Teaching English tense and aspect with the help of cognitive grammar: An empirical study

Form-focused instruction is usually based on traditional practical/pedagogical grammar descriptions of grammatical features. The comparison of such traditional accounts with cognitive grammar (CG) descriptions seems to favor CG as a basis of pedagogical rules. This is due to the insistence of CG on the meaningfulness of grammar and its detailed analyses of the meanings of particular grammatical features. The differences between traditional and CG rules/descriptions are exemplified by juxtaposing the two kinds of principles concerning the use of the present simple and present progressive to refer to situations happening or existing at speech time. The descriptions provided the bases for the instructional treatment in a quasi-experimental study exploring the effectiveness of using CG descriptions of the two tenses, and of their interplay with stative (imperfective) and dynamic (perfective) verbs, and comparing this effectiveness with the value of grammar teaching relying on traditional accounts found in standard pedagogical grammars. The study involved 50 participants divided into three groups, with one of them constituting the control group and the other two being experimental ones. One of the latter received treatment based on CG descriptions and the other on traditional accounts. CG-based instruction was found to be at least moderately effective in terms of fostering mostly explicit grammatical knowledge and its effectiveness turned out be comparable to that of teaching based on traditional descriptions.

Freedom of the Spirit

sermon text; MS Word document

Neural Dynamics of Autistic Behaviors: Cognitive, Emotional, and Timing Substrates

What brain mechanisms underlie autism and how do they give rise to autistic behavioral symptoms? This article describes a neural model, called the iSTART model, which proposes how cognitive, emotional, timing, and motor processes may interact together to create and perpetuate autistic symptoms. These model processes were originally developed to explain data concerning how the brain controls normal behaviors. The iSTART model shows how autistic behavioral symptoms may arise from prescribed breakdowns in these brain processes.

From Parallel Sequence Representations to Calligraphic Control: A Conspiracy of Neural Circuits

Calligraphic writing presents a rich set of challenges to the human movement control system. These challenges include: initial learning, and recall from memory, of prescribed stroke sequences; critical timing of stroke onsets and durations; fine control of grip and contact forces; and letter-form invariance under voluntary size scaling, which entails fine control of stroke direction and amplitude during recruitment and derecruitment of musculoskeletal degrees of freedom. Experimental and computational studies in behavioral neuroscience have made rapid progress toward explaining the learning, planning and contTOl exercised in tasks that share features with calligraphic writing and drawing. This article summarizes computational neuroscience models and related neurobiological data that reveal critical operations spanning from parallel sequence representations to fine force control. Part one addresses stroke sequencing. It treats competitive queuing (CQ) models of sequence representation, performance, learning, and recall. Part two addresses letter size scaling and motor equivalence. It treats cursive handwriting models together with models in which sensory-motor tmnsformations are performed by circuits that learn inverse differential kinematic mappings. Part three addresses fine-grained control of timing and transient forces, by treating circuit models that learn to solve inverse dynamics problems.

The VITEWRITE Model of Handwriting Production

This article describes the VITEWRITE model for generating handwriting movements. The model consists of a sequential controller, or motor program, that interacts with a trajectory generator to move a hand with redundant degrees of freedom. The neural trajectory generator is the Vector Integration to Endpoint (VITE) model for synchronous variable-speed control of multijoint movements. VITE properties enable a simple control strategy to generate complex handwritten script if the hand model contains redundant degrees of freedom. The controller launches transient directional commands to independent hand synergies at times when the hand begins to move, or when a velocity peak in the outflow command to a given synergy occurs. The VITE model translates these temporally disjoint synergy commands into smooth curvilinear trajectories among temporally overlapping synergetic movements. Each synergy exhibits a unimodal velocity profile during any stroke, generates letters that are invariant under speed and size rescaling, and enables effortless connection of letter shapes into words. Speed and size rescaling are achieved by scalar GO and GRO signals that express computationally simple volitional commands. Psychophysical data such as the isochrony principle, asymmetric velocity profiles, and the two-thirds power law relating movement curvature and velocity arise as emergent properties of model interactions.

A Network for Learning Kinematics with Application to Human Reaching Models

A model for self-organization of the coordinate transformations required for spatial reaching is presented. During a motor babbling phase, a mapping from spatial coordinate directions to joint motion directions is learned. After learning, the model is able to produce straight-line spatial velocity trajectories with characteristic bell-shaped spatial velocity profiles, as observed in human reaches. Simulation results are presented for transverse plane reaching using a two degree-of-freedom arm.

