Biology subjects

Brown, P.

Publications and source records attributed to Brown, P..

At least 37 records · Page 2Linked to original sources

bioRxiv2020

Comparison of Rhesus and Cynomolgus macaques as an authentic model for COVID-19.

A novel coronavirus, SARS-CoV-2, has been identified as the causative agent of the current COVID-19 pandemic. Animal models, and in particular non-human primates, are essential to understand the pathogenesis of emerging diseases and to the safety and efficacy of novel vaccines and therapeutics. Here, we show that SARS-CoV-2 replicates in the upper and lower respiratory tract and causes pulmonary lesions in both rhesus and cynomolgus macaques, resembling the mild clinical cases of COVID-19 in humans. Immune responses against SARS-CoV-2 were also similar in both species and equivalent to those reported in milder infections and convalescent human patients. Importantly, we have devised a new method for lung histopathology scoring that will provide a metric to enable clearer decision making for this key endpoint. In contrast to prior publications, in which rhesus are accepted to be the optimal study species, we provide convincing evidence that both macaque species authentically represent mild to moderate forms of COVID-19 observed in the majority of the human population and both species should be used to evaluate the safety and efficacy of novel and repurposed interventions against SARS-CoV-2. Accessing cynomolgus macaques will greatly alleviate the pressures on current rhesus stocks.

microbiology↗

bioRxiv2020

An Assistive Computer Vision Tool to Automatically Detect Changes in Fish Behavior In Response to Ambient Odor

The analysis of fish behavior in response to odor stimulation is a crucial component of the general study of cross-modal sensory integration in vertebrates. In zebrafish, the centrifugal pathway runs between the olfactory bulb and the neural retina, originating at the terminalis neuron in the olfactory bulb. Any changes in the ambient odor of a fishs environment warrants a change in visual sensitivity and can trigger mating-like behavior in males due to increased GnRH signaling in the terminalis neuron. Behavioral experiments to study this phenomenon are commonly conducted in a controlled environment where a video of the fish is recorded over time before and after the application of chemicals to the water. Given the subtleties of behavioral change, trained biologists are currently required to annotate such videos as part of a study. This process of manually analyzing the videos is time-consuming, requires multiple experts to avoid human error/bias and cannot be easily crowdsourced on the Internet. Machine learning algorithms from computer vision, on the other hand, have proven to be effective for video annotation tasks because they are fast, accurate, and, if designed properly, can be less biased than humans. In this work, we propose to automate the entire process of analyzing videos of behavior changes in zebrafish by using tools from computer vision, relying on minimal expert supervision. The overall objective of this work is to create a generalized tool to predict animal behaviors from videos using state-of-the-art deep learning models, with the dual goal of advancing understanding in biology and engineering a more robust and powerful artificial information processing system for biologists.

animal behavior and cognition↗

bioRxiv2020

Basal ganglia high-frequency activity is co-modulated with the phase of motor cortical beta and shifted between the subthalamic nucleus and the internal pallidum during sustained motor control

Beta oscillations are readily observed in motor cortex and the basal ganglia, but to which extent they are functionally relevant is unclear. To understand how activity transfer between different nodes of the cortico-basal ganglia network is affected by cortical beta oscillations in different behavioural conditions, we recorded local field potentials and electroencephalography (EEG) activity in a low-force motor control task and during rest in Parkinsons patients undergoing deep brain stimulation (DBS) surgery. The patients received DBS of either the subthalamic nucleus (STN) or the internal globus pallidus (GPi), which allowed us to investigate if STN and GPi broad-band high-frequency activity (HFA; >150 Hz) is co-modulated with the phase of motor cortical beta activity. We found significant modulation patterns in the STN and the GPi, which were inverted while patients performed the task, showing that GPi activity fluctuations likely are crafted by other inputs than the direct excitatory STN afferents. We also found that consistent STN modulation disappeared during rest, showing disengagement in this condition, while GPi modulation was maintained, again evidencing that beta-band activity fluctuations in the GPi can be relatively independent of those in the STN. The difference between HFA modulation patterns in the task and rest recordings suggests a potential functional role of beta phase-locked HFA modulation in controlling sustained contractions. Examination of HFA co-modulation patterns at different sites of the cortico-basal ganglia-thalamo-cortical network under different behavioural conditions may provide a tool with which to define the impact of beta synchronization on network communication.

