A Solution of the Figure-ground Problem for Biological Vision

A neural network model of 3-D visual perception and figure-ground separation by visual cortex is introduced. The theory provides a unified explanation of how a 2-D image may generate a 3-D percept; how figures pop-out from cluttered backgrounds; how spatially sparse disparity cues can generate continuous surface representations at different perceived depths; how representations of occluded regions can be completed and recognized without usually being seen; how occluded regions can sometimes be seen during percepts of transparency; how high spatial frequency parts of an image may appear closer than low spatial frequency parts; how sharp targets are detected better against a figure and blurred targets are detector better against a background; how low spatial frequency parts of an image may be fused while high spatial frequency parts are rivalrous; how sparse blue cones can generate vivid blue surface percepts; how 3-D neon color spreading, visual phantoms, and tissue contrast percepts are generated; how conjunctions of color-and-depth may rapidly pop-out during visual search. These explanations arise derived from an ecological analysis of how monocularly viewed parts of an image inherit the appropriate depth from contiguous binocularly viewed parts, as during DaVinci stereopsis. The model predicts the functional role and ordering of multiple interactions within and between the two parvocellular processing streams that join LGN to prestriate area V4. Interactions from cells representing larger scales and disparities to cells representing smaller scales and disparities are of particular importance.

Normal and Amnesis Learning, Recognition, and Memory by a Neural Model of Cortico-Hippocampal Interactions

The processes by which humans and other primates learn to recognize objects have been the subject of many models. Processes such as learning, categorization, attention, memory search, expectation, and novelty detection work together at different stages to realize object recognition. In this article, Gail Carpenter and Stephen Grossberg describe one such model class (Adaptive Resonance Theory, ART) and discuss how its structure and function might relate to known neurological learning and memory processes, such as how inferotemporal cortex can recognize both specialized and abstract information, and how medial temporal amnesia may be caused by lesions in the hippocampal formation. The model also suggests how hippocampal and inferotemporal processing may be linked during recognition learning.

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.

The role of the IL-1 type 1 receptor in the life, death and differentiation of adult hippocampal neural precursor cells

Neurogenesis occurs in two distinct regions of the adult brain; the subgranular zone (SGZ) of the dentate gyrus (DG) in the hippocampus, and the subventricular zone (SVZ) lining the lateral ventricles. It is now well-known that adult hippocampal neurogenesis can be modulated by a number of intrinsic and extrinsic factors e.g. local signalling molecules, exercise, environmental enrichment and learning. Moreover, levels of adult hippocampal neurogenesis decrease with age, at least in rodents, and alterations in hippocampal neurogenesis have been reported in animal models and human studies of neuropsychiatric and neurodegenerative conditions. Neuroinflammation is a common pathological feature of these conditions and is also a potent modulator of adult hippocampal neurogenesis. Recently, the orphan nuclear receptor TLX has been identified as an important regulator of adult hippocampal neurogenesis as its expression is necessary to maintain the neural precursor cell (NPC) pool in the adult DG. Likewise, exposure of animals to voluntary exercise has been consistently demonstrated to promote adult hippocampal neurogenesis. Lentivirus (LV)- mediated gene transfer is a useful tool to elucidate gene function and to explore potential therapeutic candidates across an array of conditions as it facilitates sustained gene expression in both dividing and post-mitotic cell populations. Both intrinsic and extrinsic factors are important regulators of adult hippocampal neurogenesis. Examining how these factors are affected by an inflammatory stimulus, and the subsequent effects on adult hippocampal neurogenesis provides important information for the development of novel treatment strategies for neuropsychiatric and neurodegenerative conditions in which adult hippocampal neurogenesis is impaired. The aims of the series of experiments presented in this thesis were to examine the effect of the pro-inflammatory cytokine interleukin-1β (IL-1β) on adult hippocampal NPCs both in vitro and in vivo. In vitro, we have shown that IL-1β reduces proliferation of adult hippocampal NPCs in a dose and time-dependent manner. In addition, we have demonstrated that TLX expression is reduced by IL-1β. Blockade of IL-1β signalling prevented both the IL-1β-induced reduction in cell proliferation and TLX expression. In vivo, we examined the effect of short term and long term exposure to LV-IL-1β in sedentary mice and in mice exposed to voluntary running. We demonstrated that impaired hippocampal neurogenesis is only evident after long term exposure to IL-1β. In mice exposed to voluntary running, hippocampal neurogenesis is significantly increased following short-term but not long-term exposure to running. Moreover, short-term running effectively prevents any IL-1β-induced effects on hippocampal neurogenesis; however, no such effects are seen following long-term exposure to running.

