927 resultados para Norton-Simon hypothesis
Resumo:
- Background Following Kapur’s hypothesis [1] that schizophrenia is the intensification of phenomenological experience caused by the upregulation of dopamine, a survey of observed dopamine responses to phenomenal information was conducted. - Method An integrative study. - Results When considered in the light of the ecological theory of perception (ETP) [2] and global workspace theory (GBT) [3] Kapur’s hypothesis makes sense: Both the ETP and the GBT require an agent to attribute salience to perceptual information in order to filter an infinite array of available information and usefully sort information by importance. Dopamine may be the primary agent for this purpose. Thus perception itself is suspected as being a dopamine-mediated, and the symptoms and signs of schizophrenia may therefore be the result of dopamine dysfunction. - Conclusions The application of both ETP and GBT to the dopamine hypothesis gives the hypothesis a much-needed causal mechanism and the confl uence of these theories also provides ETP with a neurological perceptual fi lter. This paper provides a compelling model for schizophrenia; a hypothesis that ties perceptual theory to Kapur ’ s concept of dopamine-mediated salience.
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The remarkable geological and evolutionary history of peninsular India has generated much interest in the patterns and processes that might have shaped the current distributions of its endemic biota. In this regard the Out of India hypothesis, which proposes that rafting peninsular India carried Gondwanan forms to Asia after the break-up of Gondwana super continent, has gained prominence. Here we have reviewed molecular studies undertaken on a range of taxa of supposedly Gondwanan origin to better understand the Out-of-India scenario. This re-evaluation of published molecular studies indicates that there is mounting evidence supporting Out-of-India scenario for various Asian taxa. Nevertheless, in many studies the evidence is inconclusive due to lack of information on the age of relevant nodes. Studies also indicate that not all Gondwanan forms of peninsular India dispersed out of India. Many of these ancient lineages are confined to peninsular India and therefore are relict Gondwanan lineages. Additionally for some taxa an Into India rather than Out-of-India scenario better explains their current distribution. To identify the Out-of-India component of Asian biota it is imperative that we understand the complex biogeographical history of India. To this end, we propose three oversimplified yet explicit phylogenetic predictions. These predictions can be tested through the use of molecular phylogenetic tools in conjunction with palaeontological and geological data.
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The aim of this study was to identify and describe the types of errors in clinical reasoning that contribute to poor diagnostic performance at different levels of medical training and experience. Three cohorts of subjects, second- and fourth- (final) year medical students and a group of general practitioners, completed a set of clinical reasoning problems. The responses of those whose scores fell below the 25th centile were analysed to establish the stage of the clinical reasoning process - identification of relevant information, interpretation or hypothesis generation - at which most errors occurred and whether this was dependent on problem difficulty and level of medical experience. Results indicate that hypothesis errors decrease as expertise increases but that identification and interpretation errors increase. This may be due to inappropriate use of pattern recognition or to failure of the knowledge base. Furthermore, although hypothesis errors increased in line with problem difficulty, identification and interpretation errors decreased. A possible explanation is that as problem difficulty increases, subjects at all levels of expertise are less able to differentiate between relevant and irrelevant clinical features and so give equal consideration to all information contained within a case. It is concluded that the development of clinical reasoning in medical students throughout the course of their pre-clinical and clinical education may be enhanced by both an analysis of the clinical reasoning process and a specific focus on each of the stages at which errors commonly occur.
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A model is presented which explains the biological role of the leader peptide in protein export. Along the lines of this model, the conformational changes of a protein with environment serves as a general mechanism for translocation. The leader peptide in the cytoplasm takes a hairpin like conformation which reverts to an extended helix upon integration into the membrane. The essential features of this model are in accord with recent results of protein export.
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This paper investigates the clustering pattern in the Finnish stock market. Using trading volume and time as factors capturing the clustering pattern in the market, the Keim and Madhavan (1996) and the Engle and Russell (1998) model provide the framework for the analysis. The descriptive and the parametric analysis provide evidences that an important determinant of the famous U-shape pattern in the market is the rate of information arrivals as measured by large trading volumes and durations at the market open and close. Precisely, 1) the larger the trading volume, the greater the impact on prices both in the short and the long run, thus prices will differ across quantities. 2) Large trading volume is a non-linear function of price changes in the long run. 3) Arrival times are positively autocorrelated, indicating a clustering pattern and 4) Information arrivals as approximated by durations are negatively related to trading flow.
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The structure and properties of the double-helical form of the alternating copolymer poly(dA-dT) are considered. Different lines of evidence are interpreted in terms of a structure in which every second phosphate-diester linkage has a conformation different from that of the normal B form. A rationale for this “alternating-B” structure is given which provides an explanation for the effects of chemical modifications of the T residues on the binding of the poly(dA-dT)· poly(dA-dT) to the lac repressor of Escherichia coli.