neuroscience↗

bioRxiv2020

Entraining stepping movements of Parkinson's patients to alternating subthalamic nucleus deep brain stimulation

Patients with advanced Parkinsons can be treated by deep brain stimulation of the subthalamic nucleus (STN). This affords a unique opportunity to record from this nucleus and stimulate it in a controlled manner. Previous work has shown that activity in the STN is modulated in a rhythmic pattern when Parkinsons patients perform stepping movements, raising the question whether the STN is involved in the dynamic control of stepping. To answer this question, we tested whether an alternating stimulation pattern resembling the stepping-related modulation of activity in the STN could entrain patients stepping movements as evidence of the STNs involvement in stepping control. Group analyses of ten Parkinsons patients (one female) showed that alternating stimulation significantly entrained stepping rhythms. We found a remarkably consistent alignment between the stepping and stimulation cycle when the stimulation speed was close to the stepping speed in the five patients that demonstrated significant individual entrainment to the stimulation cycle. Our study provides evidence that the STN is causally involved in dynamic control of step timing, and motivates further exploration of this biomimetic stimulation pattern as a basis for the development of specific deep brain stimulation strategies to ameliorate gait impairments.

neuroscience↗

bioRxiv2020

Intersection of structural and functional connectivity of the nucleus basalis of Meynert in Parkinson's disease dementia and Lewy body dementia

Parkinsons disease dementia (PDD) and dementia with Lewy bodies (DLB) are related conditions that are associated with cholinergic system dysfunction. Dysfunction of the nucleus basalis of Meynert (NBM), a basal forebrain structure that provides the dominant source of cortical cholinergic innervation, has been implicated in the pathogenesis of both PDD and DLB. Here we leverage the temporal resolution of magnetoencephalography (MEG) with the spatial resolution of MRI tractography in order to explore the intersection of functional and structural connectivity of the NBM in a unique cohort of PDD and DLB patients undergoing Deep Brain Stimulation (DBS) of this structure. We observe that NBM-cortical structural and functional connectivity correlate within spatially and spectrally segregated networks including: 1) a beta band network to supplementary motor area (SMA), where activity in the SMA was found to drive activity in the NBM, 2) a delta/theta band network to medial temporal lobe structures encompassing the parahippocampal gyrus and 3) a delta/theta band network to visual areas including lingual gyrus. These findings reveal functional networks of the NBM that are likely to subserve important roles in motor control, memory and visual function respectively. Furthermore, they motivate future studies aimed at disentangling network contribution to disease phenotype.

neuroscience↗

bioRxiv2020

Neural signatures of pathological hyperdirect pathway activity in Parkinson's disease

Parkinsons disease (PD) is characterised by the emergence of pathological patterns of oscillatory synchronisation across the cortico-basal-ganglia circuit. The relationship between anatomical connectivity and oscillatory synchronisation within this system remains poorly understood. We address this by integrating evidence from invasive electrophysiology, magnetoencephalography, tractography and computational modelling in patients. Coupling between supplementary motor area (SMA) and subthalamic nucleus (STN) within the high beta frequency (21-30 Hz) range correlated with fibre tract densities between these two structures. Additionally within the STN, non-linear waveform features suggestive of cortical synchronisation correlated with cortico-STN fibre densities. Finally, computational modelling revealed that exaggerated hyperdirect cortical inputs to the STN in the upper beta frequency range can provoke the generation of widespread pathological synchrony at lower beta (13-20 Hz) frequencies. These observations reveal a spectral signature of the hyperdirect pathway at high beta frequencies and provide evidence for its pathophysiological role in oscillatory network dysfunction in PD. One sentence summarySignatures of the hyperdirect pathway and its likely role in pathological network disruption in Parkinsons disease are identified.

neuroscience↗

bioRxiv2020

Dose-dependent response to infection with SARS-CoV-2 in the ferret model: evidence of protection to re-challenge

