Backwards is the way forward: feedback in the cortical hierarchy predicts the expected future

Clark offers a powerful description of the brain as a prediction machine, which offers progress on two distinct levels. First, on an abstract conceptual level, it provides a unifying framework for perception, action, and cognition (including subdivisions such as attention, expectation, and imagination). Second, hierarchical prediction offers progress on a concrete descriptive level for testing and constraining conceptual elements and mechanisms of predictive coding models (estimation of predictions, prediction errors, and internal models)

A RISK-INFORMED DECISION-MAKING METHODOLOGY TO IMPROVE LIQUID ROCKET ENGINE PROGRAM TRADEOFFS

This work provides a risk-informed decision-making methodology to improve liquid rocket engine program tradeoffs with the conflicting areas of concern affordability, reliability, and initial operational capability (IOC) by taking into account psychological and economic theories in combination with reliability engineering. Technical program risks are associated with the number of predicted failures of the test-analyze-and-fix (TAAF) cycle that is based on the maturity of the engine components. Financial and schedule program risks are associated with the epistemic uncertainty of the models that determine the measures of effectiveness in the three areas of concern. The affordability and IOC models' inputs reflect non-technical and technical factors such as team experience, design scope, technology readiness level, and manufacturing readiness level. The reliability model introduces the Reliability- As-an-Independent-Variable (RAIV) strategy that aggregates fictitious or actual hotfire tests of testing profiles that differ from the actual mission profile to estimate the system reliability. The main RAIV strategy inputs are the physical or functional architecture of the system, the principal test plan strategy, a stated reliability-bycredibility requirement, and the failure mechanisms that define the reliable life of the system components. The results of the RAIV strategy, which are the number of hardware sets and number of hot-fire tests, are used as inputs to the affordability and the IOC models. Satisficing within each tradeoff is attained by maximizing the weighted sum of the normalized areas of concern subject to constraints that are based on the decision-maker's targets and uncertainty about the affordability, reliability, and IOC using genetic algorithms. In the planning stage of an engine program, the decision variables of the genetic algorithm correspond to fictitious hot-fire tests that include TAAF cycle failures. In the program execution stage, the RAIV strategy is used as reliability growth planning, tracking, and projection model. The main contributions of this work are the development of a comprehensible and consistent risk-informed tradeoff framework, the RAIV strategy that links affordability and reliability, a strategy to define an industry or government standard or guideline for liquid rocket engine hot-fire test plans, and an alternative to the U.S. Crow/AMSAA reliability growth model applying the RAIV strategy

Attention is more than prediction precision [Commentary on target article]

A cornerstone of the target article is that, in a predictive coding framework, attention can be modelled by weighting prediction error with a measure of precision. We argue that this is not a complete explanation, especially in the light of ERP (event-related potentials) data showing large evoked responses for frequently presented target stimuli, which thus are predicted

Markov chain Monte Carlo analyses of longitudinal biomedical magnetic resonance data

Markov chain Monte Carlo simulation was used in an analysis of the data acquired in three longitudinal biomedical magnetic resonance studies. The first of these investigations uses a Bayesian nonlinear hierarchical random coefficients model to examine the longitudinal extracellular direct current (DC) potential and apparent diffusion coefficient (ADC) responses to focal ischaemia in the rat. The purpose is to perform a formal analysis of the temporal relationship between the two responses, and thus to examine the data for compatibility with a common latent (driving) process and, alternatively, the existence of an ADC threshold for anoxic depolarisation. The DC-potential and ADC transition parameter posterior probability distributions were generated, paying particular attention to the within-subject differences between the DC-potential and ADC transition characteristics. The results indicate that the DC-potential and ADC changes are not driven by a common latent process and, in addition, provide no evidence for a consistent ADC threshold associated with anoxic depolarisation. The second analysis uses data acquired in a nuclear magnetic resonance spectroscopic study into the effects of intestinal ischaemia and subsequent reperfusion on liver metabolism in the rat. The purpose of the analysis is to examine the temporal relationship between energy status [inorganic phosphate to adenosine triphosphate ratio (PAR)] and the pH response, the former of which is an indicator of liver energy failure. The posterior distribution obtained for the PAR-pH onset time difference indicates that the pH response precedes the change in PAR, suggesting that intracellular acidosis cannot be ruled out as a contributing factor to the observed liver failure. The third dataset was acquired in an electron spin resonance study of the Arrhenius behaviour of the rabbit muscle sarcoplasmic reticulum membrane. An MCMC Arrhenius plot changepoint analysis is used to estimate the order parameter 'transition' temperature

