The role that choice of model plays in predictions for epilepsy surgery

This is the final version. Available on open access from Nature Research via the DOI in this recordMathematical modelling has been widely used to predict the effects of perturbations to brain networks. An important example is epilepsy surgery, where the perturbation in question is the removal of brain tissue in order to render the patient free of seizures. Different dynamical models have been proposed to represent transitions to ictal states in this context. However, our choice of which mathematical model to use to address this question relies on making assumptions regarding the mechanism that defines the transition from background to the seizure state. Since these mechanisms are unknown, it is important to understand how predictions from alternative dynamical descriptions compare. Herein we evaluate to what extent three different dynamical models provide consistent predictions for the effect of removing nodes from networks. We show that for small, directed, connected networks the three considered models provide consistent predictions. For larger networks, predictions are shown to be less consistent. However consistency is higher in networks that have sufficiently large differences in ictogenicity between nodes. We further demonstrate that heterogeneity in ictogenicity across nodes correlates with variability in the number of connections for each node.Engineering and Physical Sciences Research Council (EPSRC)Medical Research Council (MRC)Epilepsy Research UKWellcome Trus

Decision-making (in)flexibility in gambling disorder

Background: Behavioral flexibility –the ability to dynamically readjust our behavior in response to reward contingency changes– is often investigated using probabilistic reversal learning tasks (PRLT). Poor PRLT performance has been proposed as a proxy for compulsivity, and theorized to be related to perseverative gambling. Previous attempts to measure inflexibility with the PRLT in patients with gambling disorder have, however, used a variety of indices that may conflate inflexibility with more general aspects of performance in the task. Methods: Trial-by-trial PRLT acquisition and reacquisition curves in 84 treatment-seeking patients with gambling disorder and 64 controls (non-gamblers and non-problem recreational gamblers) were analyzed to distinguish between (a) variability in acquisition learning, and (b) reacquisition learning in reversed contingency phases. Complementarily, stay/switch responses throughout the task were analyzed to identify (c) premature switching, and (d) sensitivity to accumulated negative feedback. Results and interpretation: Even after controlling for differences in acquisition learning, patients were slower to readjust their behavior in reversed contingency phases, and were more prone to maintain their decisions despite accumulated negative feedback. Inflexibility in patients with gambling disorder is thus a robust phenomenon that could predate gambling escalation, or result from massive exposure to gambling activities.This work was supported by grants from the Spanish Government (PSI2017-85488-P: Ministerio de Economía y Competitividad, Secretaría de Estado de Investigación, Desarrollo e Innovación, Convocatoria 2017 de Proyectos I+ D de Excelencia, Spain, co-funded by the Fondo Europeo de Desarrollo Regional, FEDER, European Commission; and PSI2013-45055: Ministerio de Economía y Competitividad, Secretaría de Estado de Invetigación, Desarrollo e Innovación, Convocatoria 2013 de Proyectos I+ D de Excelencia). Additionally, JFN was supported by a grant from the Spanish Government (PSI2017-85159-P. Ministerio de Ciencia, Innovación y Universidades). Funding agencies had no role in the study design, collection, analysis or interpretation of the data, writing the manuscript, or the decision to submit the paper for publication

The effects of non-unity lewis numbers on turbulent premixed flame interactions in a twin V-flame configuration

The influence of Lewis number on turbulent premixed flame interactions is investigated using Automatic Feature Extraction (AFE) applied to high-resolution flame simulation data. Premixed turbulent twin V-flames under identical turbulence conditions are simulated at global Lewis numbers of 0.4, 0.8, 1.0 and 1.2. Information on the position, frequency and magnitude of the interactions is compared, and the sensitivity of the results to sample interval is discussed. It is found that both the frequency and magnitude of normal type interactions increases with decreasing Lewis number. Counter-normal type interactions become more likely as the Lewis number increases. The variation in both the frequency and the magnitude of the interactions is found to be caused by large-scale changes in flame wrinkling resulting from differences in the thermo-diffusive stability of the flames. During flame interactions thermo-diffusive effects are found to be insignificant due to the separation of time scales.EPSRC funding through grant number EP/F028741/1, and funding from Rolls-Royce is acknowledged.This is an Accepted Manuscript of an article published by Taylor & Francis in Combustion Science and Technology on 16 May 2013, available online: http://wwww.tandfonline.com/10.1080/00102202.2013.763801

The influence of incentives and survey design on mail survey response rates for mature consumers

The mail survey is still the preferred research tool for the mature consumer population and questions remain about ways of boosting survey response rates. The influence of two incentives were explored, a foil-wrapped tea bag and a $1 donation for each returned questionnaire in the study design. A significant higher response rate was only achieved for the first incentive. The effectiveness of a range of incentives and survey design features were investigated. Respondents indicated that their preferred incentive was a$500 donation to a charity. With the ongoing use of mail surveys almost mandatory for populations like this one, this study shows that incentives and design features such as CEO endorsement are important elements in improving response rates

