Neural models of inter-cortical networks in the primate visual system for navigation, attention, path perception, and static and kinetic figure-ground perception

Vision provides the primary means by which many animals distinguish foreground objects from their background and coordinate locomotion through complex environments. The present thesis focuses on mechanisms within the visual system that afford figure-ground segregation and self-motion perception. These processes are modeled as emergent outcomes of dynamical interactions among neural populations in several brain areas. This dissertation specifies and simulates how border-ownership signals emerge in cortex, and how the medial superior temporal area (MSTd) represents path of travel and heading, in the presence of independently moving objects (IMOs). Neurons in visual cortex that signal border-ownership, the perception that a border belongs to a figure and not its background, have been identified but the underlying mechanisms have been unclear. A model is presented that demonstrates that inter-areal interactions across model visual areas V1-V2-V4 afford border-ownership signals similar to those reported in electrophysiology for visual displays containing figures defined by luminance contrast. Competition between model neurons with different receptive field sizes is crucial for reconciling the occlusion of one object by another. The model is extended to determine border-ownership when object borders are kinetically-defined, and to detect the location and size of shapes, despite the curvature of their boundary contours. Navigation in the real world requires humans to travel along curved paths. Many perceptual models have been proposed that focus on heading, which specifies the direction of travel along straight paths, but not on path curvature. In primates, MSTd has been implicated in heading perception. A model of V1, medial temporal area (MT), and MSTd is developed herein that demonstrates how MSTd neurons can simultaneously encode path curvature and heading. Human judgments of heading are accurate in rigid environments, but are biased in the presence of IMOs. The model presented here explains the bias through recurrent connectivity in MSTd and avoids the use of differential motion detectors which, although used in existing models to discount the motion of an IMO relative to its background, is not biologically plausible. Reported modulation of the MSTd population due to attention is explained through competitive dynamics between subpopulations responding to bottom-up and top- down signals

The multidimensional spectrum of imagination: Images, Dreams, Hallucinations, and Active, Imaginative Perception.

A theory of the structure and cognitive function of the human imagination that attempts to do justice to traditional intuitions about its psychological centrality is developed, largely through a detailed critique of the theory propounded by Colin McGinn. Like McGinn, I eschew the highly deflationary views of imagination, common amongst analytical philosophers, that treat it either as a conceptually incoherent notion, or as psychologically trivial. However, McGinn fails to develop his alternative account satisfactorily because (following Reid, Wittgenstein and Sartre) he draws an excessively sharp, qualitative distinction between imagination and perception, and because of his flawed, empirically ungrounded conception of hallucination. His arguments in defense of these views are rebutted in detail, and the traditional, passive, Cartesian view of visual perception, upon which several of them implicitly rely, is criticized in the light of findings from recent cognitive science and neuroscience. It is also argued that the apparent intuitiveness of the passive view of visual perception is a result of mere historical contingency. An understanding of perception (informed by modern visual science) as an inherently active process enables us to unify our accounts of perception, mental imagery, dreaming, hallucination, creativity, and other aspects of imagination within a single coherent theoretical framework

MS FT-2-2 7 Orthogonal polynomials and quadrature: Theory, computation, and applications

Quadrature rules find many applications in science and engineering. Their analysis is a classical area of applied mathematics and continues to attract considerable attention. This seminar brings together speakers with expertise in a large variety of quadrature rules. It is the aim of the seminar to provide an overview of recent developments in the analysis of quadrature rules. The computation of error estimates and novel applications also are described

Generalized averaged Gaussian quadrature and applications

A simple numerical method for constructing the optimal generalized averaged Gaussian quadrature formulas will be presented. These formulas exist in many cases in which real positive GaussKronrod formulas do not exist, and can be used as an adequate alternative in order to estimate the error of a Gaussian rule. We also investigate the conditions under which the optimal averaged Gaussian quadrature formulas and their truncated variants are internal

A novel parametric scale for determining rehabilitation progress in the upper limb

PhD ThesisThe process of sensorimotor rehabilitation depends upon the clinical condition, age and circumstances of the patient and is unlikely to be continuous or predictable in nature. Mapping progress in conditions such as stroke, cerebral palsy and traumatic brain injury relies upon a variety of qualitative assessments, each resulting in different scales of measurement. Most current assessments are elaborate, specific to certain participants and/or stages of a condition, and subject to inter-rater and intra-rater variability. A simple and reliable measuring system is required that can capture rehabilitation progress from an initial state through to complete rehabilitation. It must be believable, flexible, understandable and accessible if the patient is to benefit from its use. Two-dimensional reaching tasks reflect movements made in typical therapies and activities of daily living. This thesis hypothesises that valuable parameters exist within positional and temporal data gathered from simple reaching tasks. Such parameters should be able to identify movement quality and hence measure state and progress during rehabilitation. They should correlate well with a variety of clinical scales to be meaningful and, as quantifiable measurands, they should be extendable beyond the range of established clinical scales. This thesis proposes a novel solution for the assessment of upper limb rehabilitation. An affordable desktop computer assessment system was developed and used with juvenile patient participants (N=11) to compare simple desktop reaching parameters with a clinical scale. A control group of normal juvenile participants (N=10) provided baseline data. The results indicated good correlation with the clinical scale based upon a weighted combination of pre-selected movement parameters. The methodology developed permits assessment against further clinical scales and additional participant groups allowing rapid, accurate, reliable and extendable assessments. The potential for mass data acquisition from clinical and domestic settings is identified to support the development of further assessments and, potentially, new therapies to address limited therapist availability and innovative treatments

Urban Informatics

This open access book is the first to systematically introduce the principles of urban informatics and its application to every aspect of the city that involves its functioning, control, management, and future planning. It introduces new models and tools being developed to understand and implement these technologies that enable cities to function more efficiently – to become ‘smart’ and ‘sustainable’. The smart city has quickly emerged as computers have become ever smaller to the point where they can be embedded into the very fabric of the city, as well as being central to new ways in which the population can communicate and act. When cities are wired in this way, they have the potential to become sentient and responsive, generating massive streams of ‘big’ data in real time as well as providing immense opportunities for extracting new forms of urban data through crowdsourcing. This book offers a comprehensive review of the methods that form the core of urban informatics from various kinds of urban remote sensing to new approaches to machine learning and statistical modelling. It provides a detailed technical introduction to the wide array of tools information scientists need to develop the key urban analytics that are fundamental to learning about the smart city, and it outlines ways in which these tools can be used to inform design and policy so that cities can become more efficient with a greater concern for environment and equity