The magnetoencephalographic and electroencephalographic (M/EEG) source reconstruction problem is an ill-posed model inversion, so it must be constrained by imposing biologically and physically plausible assumptions. Different M/EEG source reconstruction methods entail different assumptions about the underlying current distribution, yet all produce subjectively plausible current estimates. This work aims to develop an objective method that can be used to test any M/EEG analysis pathway. We make use of advances in diffeomorphic brain shape modeling to construct a set of parametrically deformable cortical surfaces that are representative of the population. These deformed (surrogate) brains provide a quantifiable parametric distortion from the ground-truth anatomy. If the current flow giving rise to the MEG data were generated on the true cortical manifold, MEG current estimates should be selective of the true anatomy. We show in simulation and with empirical data how the correct reconstruction assumptions depend closely on the true anatomy. We present a method to quantify the performance of MEG source reconstruction algorithms (and metrics of fit) in terms of millimeters of distortion.

Studying the brain in motion promises deep insights into the neural circuits that support complex, real-world behaviour. In humans, wearable optically pumped magnetometers (OPMs) enable magnetoencephalography (MEG) with millisecond temporal resolution and millimetre spatial precision during movement. Integrating this technology with virtual reality (VR) could enable fully naturalistic experimental paradigms, but magnetic interference from existing head-mounted displays (HMDs) prevents reliable whole-brain MEG recordings. Here, we present and validate a VR system that integrates with wearable, OPM-based MEG. At its core is a purpose-designed HMD with minimal ferromagnetic material, resulting in magnetic flux density two orders of magnitude lower than consumer-grade alternatives at comparable resolution and weight. Using phantom measurements and established perceptual and cognitive benchmark tasks across participants, we demonstrate robust stimulus-induced neuronal activity at both sensor and source level. Crucially, these sources span the entire brain, including visual, motor and prefrontal cortices, as well as hippocampus. Our proposed VR system is straightforward to produce, readily extendable, and enables whole-brain MEG during immersive, naturalistic behaviours. ### Competing Interest Statement The authors have declared no competing interest. European Research Council, https://ror.org/0472cxd90, ERC-2018 CoG-816564 ActionContraThreat Wellcome Trust, 226793/Z/22/Z Ministry of Culture and Science of the State of North Rhine-Westphalia, Germany, iBehave, PB22-063A InVirtuo 4.0

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 subject's 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 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 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 combining video telemetry with mobile magnetoencephalography and other legacy imaging methods for future studies of complex and naturalistic behaviours.

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.

A central challenge in movement neuroscience is developing methods for non-invasive spatiotemporal imaging of brain activity during natural, whole-body movement. We test the utility of a new brain imaging modality, optically pumped magnetoencephalography (OP-MEG), as an instrument to study the spatiotemporal dynamics of human walking. Specifically, we ask whether known physiological signals can be recovered during discrete steps involving large-scale, whole-body translation. Our findings show that by using OP-MEG, we can image the brain during large-scale, natural movements. We provide proof-of-principle evidence for movement-related changes in beta band activity during stepping vs. standing, which are source-localized to the sensorimotor cortex. This work supports the significant potential of the OP-MEG modality for addressing fundamental questions in human gait research relevant to both the physiological and pathological mechanisms of walking.

This paper marks the 30th anniversary of the Statistical Parametric Mapping (SPM) software and the journal Cerebral Cortex: two modest milestones that mark the inception of cognitive neuroscience. We take this opportunity to reflect on SPM, a generation after its introduction. Each of the authors of this paper-who represent a small selection of the many contributors to SPM-were asked to consider lessons learned, what has gone well, and where there is room for improvement in future development. We hope that this review of SPM-and its aspirations-will provide some context for current imaging neuroscience and foreground some potential directions for the future of the field.

Voluntary movements are composed of small sub-movements generated by pulsatile bursts of muscle activity at 4-10 Hz. These motor intermittencies synchronize with rhythmic brain activity and vary with movement velocity and sensory delays, suggesting they are a signature of a central oscillatory motor control mechanism. We hypothesized that these pulsatile movements arise from a cerebellar clocking mechanism-a neuronal timing process that flexibly adjusts its dynamics to maintain motor precision under temporal uncertainty. If so, cerebellar rhythms should modulate their influence on movement depending on cue predictability. To test this, we used optically pumped magnetoencephalography (OP-MEG), which enables high-quality, movement-tolerant recordings of the brain with dense cerebellar coverage. Six participants performed an auditory-paced finger flexion–extension task at approximately 1 Hz with either regular or irregular cue timing to vary predictability. All participants exhibited clear 4-10 Hz intermittencies in their kinematics, synchronized to neural activity in the cerebellum and the posterior parietal cortex. Our connectivity analysis revealed for the first time, that cerebellar activity at this frequency, predominantly reflects sensory feedback, but during regular, predictable cueing, the cerebellum shifts to exert a greater feedforward influence on movement. Moreover, cerebellar oscillations were most persistently phase-aligned with motor intermittent rhythms during accurately timed actions, an effect that was absent under irregular cueing. These findings support the idea that the cerebellum implements an oscillatory forward model for motor timing and provide novel evidence for its ability to adjusting its role in coordinating sensorimotor integration according to sensory predictability. Motor intermittencies may thus represent the output of a cerebellar timing process that underpins precise voluntary action. ### Competing Interest Statement The authors have declared no competing interest.

