Contributions of Dorsal/Ventral Hippocampus and Dorsolateral/Dorsomedial Striatum to Interval Timing

Humans and animals have remarkable capabilities in keeping time and using time as a guide to orient their learning and decision making. Psychophysical models of timing and time perception have been proposed for decades and have received behavioral, anatomical and pharmacological data support. However, despite numerous studies that aimed at delineating the neural underpinnings of interval timing, a complete picture of the neurobiological network of timing in the seconds-to-minutes range remains elusive. Based on classical interval timing protocols and proposing a Timing, Immersive Memory and Emotional Regulation (TIMER) test battery, the author investigates the contributions of the dorsal and ventral hippocampus as well as the dorsolateral and the dorsomedial striatum to interval timing by comparing timing performances in mice after they received cytotoxic lesions in the corresponding brain regions. On the other hand, a timing-based theoretical framework for the emergence of conscious experience that is closely related to the function of the claustrum is proposed so as to serve both biological guidance and the research and evolution of “strong” artificial intelligence. Finally, a new “Double Saturation Model of Interval Timing” that integrates the direct- and indirect- pathways of striatum is proposed to explain the set of empirical findings.

Learning and Exploiting Camera Geometry for Computer Vision

This work explores the use of statistical methods in describing and estimating camera poses, as well as the information feedback loop between camera pose and object detection. Surging development in robotics and computer vision has pushed the need for algorithms that infer, understand, and utilize information about the position and orientation of the sensor platforms when observing and/or interacting with their environment.

The first contribution of this thesis is the development of a set of statistical tools for representing and estimating the uncertainty in object poses. A distribution for representing the joint uncertainty over multiple object positions and orientations is described, called the mirrored normal-Bingham distribution. This distribution generalizes both the normal distribution in Euclidean space, and the Bingham distribution on the unit hypersphere. It is shown to inherit many of the convenient properties of these special cases: it is the maximum-entropy distribution with fixed second moment, and there is a generalized Laplace approximation whose result is the mirrored normal-Bingham distribution. This distribution and approximation method are demonstrated by deriving the analytical approximation to the wrapped-normal distribution. Further, it is shown how these tools can be used to represent the uncertainty in the result of a bundle adjustment problem.

Another application of these methods is illustrated as part of a novel camera pose estimation algorithm based on object detections. The autocalibration task is formulated as a bundle adjustment problem using prior distributions over the 3D points to enforce the objects' structure and their relationship with the scene geometry. This framework is very flexible and enables the use of off-the-shelf computational tools to solve specialized autocalibration problems. Its performance is evaluated using a pedestrian detector to provide head and foot location observations, and it proves much faster and potentially more accurate than existing methods.

Finally, the information feedback loop between object detection and camera pose estimation is closed by utilizing camera pose information to improve object detection in scenarios with significant perspective warping. Methods are presented that allow the inverse perspective mapping traditionally applied to images to be applied instead to features computed from those images. For the special case of HOG-like features, which are used by many modern object detection systems, these methods are shown to provide substantial performance benefits over unadapted detectors while achieving real-time frame rates, orders of magnitude faster than comparable image warping methods.

The statistical tools and algorithms presented here are especially promising for mobile cameras, providing the ability to autocalibrate and adapt to the camera pose in real time. In addition, these methods have wide-ranging potential applications in diverse areas of computer vision, robotics, and imaging.

