Adaptação transcultural e validação da Readiness for Interprofessional Learning Scale no Brasil

RESUMO Objetivo Realizar a adaptação transcultural e a validação da versão de 29-itens daReadiness for Interprofessional Learning Scale (RIPLS) para língua portuguesa falada no Brasil. Método Foram adotadas cinco etapas: três traduções, síntese, três retrotraduções, avaliação por especialistas e pré-teste. A validação contou com 327 estudantes de 13 cursos de graduação de uma universidade pública. Foram realizadas análises paralelas com o software R e a análise fatorial utilizando Modelagem de Equações Estruturais. Resultados A análise fatorial resultou em uma escala de 27 itens e três fatores: Fator 1 – Trabalho em equipe e colaboração com 14 itens (1-9, 12-16), Fator 2 – Identidade profissional, oito itens (10, 11, 17, 19, 21-24), e Fator 3 – Atenção à saúde centrada no paciente, cinco itens (25-29). Alfa de Cronbach dos três fatores foi respectivamente: 0,90; 0,66; 0,75. Análise de variância mostrou diferenças significativas nas médias dos fatores dos grupos profissionais. Conclusão Foram identificadas evidências de validação da versão em português da RIPLS em sua aplicação no contexto nacional.

A la recherche de symptômes de désorientation dépendant d'un déficit d'intégration multisensorielle chez l'animal : un éclairage sur les mécanismes fondamentaux de la schizophrénie

