Integrating Brain and Biomechanical Models—A New Paradigm for Understanding Neuro-muscular Control

To date, realistic models of how the central nervous system governs behavior have been restricted in scope to the brain, brainstem or spinal column, as if these existed as disembodied organs. Further, the model is often exercised in relation to an in vivo physiological experiment with input comprising an impulse, a periodic signal or constant activation, and output as a pattern of neural activity in one or more neural populations. Any link to behavior is inferred only indirectly via these activity patterns. We argue that to discover the principles of operation of neural systems, it is necessary to express their behavior in terms of physical movements of a realistic motor system, and to supply inputs that mimic sensory experience. To do this with confidence, we must connect our brain models to neuro-muscular models and provide relevant visual and proprioceptive feedback signals, thereby closing the loop of the simulation. This paper describes an effort to develop just such an integrated brain and biomechanical system using a number of pre-existing models. It describes a model of the saccadic oculomotor system incorporating a neuromuscular model of the eye and its six extraocular muscles. The position of the eye determines how illumination of a retinotopic input population projects information about the location of a saccade target into the system. A pre-existing saccadic burst generator model was incorporated into the system, which generated motoneuron activity patterns suitable for driving the biomechanical eye. The model was demonstrated to make accurate saccades to a target luminance under a set of environmental constraints. Challenges encountered in the development of this model showed the importance of this integrated modeling approach. Thus, we exposed shortcomings in individual model components which were only apparent when these were supplied with the more plausible inputs available in a closed loop design. Consequently we were able to suggest missing functionality which the system would require to reproduce more realistic behavior. The construction of such closed-loop animal models constitutes a new paradigm of computational neurobehavior and promises a more thoroughgoing approach to our understanding of the brain’s function as a controller for movement and behavior

Computational modelling of normal function and pathology in neural systems: new tools, techniques and results in cortex and basal ganglia.

Oscillations between various populations of neurons are common and well documented. However, there are oscillations that can emerge within networks of neurons that are pathological and highly detrimental to the normal functioning of the brain. This thesis is concerned with modelling the transition from healthy network states to the pathological oscillatory states in two different brain disorders; epilepsy and Parkinson’s disease (PD). To study these transitions, existing computational methods for modelling large systems of interacting populations of neurons are used and new tools are developed. The first half of this thesis explores the evidence for the dynamic evolution of focal epilepsy using bifurcation analysis of a neural mass model, and relating these bifurcations to specific features of clinical data recordings in the time-domain. These findings are used to map out the evolution of seizures based on features of segments of the clinically recorded electroencephalograms. The similarity of seizure evolution within patients is tested. Statistically significant similarities were found between the evolutions of seizures from the same patient. In the latter half of the thesis a way of creating firing rate models is described, in which the value of the membrane time constant is dependent on the activity of afferent populations. This method is applied to modelling the basal ganglia (BG). The hypothesis that the BG are responsible for selection in the primate brain is tested and confirmed. The model is then used to investigate the development of PD. It was found that the loss of dopaminergic innervation caused a failure of selection capability but did not directly give rise to the beta oscillations ubiquitous in PD. Network connection strength changes that are seen in PD cause the model to regain selection functionality but lead to a beta frequency resting state oscillation, as is the case in real PD

Diagnosing links between atmospheric moisture and extreme daily precipitation over the UK

Atmospheric moisture characteristics associated with the heaviest 1% of daily rainfall events affecting regions of the British Isles are analysed over the period 1997–2008. A blended satellite/rain-gauge data set (GPCP-1DD) and regionally averaged daily rain-gauge observations (HadUKP) are combined with the ERA Interim reanalysis. These are compared with simulations from the HadGEM2-A climate model which applied observed sea surface temperature and realistic radiative forcings. Median extreme daily rainfall across the identified events and locations is larger for GPCP (32 mm day−1) than HadUKP and the simulations (∼25 mm day−1). The heaviest observed and simulated daily rainfall events are associated with increased specific humidity and horizontal transport of moisture (median 850 hPa specific humidity of ∼6 g kg−1 and vapour transport of ∼150 g kg−1 m s−1 for both observed and simulated events). Extreme daily rainfall events are less common during spring and summer across much of the British Isles, but in the south east region, they contribute up to 60% of the total number of distinct extreme daily rainfall events during these months. Compared to winter events, the summer events over south east Britain are associated with a greater magnitude and more southerly location of moisture maxima and less spatially extensive regions of enhanced moisture transport. This contrasting dependence of extreme daily rainfall on moisture characteristics implies a range of driving mechanisms that depend upon location and season. Higher spatial and temporal resolution data are required to explore these processes further, which is vital in assessing future projected changes in rainfall and associated flooding