Representations of Catholicism in selected works by Colm Tóibín

The aim of this thesis is to provide an original and extensive study of Colm Tóibín as the “secular revisionist who acknowledges Catholicism as an enduring element of Irish society” (Ryan, Ireland and Scotland 251). Tóibín is uniquely placed to interpret many aspects of Ireland in the latter half of the twentieth century and I will argue that intertwined with his revisionism of Irish history is a reimagining of Ireland and Catholicism in fictive terms. An extensive amount of material from Tóibín’s time as a journalist and travel writer will feature in my research because it validates my argument concerning his prolonged engagement with Catholicism. Similarly, a broad range of Tóibín’s prose will be studied because it affords opportunities for an exploration of a literary Catholic oeuvre in his fiction. Therefore, I am emphasizing that a crucial linkage of Catholicism is identifiable throughout Tóibín’s diverse canon of work. However, I will argue that divergences of attitude and mode can be found in how Tóibín depicts Catholicism in his journalism and fiction. My argument identifies Tóibín’s recurrent journalistic questioning of the Church’s teaching and leadership but I classify a benignity towards Catholicism in his travel writing and fiction. Overall, Tóibín’s fiction merits significant status in this thesis because of the representations of Catholicism in the work of a writer who has been short-listed three times for The Booker Prize.

Renal failure and the neural control of the kidney

Renal failure (RF) is associated with an over activation of the sympathetic nervous system. The aim of this thesis was to investigate the hypothesis that as the kidney progresses into RF there is an inappropriate and sustained activation of renal afferent nerves which results in a dysregulation of basal RSNA and reflexly controlled RSNA by the high and low pressure baroreceptors. Baroreflex gain curves for both RSNA and HR were generated in control and RF rats. This study clearly showed a blunted high-pressure baroreflex in RF rats, an impairment which was almost completely corrected by bilateral renal denervation. The integrity of the low-pressure cardiopulmonary receptors to inhibit RSNA was investigated using acute saline volume. Again, a blunted reflex sympatho-inhibition of RSNA was observed, which was corrected by renal denervation. Finally a functional study to examine how the renal excretory response to volume expansion differed in RF was carried out. This study revealed an impairment of the low-pressure baroreflex control of the sympathetic outflow. The result of these studies suggest that cisplatin induced RF initiates a neural signal from within the kidney, which over rides the normal reflex regulation of RSNA by the high and low – pressure baroreceptors and that this impairment in function can be normalised by renal denervation. This raises further questions as to the mechanisms involved in the afferent over activation arising from the diseased kidneys.

Locating the transnational: representations and aesthetics of the city in contemporary European cinemas

This thesis focuses on two Western European cinematic cities, and two unique periods of their respective nations’ histories, in a bid to “locate” the transnational within a contemporary European milieu. I argue that my geo-cinematic case studies are emblematic of broader questions of the problematics of national identity in contemporary Europe in the face of cross-national flows yet, as a result of their representations as cities both “anchored” and “in flux”, they reject a European postnational identity. Through its engagement with cinematic Rome as the “Eternal City” of Europe and cinematic Dublin as the “newly Europeanised” city, my thesis traces how representations and aesthetics of the urban spaces of these two cities correspond with the tensions at the heart of the respective eras in question. Via the figures that inhabit it, navigate it and search for it, the city is utilised to highlight fixity and mobility, centrality and dislocation, in explicit and implicit ways, amid the rapidly changing landscape of its national terrain. It is through my analyses of the filmed places and sociopolitical, socioeconomic and sociocultural spaces of these capital cities under the rubric of the transnational that this research demonstrates the “pluralities” of the construct in its cinematic manifestations. It is also my aim to evaluate the concept of cinematic transnationalism when identifying and accounting for representations of a specific national, historical timeframe, when the momentousness of the changes that occur is not bound by the national, but rather is reflective of the influence of both domestic and external forces. To this end, my thesis draws attention to instances in which the nation is shown to persist and resist dilution, arguing that it is only against the backdrop and continuity of the nation (in its evershifting guises) that the transnational can be conceived in representative and aesthetic terms.

