Biology subjects

West, T. O.

Publications and source records attributed to West, T. O..

8 recordsLinked to original sources

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

Beyond beta: Aperiodic broadband power reflects Parkinson's disease severity - a multicenter study

Parkinsons disease is linked to increased beta oscillations in the subthalamic nucleus, which correlate with motor symptoms. However, findings across studies have varied. Our standardized analysis of multicenter datasets shows that small sample sizes contributed to these discrepancies--a challenge we address by pooling datasets into one large cohort (n=119). Moving beyond beta power, we disentangled spectral components reflecting distinct neural processes. Combining aperiodic offset, low beta, and low gamma oscillations explained significantly more variance in symptom severity than beta alone. Moreover, interhemispheric within-patient analyses showed that, unlike beta oscillations, aperiodic broadband power-likely reflecting spiking activity-was increased in the more affected hemisphere. These findings identify aperiodic broadband power as a potential biomarker for adaptive deep brain stimulation and provide novel insights into the relationship between subthalamic hyperactivity and motor symptoms in human Parkinsons disease.

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.

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bioRxiv2022

When do bursts matter in the motor cortex? Investigating changes in the intermittencies of beta rhythms associated with movement states.

Time series of brain activity recorded from different anatomical regions and in different behavioural states and pathologies can be summarised by the power spectrum. Recently, attention has shifted to characterising the properties of changing temporal dynamics in rhythmic neural activity. Here, we present evidence from electrocorticography recordings made from the motor cortex to show that, dependent on the specific motor context, the statistics of temporal transients in beta frequency (14-30 Hz) rhythms (i.e., bursts) can significantly add to the description of states such rest, movement preparation, movement execution, and movement imagery. We show that the statistics of burst duration and amplitude can significantly improve the classification of motor states and that burst features reflect nonlinearities not detectable in the power spectrum, with states increasing in order of nonlinearity from movement execution to movement preparation to rest. Further, we provide mechanistic explanations for these features by fitting models of the motor cortical microcircuit to the empirical data and investigate how dynamical instabilities interact with noise to generate burst dynamics. Finally, we examine how beta bursting in motor cortex may influence the integration of exogenous inputs to the cortex and suggest that properties of spontaneous activity cannot be reliably used to infer the response of the cortex to external inputs. These findings have significance for the classification of motor states, for instance in novel brain-computer interfaces. Critically, we increase the understanding of how transient brain rhythms may contribute to cortical processing, which in turn, may inform novel approaches for its modulation with brain stimulation.

neuroscience↗

bioRxiv2020

State Dependency of Beta Oscillations in the Cortico-Basal-Ganglia Circuit and their Neuromodulation under Phase Locked Inputs

State-of-the-art therapeutic brain stimulation strategies are delivered open loop, using fixed parameters. However, brain states exhibit spontaneous fluctuations dependent upon different behavioural or disease states. Here, we use a model of the cortico-basal ganglia-thalamic circuit to demonstrate how connectivity underpins changes in subcortical beta oscillations - a commonly used control parameter for deep brain stimulation in Parkinsons disease. We show that recurrent cortical-subcortical loops involving either the cortico-subthalamic or pallido-subthalamic pathways can act in antagonism to modulate the expression of beta band activity (14-30 Hz). These pathways alter the relative timing of intermittent activity across the network, with increased pallido-subthalamic connectivity increasing the propensity of the circuit to enter a state of autonomous oscillation. We demonstrate that phase-locked stimulation can modulate these oscillations, with an efficacy that ultimately depends upon the connectivity across the circuit. This work outlines critical factors required to implement state-adaptive closed-loop brain stimulation. HighlightsO_LIConverging inputs to the subthalamic nucleus arriving via the external segment of globus pallidus and cortex act in antagonism and promote different beta rhythms. C_LIO_LIPhase locked stimulation has the capacity to selectively enhance or suppress a brain rhythm depending on the stimulation timing. C_LIO_LIThe efficacy of stimulation and the parameters required to deliver it, e.g. stimulation timing, effective sensing and stimulation locations, are functions of network state. C_LI

neuroscience↗

bioRxiv2019

Mechanistic Inference of Brain Network Dynamics with Approximate Bayesian Computation

Brain networks and the neural dynamics that unfold upon them are of great interest across the many scales of systems neuroscience. The tools of inverse modelling provide a way of both constraining and selecting models of large scale brain networks from empirical data. Such models have the potential to yield broad theoretical insights in the understanding of the physiological processes behind the integration and segregation of activity in the brain. In order to make inverse modelling computationally tractable, simplifying model assumptions have often been adopted that appeal to steady-state approximations to neural dynamics and thus prevent the investigation of stochastic or intermittent dynamics such as gamma or beta burst activity. In this work we describe a framework that uses the Approximate Bayesian Computation (ABC) algorithm for the inversion of neural models that can flexibly represent any statistical feature of empirically recorded data and eschew the need to assume a locally linearized system. Further, we demonstrate how Bayesian model comparison can be applied to fitted models to enable the selection of competing hypotheses regarding the causes of neural data. This work establishes a validation of the procedures by testing for both the face validity (i.e. the ability to identify the original model that has generated the observed data) and predictive validity (i.e. the consistency of the parameter estimation across multiple realizations of the same data). From the validation and example applications presented here we conclude that the proposed framework provides a novel opportunity to researchers aiming to explain how complex brain dynamics emerge from neural circuits.