Evidence for olivine deformation in kimberlites and other mantle-derived magmas during crustal emplacement

This paper highlights published and new field and petrographic observations for late-stage (crustal level) deformation associated with the emplacement of kimberlites and other mantle-derived magmas. Thus, radial and tangential joint sets in the competent 183 Ma Karoo basalt wall rocks to the 5 ha. Lemphane kimberlite blow in northern Lesotho have been ascribed to stresses linked to eruption of the kimberlite magma. Further examples of emplacement-related stresses in kimberlites are brittle fractures and close-spaced parallel shears which disrupt olivine macrocrysts. In each of these examples, there is no evidence of post-kimberlite regional tectonism which might explain these features, indicating that they reflect auto-deformation in the kimberlite during or immediately post-emplacement. On a microscopic scale, these inferred late-stage stresses are reflected by fractures and domains of undulose extinction which traverse core and margins of some euhedral and anhedral olivines in kimberlites and olivine melilitites. Undulose extinction and kink bands have also been documented in olivines in cumulates from layered igneous intrusions. Our observations thus indicate that these deformation features can form at shallow levels (crustal pressures), which is supported by experimental evidence. Undulose extinction and kink bands have previously been presented as conclusive evidence for a mantle provenance of the olivines—i.e. that they are xenocrysts. The observation that these deformation textures can form in both mantle and crustal environments implies that they do not provide reliable constraints on the provenance of the olivines. An understanding of the processes responsible for crustal deformation of kimberlites could potentially refine our understanding of kimberlite emplacement processes

Anthropogenic intensification of short-duration rainfall extremes

Short- duration (1-3 h) rainfall extremes can cause serious damage to societies through rapidly developing (flash) flooding and are determined by complex, multifaceted processes that are altering as Earth's climate warms. In this Review, we examine evidence from observational, theoretical and modelling studies for the intensification of these rainfall extremes, the drivers and the impact on flash flooding. Both short- duration and long- duration (\textgreater1 day) rainfall extremes are intensifying with warming at a rate consistent with the increase in atmospheric moisture (~7% K-1), while in some regions, increases in short- duration extreme rainfall intensities are stronger than expected from moisture increases alone. These stronger local increases are related to feedbacks in convective clouds, but their exact role is uncertain because of the very small scales involved. Future extreme rainfall intensification is also modulated by changes to temperature stratification and large- scale atmospheric circulation. The latter remains a major source of uncertainty. Intensification of short- duration extremes has likely increased the incidence of flash flooding at local scales and this can further compound with an increase in storm spatial footprint to considerably increase total event rainfall. These findings call for urgent climate change adaptation measures to manage increasing flood risks

Quantification of Fetal Renal Function Using Fetal Urine Production Rate and Its Reflection on the Amniotic and Fetal Creatinine Levels During Pregnancy

Adequate prediction of fetal exposure of drugs excreted by the kidney requires the incorporation of time-varying renal function parameters into a pharmacokinetic model. Published data on measurements of fetal urinary production rate (FUPR) and creatinine at various gestational ages were collected and integrated for prediction of the fetal glomerular filtration rate (GFR). The predicted GFR values were then compared to neonatal values recorded at birth. Collected data for FUPR across different gestational ages using both 3D (N = 517) and 2D (N = 845) ultrasound methods showed that 2D techniques yield significantly lower estimates of FUPR than 3D (p &amp;lt; 0.0001). A power law function was shown to best capture the change in FUPR with fetal age (FA) for both 2D (FUPR2D(mLmin)=0.000169  FA2.19); and 3D (FUPR3D (mLmin)= 3.21×10-7 FA4.21) data. The predicted FUPR based on the observed 3D data was shown to be strongly linearly related (R2 = 0.95) to measured values of amniotic creatinine concentration (N = 664). The FUPR3D data together with creatinine levels in the fetal urine and serum resulted in median predicted fetal GFR values of 0.47, 1.2, 2.5, and 4.9 ml/min at 23, 28, 33, and 38 weeks of fetal age (50% CV), respectively. These values are in good agreement with neonatal values observed immediately at birth. The derived FUPR and creatinine functions can be utilized to assess fetal renal maturation and predict fetal renal clearance.</jats:p