Identifying novel molecular mechanisms of ghrelin receptor signalling underlying neural control of food intake: interaction with stress and impulsivity

The gut-hormone, ghrelin, activates the centrally expressed growth hormone secretagogue 1a (GHS-R1a) receptor, or ghrelin receptor. The ghrelin receptor is a G-protein coupled receptor (GPCR) expressed in several brain regions, including the arcuate nucleus (Arc), lateral hypothalamus (LH), ventral tegmental area (VTA), nucleus accumbens (NAcc) and amygdala. Activation of the GHS-R1a mediates a multitude of biological activities, including release of growth hormone and food intake. The ghrelin signalling system also plays a key role in the hedonic aspects of food intake and activates the dopaminergic mesolimbic circuit involved in reward signalling. Recently, ghrelin has been shown to be involved in mediating a stress response and to mediate stress-induced food reward behaviour via its interaction with the HPA-axis at the level of the anterior pituitary. Here, we focus on the role of the GHS-R1a receptor in reward behaviour, including the motivation to eat, its anxiogenic effects, and its role in impulsive behaviour. We investigate the functional selectivity and pharmacology of GHS-R1a receptor ligands as well as crosstalk of the GHS-R1a receptor with the serotonin 2C (5-HT2C) receptor, which represent another major target in the regulation of eating behaviour, stress-sensitivity and impulse control disorders. We demonstrate, to our knowledge for the first time, the direct impact of GHS-R1a signalling on impulsive responding in a 2-choice serial reaction time task (2CSRTT) and show a role for the 5-HT2C receptor in modulating amphetamine-associated impulsive action. Finally, we investigate differential gene expression patterns in the mesocorticolimbic pathway, specifically in the NAcc and PFC, between innate low- and high-impulsive rats. Together, these findings are poised to have important implications in the development of novel treatment strategies to combat eating disorders, including obesity and binge eating disorders as well as impulse control disorders, including, substance abuse and addiction, attention deficit hyperactivity disorder (ADHD) and mood disorders.

Neural network analysis identifies scaffold properties necessary for in vitro chondrogenesis in elastin-like polypeptide biopolymer scaffolds.

The successful design of biomaterial scaffolds for articular cartilage tissue engineering requires an understanding of the impact of combinations of material formulation parameters on diverse and competing functional outcomes of biomaterial performance. This study sought to explore the use of a type of unsupervised artificial network, a self-organizing map, to identify relationships between scaffold formulation parameters (crosslink density, molecular weight, and concentration) and 11 such outcomes (including mechanical properties, matrix accumulation, metabolite usage and production, and histological appearance) for scaffolds formed from crosslinked elastin-like polypeptide (ELP) hydrogels. The artificial neural network recognized patterns in functional outcomes and provided a set of relationships between ELP formulation parameters and measured outcomes. Mapping resulted in the best mean separation amongst neurons for mechanical properties and pointed to crosslink density as the strongest predictor of most outcomes, followed by ELP concentration. The map also grouped formulations together that simultaneously resulted in the highest values for matrix production, greatest changes in metabolite consumption or production, and highest histological scores, indicating that the network was able to recognize patterns amongst diverse measurement outcomes. These results demonstrated the utility of artificial neural network tools for recognizing relationships in systems with competing parameters, toward the goal of optimizing and accelerating the design of biomaterial scaffolds for articular cartilage tissue engineering.

Differential Apaf-1 levels allow cytochrome c to induce apoptosis in brain tumors but not in normal neural tissues.

Brain tumors are typically resistant to conventional chemotherapeutics, most of which initiate apoptosis upstream of mitochondrial cytochrome c release. In this study, we demonstrate that directly activating apoptosis downstream of the mitochondria, with cytosolic cytochrome c, kills brain tumor cells but not normal brain tissue. Specifically, cytosolic cytochrome c is sufficient to induce apoptosis in glioblastoma and medulloblastoma cell lines. In contrast, primary neurons from the cerebellum and cortex are remarkably resistant to cytosolic cytochrome c. Importantly, tumor tissue from mouse models of both high-grade astrocytoma and medulloblastoma display hypersensitivity to cytochrome c when compared with surrounding brain tissue. This differential sensitivity to cytochrome c is attributed to high Apaf-1 levels in the tumor tissue compared with low Apaf-1 levels in the adjacent brain tissue. These differences in Apaf-1 abundance correlate with differences in the levels of E2F1, a previously identified activator of Apaf-1 transcription. ChIP assays reveal that E2F1 binds the Apaf-1 promoter specifically in tumor tissue, suggesting that E2F1 contributes to the expression of Apaf-1 in brain tumors. Together, these results demonstrate an unexpected sensitivity of brain tumors to postmitochondrial induction of apoptosis. Moreover, they raise the possibility that this phenomenon could be exploited therapeutically to selectively kill brain cancer cells while sparing the surrounding brain parenchyma.