Contributions Of the Human Medial Prefrontal Cortex To Associative Recognition Memory: Evidence From Functional Neuroimaging

Neuroimaging studies of episodic memory, or memory of events from our personal past, have predominantly focused their attention on medial temporal lobe (MTL). There is growing acknowledgement however, from the cognitive neuroscience of memory literature, that regions outside the MTL can support episodic memory processes. The medial prefrontal cortex is one such region garnering increasing interest from researchers. Using behavioral and functional magnetic resonance imaging measures, over two studies, this thesis provides evidence of a mnemonic role of the medial PFC. In the first study, participants were scanned while judging the extent to which they agreed or disagreed with the sociopolitical views of unfamiliar individuals. Behavioral tests of associative recognition revealed that participants remembered with high confidence viewpoints previously linked with judgments of strong agreement/disagreement. Neurally, the medial PFC mediated the interaction between high-confidence associative recognition memory and beliefs associated with strong agree/disagree judgments. In an effort to generalize this finding to well-established associative information, in the second study, we investigated associative recognition memory for real-world concepts. Object-scene pairs congruent or incongruent with a preexisting schema were presented to participants in a cued-recall paradigm. Behavioral tests of conceptual and perceptual recognition revealed memory enhancements arising from strong resonance between presented pairs and preexisting schemas. Neurally, the medial PFC tracked increases in visual recall of schema-congruent pairs whereas the MTL tracked increases in visual recall of schema-incongruent pairs. Additionally, ventral areas of the medial PFC tracked conceptual components of visual recall specifically for schema-congruent pairs. These findings are consistent with a recent theoretical proposal of medial PFC contributions to memory for schema-related content. Collectively, these studies provide evidence of a role for the medial PFC in associative recognition memory persisting for associative information deployed in our daily social interactions and for those associations formed over multiple learning episodes. Additionally, this set of findings advance our understanding of the cognitive contributions of the medial PFC beyond its canonical role in processes underlying social cognition.

What is social innovation? The paradigm shift and its relationship with Social Work

Innovation is a fundamental part of social work. In recent years there has been a shift in the innovation paradigm, making it easier to accept this relationship. National and supranational policies aimed at promoting innovation appear to be specifically guided by this idea. To be able to affirm this hypothesis, it is necessary to review the perception that social workers have of their duties. It is also useful to examine particular cases that show how such social innovation arises.

Non-conventional advertising formats in television versus spots: An analysis based on the generated recall

Advertising investment and audience figures indicate that television continues to lead as a mass advertising medium. However, its effectiveness is questioned due to problems such as zapping, saturation and audience fragmentation. This has favoured the development of non-conventional advertising formats. This study provides empirical evidence for the theoretical development. This investigation analyzes the recall generated by four non-conventional advertising formats in a real environment: short programme (branded content), television sponsorship, internal and external telepromotion versus the more conventional spot. The methodology employed has integrated secondary data with primary data from computer assisted telephone interviewing (CATI) were performed ad-hoc on a sample of 2000 individuals, aged 16 to 65, representative of the total television audience. Our findings show that non-conventional advertising formats are more effective at a cognitive level, as they generate higher levels of both unaided and aided recall, in all analyzed formats when compared to the spot.

Development and Evaluation of a Computer-Based, Self-Management Tool for People Recently Diagnosed with Type 2 Diabetes

Aim. The purpose of this study was to develop and evaluate a computer-based, dietary, and physical activity self-management program for people recently diagnosed with type 2 diabetes. 
Methods. The computer-based program was developed in conjunction with the target group and evaluated in a 12-week randomised controlled trial (RCT). Participants were randomised to the intervention (computer-program) or control group (usual care). Primary outcomes were diabetes knowledge and goal setting (ADKnowl questionnaire, Diabetes Obstacles Questionnaire (DOQ)) measured at baseline and week 12. User feedback on the program was obtained via a questionnaire and focus groups. Results. Seventy participants completed the 12-week RCT (32 intervention, 38 control, mean age 59 (SD) years). After completion there was a significant between-group difference in the “knowledge and beliefs scale” of the DOQ. Two-thirds of the intervention group rated the program as either good or very good, 92% would recommend the program to others, and 96% agreed that the information within the program was clear and easy to understand. 
Conclusions. The computer-program resulted in a small but statistically significant improvement in diet-related knowledge and user satisfaction was high. With some further development, this computer-based educational tool may be a useful adjunct to diabetes self-management.