In December 2019 an outbreak of coronavirus disease (COVID-19) emerged in Wuhan, China. The causative agent was subsequently identified and named severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) which rapidly spread worldwide causing a pandemic. Currently there are no licensed vaccines or therapeutics available against SARS-CoV-2 but numerous candidate vaccines are in development and repurposed drugs are being tested in the clinic. There is a vital need for authentic COVID-19 animal models to further our understanding of pathogenesis and viral spread in addition to pre-clinical evaluation of candidate interventions. Here we report a dose titration study of SARS-CoV-2 to determine the most suitable infectious dose to use in the ferret model. We show that a high (5x106 pfu) and medium (5x104 pfu) dose of SARS-CoV-2 induces consistent upper respiratory tract (URT) viral RNA shedding in both groups of six challenged animals, whilst a low dose (5x102 pfu) resulted in only one of six displaying signs of URT viral RNA replication. The URT shedding lasted up to 21 days in the high dose animals with intermittent positive signal from day 14. Sequential culls revealed distinct pathological signs of mild multifocal bronchopneumonia in approximately 5-15% of the lung, observed on day 3 in high and medium dosed animals, with presence of mild broncho-interstitial pneumonia on day 7 onwards. No obvious elevated temperature or signs of coughing or dyspnoea were observed although animals did present with a consistent post-viral fatigue lasting from day 9-14 in the medium and high dose groups. After virus shedding ceased, re-challenged ferrets were shown to be fully protected from acute lung pathology. The endpoints of URT viral RNA replication in addition to distinct lung pathology and post viral fatigue were observed most consistently in the high dose group. This ferret model of SARS-CoV-2 infection presents a mild clinical disease (as displayed by 80% of patients infected with SARS-CoV-2). In addition, intermittent viral shedding on days 14-21 parallel observations reported in a minority of clinical cases.

microbiology↗

bioRxiv2020

Physiological Artifacts and the Implications for Brain-Machine-Interface Design

The accurate measurement of brain activity by Brain-Machine-Interfaces (BMI) and closed-loop Deep Brain Stimulators (DBS) is one of the most important steps in communicating between the brain and subsequent processing blocks. In conventional chest-mounted systems, frequently used in DBS, a significant amount of artifact can be induced in the sensing interface, often as a common-mode signal applied between the case and the sensing electrodes. Attenuating this common-mode signal can be a serious challenge in these systems due to finite commonmode-rejection-ratio (CMRR) capability in the interface. Emerging BMI and DBS devices are being developed which can mount on the skull. Mounting the system on the cranial region can potentially suppress these induced physiological signals by limiting the artifact amplitude. In this study, we model the effect of artifacts by focusing on cardiac activity, using a current-source dipole model in a torso-shaped volume conductor. Performing finite element simulation with the different DBS architectures, we estimate the ECG common mode artifacts for several device architectures. Using this model helps define the overall requirements for the total system CMRR to maintain resolution of brain activity. The results of the simulations estimate that the cardiac artifacts for skull-mounted systems will have a significantly lower effect than non-cranial systems that include the pectoral region. It is expected that with a pectoral mounted device, a minimum of 60-80 dB CMRR is required to suppress the ECG artifact, while in cranially-mounted devices, a 20 dB CMRR is sufficient, in the worst-case scenario. The methods used for estimating cardiac artifacts can be extended to other sources such as motion/muscle sources. The susceptibility of the device to artifacts has significant implications for the practical translation of closed-loop DBS and BMI, including the choice of biomarkers and the design requirements for insulators and lead systems.