Abstract Fundamental research in psychiatric neurosciences assumes that psychiatric disorders are associated with neurobiological factors. Identification of these factors would provide therapeutic targets as well as a better understanding of the relationship between- brain and behaviour in pathological processes. We conducted experiments in an animal model of schizophrenia. Several behavioural tasks were used to evaluate spatial and working memory in these animals. The model is based on glutathione deficit during cerebral development. Indeed, a 50% decrease of glutathione has been reported in prefrontal cortex of patients with schizophrenia. Glutathione is a major antioxidant in the brain and its deficit could lead to abnormal brain connectivity. The glutathione deficit was induced in rats by perinatal (PS-P16) subcutaneous injections with Lbuthionine-(S,R)-sullfoximine (BSO), an inhibitor of glutathione synthesis. This treatment leads to a transitory 50% glutathione levels during brain development. In parallel, we conducted behavioural testing in rats with a medial prefrontal cortex lesion. This allowed us to compare early damage induced by BSO treatment with a focal lesion in adults of a brain area known to present anomalies in schizophrenia. Finally, we conducted a series of experiments in senescent rats to evaluate if cognitive deficits could be related to neurobiological changes. Our results show that an early glutathione deficit provokes cognitive deficits in adulthood. These spatial and working memory deficits resemble the cognitive deficits observed in schizophrenia. The comparison with prefrontal rats revealed that the early brain glutathione deficit provoked more severe cognitive deficits than the prefrontal lesion in adult rats. Moreover, in both cases, we observed a dissociation in memory deficits depending on the type of locomotion that was used in behavioural experiments. Indeed, BSO treated rats as well as prefrontal rats showed place learning or working memory deficits in tasks conducted on dry surfaces where they had to walk. In contrast, they showed no deficit when the same cognitive functions were tested in the water maze. This dissociation might be sustained by a difference in requirement of sensory integration between walking and swimming tasks. Résumé La recherche fondamentale en neurosciences psychiatriques repose sur le présupposé selon lequel les symptômes manifestés dans les troubles psychiatriques auraient des concomitants neurobiologiques. Ceux-ci, une fois identifiés, offriraient des cibles pour une démarche thérapeutique ainsi que des modèles permettant de mieux comprendre les soubassements biologiques du comportement et des activités mentales. Nos expériences s'articulent autour de la question de la modélisation de la schizophrénie chez l'animal. Nous avons recherché chez ces animaux des troubles cognitifs et sensoriels associés à la schizophrénie. En effet, chez l'homme comme chez l'animal, la mémoire spatiale et la mémoire de travail dépendent fortement de la capacité d'intégration et d'organisation des informations sensorielles. Les premières expériences ont été menées suite à une perturbation périnatale du développement cérébral. Celle-ci visait à reproduire une diminution du taux de glutathion dans le cerveau, des recherches précédentes ayant observé une diminution de 50% du taux de glutathion dans le cortex préfrontal de patients schizophrènes. Le glutathion étant un antioxydant majeur dans le cerveau, son déficit pourrait conduire à des perturbations de la circuiterie cérébrale. Nous avons reproduit ce déficit chez le rat, par injection de Lbuthionine-(S,R)-sullfoximine (BSO), un inhibiteur de la synthèse du glutathion... Ce traitement a été administré pendant la période périnatale (du jour postnatal 5 au jour 16) provoquant une diminution de 50% du taux de glutathion. Nous avons ensuite évalué lës répercussions de cette atteinte précoce sur le comportement des rats à l'âge adulte. Ce modèle s'inscrit donc dans l'hypothèse neurodéveloppementale qui associe la schizophrénie à une atteinte du développement cérébral normal. Nous avons ensuite conduit des expériences similaires chez des rats ayant subi une lésion du cortex préfrontal pour comparer les répercussions du traitement périnatal avec une lésion, à l'âge adulte, d'une aire cérébrale connue pour présenter des anomalies chez les patients. Finalement, nous avons évalué si les processus sensoriels et cognitifs précédemment étudiés pouvaient également être affectés lors du vieillissement normal en recherchant des corrélats biologiques des déficits de mémoire liés à l'âge avancé. Nos résultats montrent que ce déficit précoce en glutathion peut avoir des répercussions surale comportement à l'âge adulte. On a relevé une similarité avec les déficits cognitifs associés.à la schizophrénie, incluant des déficits de mémoire de travail ainsi que des déficits de mémoire spatiale. Ces déficits étaient fortement liés au type de locomotion utilisée et n'ont été observés que dans les tâches où les animaux devaient rejoindre un but en marchant mais pas dans lés tests dans lesquels ils devaient localiser une cible en nageant. Les déficits induits par la lésion préfrontale chez l'adulte étaient beaucoup plus légers que ceux découlant de l'atteinte périnatale mais présentaient une dissociation analogue en fonction du type de locomotion. De plus, des tests similaires menés au cours du vieillissement confirment que la mémoire de travail peut être affectée sélectivement par le vieillissement dans une tâche où les animaux doivent marcher, tout en restant intacte dans le bassin de Morris. Les déficits cognitifs liés au vieillissement étaient significativement corrélés à des différences de niveaux des protéines post-synaptiques PSD95 (postsynaptic density 95). L'ensemble des résultats montre que les tests qui sont fréquemment utilisés pour évaluer la mémoire chez l'animal pourraient faire appel à des processus différents. Cette différence pourrait notamment tenir au niveau d'intégration sensorielle requis pour résoudre la tâche, qui est particulièrement sollicitée au cours d'une locomotion intermittente.

An Automatic Approach for Learning and Tuning Gaussian Interval Type-2 Fuzzy Membership Functions Applied to Lung CAD Classification System

The potential of type-2 fuzzy sets for managing high levels of uncertainty in the subjective knowledge of experts or of numerical information has focused on control and pattern classification systems in recent years. One of the main challenges in designing a type-2 fuzzy logic system is how to estimate the parameters of type-2 fuzzy membership function (T2MF) and the Footprint of Uncertainty (FOU) from imperfect and noisy datasets. This paper presents an automatic approach for learning and tuning Gaussian interval type-2 membership functions (IT2MFs) with application to multi-dimensional pattern classification problems. T2MFs and their FOUs are tuned according to the uncertainties in the training dataset by a combination of genetic algorithm (GA) and crossvalidation techniques. In our GA-based approach, the structure of the chromosome has fewer genes than other GA methods and chromosome initialization is more precise. The proposed approach addresses the application of the interval type-2 fuzzy logic system (IT2FLS) for the problem of nodule classification in a lung Computer Aided Detection (CAD) system. The designed IT2FLS is compared with its type-1 fuzzy logic system (T1FLS) counterpart. The results demonstrate that the IT2FLS outperforms the T1FLS by more than 30% in terms of classification accuracy.