Laminar Cortical Dynamics of Cognitive and Motor Working Memory, Sequence Learning and Performance: Toward a Unified Theory of How the Cerebral Cortex Works

How do the layered circuits of prefrontal and motor cortex carry out working memory storage, sequence learning, and voluntary sequential item selection and performance? A neural model called LIST PARSE is presented to explain and quantitatively simulate cognitive data about both immediate serial recall and free recall, including bowing of the serial position performance curves, error-type distributions, temporal limitations upon recall, and list length effects. The model also qualitatively explains cognitive effects related to attentional modulation, temporal grouping, variable presentation rates, phonemic similarity, presentation of non-words, word frequency/item familiarity and list strength, distracters and modality effects. In addition, the model quantitatively simulates neurophysiological data from the macaque prefrontal cortex obtained during sequential sensory-motor imitation and planned performance. The article further develops a theory concerning how the cerebral cortex works by showing how variations of the laminar circuits that have previously clarified how the visual cortex sees can also support cognitive processing of sequentially organized behaviors.

A Self-Organizing Neural Model of Motor Equivalent Reaching and Tool Use by a Multijoint Arm

This paper describes a self-organizing neural model for eye-hand coordination. Called the DIRECT model, it embodies a solution of the classical motor equivalence problem. Motor equivalence computations allow humans and other animals to flexibly employ an arm with more degrees of freedom than the space in which it moves to carry out spatially defined tasks under conditions that may require novel joint configurations. During a motor babbling phase, the model endogenously generates movement commands that activate the correlated visual, spatial, and motor information that are used to learn its internal coordinate transformations. After learning occurs, the model is capable of controlling reaching movements of the arm to prescribed spatial targets using many different combinations of joints. When allowed visual feedback, the model can automatically perform, without additional learning, reaches with tools of variable lengths, with clamped joints, with distortions of visual input by a prism, and with unexpected perturbations. These compensatory computations occur within a single accurate reaching movement. No corrective movements are needed. Blind reaches using internal feedback have also been simulated. The model achieves its competence by transforming visual information about target position and end effector position in 3-D space into a body-centered spatial representation of the direction in 3-D space that the end effector must move to contact the target. The spatial direction vector is adaptively transformed into a motor direction vector, which represents the joint rotations that move the end effector in the desired spatial direction from the present arm configuration. Properties of the model are compared with psychophysical data on human reaching movements, neurophysiological data on the tuning curves of neurons in the monkey motor cortex, and alternative models of movement control.

A Neural Network Model for Cursive Script Production

This article describes a neural network model, called the VITEWRITE model, for generating handwriting movements. The model consists of a sequential controller, or motor program, that interacts with a trajectory generator to move a. hand with redundant degrees of freedom. The neural trajectory generator is the Vector Integration to Endpoint (VITE) model for synchronous variable-speed control of multijoint movements. VITE properties enable a simple control strategy to generate complex handwritten script if the hand model contains redundant degrees of freedom. The proposed controller launches transient directional commands to independent hand synergies at times when the hand begins to move, or when a velocity peak in a given synergy is achieved. The VITE model translates these temporally disjoint synergy commands into smooth curvilinear trajectories among temporally overlapping synergetic movements. The separate "score" of onset times used in most prior models is hereby replaced by a self-scaling activity-released "motor program" that uses few memory resources, enables each synergy to exhibit a unimodal velocity profile during any stroke, generates letters that are invariant under speed and size rescaling, and enables effortless. connection of letter shapes into words. Speed and size rescaling are achieved by scalar GO and GRO signals that express computationally simple volitional commands. Psychophysical data concerning band movements, such as the isochrony principle, asymmetric velocity profiles, and the two-thirds power law relating movement curvature and velocity arise as emergent properties of model interactions.

Assessing the impulse control of violent offenders using computer-based cognitive performance tasks

The topic of this thesis is impulsivity. The meaning and measurement of impulse control is explored, with a particular focus on forensic settings. Impulsivity is central to many areas of psychology; it is one of the most common diagnostic criteria of mental disorders and is fundamental to the understanding of forensic personalities. Despite this widespread importance there is little agreement as to the definition or structure of impulsivity, and its measurement is fraught with difficulty owing to a reliance on self-report methods. This research aims to address this problem by investigating the viability of using simple computerised cognitive performance tasks as complementary components of a multi-method assessment strategy for impulse control. Ultimately, the usefulness of this measurement strategy for a forensic sample is assessed. Impulsivity is found to be a multifaceted construct comprised of a constellation of distinct sub-dimensions. Computerised cognitive performance tasks are valid and reliable measures that can assess impulsivity at a neuronal level. Self-report and performance task methods assess distinct components of impulse control and, for the optimal assessment of impulse control, a multi-method battery of self-report and performance task measures is advocated. Such a battery is shown to have demonstrated utility in a forensic sample, and recommendations for forensic assessment in the Irish context are discussed.