Arteterapia em Idosos: efeitos nas funções cognitivas

Enquadramento: O envelhecimento abarca muitas transformações, desencadeando variadas mudanças do organismo, nomeadamente problemas cognitivos. A intervenção através da Arteterapia tem-se revelado eficaz na conservação do funcionamento das funções cognitivas dos idosos, sendo este um tema de extrema importância na manutenção da sua qualidade de vida. Objectivos: Identificar características sócio-demográficas da amostra; verificar se a Intervenção de arteterapia produz efeitos nas funções cognitivas dos idosos; verificar se estes efeitos correspondem a melhorias nas funções cognitivas. Métodos: A investigação adoptada é do tipo qualitativo, quase-experimental, (ensaio de Campo) sem grupo de controlo, que decorreu durante 3 meses (de Fevereiro a Abril de 2011), com sessões de 2 horas, três vezes por semana. Participaram no estudo 6 idosos institucionalizados, do sexo feminino com uma média de idades de 85 anos. Foi aplicado um questionário caracterizador da amostra, o Mini-Mental State Examination (MMSE) (adaptado à população portuguesa) para a avaliação das funções cognitivas gerais, assim como o Teste da Figura Complexa de Rey, para avaliação da percepção visual e memória. Resultados: Existe uma melhoria em todos os itens avaliados, quando comparados os resultados pré-teste e pós-teste. Em suma, verificamos que a média de respostas correctas em todos os testes aplicados, antes da intervenção foi de 52,9% e após a intervenção foi de 69,8%. Desta forma apuramos um aumento global de 16,9% de respostas correctas, após a intervenção Arteterapeutica. O item onde os participantes demonstraram maiores dificuldades no momento anterior à intervenção, foi no exercício de reprodução de memória na Figura complexa de Rey, e na Atenção e Calculo e na Habilidade Construtiva (MMSE). No entanto, após a intervenção, as maiores subidas verificadas foram precisamente nestes dois últimos itens mencionados (30% e 33,3%, respectivamente). / Background: The aging encompasses many changes, triggering the body's various changes, including cognitive problems. Intervention through Art Therapy has proved effective in preserving the functioning of the cognitive functions of elderly people, and this is an issue of utmost importance in maintaining their quality of life. Objectives: To identify socio-demographic characteristics of the sample, verify that the art therapy intervention effect on cognitive function of older persons; verify that these effects correspond to improvements in cognitive functions. Methods: The research adopted is a qualitative, quasi-experimental (test field) with no control group, which ran for three months (February to April 2011), with sessions of two hours, three times a week. This study analyzed six institutionalized elderly female with a mean age of 85 years. A questionnaire was given characterization of the sample, the Mini-Mental State Examination (MMSE) (adapted to the Portuguese population) for the assessment of general cognitive function, as well as the Test of Rey Complex Figure, for evaluation of visual perception and memory. Results: The analysis of the results allows us to verify that there is an improvement in all evaluated items, when comparing pretest and posttest. In summary, we found that the average of correct answers in all tests, before the intervention was 52.9% and after the intervention was 69.8%, verifying an overall increase of 16.9% of correct answers, after the intervention. The item where participants demonstrated greater difficulties at the moment before the intervention was playing in the exercise of memory in the Rey Complex Figure, and attention and calculation ability and Constructive (MMSE). However, after the intervention, the highest increases were observed especially in these last two items mentioned (30% and 33.3% respectively).