Strong minimax lower bounds for learning

Minimax lower bounds for concept learning state, for example, thatfor each sample size $n$ and learning rule $g_n$, there exists a distributionof the observation $X$ and a concept $C$ to be learnt such that the expectederror of $g_n$ is at least a constant times $V/n$, where $V$ is the VC dimensionof the concept class. However, these bounds do not tell anything about therate of decrease of the error for a {\sl fixed} distribution--concept pair.\\In this paper we investigate minimax lower bounds in such a--stronger--sense.We show that for several natural $k$--parameter concept classes, includingthe class of linear halfspaces, the class of balls, the class of polyhedrawith a certain number of faces, and a class of neural networks, for any{\sl sequence} of learning rules $\{g_n\}$, there exists a fixed distributionof $X$ and a fixed concept $C$ such that the expected error is larger thana constant times $k/n$ for {\sl infinitely many n}. We also obtain suchstrong minimax lower bounds for the tail distribution of the probabilityof error, which extend the corresponding minimax lower bounds.

Two-sided learning in New Keynesian models: Dynamics, (lack of) convergence and the value of information

This paper investigates the role of learning by private agents and the central bank(two-sided learning) in a New Keynesian framework in which both sides of the economyhave asymmetric and imperfect knowledge about the true data generating process. Weassume that all agents employ the data that they observe (which may be distinct fordifferent sets of agents) to form beliefs about unknown aspects of the true model ofthe economy, use their beliefs to decide on actions, and revise these beliefs througha statistical learning algorithm as new information becomes available. We study theshort-run dynamics of our model and derive its policy recommendations, particularlywith respect to central bank communications. We demonstrate that two-sided learningcan generate substantial increases in volatility and persistence, and alter the behaviorof the variables in the model in a significant way. Our simulations do not convergeto a symmetric rational expectations equilibrium and we highlight one source thatinvalidates the convergence results of Marcet and Sargent (1989). Finally, we identifya novel aspect of central bank communication in models of learning: communicationcan be harmful if the central bank's model is substantially mis-specified.

Learning ability and longevity: a symmetrical evolutionary trade-off in Drosophila.

Learning ability can be substantially improved by artificial selection in animals ranging from Drosophila to rats. Thus these species have not used their evolutionary potential with respect to learning ability, despite intuitively expected and experimentally demonstrated adaptive advantages of learning. This suggests that learning is costly, but this notion has rarely been tested. Here we report correlated responses of life-history traits to selection for improved learning in Drosophila melanogaster. Replicate populations selected for improved learning lived on average 15% shorter than the corresponding unselected control populations. They also showed a minor reduction in fecundity late in life and possibly a minor increase in dry adult mass. Selection for improved learning had no effect on egg-to-adult viability, development rate, or desiccation resistance. Because shortened longevity was the strongest correlated response to selection for improved learning, we also measured learning ability in another set of replicate populations that had been selected for extended longevity. In a classical olfactory conditioning assay, these long-lived flies showed an almost 40% reduction in learning ability early in life. This effect disappeared with age. Our results suggest a symmetrical evolutionary trade-off between learning ability and longevity in Drosophila.

Speed of convergence of recursive least squares learning with ARMA perceptions

This paper fills a gap in the existing literature on least squareslearning in linear rational expectations models by studying a setup inwhich agents learn by fitting ARMA models to a subset of the statevariables. This is a natural specification in models with privateinformation because in the presence of hidden state variables, agentshave an incentive to condition forecasts on the infinite past recordsof observables. We study a particular setting in which it sufficesfor agents to fit a first order ARMA process, which preserves thetractability of a finite dimensional parameterization, while permittingconditioning on the infinite past record. We describe how previousresults (Marcet and Sargent [1989a, 1989b] can be adapted to handlethe convergence of estimators of an ARMA process in our self--referentialenvironment. We also study ``rates'' of convergence analytically and viacomputer simulation.