An investigation on the use of SNR distributions for the optimisation of coarse-fine spectrum sensing for cognitive radio

This thesis investigates the optimisation of Coarse-Fine (CF) spectrum sensing architectures under a distribution of SNRs for Dynamic Spectrum Access (DSA). Three different detector architectures are investigated: the Coarse-Sorting Fine Detector (CSFD), the Coarse-Deciding Fine Detector (CDFD) and the Hybrid Coarse-Fine Detector (HCFD). To date, the majority of the work on coarse-fine spectrum sensing for cognitive radio has focused on a single value for the SNR. This approach overlooks the key advantage that CF sensing has to offer, namely that high powered signals can be easily detected without extra signal processing. By considering a range of SNR values, the detector can be optimised more effectively and greater performance gains realised. This work considers the optimisation of CF spectrum sensing schemes where the security and performance are treated separately. Instead of optimising system performance at a single, constant, low SNR value, the system instead is optimised for the average operating conditions. The security is still provided such that at the low SNR values the safety specifications are met. By decoupling the security and performance, the system’s average performance increases whilst maintaining the protection of licensed users from harmful interference. The different architectures considered in this thesis are investigated in theory, simulation and physical implementation to provide a complete overview of the performance of each system. This thesis provides a method for estimating SNR distributions which is quick, accurate and relatively low cost. The CSFD is modelled and the characteristic equations are found for the CDFD scheme. The HCFD is introduced and optimisation schemes for all three architectures are proposed. Finally, using the Implementing Radio In Software (IRIS) test-bed to confirm simulation results, CF spectrum sensing is shown to be significantly quicker than naive methods, whilst still meeting the required interference probability rates and not requiring substantial receiver complexity increases.

Towards a cognitive neurobiology of brain-gut axis disorders

The past two decades have seen substantial gains in our understanding of the complex processes underlying disturbed brain-gut communication in disorders such as irritable bowel syndrome (IBS) and inflammatory bowel disease (IBD). Despite a growing understanding of the neurobiology of brain-gut axis dysfunction, there is a relative paucity of investigations into how the various factors involved in dysregulating the brain-gut axis, including stress, immune activation and pain, could impact on fundamental brain processes such as cognitive performance. To this end, we proposed a cognitive neurobiology of brain-gut axis dysfunction and took a novel approach to examine how disturbed brain-gut interactions may manifest as altered cognitive performance in IBS and IBD, both cross-sectionally and prospectively. We have demonstrated that, disorders of the brain-gut axis are characterised by stable deficits in specific cognitive domains. Specifically, patients with IBS exhibit a consistent hippocampal mediated visuospatial memory impairment. In addition we have found evidence to suggest a similar visuospatial impairment in IBD. However, our most consistent finding within this population was that patients with Crohn’s disease exhibit impaired selective attention/ response inhibition on the classic Stroop interference test. These cognitive deficits may serve to perpetuate and sustain brain-gut axis dysfunction. Furthermore, this research has shed light on some of the underlying neurobiological mechanisms that may be mediating cognitive dysfunction in IBS. Our findings may have significant implications for the individual who suffers from a brain-gut axis disorder and may also inform future treatment strategies. Taken together, these findings can be incorporated into existing neurobiological models of brain-gut axis dysfunction, to develop a more comprehensive model accounting for the cognitive-neurobiology of brain-gut axis disorders. This has furthered our understanding of disease pathophysiology and may ultimately aid in both the diagnosis and treatment of these highly prevalent, but poorly understood disorders.

Spinoza on method and freedom

The thesis as a whole argues that Spinoza’s Ethics in both method and content is aimed at the normal, partly rational person. Chapter 1 is on Spinoza’s writing style, finding that rather than being arid and technical, it aims to convince the reader by means of various rhetorical techniques, so does not assume an already rational reader. The following chapters of Part 1 examine whether the Ethics’ use of the synthetic geometric method exposes it to Descartes’ critique of that method in the “Second Replies” to his Meditations, that it is not suitable for pedagogy. This involves a consideration of the role of the TIE, finding in that early text not the analytic wing of a two-part analytic-synthetic method, but rather a defence and necessitation of a stand-alone synthetic method. Part 2 of the thesis develops this study of Spinoza’s writing for the common man to consider whether he is writing about the common man. This is done by examining one of the seemingly most abstract propositions in the Ethics, 4P72, which claims that a free man will not deceive even to save his own life. The study examines who exactly is this “free man” and what is his role in the Ethics. The study looks at the examples of free men in the TTP and at the concept of the model in the Ethics, and finds that rather than the free man being an impossible ideal which we can aim at but never achieve, everyone is free to some extent, and that even normal people are at times “the free man”.

The Quick Mild Cognitive Impairment (Qmci) screen: developing a new screening test for mild cognitive impairment and dementia

Introduction: Identifying mild cognitive impairment (MCI) is challenging. Few short instruments have sufficient sensitivity and specificity for use in busy clinical practice. This thesis explores the development, psychometric evaluation and validation of a new short (3–5 min) cognitive screening instrument, designed to screen for MCI and early dementia, called the Quick Mild Cognitive Impairment (Q