Infrared image enhancement based on hybrid-domain consideration and data fusion methods

Au cours des dernières décennies, l’effort sur les applications de capteurs infrarouges a largement progressé dans le monde. Mais, une certaine difficulté demeure, en ce qui concerne le fait que les objets ne sont pas assez clairs ou ne peuvent pas toujours être distingués facilement dans l’image obtenue pour la scène observée. L’amélioration de l’image infrarouge a joué un rôle important dans le développement de technologies de la vision infrarouge de l’ordinateur, le traitement de l’image et les essais non destructifs, etc. Cette thèse traite de la question des techniques d’amélioration de l’image infrarouge en deux aspects, y compris le traitement d’une seule image infrarouge dans le domaine hybride espacefréquence, et la fusion d’images infrarouges et visibles employant la technique du nonsubsampled Contourlet transformer (NSCT). La fusion d’images peut être considérée comme étant la poursuite de l’exploration du modèle d’amélioration de l’image unique infrarouge, alors qu’il combine les images infrarouges et visibles en une seule image pour représenter et améliorer toutes les informations utiles et les caractéristiques des images sources, car une seule image ne pouvait contenir tous les renseignements pertinents ou disponibles en raison de restrictions découlant de tout capteur unique de l’imagerie. Nous examinons et faisons une enquête concernant le développement de techniques d’amélioration d’images infrarouges, et ensuite nous nous consacrons à l’amélioration de l’image unique infrarouge, et nous proposons un schéma d’amélioration de domaine hybride avec une méthode d’évaluation floue de seuil amélioré, qui permet d’obtenir une qualité d’image supérieure et améliore la perception visuelle humaine. Les techniques de fusion d’images infrarouges et visibles sont établies à l’aide de la mise en oeuvre d’une mise en registre précise des images sources acquises par différents capteurs. L’algorithme SURF-RANSAC est appliqué pour la mise en registre tout au long des travaux de recherche, ce qui conduit à des images mises en registre de façon très précise et des bénéfices accrus pour le traitement de fusion. Pour les questions de fusion d’images infrarouges et visibles, une série d’approches avancées et efficaces sont proposés. Une méthode standard de fusion à base de NSCT multi-canal est présente comme référence pour les approches de fusion proposées suivantes. Une approche conjointe de fusion, impliquant l’Adaptive-Gaussian NSCT et la transformée en ondelettes (Wavelet Transform, WT) est propose, ce qui conduit à des résultats de fusion qui sont meilleurs que ceux obtenus avec les méthodes non-adaptatives générales. Une approche de fusion basée sur le NSCT employant la détection comprime (CS, compressed sensing) et de la variation totale (TV) à des coefficients d’échantillons clairsemés et effectuant la reconstruction de coefficients fusionnés de façon précise est proposée, qui obtient de bien meilleurs résultats de fusion par le biais d’une pré-amélioration de l’image infrarouge et en diminuant les informations redondantes des coefficients de fusion. Une procédure de fusion basée sur le NSCT utilisant une technique de détection rapide de rétrécissement itératif comprimé (fast iterative-shrinking compressed sensing, FISCS) est proposée pour compresser les coefficients décomposés et reconstruire les coefficients fusionnés dans le processus de fusion, qui conduit à de meilleurs résultats plus rapidement et d’une manière efficace.

Allusion and Cultural Memory in Late Antiquity: Ausonius, Prudentius, and Claudian

Thesis (Ph.D.)--University of Washington, 2016-08

Is Experts' Knowledge Modular?

This paper explores, both with empirical data and with computer simulations, the extent to which modularity characterises experts' knowledge. We discuss a replication of Chase and Simon's (1973) classic method of identifying 'chunks', i.e., perceptual patterns stored in memory and used as units. This method uses data about the placement of pairs of items in a memory task and consists of comparing latencies between these items and the number and type of relations they share. We then compare the human data with simulations carried out with CHREST, a computer model of perception and memory. We show that the model, based upon the acquisition of a large number of chunks, accounts for the human data well. This is taken as evidence that human knowledge is organised in a modular fashion.