Neural dynamics at the laminar level are critical components of cortical computations, but in humans, non-invasive methods to study these dynamics have been limited to coarse distinctions between deep and superficial layers. Here, we demonstrate that high-precision magnetoencephalography (hpMEG) can achieve laminar inference by localizing sources across all six cortical laminae. Using a multilayer source reconstruction approach, we systematically assess the limits of hpMEG’s depth resolution, and show that laminar precision is achievable under optimal signal-to-noise ratios and co-registration accuracy. Our simulations reveal that accurate source reconstruction depends critically on aligning dipole orientations with the underlying cortical columnar structure, and that regional variations in cortical anatomy influence reconstruction fidelity. These findings position hpMEG as a powerful tool for investigating laminar-specific neural dynamics in cognition and behavior, and offer new opportunities to bridge invasive electrophysiology and human neuroimaging. ### Competing Interest Statement The authors have declared no competing interest. European Research Council, https://ror.org/0472cxd90, ERC-CoG 864550

Essential Tremor (ET) is a very common neurological disorder characterised by involuntary rhythmic movements attributable to pathological synchronization within corticothalamic circuits. Previous work has focused on tremor in isolation, overlooking broader disturbances to motor control during naturalistic movements such as reaching. We hypothesised that ET disrupts the sequential engagement of large-scale rhythmic brain networks, leading to both tremor and deficits in motor planning and execution. To test this, we performed whole-head neuroimaging during an upper-limb reaching task using high-density electroencephalography in ET patients and healthy controls, alongside optically pumped magnetoencephalography in a smaller cohort. Key motor regions-including the supplementary motor area, premotor cortex, posterior parietal cortex, and motor cerebellum-were synchronized to tremor rhythms. Patients exhibited a 15 % increase in low beta (14-21 Hz) desynchronization over the supplementary motor area during movement, which strongly correlated with tremor severity (R2 = 0.85). A novel dimensionality reduction technique revealed four distinct networks accounting for 97 % of the variance in motor-related brain-wide oscillations, with ET altering their sequential engagement. Consistent with our hypothesis, the frontoparietal beta network- normally involved in motor planning-exhibited additional desynchronization during movement execution in ET patients. This altered engagement correlated with slower movement velocities, suggesting an adaptation towards feedback-driven motor control. These findings reveal fundamental disruptions in distributed motor control networks in ET and identify novel biomarkers as targets for next-generation brain stimulation therapies.

Current flow that gives rise to non-invasive Magnetoencephalographic (MEG) data derives predominantly from pyramidal neurons oriented orthogonal to the cortical surface. The estimate of current flow based on extra-cranial magnetic fields is a well-known ill-posed problem; however, this current distribution must depend on anatomy. In other words, a veridical estimate of current flow should discriminate between true and distorted versions of the brain. Here, we make use of advances in diffeomorphic brain shape modelling to construct a set of parametrically deformable cortical surfaces. We use a latent space of 100 components to construct cortical surfaces that are representative of the population. We show how these geometric distortions can be used to quantify the performance of MEG source reconstruction algorithms and metrics of fit. ### Competing Interest Statement The authors have declared no competing interest.

Non-invasive spatiotemporal imaging of brain activity during large-scale, whole body movement is a significant methodological challenge for the field of movement neuroscience. Here, we present a dataset recorded using a new imaging modality – optically-pumped magnetoencephalography (OP-MEG) – to record brain activity during human stepping. Participants (n=3) performed a visually guided stepping task requiring precise foot placement while dual-axis and triaxial OP-MEG and leg muscle activity (electromyography, EMG) were recorded. The dataset also includes a structural MRI for each participant and foot kinematics. This multimodal dataset offers a resource for methodological development and testing for OPM data (e.g., movement-related interference rejection), within-subject analyses, and exploratory analyses to generate hypotheses for further work on the neural control of human stepping.

Statistical Parametric Mapping (SPM) is an integrated set of methods for testing hypotheses about the brain's structure and function, using data from imaging devices. These methods are implemented in an open source software package, SPM, which has been in continuous development for more than 30 years by an international community of developers. This paper reports the release of SPM 25.01, a major new version of the software that incorporates novel analysis methods, optimisations of existing methods, as well as improved practices for open science and software development.

