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

Pharmacological Fingerprints of Contextual Uncertainty

Successful interaction with the environment requires flexible updating of our beliefs about the world. By estimating the likelihood of future events, it is possible to prepare appropriate actions in advance and execute fast, accurate motor responses. According to theoretical proposals, agents track the variability arising from changing environments by computing various forms of uncertainty. Several neuromodulators have been linked to uncertainty signalling, but comprehensive empirical characterisation of their relative contributions to perceptual belief updating, and to the selection of motor responses, is lacking. Here we assess the roles of noradrenaline, acetylcholine, and dopamine within a single, unified computational framework of uncertainty. Using pharmacological interventions in a sample of 128 healthy human volunteers and a hierarchical Bayesian learning model, we characterise the influences of noradrenergic, cholinergic, and dopaminergic receptor antagonism on individual computations of uncertainty during a probabilistic serial reaction time task. We propose that noradrenaline influences learning of uncertain events arising from unexpected changes in the environment. In contrast, acetylcholine balances attribution of uncertainty to chance fluctuations within an environmental context, defined by a stable set of probabilistic associations, or to gross environmental violations following a contextual switch. Dopamine supports the use of uncertainty representations to engender fast, adaptive responses. \ua9 2016 Marshall et al

Somatic salience and sensory precision in persistent depression

Persistent depression is a debilitating health condition with a poor prognosis even in the context of current gold-standard pharmacological and psychological interventions. A better understanding of the mechanisms contributing to its maintenance is needed to facilitate the development of more targeted psychological interventions. Bayesian predictive processing models of depression propose that negative emotional and physiological outcomes arise in depressive illness as a result of disturbed interoceptive precision estimation in depressed individuals; however, evidence from the clinical and cognitive neuroscience literatures suggests the hypothesis that sensory precision is attenuated in persistent depression across sensory modalities in general. A series of studies was designed to index sensory precision across somatic and auditory modalities and to identify the level at which any disruption manifested in persistently-depressed participants relative to controls. Study 1 (Chapter 3) measured baseline signal discriminability under conditions of focused attention. Study 2 (Chapter 4) measured the impact of failures of voluntary attention on signal discriminability. Study 3 (Chapter 5) used a simulation approach to model sensory precision in the first two studies and to identify mechanisms which could successfully predict the data. Studies 4 (Chapter 6) and 5 (Chapter 7) measured attentional capture by task-irrelevant and predictive sensory cues respectively. Study 6 (Chapter 8) partially replicated Studies 4 and 5 and used the resulting data to estimate the group-level sensory precision and salience parameters of a predictive processing model of precision optimization. The results suggest that sensory precision is attenuated in persistent depression across sensory modalities, and that this attenuation results from disturbances of voluntary and involuntary attention rather than baseline perceptual sensitivity. Under conditions of voluntary attention, reduced sensory precision may result from efforts at resource conservation; and under conditions of involuntary attentional capture, it may be related to a loss of target discriminability and salience. Conversely, the bottom-up salience of somatic stimuli was uniquely enhanced among depressed participants and was predicted by high anxiety and by low interoceptive sensibility. These findings open up new avenues for investigation of the mechanisms underlying persistent forms of depression, and have direct implications for clinical practice with respect to psychological intervention.Medical Research Council Studentshi

The Terror Network Industrial Complex: A Measurement and Analysis of Terrorist Networks and War Stocks

This paper presents a measurement study and analysis of the structure of multiple Islamic terrorist networks to determine if similar characteristics exist between those networks. We examine data gathered from four terrorist groups: Al-Qaeda, ISIS, Lashkar-e-Taiba (LeT) and Jemaah Islamiyah (JI) consisting of six terror networks. Our study contains 471 terrorists’ nodes and 2078 links. Each terror network is compared in terms efficiency, communication and composition of network metrics. The paper examines the effects these terrorist attacks had on US aerospace and defence stocks (herein War stocks). We found that the Islamic terror groups increase recruitment during the planned attacks, communication increases during and after the attacks between the subordinate terrorists and low density is a common feature of Islamic terrorist groups. The Al- Qaeda organisation structure was the most complex and superior in terms of secrecy, diameter, clustering, modularity and density. Jemaah Islamiyah followed a similar structure but not as superior. The ISIS and LeT organisational structures were more concerned with the efficiency of the operation rather than secrecy. We found that war stocks prices and the S+P 500 were lower the day after the attacks, however, the war stocks slightly outperformed the S+P 500 the day after the attacks. Further, we found that war stock prices were significantly lower one month after the terrorist attacks but the S+P 500 rebounded one month later

Egocentric Chunking in the Predictive Brain : A Cognitive Basis of Expert Performance in High-Speed Sports