Essays on issues in climate change policy

This thesis addresses three themes relating to climate change. The first is which types of fossil fuel to leave in the ground when they can differ in both their extraction cost and emissions rate. The analysis shows that without resource constraints there will always be use of at least one fossil fuel in the steady-state. With exhaustion constraints, any fossil fuel that has a lower extraction cost than the marginal cost of the backstop will be extracted in finite time regardless of the emissions rate. The only environmental consideration is the timing of extraction rather than leaving fossil fuel stock in the ground forever. The second theme is how altruistic concern of individuals for the well-being of others influences the socially optimal consumption levels and optimal emissions tax in a global context. If individuals have altruistic concern but believe that their consumption is negligible, they will not change their behaviour. However, non-cooperative governments maximising domestic welfare will internalise some of the damage inflicted on other countries depending on the level of altruistic concern individuals have and the cooperative optimum also changes as altruism leads individuals to effectively experience damage in other countries as well as the direct damage to them. Still, for behaviour to change, individuals need to make their decisions in a different way. The third chapter develops a new theory of moral behaviour whereby individuals balance the cost of not acting in their own self-interest against the hypothetical moral value of adopting a Kantian form of behaviour, asking what would happen if everyone else acted in the same way as they did. If individuals behave this way, then altruism matters and it may induce individuals to cut back their consumption. But nevertheless the optimal environmental tax is exactly the same as the standard Pigovian tax

Embodied cognition and executive functioning : the effect of whole body interaction on children's planning and inhibition

Modern user interfaces (UI) are becoming more ‘embodied’ as they facilitate bodily processes. Games consoles now often include body tracking hardware. Tenants of the theories of embodied cognition and executive function (EF) have stipulated that cognition is to some extent tied to the motor system, and so, that cognitive processing benefits from physical interaction. To date however, the research in this domain has focussed on adult populations. Ultimately, children are going to experience this UI revolution throughout the lifespan. So, in the following thesis I examined whether whole body interaction supported by a gaming floor mat improved children’s performance on a set of EF tasks. A set of new, gamified EF tasks were developed and completed using two interfaces (a floor mat and a keyboard) at separate sessions. The results revealed children were equally competent at each EF task using either device. Another notable finding was the effect of gamification on performance. The findings are discussed in the context of developmental psychology, experiment composition, and children’s interactions with technology

Causal inferential dynamic network analysis

In this dissertation I present developments in statistical methodologies that deal with interdependent data, i.e. data in which the units of observation are connected to each other resulting in a network of interdependence between them. Data considered interdependent poses a challenge to traditional statistical methodologies that assume units of observation to be independent and identically distributed. I focus on networks, and in particular social networks, as a tool to characterise these units of observation, called nodes, their observable attributes, and the connections between them. The developments in this dissertation are used to try to answer questions about the causal relationship between the observed variables, conditional on the network structure. In chapter 3 I present a causal analysis of the the Sexually Transmitted infections And Sexual Health (STASH) intervention and find that it had a positive effect of treatment (direct effect), but no effect of interference (effect of treatment spilling over to other individuals). I consider the methodology developed by Forastiere et al. (2020), as well as a flexible regression approach, to model the potential outcomes of the intervention for different levels of treatment and spillover, conditional on the joint propensity to be treated, directly and indirectly. Using a simulation study, I find that the proposed flexible approach has similar performance in terms of bias and uncertainty to the approach by Forastiere et al. (2020) when estimating the effect of the intervention, without the need for full information on the outcome model. In addition, our simulations suggest that regardless of methodology, estimation using a small sample produces larger uncertainty bounds. In chapter 4 I present a methodology to identify social influence and separate it from the effect of prior similarity in bipartite event cascades, when analysed using the relational event model (REM). The REM can be used to analyse the interdependent nature of data where the behaviour by an actor can be caused by the recent behaviour of similar actors (social influence). Homophily statistics can test for such contagion, given one or more actor attributes or network relations. However, social influence along the cascade, and independent but similar behaviour as a consequence of shared attributes, are generally confounded. Using Monte Carlo simulations, I show the limits of a randomisation test as a tool to distinguish from these two competing mechanisms (influence and prior similarities). The simulations, as well as an empirical example in political science, delineate the scope conditions of the randomisation inference test used and demonstrate its efficacy under different mixture regimes of influence and similarity. Chapter 5 presents a Bayesian methodology to estimate parameters for social networks using the exponential family of distributions via a network sampler that produces candidates in which both the connections between the nodes and their attributes are considered endogenous. Parameter estimation for networks with the exponential family is based on sampling networks candidates conditional on a fixed value of the parameter. Traditional estimation produces networks where only the connections between the nodes are switched to produce viable candidates. Fellows and Handcock (2012) developed a sampler that produces networks where both the connections and some nodal attributes are switched (toggled, as it is referred to in the literature) in order to generate viable samples. I propose using a Bayesian estimation routine with a sampler that also toggles node attributes and network connections, based on Caimo and Friel (2011)’s approach, to replace estimation using maximum likelihood, and produce samples from the posterior distribution for the parameter. This results in an estimating methodology that considers a data generating process in which networks are generated by changing edges and node attributes, and conditional on having a proper model, is less prone to produce degenerate results