Imaging Learned Song Representations in Populations of Sensorimotor Neurons Essential to Vocal Communication

Perceiving or producing complex vocalizations such as speech and birdsongs require the coordinated activity of neuronal populations, and these activity patterns can vary over space and time. How learned communication signals are represented by populations of sensorimotor neurons essential to vocal perception and production remains poorly understood. Using a combination of two-photon calcium imaging, intracellular electrophysiological recording and retrograde tracing methods in anesthetized adult male zebra finches (Taeniopygia guttata), I addressed how the bird's own song and its component syllables are represented by the spatiotemporal patterns of activity of two spatially intermingled populations of projection neurons (PNs) in HVC, a sensorimotor area required for song perception and production. These experiments revealed that neighboring PNs can respond at markedly different times to song playback and that different syllables activate spatially intermingled HVC PNs within a small region. Moreover, noise correlation analysis reveals enhanced functional connectivity between PNs that respond most strongly to the same syllable and also provides evidence of a spatial gradient of functional connectivity specific to PNs that project to song motor nucleus (i.e. HVC_RA cells). These findings support a model in which syllabic and temporal features of song are represented by spatially intermingled PNs functionally organized into cell- and syllable-type networks.

Computational inference of neural information flow networks.

Determining how information flows along anatomical brain pathways is a fundamental requirement for understanding how animals perceive their environments, learn, and behave. Attempts to reveal such neural information flow have been made using linear computational methods, but neural interactions are known to be nonlinear. Here, we demonstrate that a dynamic Bayesian network (DBN) inference algorithm we originally developed to infer nonlinear transcriptional regulatory networks from gene expression data collected with microarrays is also successful at inferring nonlinear neural information flow networks from electrophysiology data collected with microelectrode arrays. The inferred networks we recover from the songbird auditory pathway are correctly restricted to a subset of known anatomical paths, are consistent with timing of the system, and reveal both the importance of reciprocal feedback in auditory processing and greater information flow to higher-order auditory areas when birds hear natural as opposed to synthetic sounds. A linear method applied to the same data incorrectly produces networks with information flow to non-neural tissue and over paths known not to exist. To our knowledge, this study represents the first biologically validated demonstration of an algorithm to successfully infer neural information flow networks.

A neural biomarker of psychological vulnerability to future life stress.

We all experience a host of common life stressors such as the death of a family member, medical illness, and financial uncertainty. While most of us are resilient to such stressors, continuing to function normally, for a subset of individuals, experiencing these stressors increases the likelihood of developing treatment-resistant, chronic psychological problems, including depression and anxiety. It is thus paramount to identify predictive markers of risk, particularly those reflecting fundamental biological processes that can be targets for intervention and prevention. Using data from a longitudinal study of 340 healthy young adults, we demonstrate that individual differences in threat-related amygdala reactivity predict psychological vulnerability to life stress occurring as much as 1 to 4 years later. These results highlight a readily assayed biomarker, threat-related amygdala reactivity, which predicts psychological vulnerability to commonly experienced stressors and represents a discrete target for intervention and prevention.

Neural networks supporting autobiographical memory retrieval in posttraumatic stress disorder.

Posttraumatic stress disorder (PTSD) affects the functional recruitment and connectivity between neural regions during autobiographical memory (AM) retrieval that overlap with default and control networks. Whether such univariate changes relate to potential differences in the contributions of the large-scale neural networks supporting cognition in PTSD is unknown. In the present functional MRI study, we employed independent-component analysis to examine the influence of the engagement of neural networks during the recall of personal memories in a PTSD group (15 participants) as compared to non-trauma-exposed healthy controls (14 participants). We found that the PTSD group recruited similar neural networks when compared to the controls during AM recall, including default-network subsystems and control networks, but group differences emerged in the spatial and temporal characteristics of these networks. First, we found spatial differences in the contributions of the anterior and posterior midline across the networks, and of the amygdala in particular, for the medial temporal subsystem of the default network. Second, we found temporal differences within the medial prefrontal subsystem of the default network, with less temporal coupling of this network during AM retrieval in PTSD relative to controls. These findings suggest that the spatial and temporal characteristics of the default and control networks potentially differ in a PTSD group versus healthy controls and contribute to altered recall of personal memory.