Publisher Copyright: Copyright © 2022 Lappi. First publication by Frontiers Media.What principles and mechanisms allow humans to encode complex 3D information, and how can it be so fast, so accurately and so flexibly transformed into coordinated action? How do these processes work when developed to the limit of human physiological and cognitive capacity—as they are in high-speed sports, such as alpine skiing or motor racing? High-speed sports present not only physical challenges, but present some of the biggest perceptual-cognitive demands for the brain. The skill of these elite athletes is in many ways an attractive model for studying human performance “in the wild”, and its neurocognitive basis. This article presents a framework theory for how these abilities may be realized in high-speed sports. It draws on a careful analysis of the case of the motorsport athlete, as well as theoretical concepts from: (1) cognitive neuroscience of wayfinding, steering, and driving; (2) cognitive psychology of expertise; (3) cognitive modeling and machine learning; (4) human-in-the loop modellling in vehicle system dynamics and human performance engineering; (5) experimental research (in the laboratory and in the field) on human visual guidance. The distinctive contribution is the way these are integrated, and the concept of chunking is used in a novel way to analyze a high-speed sport. The mechanisms invoked are domain-general, and not specific to motorsport or the use of a particular type of vehicle (or any vehicle for that matter); the egocentric chunking hypothesis should therefore apply to any dynamic task that requires similar core skills. It offers a framework for neuroscientists, psychologists, engineers, and computer scientists working in the field of expert sports performance, and may be useful in translating fundamental research into theory-based insight and recommendations for improving real-world elite performance. Specific experimental predictions and applicability of the hypotheses to other sports are discussed.Peer reviewe

Promethean and Posthuman Freedom: Brassier on Improvisation and Time

Ray Brassier's "Unfree Improvisation/Compulsive Freedom" (written for the 2013 collaboration with Basque noise artist Mattin at Glasgow's Tramway) is a terse but insightful discussion of the notion of freedom in improvisation. He argues that we should view freedom not as the determination of an act from outside the causal order, but as the reflective self-determination by action within the causal order. This requires a system that acts in conformity to rules but can represent and modify these rules with implications for its future behaviour.Brassier does not provide a detailed account of how self-determination works in improvisation. His text implies that the act of improvisation involves an encounter between rule-governed rationality and idiomatic patterns or causes but does not specify how such rules operate in music, what their nature is or how the encounter between rules and more rudimentary “pattern-governed” behaviour occurs.I will argue that, in any case, there are no such rules to be had. Instead, claims about what is permissible or implied in musical processes index highly-context sensitive perceptual and affective responses to musical events. I develop this picture in the light of recent accounts of predictive processing and active inference in cognitive science.This account provides an alternate way of expressing Brassier’s remarks on the relationship between music and history in “Unfree Improvisation” one that eschews normative discourse in favour of an ontology of social and biological assemblages, their affects, and the processes they entrain.This adjustment is of more than aesthetic interest. Brassier’s text suggests that the temporality of the improvising act models an insurgent relation to time: specifically, the remorseless temporality explored in his writings on Prometheanism and Radical Enlightenment. I will conclude by using use this analogy to elaborate the idea of a posthuman agency adapted to a hypermodern milieu of self-augmenting technological change

Spatial Updating in Human Cortex

Single neurons in several cortical areas in monkeys update visual information in conjunction with eye movements. This remapping of stimulus representations is thought to contribute to spatial constancy. The central hypothesis here is that spatial updating also occurs in humans and that it can be visualized with functional MRI.In Chapter 2, we describe experiments in which we tested the role of human parietal cortex in spatial updating. We scanned subjects during a task that involved remapping of visual signals across hemifields. This task is directly analogous to the single-step saccade task used to test spatial updating in monkeys. We observed an initial response in the hemisphere contralateral to the visual stimulus, followed by a remapped response in the hemisphere ipsilateral to the stimulus. Our results demonstrate that updating of visual information occurs in human parietal cortex and can be visualized with fMRI.The experiments in Chapter 2 show that updated visual responses have a characteristic latency and response shape. Chapter 3 describes a statistical model for estimating these parameters. The method is based on a nonlinear, fully Bayesian, hierarchical model that decomposes the fMRI time series data into baseline, smooth drift, activation signal, and noise. This chapter shows that this model performs well relative to commonly-used general linear models. In Chapter 4, we use the statistical method described in Chapter 3 to test for the presence of spatial updating activity in human extrastriate visual cortex. We identified the borders of several retinotopically defined visual areas in the occipital lobe. We then tested for spatial updating using the single step saccade task. We found a roughly monotonic relationship between the strength of updating activity and position in the visual area hierarchy. We observed the strongest responses in area V4, and the weakest response in V1. We conclude that updating is not restricted to brain regions involved primarily in attention and the generation of eye movements, but rather, is present in occipital lobe visual areas as well

Mathematics

The inherent complexity of criminal behaviour means that it is not a topic to which the field of mathematics has traditionally been thought to apply. In recent years, however, the study of crime has mirrored that of several other social phenomena in attracting increased attention from within the mathematical community. As well as being facilitated by a dramatic revolution in data availability, this has largely been driven by the growth of mathematical tools designed to confront the challenges presented by such systems; an approach encapsulated by the term ‘complexity science’. This chapter outlines the ways in which mathematical approaches can contribute to the understanding of crime, with particular emphasis on the role of modelling in offering insight into the mechanisms underlying criminal phenomena. A number of mathematical approaches are reviewed in this context, including dynamical systems theory, network science and game theory. Following this, previous research of this type on a number of criminological topics is reviewed, before the chapter concludes by considering the outlook for work in this area and some key issues which remain to be resolved