bioengineering↗

bioRxiv2020

Genetic variation associated with PPO-inhibiting herbicide tolerance in sorghum

Herbicide application is crucial for weed management in most crop production systems, but for sorghum herbicide options are limited. Sorghum is sensitive to residual protoporphyrinogen oxidase (PPO)- inhibiting herbicides, such as fomesafen, and a long re-entry period is required before sorghum can be planted after its application. Improving sorghum for tolerance to such residual herbicides would allow for increased sorghum production and the expansion of herbicide options for growers. To investigate the underlying mechanism of tolerance to residual fomesafen, a genome-wide association mapping study was conducted using the sorghum biomass panel (SBP) and field-collected data, and a greenhouse assay was developed to confirm the field phenotypes. A total of 26 significant SNPs (FDR<0.05), spanning a 215.3 kb region, were detected on chromosome 3. The ten most significant SNPs included two in genic regions (Sobic.003G136800, and Sobic.003G136900) and eight SNPs in the intergenic region encompassing the genes Sobic.003G136700, Sobic.003G136800, Sobic.003G137000, Sobic.003G136900, and Sobic.003G137100. The gene Sobic.003G137100 (PPXI), which encodes the PPO1 enzyme, one of the targets of PPO-inhibiting herbicides, was located 12kb downstream of the significant SNP S03_13152838. We found that PPXI is highly conserved in sorghum and expression does not significantly differ between tolerant and sensitive sorghum lines. Our results suggest that PPXI most likely does not underlie the observed herbicide tolerance. Instead, the mechanism underlying herbicide tolerance in the SBP is likely metabolism-based resistance, possibly regulated by the action of multiple genes. Further research is necessary to confirm candidate genes and their functions.

plant biology↗

bioRxiv2020

Average beta burst duration profiles provide a signature of dynamical changes between the ON and OFF medication states in Parkinson's disease

Parkinsons disease motor symptoms are associated with an increase in subthalamic nucleus beta band oscillatory power. However, these oscillations are phasic, and there is a growing body of evidence suggesting that beta burst duration may be of critical importance to motor symptoms. This makes insights into the dynamics of beta bursting generation valuable, in particular to refine closed-loop deep brain stimulation in Parkinsons disease. In this study, we ask the question "Can average burst duration reveal how dynamics change between the ON and OFF medication states?". Our analysis of local field potentials from the subthalamic nucleus demonstrates using linear surrogates that the system generating beta oscillations is more likely to act in a non-linear regime OFF medication and that the change in a non-linearity measure is correlated with motor impairment. In addition, we pinpoint the simplest dynamical changes that could be responsible for changes in the temporal patterning of beta oscillations between medication states by fitting to data biologically inspired models, and simpler beta envelope models. Finally, we show that the non-linearity can be directly extracted from average burst duration profiles under the assumption of constant noise in envelope models. This reveals that average burst duration profiles provide a window into burst dynamics, which may underlie the success of burst duration as a biomarker. In summary, we demonstrate a relationship between average burst duration profiles, dynamics of the system generating beta oscillations, and motor impairment, which puts us in a better position to understand the pathology and improve therapies such as deep brain stimulation. Author summaryIn Parkinsons disease, motor impairment is associated with abnormal oscillatory activity of neurons in deep motor regions of the brain. These oscillations come in the shape of bursts, and the duration of these bursts has recently been shown to be of importance to motor symptoms. To better understand the disease and refine therapies, we relate the duration of these bursts to properties of the system generating them in the pathological state and in a proxy of the healthy state. The data suggest that the system generating bursts involves more complexity in the pathological state, and we show that a measure of this complexity is associated with motor impairment. We propose biologically inspired models and simpler models that can generate the burst patterns observed in the pathological and healthy state. The models confirm what was observed in data, and tell us how burst generation mechanisms could differ in the disease. Finally, we identify a mathematical link allowing us to infer properties of the burst generating system from burst duration measurements in patient recordings. This sheds some light on the significance of burst duration as a marker of pathology.

neuroscience↗

bioRxiv2019

\"Ghost ponds\" - How to resurrect in-filled farmland ponds to assist aquatic biodiversity conservation in agricultural landscapes

Growing recognition of the importance of ponds for landscape-scale biodiversity has led to considerable interest in their conservation, focusing on new pond creation, or existing pond restoration. However, there is a third approach; the re-excavation of ghost ponds - former ponds deliberately filled-in due to agricultural intensification. Previous work has shown ghost ponds to retain viable sediment propagules of many aquatic plants for over a century, allowing for the rapid re-colonisation of resurrected pond sites. Here we detail the practicalities of the ghost pond resurrection approach, describing how to locate, identify, and excavate ghost ponds in agricultural land. We also report on colonisation by aquatic macrophytes and water beetles (Coleoptera) for three ghost pond resurrections in Norfolk, eastern England and make comparisons with neighbouring extant ponds restored to open-canopy conditions via major scrub and sediment removal at the same time. Ecologically important macrophyte taxa, including charophyte and Potamogeton species, successfully established in the ghost ponds and within one year they supported a comparable species diversity to the adjacent restored ponds. Our findings show that, where appropriate to land management goals, ghost pond resurrection could be a very valuable conservation approach within farmed landscapes.

