988 resultados para context processing
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The amygdala plays a critical role in determining the emotional significance of sensory stimuli and the production of fear-related responses. Large amygdalar lesions have been shown to practically abolish innate defensiveness to a predator; however, it is not clear how the different amygdalar systems participate in the defensive response to a live predator. Our first aim was to provide a comprehensive analysis of the amygdalar activation pattern during exposure to a live cat and to a predator-associated context. Accordingly, exposure to a live predator up-regulated Fos expression in the medial amygdalar nucleus (MEA) and in the lateral and posterior basomedial nuclei, the former responding to predator-related pheromonal information and the latter two nuclei likely to integrate a wider array of predatory sensory information, ranging from olfactory to non-olfactory ones, such as visual and auditory sensory inputs. Next, we tested how the amygdalar nuclei most responsive to predator exposure (i.e. the medial, posterior basomedial and lateral amygdalar nuclei) and the central amygdalar nucleus (CEA) influence both unconditioned and contextual conditioned anti-predatory defensive behavior. Medial amygdalar nucleus lesions practically abolished defensive responses during cat exposure, whereas lesions of the posterior basomedial or lateral amygdalar nuclei reduced freezing and increased risk assessment displays (i.e. crouch sniff and stretch postures), a pattern of responses compatible with decreased defensiveness to predator stimuli. Moreover, the present findings suggest a role for the posterior basomedial and lateral amygdalar nuclei in the conditioning responses to a predator-related context. We have further shown that the CEA does not seem to be involved in either unconditioned or contextual conditioned anti-predatory responses. Overall, the present results help to clarify the amygdalar systems involved in processing predator-related sensory stimuli and how they influence the expression of unconditioned and contextual conditioned anti-predatory responses. (C) 2011 IBRO. Published by Elsevier Ltd. All rights reserved.
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A student from the Data Processing program at the New York Trade School is shown working. Black and white photograph with some edge damage due to writing in black along the top.
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Felice Gigante a graduate from the New York Trade School Electronics program works on a machine in his job as Data Processing Customer Engineer for the International Business Machines Corp. Original caption reads, "Felice Gigante - Electronices, International Business Machines Corp." Black and white photograph with caption glued to reverse.
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The goal of a research programme Evidence Algorithm is a development of an open system of automated proving that is able to accumulate mathematical knowledge and to prove theorems in a context of a self-contained mathematical text. By now, the first version of such a system called a System for Automated Deduction, SAD, is implemented in software. The system SAD possesses the following main features: mathematical texts are formalized using a specific formal language that is close to a natural language of mathematical publications; a proof search is based on special sequent-type calculi formalizing natural reasoning style, such as application of definitions and auxiliary propositions. These calculi also admit a separation of equality handling from deduction that gives an opportunity to integrate logical reasoning with symbolic calculation.
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The effectiveness of Cognitive Behavioral Therapy (CBT) for eating disorders has established a link between cognitive processes and unhealthy eating behaviors. However, the relationship between individual differences in unhealthy eating behaviors that are not related to clinical eating disorders, such as overeating and restrained eating, and the processing of food related verbal stimuli remains undetermined. Furthermore, the cognitive processes that promote unhealthy and healthy exercise patterns remain virtually unexplored by previous research. The present study compared individual differences in attitudes and behaviors around eating and exercise to responses to food and exercise-related words using a Lexical Decision Task (LDT). Participants were recruited from Colby (n = 61) and the greater Waterville community (n = 16). The results indicate the following trends in the data: Individuals who scored high in “thin ideal” responded faster to food-related words than individuals with low “thin Ideal” scores did. Regarding the exercise-related data, individuals who engage in more “low intensity exercise” responded faster to exercise-related words than individuals who engage in less “low intensity exercise” did. These findings suggest that cognitive schemata about food and exercise might mediate individual’s eating and exercise patterns.
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Hierarchical structure with nested nonlocal dependencies is a key feature of human language and can be identified theoretically in most pieces of tonal music. However, previous studies have argued against the perception of such structures in music. Here, we show processing of nonlocal dependencies in music. We presented chorales by J. S. Bach and modified versions inwhich the hierarchical structure was rendered irregular whereas the local structure was kept intact. Brain electric responses differed between regular and irregular hierarchical structures, in both musicians and nonmusicians. This finding indicates that, when listening to music, humans apply cognitive processes that are capable of dealing with longdistance dependencies resulting from hierarchically organized syntactic structures. Our results reveal that a brain mechanism fundamental for syntactic processing is engaged during the perception of music, indicating that processing of hierarchical structure with nested nonlocal dependencies is not just a key component of human language, but a multidomain capacity of human cognition.