RICH AND EFFICIENT VISUAL DATA REPRESENTATION

Increasing the size of training data in many computer vision tasks has shown to be very effective. Using large scale image datasets (e.g. ImageNet) with simple learning techniques (e.g. linear classifiers) one can achieve state-of-the-art performance in object recognition compared to sophisticated learning techniques on smaller image sets. Semantic search on visual data has become very popular. There are billions of images on the internet and the number is increasing every day. Dealing with large scale image sets is intense per se. They take a significant amount of memory that makes it impossible to process the images with complex algorithms on single CPU machines. Finding an efficient image representation can be a key to attack this problem. A representation being efficient is not enough for image understanding. It should be comprehensive and rich in carrying semantic information. In this proposal we develop an approach to computing binary codes that provide a rich and efficient image representation. We demonstrate several tasks in which binary features can be very effective. We show how binary features can speed up large scale image classification. We present learning techniques to learn the binary features from supervised image set (With different types of semantic supervision; class labels, textual descriptions). We propose several problems that are very important in finding and using efficient image representation.

The Scots in Ireland: culture, colonialism and memory, 1315-1826

This thesis examines three key moments in the intersecting histories of Scotland, Ireland and England, and their impact on literature. Chapter one Robert Bruce and the Last King of Ireland: Writing the Irish Invasion, 1315- 1826‘, is split into two parts. Part one, Barbour‘s (other) Bruce‘ focuses on John Barbour‘s The Bruce (1375) and its depiction of the Bruce‘s Irish campaign (1315-1318). It first examines the invasion material from the perspective of the existing Irish and Scottish relationship and their opposition to English authority. It highlights possible political and ideological motivations behind Barbour‘s negative portrait of Edward Bruce - whom Barbour presents as the catalyst for the invasion and the source of its carnage and ultimate failure - and his partisan comparison between Edward and his brother Robert I. It also probes the socio-polticial and ideological background to the Bruce and its depiction of the Irish campaign, in addition to Edward and Robert. It peers behind some of the Bruce‘s most lauded themes such as chivalry, heroism, loyalty, and patriotism, and exposes its militaristic feudal ideology, its propaganda rich rhetoric, and its illusions of freedom‘. Part one concludes with an examination of two of the Irish section‘s most marginalised figures, the Irish and a laundry woman. Part two, Cultural Memories of the Bruce Invasion of Ireland, 1375-1826‘, examines the cultural memory of the Bruce invasion in three literary works from the Medieval, Early Modern and Romantic periods. The first, and by far the most significant memorialisation of the invasion is Barbour‘s Bruce, which is positioned for the first time within the tradition of ars memoriae (art of memory) and present-day cultural memory theories. The Bruce is evaluated as a site of memory and Barbour‘s methods are compared with Icelandic literature of the same period. The recall of the invasion in late sixteenth century Anglo-Irish literature is then considered, specifically Edmund Spenser‘s A View of the State of Ireland, which is viewed in the context of contemporary Ulster politics. The final text to be considered is William Hamilton Drummond‘s Bruce’s Invasion of Ireland (1826). It is argued that Drummond‘s poem offers an alternative Irish version of the invasion; a counter-memory that responds to nineteenth-century British politics, in addition to the controversy surrounding the publication of the Ossian fragments. Chapter two, The Scots in Ulster: Policies, Proposals and Projects, 1551-1575‘, examines the struggle between Irish and Scottish Gaels and the English for dominance in north Ulster, and its impact on England‘s wider colonial ideology, strategy, literature and life writing. Part one entitled Noisy neighbours, 1551-1567‘ covers the deputyships of Sir James Croft, Sir Thomas Radcliffe, and Sir Henry Sidney, and examines English colonial writing during a crucial period when the Scots provoked an increase in militarisation in the region. Part two Devices, Advices, and Descriptions, 1567-1575‘, deals with the relationship between the Scots and Turlough O‘Neill, the influence of the 5th Earl of Argyll, and the rise of Sorley Boy MacDonnell. It proposes that a renewed Gaelic alliance hindered England‘s conquest of Ireland and generated numerous plantation proposals and projects for Ulster. Many of which exhibit a blurring‘ between the documentary and the literary; while all attest to the considerable impact of the Gaelic Scots in both motivating and frustrating various projects for that province, the most prominent of which were undertaken by Sir Thomas Smith in 1571 and Walter Devereux, 1st Earl of Essex in 1573.