ecology↗

bioRxiv2019

Adaptive Deep Brain Stimulation as an Advanced Parkinson’s disease Treatment (ADAPT): a pseudorandomised clinical trial

BackgroundBeta-based adaptive Deep Brain Stimulation (aDBS) is effective in Parkinsons disease (PD), when assessed in the immediate post-implantation phase. However, the potential benefits of aDBS in patients with electrodes chronically implanted, in whom the benefits of the microlesion effect have disappeared, are yet to be assessed. MethodsTo determine the acute effectiveness and side-effect profile of aDBS in PD compared to conventional continuous DBS (cDBS) and no stimulation (NoStim), years after DBS implantation. 13 PD patients undergoing battery replacement were pseudo-randomised in a crossover fashion, in- to three conditions (NoStim, aDBS or cDBS). Patient videos were blindly evaluated using a short version of the Unified Parkinsons Disease Rating Scale (subUPDRS) and the Speech Intelligibility Test (SIT). ResultsPatients had a mean disease duration of 16 years, and the mean time since DBS implantation was 6.9 years. subUPDRS scores (11 patients tested) were significantly lower both in aDBS (p=<.001), and cDBS (p=.001), when compared to NoStim. Bradykinesia subscores were significantly lower in aDBS (p=.002), but not in cDBS (p=.08), when compared to NoStim. Two patients presented re-emerging tremor during NoStim. SIT scores of patients with stimulation-induced dysarthria (11 patients tested) significantly worsened in cDBS (p=.009), but not in aDBS (p=.407), when compared to NoStim. Overall, stimulation was applied 48.8% of the time during aDBS. ConclusionBeta oscillations is effective in PD patients with bradykinetic phenotypes, delivers less stimulation than cDBS, and potentially has a more favourable speech side-effect profile. Patients with prominent tremor may require a modified adaptive control strategy.

neuroscience↗

bioRxiv2019

Neurofeedback linked suppression of subthalamic beta oscillations speeds up movement initialisation in Parkinsonian Patients

Enhanced beta oscillations (13-30 Hz) in the subthalamic nucleus (STN) have been associated with clinical impairment in Parkinsons disease (PD), such as rigidity and slowing of movement, with the suppression of STN beta activity through medication or deep brain stimulation correlating with improvement in these symptoms. Recent studies have also emphasized the importance of the time dynamics of the STN beta oscillations in the pathology of PD. An increased probability of prolonged beta bursts, defined as periods when beta band power exceeds a certain threshold, was more closely related to motor symptoms than average power; and the occurrence of beta bursts just before a go cue slows cued movements. Here we adopted a sequential neurofeedback-behaviour task paradigm to investigate whether patients with PD can learn to suppress pathological beta oscillations recorded from STN with neurofeedback training and whether the training improves the motor performance. Results from twelve patients showed that, compared with the control condition, the neurofeedback training led to reduced incidence and duration of beta bursts in the STN local field potential (LFP) and also reduced the synchrony between the STN LFP and cortical activities measured through EEG in the beta frequency band. The changes were accompanied by a reduced reaction time in cued movements. These results suggest that volitional suppression of beta bursts facilitated by neurofeedback training could help improve movement initialisation in Parkinsons disease.\n\nSignificance StatementOur study suggests that a neurofeedback paradigm which focuses on the time dynamics of the target neural signal can facilitate volitional suppression of pathological beta oscillations in the STN in Parkinsons disease. Neurofeedback training was accompanied by reduced reaction time in cued movements, but associated with increased tremor in tremulous patients. The results strengthen the link between subthalamic beta oscillations and motor impairment, and also suggest that different symptom-specific neural signals could be targeted to improve neuromodulation strategies, either through brain stimulation or neurofeedback training, for patients with tremor and bradykinesia-rigidity.