Introduction:There is a profound lack of electrophysiological data from the cerebellum in humans, as compared to animals, because it is difficult to record cerebellar activity non-invasively using magnetoencephalography (MEG) or electroencephalography (EEG). Recent developments in wearable MEG sensors hold potential to overcome this limitation, as they allow the placement of sensors closer to the cerebellum. Methods:We leveraged the development of wearable optically pumped magnetometers to record on-scalp MEG (OP-MEG) during an established cerebellar learning paradigm-eyeblink conditioning. In four healthy human adults, we first validated that OP-MEG can reliably detect cerebellar responses by examining responses to an air puff stimulus. Results:Significant responses were observed in sensors positioned over the cerebellar region in all four adults in response to the air puff. We then indirectly tested the hypothesis that these responses reflect the population-level spiking activity of Purkinje cells. The air-puff-evoked responses diminished during the acquisition of conditioned responses, corresponding with previously observed changes in Purkinje cell activity in animals. Additionally, in three out of four participants, we observed a cerebellar evoked response just prior to the peak of the conditioned blink, resembling learning-associated shifts in Purkinje cell response latencies. Discussion:This study demonstrates that OP-MEG is a viable method for recording cerebellar activity in humans. By bridging invasive animal recordings with non-invasive human neuroimaging, these findings provide further evidence of the cerebellum's role in human learning.

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. ### Competing Interest Statement The authors have declared no competing interest.

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.

AbstractBackground and ObjectivesMagnetoencephalography (MEG) using optically pumped magnetometers (OP-MEG) is a relatively novel neuroimaging modality that holds great clinical promise for presurgical planning in epilepsy. However, there is limited data demonstrating that interictal discharges from deep neural sources can be visually identified and localised using OP-MEG. In this study, we sought to demonstrate the potential of OP-MEG for recording interictal epileptiform activity from patients with mesial temporal lobe epilepsy, the most common focal epilepsy, with a diverse range of aetiologies.MethodsWe recorded whole-head OP-MEG for a minimum of 30 minutes from 8 patients with temporal lobe epilepsies. Patients were seated with their head unconstrained. For comparison, we collected information from previous clinical assessment, including findings from MRI and EEG telemetry.ResultsWe observed interictal epileptiform activity in 4 of the patients, in 3 of which the localisation of the activity was concordant with previous clinical MRI and EEG. In 2 of those patients, we also observed ictal events. Of those 2 patients, one had a clear abnormality in MRI, with which the localisation of this ictal activity was concordant. The other patient’s MRI was negative, but the ictal localisation is consistent with the seizure semiology.DiscussionWe demonstrate that interictal and ictal epileptiform activity from mesial temporal lobe epilepsies can be observed with OP-MEG and localised to the region of the anatomical lesion, identified in MRI. This affirms the utility of OP-MEG for epilepsy surgery planning.

When planning for epilepsy surgery, multiple potential sites for resection may be identified through anatomical imaging. Magnetoencephalography (MEG) using optically pumped sensors (OP-MEG) is a non-invasive functional neuroimaging technique which could be used to help identify the epileptogenic zone from these candidate regions. Here we test the utility of a-priori information from anatomical imaging for differentiating potential lesion sites with OP-MEG. We investigate a number of scenarios: whether to use rigid or flexible sensor arrays, with or without a-priori source information and with or without source modelling errors. We simulated OP-MEG recordings for 1309 potential lesion sites identified from anatomical images in the Multi-centre Epilepsy Lesion Detection (MELD) project. To localise the simulated data, we used three source inversion schemes: unconstrained, prior source locations at centre of the candidate sites, and prior source locations within a volume around the lesion location. We found that prior knowledge of the candidate lesion zones made the inversion robust to errors in sensor gain, orientation and even location. When the reconstruction was too highly restricted and the source assumptions were inaccurate, the utility of this a-priori information was undermined. Overall, we found that constraining the reconstruction to the region including and around the participant’s potential lesion sites provided the best compromise of robustness against modelling or measurement error.

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.

Non-invasive imaging of the human spinal cord is a vital tool for understanding the mechanisms underlying its functions in both healthy and pathological conditions. However, non-invasive imaging presents a significant methodological challenge because the spinal cord is difficult to access with conventional neurophysiological approaches, due to its proximity to other organs and muscles, as well as the physiological movements caused by respiration, heartbeats, and cerebrospinal fluid (CSF) flow. Here, we discuss the present state and future directions of spinal cord imaging, with a focus on the estimation of current flow through magnetic field measurements. We discuss existing cryogenic (superconducting) and non-cryogenic (optically-pumped magnetometer-based, OPM) systems, and highlight their strengths and limitations for studying human spinal cord function. While significant challenges remain, particularly in source imaging and interference rejection, magnetic field-based neuroimaging offers a novel avenue for advancing research in various areas. These include sensorimotor processing, cortico-spinal interplay, brain and spinal cord plasticity during learning and recovery from injury, and pain perception. Additionally, this technology holds promise for diagnosing and optimizing the treatment of spinal cord disorders.