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This paper presents a novel hypothesis on the function of massive feedback pathways in mammalian visual systems. We propose that the cortical feature detectors compete not for the right to represent the output at a point, but for exclusive rights to abstract and represent part of the underlying input. Feedback can do this very naturally. A computational model that implements the above idea for the problem of line detection is presented and based on that we suggest a functional role for the thalamo-cortical loop during perception of lines. We show that the model successfully tackles the so called Cross problem. Based on some recent experimental results, we discuss the biological plausibility of our model. We also comment on the relevance of our hypothesis (on the role of feedback) to general sensory information processing and recognition. (C) 1998 Published by Elsevier Science Ltd. All rights reserved.
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Two- and three-state models for the adsorption of organic compounds at the electrode/electrolyte interface are proposed. Different size requirements, if any, for the neutral molecule and the adsorbing solvent are also considered. It is shown how the empirical, generalised surface layer (GSL) relationship (between the potential difference and the electrode charge) formulated by Damaskin et al. can be understood at the molecular level.
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Background: The correlation of genetic distances between pairs of protein sequence alignments has been used to infer protein-protein interactions. It has been suggested that these correlations are based on the signal of co-evolution between interacting proteins. However, although mutations in different proteins associated with maintaining an interaction clearly occur (particularly in binding interfaces and neighbourhoods), many other factors contribute to correlated rates of sequence evolution. Proteins in the same genome are usually linked by shared evolutionary history and so it would be expected that there would be topological similarities in their phylogenetic trees, whether they are interacting or not. For this reason the underlying species tree is often corrected for. Moreover processes such as expression level, are known to effect evolutionary rates. However, it has been argued that the correlated rates of evolution used to predict protein interaction explicitly includes shared evolutionary history; here we test this hypothesis. Results: In order to identify the evolutionary mechanisms giving rise to the correlations between interaction proteins, we use phylogenetic methods to distinguish similarities in tree topologies from similarities in genetic distances. We use a range of datasets of interacting and non-interacting proteins from Saccharomyces cerevisiae. We find that the signal of correlated evolution between interacting proteins is predominantly a result of shared evolutionary rates, rather than similarities in tree topology, independent of evolutionary divergence. Conclusions: Since interacting proteins do not have tree topologies that are more similar than the control group of non-interacting proteins, it is likely that coevolution does not contribute much to, if any, of the observed correlations.
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We consider a visual search problem studied by Sripati and Olson where the objective is to identify an oddball image embedded among multiple distractor images as quickly as possible. We model this visual search task as an active sequential hypothesis testing problem (ASHT problem). Chernoff in 1959 proposed a policy in which the expected delay to decision is asymptotically optimal. The asymptotics is under vanishing error probabilities. We first prove a stronger property on the moments of the delay until a decision, under the same asymptotics. Applying the result to the visual search problem, we then propose a ``neuronal metric'' on the measured neuronal responses that captures the discriminability between images. From empirical study we obtain a remarkable correlation (r = 0.90) between the proposed neuronal metric and speed of discrimination between the images. Although this correlation is lower than with the L-1 metric used by Sripati and Olson, this metric has the advantage of being firmly grounded in formal decision theory.
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This paper considers sequential hypothesis testing in a decentralized framework. We start with two simple decentralized sequential hypothesis testing algorithms. One of which is later proved to be asymptotically Bayes optimal. We also consider composite versions of decentralized sequential hypothesis testing. A novel nonparametric version for decentralized sequential hypothesis testing using universal source coding theory is developed. Finally we design a simple decentralized multihypothesis sequential detection algorithm.
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Dani Rodrik es un conocido economista, nacido en Turquía, Profesor de Economía Política Internacional en la John F. Kennedy School of Government, de Harvard University. Su trabajo se ha destacando en temas de economía internacional, desarrollo económico y economía política. Su área central de investigación se centra en la explicación de que constituye una buena política económica y por qué algunos gobiernos son mejores que otros al adoptar distintas políticas, logrando distintos resultados en materia de desarrollo económico. En este sentido, es un defensor de la estrategia “productivista” del Este de Asia, asignando al Estado y a determinada política económica activa un rol central.
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Optimal Bayesian multi-target filtering is, in general, computationally impractical owing to the high dimensionality of the multi-target state. The Probability Hypothesis Density (PHD) filter propagates the first moment of the multi-target posterior distribution. While this reduces the dimensionality of the problem, the PHD filter still involves intractable integrals in many cases of interest. Several authors have proposed Sequential Monte Carlo (SMC) implementations of the PHD filter. However, these implementations are the equivalent of the Bootstrap Particle Filter, and the latter is well known to be inefficient. Drawing on ideas from the Auxiliary Particle Filter (APF), we present a SMC implementation of the PHD filter which employs auxiliary variables to enhance its efficiency. Numerical examples are presented for two scenarios, including a challenging nonlinear observation model.