magnetometer-based MEG study

There is a profound lack of electrophysiological data from the cerebellum in humans, as compared to animals, because the pervading perception is that it is difficult to record human cerebellar activity non-invasively using magnetoencephalography (MEG) or electroencephalography (EEG). We used on-scalp MEG based on optically pumped magnetometers (OP-MEG) to detect learning related cerebellar signals in a classical eyeblink conditioning paradigm. In four healthy human adults, we observed unconditioned stimulus-related evoked responses locating in the cerebellum. These evoked responses diminished during the acquisition of conditioned responses, which corresponds with previous observed changes of Purkinje cell activities in animals. We also observed evoked responses immediately before conditioned blinks in 3 out of 4 participants, which were also located in the cerebellum. We discuss the potential nature of these cerebellar evoked responses and future applications of OP-MEG to the studies of human cerebellar physiology.

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bioRxiv2022

Concurrent spinal and brain imaging with optically pumped magnetometers

The spinal cord and its interactions with the brain are fundamental for movement control and somatosensation. However, brain and spinal cord electrophysiology in humans have largely been treated as distinct enterprises, in part due to the relative inaccessibility of the spinal cord. Consequently, there is a dearth of knowledge on human spinal electrophysiology, including the multiple pathologies of the central nervous system that affect the spinal cord as well as the brain. Here we exploit recent advances in the development of wearable optically pumped magnetometers (OPMs) which can be flexibly arranged to provide coverage of both the spinal cord and the brain concurrently in unconstrained environments. Our system for magnetospinoencephalography (MSEG) measures both spinal and cortical signals simultaneously by employing a custom-made spinal scanning cast. We evidence the utility of such a system by recording simultaneous spinal and cortical evoked responses to median nerve stimulation, demonstrating the novel ability for concurrent non-invasive millisecond imaging of brain and spinal cord.

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bioRxiv2021

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). To adequately model the signals arising from the cortex, 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 gives significant advantages not only in terms of external noise rejection but also minimizes cost, weight and cross-talk.

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bioRxiv2021

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{degrees} 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{degrees}. 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).

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bioRxiv2021

Magnetic Field Mapping and Correction for Moving OP-MEG

BackgroundOptically pumped magnetometers (OPMs) have made moving, wearable magnetoencephalography (MEG) possible. The OPMs typically used for MEG require a low background magnetic field to operate, which is achieved using both passive and active magnetic shielding. However, the background magnetic field is never truly zero Tesla, and so the field at each of the OPMs changes as the participant moves. This leads to position and orientation dependent changes in the measurements, which manifest as low frequency artefacts in MEG data. ObjectiveWe modelled the spatial variation in the magnetic field and used the model to predict the movement artefact found in a dataset. MethodsWe demonstrate a method for modelling this field with a triaxial magnetometer, then showed that we can use the same technique to predict the movement artefact in a real OPM-based MEG (OP-MEG) dataset. ResultsUsing an 86-channel OP-MEG system, we found that this modelling method maximally reduced the power spectral density of the data by 26.2 {+/-} 0.6 dB at 0 Hz, when applied over 5 s non-overlapping windows. ConclusionThe magnetic field inside our state-of-the art magnetically shielded room can be well described by low-order spherical harmonic functions. We achieved a large reduction in movement noise when we applied this model to OP-MEG data. SignificanceReal-time implementation of this method could reduce passive shielding requirements for OP-MEG recording and allow the measurement of low-frequency brain activity during natural participant movement.

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bioRxiv2021

Testing covariance models for MEG source reconstruction of hippocampal activity

Beamforming is one of the most commonly used source reconstruction methods for magneto- and electroencephalography (M/EEG). One underlying assumption, however, is that distant sources are uncorrelated and here we tested whether this is an appropriate model for the human hippocampal data. We revised the Empirical Bayesian Beamfomer (EBB) to accommodate specific a-priori correlated source models. We showed in simulation that we could use model evidence (as approximated by Free Energy) to distinguish between different correlated and uncorrelated source scenarios. Using group MEG data in which the participants performed a hippocampal-dependent task, we explored the possibility that the hippocampus or the cortex or both were correlated in their activity across hemispheres. We found that incorporating a correlated hippocampal source model significantly improved model evidence. Our findings help to explain why, up until now, the majority of MEG-reported hippocampal activity (typically making use of beamformers) has been estimated as unilateral.

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bioRxiv2021

Laminar dynamics of beta bursts in human motor cortex

Modulation of 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 bursting events rather than slowly modulating oscillations, suggesting a more rapid, information-encoding functional role than previously believed. Insight into how beta bursts are generated in sensorimotor circuits can provide important constraints to theories about their functional role for movement control. To this end, we 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.

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bioRxiv2020

Modelling optically pumped magnetometerinterference as a mean (magnetic) field

Here we propose that much of the magnetic interference observed when using optically pumped magnetometers can be modeled spatially as a mean (magnetic) field. We show that this approximation reduces sensor level variability 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 models 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 the mean field correction increases reconstructed SNR in relevant brain regions in both the spatial and temporal domain. Considering the models simplicity and efficacy, we suggest that this mean field correction can be a powerful preprocessing step for arrays of optically pumped magnetometers.

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bioRxiv2020

The effect of object type on building scene imagery - an MEG study

Previous studies have reported that some objects evoke a sense of local three-dimensional space (space-defining; SD), while others do not (space-ambiguous; SA), despite being imagined or viewed in isolation devoid of a background context. Moreover, people show a strong preference for SD objects when given a choice of objects with which to mentally construct scene imagery. When deconstructing scenes, people retain significantly more SD objects than SA objects. It therefore seems that SD objects might enjoy a privileged role in scene construction. In the current study, we leveraged the high temporal resolution of magnetoencephalography (MEG) to compare the neural responses to SD and SA objects while they were being used to build imagined scene representations, as this has not been examined before using neuroimaging. On each trial, participants gradually built a scene image from three successive auditorily-presented object descriptions and an imagined 3D space. We then examined the neural dynamics associated with the points during scene construction when either SD or SA objects were being imagined. We found that SD objects elicited theta changes relative to SA objects in two brain regions, the right ventromedial prefrontal cortex (vmPFC) and right superior temporal gyrus (STG). Furthermore, using dynamic causal modelling, we observed that the vmPFC drove STG activity. These findings may indicate that SD objects serve to activate schematic and conceptual knowledge in vmPFC and STG upon which scene representations are then built.

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bioRxiv2020

Dynamic causal modeling of layered magnetoencephalographic event-related responses

The layered architecture of cortex is thought to play a fundamental role in shaping cortical computations. However, direct electrophysiological measurements of layered activity are not possible non-invasively in humans. Recent advances have shown that a distinction of two layers can be achieved using magnetoencephalography in combination with head casts and advanced spatial modeling. In this technical note, we present a dynamic causal model of a single cortical microcircuit that models event related potentials. The model captures the average dynamics of a detailed two layered circuit. It combines a temporal model of neural dynamics with a spatial model of a layer specific lead field to facilitate layer separation. In simulations we show that the spatial arrangement of the two layers can be successfully recovered using Bayesian inference. The layered model can also be distinguished from a single dipole model. We conclude that precision magnetoencephalography in combination with detailed dynamical system modeling can be used to study non-invasively the fast dynamics of layered computations.

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