79 resultados para Stochastic neurodynamics


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The elevated plus-maze is an animal model of anxiety used to study the effect of different drugs on the behavior of the animal It consists of a plus-shaped maze with two open and two closed arms elevated 50 cm from the floor The standard measures used to characterize exploratory behavior in the elevated plus-maze are the time spent and the number of entries in the open arms In this work we use Markov chains to characterize the exploratory behavior of the rat in the elevated plus-maze under three different conditions normal and under the effects of anxiogenic and anxiolytic drugs The spatial structure of the elevated plus-maze is divided into squares which are associated with states of a Markov chain By counting the frequencies of transitions between states during 5-min sessions in the elevated plus-maze we constructed stochastic matrices for the three conditions studied The stochastic matrices show specific patterns which correspond to the observed behaviors of the rat under the three different conditions For the control group the stochastic matrix shows a clear preference for places in the closed arms This preference is enhanced for the anxiogenic group For the anxiolytic group the stochastic matrix shows a pattern similar to a random walk Our results suggest that Markov chains can be used together with the standard measures to characterize the rat behavior in the elevated plus-maze (C) 2010 Elsevier B V All rights reserved

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The present study was carried out to investigate the cytogenetic effects of therapeutic exposure to radioiodine preceded by rhTSH in an animal model. Three groups of Wistar rats (n = 6) were used: one group was treated only with I-131 (11.1 MBq/animal); the other two groups received rhTSH (1.2 mu g/rat of either Thyrogen or rhTSH-IPEN, respectively) 24 h before administration of radioiodine. The percentage of lymphocytes with chromosome aberrations and the average number of aberrations and of dicentrics per cell were determined on blood samples collected 24 h, 7 and 30 days after administration of I-131. The data show that the treatment with radioiodine alone or associated with rhTSH resulted in a greater quantity of chromosome alterations in relation to basal values after 24 h, with a gradual decline after 7 and 30 days of treatment. An increase in chromosome alterations was also seen after rhTSH treatment alone. Neither of the treatments, i.e., with I-131 alone or associated with hormone, resulted in an aneugenic effect or influenced the kinetics of cellular proliferation in rat blood lymphocytes. There was no significant difference between the cytogenetic effects of Thyrogen and rhTSH-IPEN treatment. These data suggest that the treatment with radioiodine, associated or not with rhTSH, affects to a limited extent a relatively small number of cells although the occurrence of late stochastic effects could not be discarded.

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In this paper, we present a fuzzy approach to the Reed-Frost model for epidemic spreading taking into account uncertainties in the diagnostic of the infection. The heterogeneities in the infected group is based on the clinical signals of the individuals (symptoms, laboratorial exams, medical findings, etc.), which are incorporated into the dynamic of the epidemic. The infectivity level is time-varying and the classification of the individuals is performed through fuzzy relations. Simulations considering a real problem with data of the viral epidemic in a children daycare are performed and the results are compared with a stochastic Reed-Frost generalization.

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In this paper we study the possible microscopic origin of heavy-tailed probability density distributions for the price variation of financial instruments. We extend the standard log-normal process to include another random component in the so-called stochastic volatility models. We study these models under an assumption, akin to the Born-Oppenheimer approximation, in which the volatility has already relaxed to its equilibrium distribution and acts as a background to the evolution of the price process. In this approximation, we show that all models of stochastic volatility should exhibit a scaling relation in the time lag of zero-drift modified log-returns. We verify that the Dow-Jones Industrial Average index indeed follows this scaling. We then focus on two popular stochastic volatility models, the Heston and Hull-White models. In particular, we show that in the Hull-White model the resulting probability distribution of log-returns in this approximation corresponds to the Tsallis (t-Student) distribution. The Tsallis parameters are given in terms of the microscopic stochastic volatility model. Finally, we show that the log-returns for 30 years Dow Jones index data is well fitted by a Tsallis distribution, obtaining the relevant parameters. (c) 2007 Elsevier B.V. All rights reserved.