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CONTEXTO E OBJETIVO: Crianças e adolescentes que vivem em situação de vulnerabilidade social apresentam uma série de problemas de saúde. Apesar disso, ainda é controversa a afirmação sobre a existência de alterações cognitivas e/ou sensoriais. O objetivo deste estudo foi investigar aspectos relacionados ao processamento auditivo, através da aplicação de testes de potencial evocado auditivo de tronco encefálico (PEATE) e avaliação comportamental do processamento auditivo em crianças em situação de rua, comparando a um grupo controle. TIPO DE ESTUDO E LOCAL: Estudo transversal no Laboratório de Processamento Auditivo, Faculdade de Medicina da Universidade de São Paulo. MÉTODOS: Os testes de processamento auditivo foram aplicados em um grupo de 27 indivíduos, subdivididos em grupos de 11 crianças (7 a 10 anos) e 16 adolescentes (11 a 16 anos) de ambos os sexos, em situação de vulnerabilidade social, e comparado a um grupo controle, formado por 21 crianças, subdivididas em grupos de 10 crianças e 11 adolescentes, pareados por idade, sem queixas. Também se aplicou os PEATE para investigação da integridade da via auditiva. RESULTADOS: Para ambas as faixas etárias, foram encontradas diferenças significantes entre grupos estudo e controle para a maioria dos testes aplicados, sendo que o grupo estudo apresentou desempenho estatisticamente pior do que o controle para todos os testes, exceto para o teste pediatric speech intelligibility. Apenas uma criança apresentou resultado alterado para os PEATE. CONCLUSÕES: Os resultados demonstraram pior desempenho do grupo estudo (crianças e adolescentes) para os testes comportamentais de processamento auditivo, apesar de estes apresentarem integridade da via auditiva em nível de tronco encefálico, demonstrada pela normalidade nos resultados do PEATE.
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A body of research has developed within the context of nonlinear signal and image processing that deals with the automatic, statistical design of digital window-based filters. Based on pairs of ideal and observed signals, a filter is designed in an effort to minimize the error between the ideal and filtered signals. The goodness of an optimal filter depends on the relation between the ideal and observed signals, but the goodness of a designed filter also depends on the amount of sample data from which it is designed. In order to lessen the design cost, a filter is often chosen from a given class of filters, thereby constraining the optimization and increasing the error of the optimal filter. To a great extent, the problem of filter design concerns striking the correct balance between the degree of constraint and the design cost. From a different perspective and in a different context, the problem of constraint versus sample size has been a major focus of study within the theory of pattern recognition. This paper discusses the design problem for nonlinear signal processing, shows how the issue naturally transitions into pattern recognition, and then provides a review of salient related pattern-recognition theory. In particular, it discusses classification rules, constrained classification, the Vapnik-Chervonenkis theory, and implications of that theory for morphological classifiers and neural networks. The paper closes by discussing some design approaches developed for nonlinear signal processing, and how the nature of these naturally lead to a decomposition of the error of a designed filter into a sum of the following components: the Bayes error of the unconstrained optimal filter, the cost of constraint, the cost of reducing complexity by compressing the original signal distribution, the design cost, and the contribution of prior knowledge to a decrease in the error. The main purpose of the paper is to present fundamental principles of pattern recognition theory within the framework of active research in nonlinear signal processing.
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Includes bibliography
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The post-processing of association rules is a difficult task, since a huge number of rules that are generated are of no interest to the user. To overcome this problem many approaches have been developed, such as objective measures and clustering. However, objective measures don't reduce nor organize the collection of rules, therefore making the understanding of the domain difficult. On the other hand, clustering doesn't reduce the exploration space nor direct the user to find interesting knowledge, therefore making the search for relevant knowledge not so easy. In this context this paper presents the PAR-COM methodology that, by combining clustering and objective measures, reduces the association rule exploration space directing the user to what is potentially interesting. An experimental study demonstrates the potential of PAR-COM to minimize the user's effort during the post-processing process. © 2012 Springer-Verlag.