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bioRxiv2019

Measuring directed functional connectivity in neural data using Non-Parametric Directionality Analysis: validation and comparison with Non-Parametric Granger Causality

Background Non-parametric directionality (NPD) is a novel method for estimation of directed functional connectivity (dFC) in neural data. The method has previously been verified in its ability to recover causal interactions in simulated spiking networks in Halliday et al. (2015) MethodsThis work presents a validation of NPD in continuous neural recordings (e.g. local field potentials). Specifically, we use autoregressive model to simulate time delayed correlations between neural signals. We then test for the accurate recovery of networks in the face of several confounds typically encountered in empirical data. We examine the effects of NPD under varying: a) signal-to-noise ratios, b) asymmetries in signal strength, c) instantaneous mixing, d) common drive, e) and parallel/convergent signal routing. We also apply NPD to data from a patient who underwent simultaneous magnetoencephalography and deep brain recording. ResultsWe demonstrate that NPD can accurately recover directed functional connectivity from simulations with known patterns of connectivity. The performance of the NPD metric is compared with non-parametric Granger causality (NPG), a well-established methodology for model free estimation of dFC. A series of simulations investigating synthetically imposed confounds demonstrate that NPD provides estimates of connectivity that are equivalent to NPG. However, we provide evidence that: i) NPD is less sensitive than NPG to degradation by noise; ii) NPD is more robust to the generation of false positive identification of connectivity resulting from SNR asymmetries; iii) NPD is more robust to corruption via moderate degrees of instantaneous signal mixing. ConclusionsThe results in this paper highlight that to be practically applied to neural data, connectivity metrics should not only be accurate in their recovery of causal networks but also resistant to the confounding effects often encountered in experimental recordings of multimodal data. Taken together, these findings position NPD at the state-of-the-art with respect to the estimation of directed functional connectivity in neuroimaging. HighlightsO_LINon-parametric directionality (NPD) is a novel directed connectivity metric. C_LIO_LINPD estimates are equivalent to Granger causality but more robust to signal confounds. C_LIO_LIMultivariate extensions of NPD can correctly identify signal routing. C_LI Abbreviations

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bioRxiv2017

Propagation of Beta/Gamma Rhythms in the Cortico-Basal Ganglia Circuits of the Parkinsonian Rat

Some motor impairments associated with Parkinsons disease are thought to arise from pathological activity in the neuronal networks formed by the basal ganglia (BG) and motor cortex. To evaluate several hypotheses proposed to explain the emergence of pathological oscillations in Parkinsonism, we investigated changes to the directed connectivity in these networks following dopamine depletion. We recorded local field potentials in the cortex and basal ganglia of anesthetized rats rendered Parkinsonian by injection of 6-hydroxydopamine (6-OHDA), with dopamine-intact rats as controls. We performed systematic analyses of the networks using a novel tool for estimation of directed neural interactions, as well as a conditioned variant which permits the analysis of the dependence of a connection upon a third reference signal. We find evidence of the dopamine dependency of both low beta (14-20 Hz) and high beta/low gamma (20-40 Hz) directed interactions within the BG and cortico-BG networks. Notably, 6-OHDA lesions were associated with enhancement of the cortical \"hyperdirect\" connection to the subthalamic nucleus (STN), as well the STNs feedback to the cortex and striatum. We find beta synchronization to be robust to conditioning using signals from any one structure. Conversely, we find that high beta/gamma drive from the cortex to subcortical regions is weakened by 6-OHDA lesions and is susceptible to conditioning. Furthermore, we provide evidence that gamma is routed from striatum in a pathway that is independent of STN. These results further inform our understanding of the substrates for pathological rhythms in salient brain networks in Parkinsonism.\n\nNew & NoteworthyWe present a novel analysis of electrophysiological recordings in the cortico-basal ganglia network with the aims of evaluating several hypotheses concerning the origins of abnormal brain rhythms associated with Parkinsons disease. We present evidence for changes in the directed connections within the network following chronic dopamine depletion in rodents. These findings speak to the plausibility of a \"short-circuiting\" of the network that gives rise to the conditions from which pathological synchronization may arise.

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