Biological Mechanisms Linking Stress and Anhedonia

Evidence from research across species suggests that stress exposure is linked with anhedonia (loss of pleasure and/or decreased motivation). However, the mechanisms through which stress might impact anhedonia remain unclear. Chapters 1 and 2 of this dissertation review putative etiological pathways from stress to anhedonia and discuss stressor characteristics that could inform experimental models of stress-induced anhedonia. Chapter 3 describes an attempt to identify which types of stress are most associated with anhedonia using stress interview data from multiple datasets. Unexpectedly, we found no credible effects on anhedonic symptoms for stressor chronicity, severity, dependence on behavior, or interpersonal focus. Instead, number of stressors endorsed was the best predictor of anhedonic symptoms. Next, Chapters 4 and 5 report on two studies that tested possible biological mediators of the stress-anhedonia link. Chapter 4 describes an analysis of the UK Biobank dataset aimed at evaluating frontostriatal functional connectivity as a mechanism of stress-induced anhedonia. Although stress exposure predicted anhedonia, analyses uncovered no stable relation between frontostriatal connectivity and anhedonia, and no support for the proposed mediation model. Chapter 5 details a study that implemented a laboratory-based stressor to assess its potential impact on motivated behavior (thought to be a key component of anhedonia), and whether any such effects might be mediated by inflammatory responding. Low concentrations of salivary cytokines suggested questionable validity of inflammatory assessment, and no effect of stress on inflammatory responding was observed. Additionally, stress produced no measurable changes in motivated behavior. Thus, analyses revealed no evidence consistent with inflammation as a mechanism of stress-induced anhedonia. Finally, Chapter 6 discusses conclusions and implications of the current findings, and provides ideas for future directions

Towards a New Ontology of Polling Inaccuracy: The Benefits of Conceiving of Elections as Heterogenous Phenomena for the Study of Pre-election Polling Error

A puzzle exists at the heart of pre-election polling. Despite continual methodological improvement and repeated attempts to identify and correct issues laid bare by misprediction, average polling accuracy has not notably improved since the conclusion of the Second World War. In this thesis, I contend that this is the result of a poll-level focus within the study of polling error that is both incommensurate with its evolution over time and the nature of the elections that polls seek to predict. I hold that differences between elections stand as a plausible source of polling error and situate them within a novel four-level model of sources of polling error. By establishing the heterogenous nature of elections as phenomena and its expected impact on polling error, I propose a new election-level ontology through which the inaccuracy of polls can be understood. I test the empirical validity of this new ontology by using a novel multi-level model to analyse error across the most expansive polling dataset assembled to date, encompassing 11,832 in-campaign polls conducted in 497 elections across 83 countries, finding that membership within different elections meaningfully impacts polling error variation. With the empirical validity of my proposed ontology established, I engage in an exploratory analysis of its benefits, finding electoral characteristics to be useful in the prediction of polling error. Ultimately, I conclude that the adoption of a new, multi-level ontology of polling error centred on the importance of electoral heterogeneity not only offers a more comprehensive theoretical account of its sources than current understandings, but is also more specifically tailored to the reality of pre-election polling than existing alternatives. I also contend that it offers pronounced practical benefits, illuminating those circumstances in which polling error is likely to vary

Epidemiological studies of bovine digital dermatitis in pasture-based dairy system in New Zealand : a thesis presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Veterinary Sciences at Massey University, Palmerston North, New Zealand