neuroscience↗

bioRxiv2019

Identification and Characterization of the First Fragment Hits for SETDB1 Tudor Domain

SET domain bifurcated protein 1 (SETDB1) is a human histone-lysine methyltransferase, which is amplified in human cancers and was shown to be crucial in the growth of non-small and small cell lung carcinoma. In addition to its catalytic domain, SETDB1 harbors a unique tandem tudor domain which recognizes histone sequences containing both methylated and acetylated lysines, and likely contributes to its localization on chromatin. Using X-ray crystallography and NMR spectroscopy fragment screening approaches, we have identified the first small molecule fragment hits that bind to histone peptide binding groove of the TTD of SETDB1. Herein, we describe the binding modes of these fragments and analogues and the biophysical characterization of key compounds. These confirmed small molecule fragments will inform the development of potent antagonists of SETDB1 interaction with histones.

pharmacology and toxicology↗

bioRxiv2019

Phase dependence of response curves to stimulation and their relationship: from a Wilson-Cowan model to essential tremor patient data

Essential tremor manifests predominantly as a tremor of the upper limbs. One therapy option is high-frequency deep brain stimulation, which continuously delivers electrical stimulation to the ventral intermediate nucleus of the thalamus at about 130 Hz. Investigators have been looking at stimulating less, chiefly to reduce side effects. One strategy, phase-locked deep brain stimulation, consists of stimulating according to the phase of the tremor, once per period. In this study, we aim to reproduce the phase dependent effects of stimulation seen in patient data with a biologically inspired Wilson-Cowan model. To this end, we first analyse patient data, and conclude that half of the datasets have response curves that are better described by sinusoidal curves than by straight lines, while an effect of phase cannot be consistently identified in the remaining half. Using the Hilbert phase we derive analytical expressions for phase and amplitude responses to phase-dependent stimulation and study their relationship in the linearisation of a stable focus model, a simplification of the Wilson-Cowan model in the stable focus regime. Analytical results provide a good approximation for response curves observed in patients with consistent significance. Additionally, we fitted the full non-linear Wilson-Cowan model to these patients, and we show that the model can fit in each case to the dynamics of patient tremor as well as the phase response curve, and the best fits are found to be stable foci for each patients (tied best fit in one instance). The model provides satisfactory prediction of how patient tremor will react to phase-locked stimulation by predicting patient amplitude response curves although they were not explicitly fitted. This can be partially explained by the relationship between the response curves in the model being compatible with what is found in the data. We also note that the non-linear Wilson-Cowan model is able to describe response to stimulation more precisely than the linearisation.

neuroscience↗

bioRxiv2019

Parkinsons disease uncovers an underlying sensitivity of subthalamic nucleus neurons to beta-frequency cortical input

Abnormally sustained beta-frequency synchronisation between the motor cortex and subthalamic nucleus (STN) is associated with motor symptoms in Parkinsons disease (PD). It is currently unclear whether STN neurons have a preference for beta-frequency input (12-35Hz), rather than cortical input at other frequencies, and how such a preference would arise following dopamine depletion. To address this question, we combined analysis of cortical and STN recordings from awake PD patients undergoing deep brain stimulation surgery with recordings of identified STN neurons in anaesthetised rats. In PD patients, we demonstrate that a subset of STN neurons are strongly and selectively sensitive to fluctuations of cortical beta oscillations over time, linearly increasing their phase-locking strength with respect to full range of instantaneous amplitude. In rats, we probed the frequency response of STN neurons more precisely, by recording spikes evoked by short bursts of cortical stimulation with variable frequency (4-40Hz) and constant amplitude. In both healthy and dopamine-depleted animals, only beta-frequency stimulation selectively led to a progressive reduction in the variability of spike timing through the stimulation train. We hypothesize, that abnormal activation of the indirect pathway, via dopamine depletion and/or cortical stimulation, could trigger an underlying sensitivity of the STN microcircuit to beta-frequency input.

neuroscience↗

bioRxiv2018

Temporal evolution of beta bursts in the parkinsonian cortico-basal ganglia network

