The computational neurology of active vision

In this thesis, we appeal to recent developments in theoretical neurobiology – namely, active inference – to understand the active visual system and its disorders. Chapter 1 reviews the neurobiology of active vision. This introduces some of the key conceptual themes around attention and inference that recur through subsequent chapters. Chapter 2 provides a technical overview of active inference, and its interpretation in terms of message passing between populations of neurons. Chapter 3 applies the material in Chapter 2 to provide a computational characterisation of the oculomotor system. This deals with two key challenges in active vision: deciding where to look, and working out how to look there. The homology between this message passing and the brain networks solving these inference problems provide a basis for in silico lesion experiments, and an account of the aberrant neural computations that give rise to clinical oculomotor signs (including internuclear ophthalmoplegia). Chapter 4 picks up on the role of uncertainty resolution in deciding where to look, and examines the role of beliefs about the quality (or precision) of data in perceptual inference. We illustrate how abnormal prior beliefs influence inferences about uncertainty and give rise to neuromodulatory changes and visual hallucinatory phenomena (of the sort associated with synucleinopathies). We then demonstrate how synthetic pharmacological perturbations that alter these neuromodulatory systems give rise to the oculomotor changes associated with drugs acting upon these systems. Chapter 5 develops a model of visual neglect, using an oculomotor version of a line cancellation task. We then test a prediction of this model using magnetoencephalography and dynamic causal modelling. Chapter 6 concludes by situating the work in this thesis in the context of computational neurology. This illustrates how the variational principles used here to characterise the active visual system may be generalised to other sensorimotor systems and their disorders

Data Mining Techniques in Pharmacovigilance: Analysis of the Publicly Accessible FDA Adverse Event Reporting System (AERS)

Pharmacovigilance is a clinically oriented discipline, which may guide appropriate drug use through a balanced assessment of drug safety. Although much has been done in recent years, efforts are needed to expand the border of pharmacovigilance. We have provided insight into the FDA_Adverse Events Reporting Systems (FDA_AERS), a worldwide publicly available pharmacovigilance archive, to exemplify how to address major methodological issues. We believe that fostering discussion among researchers will increase transparency and facilitate definition of the most reliable approaches. By virtue of its large population coverage and free availability, the FDA_AERS has the potential to pave the way to a new way of looking to signal detection in PhV. Our key messages are: (1) before applying statistical tools (i.e., Data Mining Approaches - DMAs) to pharmacovigilance database for signal detection, all aspects related to data quality should be considered (e.g., drug mapping, missing data and duplicates); (2) at present, the choice of a given DMA mostly relies on local habits, expertise and attitude and there is room for improvement in this area; (3) DMA performance may be highly situation dependent; (4) over-reliance on these methods may have deleterious consequences, especially with the so-called "designated medical events", for which a case-by-case analysis is mandatory and complements disproportionality; and (5) the most appropriate selection of pharmacovigilance tools needs to be tailored to each situation, being mindful of the numerous biases and confounders that may influence performance and incremental utility of DMAs

Effectiveness of intensive physiotherapy for gait improvement in stroke: systematic review

Introduction: Stroke is one of the leading causes of functional disability worldwide. Approximately 80% of post-stroke subjects have motor changes. Improvement of gait pattern is one of the main objectives of physiotherapists intervention in these cases. The real challenge in the recovery of gait after stroke is to understand how the remaining neural networks can be modified, to be able to provide response strategies that compensate for the function of the affected structures. There is evidence that intensive training, including physiotherapy, positively influences neuroplasticity, improving mobility, pattern and gait velocity in post-stroke recovery. Objectives: Review and analyze in a systematic way the experimental studies (RCT) that evaluate the effects of Intensive Physiotherapy on gait improvement in poststroke subjects. Methodology: Were only included all RCT performed in humans, without any specific age, that had a clinical diagnosis of stroke at any stage of evolution, with sensorimotor deficits and functional gait changes. The databases used were: Pubmed, PEDro (Physiotherapy Evidence Database) and CENTRAL (Cochrane Center Register of Controlled Trials). Results: After the application of the criteria, there were 4 final studies that were included in the systematic review. 3 of the studies obtained a score of 8 on the PEDro scale and 1 obtained a score of 4. The fact that there is clinical and methodological heterogeneity in the studies evaluated, supports the realization of the current systematic narrative review, without meta-analysis. Discussion: Although the results obtained in the 4 studies are promising, it is important to note that the significant improvements that have been found, should be carefully considered since pilot studies with small samples, such as these, are not designed to test differences between groups, in terms of the effectiveness of the intervention applied. Conclusion: Intensive Physiotherapy seems to be safe and applicable in post-stroke subjects and there are indications that it is effective in improving gait, namely speed, travelled distance and spatiotemporal parameters. However, there is a need to develop more RCTs with larger samples and that evaluate the longterm resultsN/

The software-simulated airworld: anticipatory code and affective aeromobilities

This paper is concerned with the way in which airspaces are organised, managed, and understood by virtual representations - software simulations that are tested and used both preemptively and in real time. We suggest that, while airspaces are often understood as simulations themselves - models and blueprints for real-world futuresöthey are among the most mediated of all contemporary social environments, produced not only through code, but based on scenarios which predict and plan for future events - real virtualities that might come true. Drawing on historical and contemporary examples of aeronautical software simulation employed by civilian and military aviation, we explore how code has become increasingly sophisticated and ubiquitous in response to the challenges set by the mobilities the simulations model and the affective susceptibility of the corporeal body that uses them. The paper explores how software simulations work to structure and mediate behaviour by producing specific emotional and affective experiences in order to prepare the body for future encounters