Listed in 2020 Dean's List of Exceptional ThesesAppendices 1, 2, 3, 6 & 7 were removed for copyright reasons, but the published articles may be accessed via the following links: Appendix 1. Farm level risk factors for bovine digital dermatitis in Taranaki, New Zealand: An analysis using a Bayesian hurdle model https://doi.org/10.1016/j.tvjl.2018.02.012 Appendix 2. Effects of climate and farm management practices on bovine digital dermatitis in spring-calving pasture-based dairy farms in Taranaki, New Zealand https://doi.org/10.1016/j.tvjl.2019.03.004 Appendix 3. Estimating the herd and cow level prevalence of bovine digital dermatitis on New Zealand dairy farms: A Bayesian superpopulation approach https://doi.org/10.1016/j.prevetmed.2019.02.014 Appendix 6. Inter-observer agreement between two observers for bovine digital dermatitis identification in New Zealand using digital photographs https://doi.org/10.1080/00480169.2019.1582369 Appendix 7. Detecting bovine digital dermatitis in the milking parlour: To wash or not to wash, a Bayesian superpopulation approach https://doi.org/10.1016/j.tvjl.2019.02.011Bovine digital dermatitis (BDD) is an infectious disease of the feet of cattle. Worldwide, it is one of the most commonly observed foot diseases on many dairy farms, and is the most important infectious cause of lameness in cattle in confined dairy system. Although BDD is generally less common in pasture-based dairy system it can still cause significant production losses and welfare issues, in such systems. This thesis contains seven original research works covering the epidemiological aspects of BDD in pasture-based cattle in New Zealand. Firstly, cross-sectional and longitudinal data obtained from Taranaki were analysed to identify the factors (including climate) associated with the disease. This was followed by a large scale cross-sectional study covering four regions in New Zealand looking at the prevalence of and risk factors for BDD. A longitudinal study was then undertaken on three farms in order to collect disease data (including BDD lesion type) over a lactation. Using this dataset, a deterministic compartment model was built to study the transmission dynamics of BDD within a dairy herd in New Zealand. Along with these large studies, two small validation studies were also carried out. The first study evaluated the agreement between two trained BDD observers in determining BDD presence/ absence in digital photographs, while the second one evaluated the reliability of clinical examination of BDD lesions in the milking parlour without prior washing of the animals’ feet. This work suggests that BDD has spread widely across New Zealand, although it has yet to reach the West Coast. In the four regions where BDD was identified, true between herd prevalences varied by region (from ~ 40% to > 65%). Furthermore, although BDD was found in many herds, true cow level prevalence was low in all affected regions, being generally less than 4% in affected herds. Several biosecurity related management practices were repeatedly identified as factors associated with increased BDD prevalence at both the herd and cow level. These included mixing heifers with animals from other properties; purchasing heifers for replacement and using outside staff to treat lame cows. In addition to the identified management practices, climate (rainfall and soil temperature) was also found to have had a significant association with the prevalence of BDD. These studies used examination in the milking parlour as the method of identifying BDD lesions. This method while the best method of lesion detection for large scale studies is not perfect. It generally requires that feet are washed prior to examination, as lesions masked by dirt are difficult to identify. Our study quantified the effect, under New Zealand conditions, of feet washing prior to examination finding sensitivities of 0.34 (95% credible interval [CrI]: 0.088-0.69) and 0.63 (95%CrI: 0.46- 0.78) for pre- and post-washing, respectively. There was a 93.95% probability that the sensitivity of examination post-washing was greater than that prewashing. Limited information on the reliability of examination in the milking parlour prompted comparison of two trained observers using digital photographs. Agreement between the two observers was good; we could be 75% sure that the two observers had almost perfect agreement and 95% sure the two observers had at least substantial agreement. It is crucial that since examination in the milking parlour is not a perfect reference test for detecting BDD lesions that when estimating prevalence, the sensitivity and specificity of this method is factored into the analysis. This is often achieved using an approach based on the binomial distribution. However, as the dairy herd is a finite population and the sampling of animals for BDD lesion is effectively sampling without replacement, the correct distribution to use is the hypergeometric one. This is computationally complex so the Bayesian superpopulation approach was developed to allow continued use of the binomial distribution. The superpopulation approach was used to estimate prevalence in this thesis, one of the first uses of this approach in the veterinary field. The appearance of BDD in New Zealand is different from that elsewhere. Most lesion have been observed are small grey, rubbery lesions which may or may not have thickened, darker edges. Less commonly larger, more proliferative lesions can also be found. Red active lesions are extremely rare. Post-treatment lesions are not a feature of the disease in New Zealand as lesions are treated only very rarely. Thus modelling approach used a BDD score system which focuses on early stage of BDD. This found that in infected dairy herds, although BDD prevalence will tend to increase year-on-year it is likely to remain relatively low (<18%) even after 10 years of within-herd transmission. It is likely that the low transmission rate during the late lactation (model assumption) results in more cases resolving than developing during this period and therefore results in the low prevalence of infectious cattle at the start of each subsequent lactation. Cattle with larger, more proliferative lesions had a stronger influence on the establishment and maintenance of DD than cattle with small lesions highlighting the importance of targeting these animals for intervention

Modern Bayesian Modeling to Solve Common but Complex Clinical and Epidemiological Problems in Ophthalmology

Ph.DDOCTOR OF PHILOSOPH