Action and perception: Neural indices of learning in infants

Early human development offers a unique perspective in investigating the potential cognitive and social implications of action and perception. Specifically, during infancy, action production and action perception undergo foundational developments. One essential component to examine developments in action processing is the analysis of others’ actions as meaningful and goal-directed. Little research, however, has examined the underlying neural systems that may be associated with emerging action and perception abilities, and infants’ learning of goal-directed actions. The current study examines the mu rhythm—a brain oscillation found in the electroencephalogram (EEG)—that has been associated with action and perception. Specifically, the present work investigates whether the mu signal is related to 9-month-olds’ learning of a novel goal-directed means-end task. The findings of this study demonstrate a relation between variations in mu rhythm activity and infants’ ability to learn a novel goal-directed means-end action task (compared to a visual pattern learning task used as a comparison task). Additionally, we examined the relations between standardized assessments of early motor competence, infants’ ability to learn a novel goal-directed task, and mu rhythm activity. We found that: 1a) mu rhythm activity during observation of a grasp uniquely predicted infants’ learning on the cane training task, 1b) mu rhythm activity during observation and execution of a grasp did not uniquely predict infants’ learning on the visual pattern learning task (comparison learning task), 2) infants’ motor competence did not predict infants’ learning on the cane training task, 3) mu rhythm activity during observation and execution was not related to infants’ measure of motor competence, and 4) mu rhythm activity did not predict infants’ learning on the cane task above and beyond infants’ motor competence. The results from this study demonstrate that mu rhythm activity is a sensitive measure to detect individual differences in infants’ action and perception abilities, specifically their learning of a novel goal-directed action.

Comparative study of human age estimation based on hand-crafted and deep face features

In the past few years, human facial age estimation has drawn a lot of attention in the computer vision and pattern recognition communities because of its important applications in age-based image retrieval, security control and surveillance, biomet- rics, human-computer interaction (HCI) and social robotics. In connection with these investigations, estimating the age of a person from the numerical analysis of his/her face image is a relatively new topic. Also, in problems such as Image Classification the Deep Neural Networks have given the best results in some areas including age estimation. In this work we use three hand-crafted features as well as five deep features that can be obtained from pre-trained deep convolutional neural networks. We do a comparative study of the obtained age estimation results with these features.

MINING AND VERIFICATION OF TEMPORAL EVENTS WITH APPLICATIONS IN COMPUTER MICRO-ARCHITECTURE RESEARCH

Computer simulation programs are essential tools for scientists and engineers to understand a particular system of interest. As expected, the complexity of the software increases with the depth of the model used. In addition to the exigent demands of software engineering, verification of simulation programs is especially challenging because the models represented are complex and ridden with unknowns that will be discovered by developers in an iterative process. To manage such complexity, advanced verification techniques for continually matching the intended model to the implemented model are necessary. Therefore, the main goal of this research work is to design a useful verification and validation framework that is able to identify model representation errors and is applicable to generic simulators. The framework that was developed and implemented consists of two parts. The first part is First-Order Logic Constraint Specification Language (FOLCSL) that enables users to specify the invariants of a model under consideration. From the first-order logic specification, the FOLCSL translator automatically synthesizes a verification program that reads the event trace generated by a simulator and signals whether all invariants are respected. The second part consists of mining the temporal flow of events using a newly developed representation called State Flow Temporal Analysis Graph (SFTAG). While the first part seeks an assurance of implementation correctness by checking that the model invariants hold, the second part derives an extended model of the implementation and hence enables a deeper understanding of what was implemented. The main application studied in this work is the validation of the timing behavior of micro-architecture simulators. The study includes SFTAGs generated for a wide set of benchmark programs and their analysis using several artificial intelligence algorithms. This work improves the computer architecture research and verification processes as shown by the case studies and experiments that have been conducted.