Biology subjects

Spedden, M. E.

Publications and source records attributed to Spedden, M. E..

9 recordsLinked to original sources

bioRxiv2026

Forward Modelling for Magnetospinography: Systematic Comparison of Boundary Element and Finite Element Methods

Magnetospinography (MSG) enables non-invasive measurement of spinal cord electrophysiology, but accurate interpretation of these signals depends critically on forward modelling assumptions. We compared four vertebral bone representations: continuous, homogeneous-toroidal, inhomogeneous-toroidal, and MRI-derived-realistic, implemented within both boundary element method (BEM) and finite element method (FEM) frameworks. Lead-fields were computed across the full spinal cord for three orthogonal source orientations. When comparing matched model pairs, BEM and FEM produced consistent forward solutions, with median relative errors below 3.1% and median squared correlation coefficients exceeding 0.998 across all bone geometries. Vertebral bone geometry exerted a systematic and orientation-dependent influence on predicted lead fields. The dominant distinction was between continuous and segmented bone representations rather than between simplified and anatomically detailed segmented models. For left-right oriented sources, segmented geometries produced substantially higher field amplitudes (fT/nAm) than the continuous model throughout the cord (35-72%), while toroidal and MRI-derived realistic models produced comparable results across both frameworks, with median r2 exceeding 0.97 between segmented models compared to 0.67-0.85 for continuous versus segmented comparisons. Sensor placement further modulated sensitivity profiles, with posterior arrays exhibiting greater sensitivity lower down the cord, but anterior and posterior sensors showing comparable sensitivity in the cervical region.

neuroscience↗

bioRxiv2025

The Cerebellum Implements an Oscillatory Forward Model for Accurate Motor Timing

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.

neuroscience↗

bioRxiv2025

Wearable MEG data recorded during human stepping

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. We validate the fidelity of the OPM data by showing movement-related beta band desynchronization source localised to the primary motor cortex. 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.

neuroscience↗

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.

neuroscience↗

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.

neuroscience↗

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.

neuroscience↗

bioRxiv2021

Behavioural variability and cortical electrophysiological signals depend on recent outcomes during human reinforcement motor learning

The history of our actions and the outcomes of these represent important information, which can inform choices, and efficiently guide future behaviour. While unsuccessful (S-) outcomes are expected to lead to more explorative motor states and increased behavioural variability, successful (S+) outcomes lead to reinforcement of the previous action and thus exploitation. Here, we show that during reinforcement motor learning, humans attribute different values to previous actions when they experience S- vs. S+ outcomes. Behavioural variability after S- outcomes is influenced more by the previous outcomes compared to what is observed after S+ outcomes. Using electroencephalography, we show that neural oscillations of the prefrontal cortex encode the level of reinforcement (high beta frequencies) and reflect the detection of reward prediction errors (theta frequencies). The results suggest that S+ experiences overwrite previous motor states to a greater extent than S- experiences and that modulations in neural oscillations in the prefrontal cortex play a potential role in encoding the (changes in) movement variability state during reinforcement motor learning.

neuroscience↗

bioRxiv2020

Development of functional corticomuscular connectivity from childhood to adulthood during precision grip with the dominant and non-dominant hand

How does the neural control of manual movements mature from childhood to adulthood? Here, we investigated developmental differences in functional corticomuscular connectivity using coherence techniques in 91 individuals recruited from four different age groups covering the age range 8-30y. EEG and EMG were recorded while participants performed a unimanual visual force-tracing task requiring fine control of the force produced in a precision grip with both the dominant and non-dominant hand. Using beamforming methods, we reconstructed source activity from EEG data displaying peak coherence with the active FDI muscle during the task in order to assess functional corticomuscular connectivity. Our results revealed that coherence was greater in adolescents and adults than in children and that the difference in coherence between children and adults was driven by a greater magnitude of descending (cortex-to-muscle) coherence. This was paralleled by the observation of a posterior-to-anterior shift in the cortical sources displaying corticomuscular coherence within the contralateral hemisphere from late adolescence. Finally, we observed that corticomuscular coherence was higher on the non-dominant compared to the dominant hand across age groups. These findings provide a detailed characterization of differences in task-related corticomuscular connectivity for individuals at different stages of typical ontogenetic development that may be related to the maturational refinement of dexterous motor control. Key points- Fine motor control is gradually refined during human motor development, but little is known about the underlying neurophysiological mechanisms. - Here, we used EEG and EMG to investigate functional corticomuscular connectivity during a precision grip with the dominant and non-dominant hand in 91 typically developed children, adolescents and adults (age range 8-30y). - We show that older adolescents and adults are characterized by greater levels of corticomuscular coherence compared to children and that this is mainly driven by greater magnitudes of descending coherence (cortex-to-muscle). This is paralleled by a more anterior cortical site of coherence in older adolescents and adults compared to younger individuals. - These results help us better understand the ontogenetic development of task-related functional connectivity in sensorimotor networks.

neuroscience↗

bioRxiv2019

Directed connectivity between primary and premotor areas underlying ankle force control in young and older adults

The control of ankle muscle force is an integral component of walking and postural control. Aging impairs the ability to produce force steadily and accurately, which can compromise functional capacity and quality of life. Here, we hypothesized that reduced force control in older adults would be associated with altered cortico-cortical communication within a network comprising the primary motor area (M1), the premotor cortex (PMC), parietal, and prefrontal regions. We examined electroencephalographic (EEG) responses from fifteen younger (20-26 yr) and fifteen older (65-73 yr) participants during a unilateral dorsiflexion force-tracing task. Dynamic Causal Modelling (DCM) and Parametric Empirical Bayes (PEB) were used to investigate how directed connectivity between contralateral M1, PMC, parietal, and prefrontal regions was related to age group and precision in force production. DCM and PEB analyses revealed that the strength of connections between PMC and M1 were related to ankle force precision and differed by age group. For young adults, bidirectional PMC-M1 coupling was negatively related to task performance: stronger backward M1-PMC and forward PMC-M1 coupling was associated with worse force precision. The older group exhibited deviations from this pattern. For the PMC to M1 coupling, there were no age-group differences in coupling strength; however, within the older group, stronger coupling was associated with better performance. For the M1 to PMC coupling, older adults followed the same pattern as young adults - with stronger coupling accompanied by worse performance - but coupling strength was lower than in the young group. Our results suggest that bidirectional M1-PMC communication is related to precision in ankle force production and that this relationship changes with aging. We argue that the observed age-related differences reflect compensatory mechanisms whereby older adults maintain performance in the face of declines in the sensorimotor system.

neuroscience↗