Prevalence and temporal dynamics of transient oscillations in the beta frequency band (15-35 Hz), referred to as beta bursts, are correlated with motor performance and tactile perception. Disturbance of these activities is a candidate mechanism for motor impairment in Parkinsons disease (PD), where the excessively long bursts correlate with symptom severity and are reduced by pharmacological and surgical treatments. To date, characterization of beta bursts in PD has been limited to the local field potentials in the subthalamic nucleus (STN) and cortical EEG. Here, we describe the changes that take place in spiking activity across the cortico-basal ganglia circuit, providing a unique insight into the network dynamics of these transient oscillations. Firstly, we demonstrate that rhythmic subthalamic spiking activity emerges at a fixed phase relationship with respect to cortical beta bursts in PD patients. Using multichannel recordings of ensembles of neurons in the 6-OHDA rat model of PD, we then dissect the beta burst dynamics across the sensorimotor cortex and several basal ganglia structures: striatum (Str), globus pallidus externus (GPe) and STN. Each subcortical structure exhibits enhanced rhythmic activity in the beta band locked to the onset of cortical beta bursts and longer cortical bursts lead to stronger subcortical rhythmicity. Crucially, enhanced subcortical rhythmic activity emerges at a fixed phase relationship with respect to the motor cortex, comparable to the relationship observed in PD patients. Striatal beta bursts terminate prior to the recruitment of those in the STN and GPe, suggesting that while they could play an important role in establishing synchrony in the beta band, they do not extensively contribute to its maintenance in other basal ganglia structures. Critically, changes in cortico-subcortical phase coupling precede the onset of a cortical beta burst, supporting the hypothesis that phase alignment across the cortico-basal ganglia network could recruit these structures into synchronous network oscillations. We provide a powerful approach that not only examines pathophysiology of PD across the motor circuit, but also offer insights that could aid in the design of novel neuromodulation strategies to manipulate the state of the motor system before pathological activities emerge.

neuroscience↗

bioRxiv2018

Predicting the effects of deep brain stimulation using a reduced coupled oscillator model

Deep brain stimulation (DBS) is known to be an effective treatment for a variety of neurological disorders, including Parkinsons disease and essential tremor (ET). At present, it involves administering a train of pulses with constant frequency via electrodes implanted into the brain. New closed-loop approaches involve delivering stimulation according to the ongoing symptoms or brain activity and have the potential to provide improvements in terms of efficiency, efficacy and reduction of side effects. The success of closed-loop DBS depends on being able to devise a stimulation strategy that minimizes oscillations in neural activity associated with symptoms of motor disorders. A useful stepping stone towards this is to construct a mathematical model, which can describe how the brain oscillations should change when stimulation is applied at a particular state of the system. Our work focuses on the use of coupled oscillators to represent neurons in areas generating pathological oscillations. Using a reduced form of the Kuramoto model, we analyse how a patient should respond to stimulation when neural oscillations have a given phase and amplitude. We predict that, provided certain conditions are satisfied, the best stimulation strategy should be phase specific but also that stimulation should have a greater effect if applied when the amplitude of brain oscillations is lower. We compare this surprising prediction with data obtained from ET patients. In light of our predictions, we also propose a new hybrid strategy which effectively combines two of the strategies found in the literature, namely phase-locked and adaptive DBS.\n\nAuthor summaryDeep brain stimulation (DBS) involves delivering electrical impulses to target sites within the brain and is a proven therapy for a variety of neurological disorders. Closed loop DBS is a promising new approach where stimulation is applied according to the state of a patient. Crucial to the success of this approach is being able to predict how a patient should respond to stimulation. Our work focusses on DBS as applied to patients with essential tremor (ET). On the basis of a theoretical model, which describes neurons as oscillators that respond to stimulation and have a certain tendency to synchronize, we provide predictions for how a patient should respond when stimulation is applied at a particular phase and amplitude of the ongoing tremor oscillations. Previous experimental studies of closed loop DBS provided stimulation either on the basis of ongoing phase or amplitude of pathological oscillations. Our study suggests how both of these measurements can be used to control stimulation. As part of this work, we also look for evidence for our theories in experimental data and find our predictions to be satisfied in one patient. The insights obtained from this work should lead to a better understanding of how to optimise closed loop DBS strategies.

neuroscience↗