Involvement of the lateral habenula in the regulation of generalized anxiety- and panic-related defensive responses in rats

Recently obtained evidence points to the involvement of the lateral habenular nuclei (LHb) in the mediation of coping defensive responses to threatening/stressful stimuli. Nevertheless, the role of this brain area in the regulation of defensive responses that have been associated with specific subtypes of anxiety disorders recognized in clinical settings is presently unknown. To address this question, we investigated the effects of either electrolytic lesions or chemical stimulation of the LHb on the defensive behaviors generated in rats by the elevated T-maze. This experimental model allows the measurement, in a same rat, of two defensive behaviors, inhibitory avoidance and escape, that have been related in terms of psychopathology to generalized anxiety and panic disorders, respectively. Bilateral electrolytic lesions of the LHb (1 mA, 10 s) impaired inhibitory avoidance acquisition and facilitated escape performance. On the other hand, chemical stimulation of the LHb by bilateral microinjection of kainic acid (30-60 pmol/0.2 mu L) had the opposite effect, i.e., facilitated inhibitory avoidance and impaired escape. The present results indicate that the LHb exerts an opposed regulatory control on generalized anxiety- and panic-related defensive responses in rats. (c) 2008 Elsevier Inc. All rights reserved.

Asymmetric page split generalized index search trees for formal concept analysis

Formal Concept Analysis is an unsupervised machine learning technique that has successfully been applied to document organisation by considering documents as objects and keywords as attributes. The basic algorithms of Formal Concept Analysis then allow an intelligent information retrieval system to cluster documents according to keyword views. This paper investigates the scalability of this idea. In particular we present the results of applying spatial data structures to large datasets in formal concept analysis. Our experiments are motivated by the application of the Formal Concept Analysis idea of a virtual filesystem [11,17,15]. In particular the libferris [1] Semantic File System. This paper presents customizations to an RD-Tree Generalized Index Search Tree based index structure to better support the application of Formal Concept Analysis to large data sources.

A Comparison of Bayesian and Sampling Theory Inferences in a Probit Model

HE PROBIT MODEL IS A POPULAR DEVICE for explaining binary choice decisions in econometrics. It has been used to describe choices such as labor force participation, travel mode, home ownership, and type of education. These and many more examples can be found in papers by Amemiya (1981) and Maddala (1983). Given the contribution of economics towards explaining such choices, and given the nature of data that are collected, prior information on the relationship between a choice probability and several explanatory variables frequently exists. Bayesian inference is a convenient vehicle for including such prior information. Given the increasing popularity of Bayesian inference it is useful to ask whether inferences from a probit model are sensitive to a choice between Bayesian and sampling theory techniques. Of interest is the sensitivity of inference on coefficients, probabilities, and elasticities. We consider these issues in a model designed to explain choice between fixed and variable interest rate mortgages. Two Bayesian priors are employed: a uniform prior on the coefficients, designed to be noninformative for the coefficients, and an inequality restricted prior on the signs of the coefficients. We often know, a priori, whether increasing the value of a particular explanatory variable will have a positive or negative effect on a choice probability. This knowledge can be captured by using a prior probability density function (pdf) that is truncated to be positive or negative. Thus, three sets of results are compared:those from maximum likelihood (ML) estimation, those from Bayesian estimation with an unrestricted uniform prior on the coefficients, and those from Bayesian estimation with a uniform prior truncated to accommodate inequality restrictions on the coefficients.

Children and economic development: Family size, gender preferences and human capital formation - theory and Indian cases

In the light of Gary Becker's economic theory of the family, considers how economic cost and benefit factors can influence the size of families that parents decide to have. Some support for the importance of such factors is found from results of structured interviews with wives in Kondh-dominated villages in western Orissa. These results are at variance with the hypothesis of Malthus about population growth. Factors that may alter the optimal family size as development proceeds are discussed. It is found in our sampling that, on the whole, there is a preference for daughters rather than sons although this is not as strong in the Kondh-dominated villages as in poor villages in the Santal tribal belt of West Bengal. While in the Kondh-dominated villages some discrimination in access to education in favour of boys compared to girls is present, little such or no such discrimination occurs in relation to access to food and medical attention. In the villages surveyed in the West Bengal Santal tribal belt, discrimination in favour of boys is more pronounced than in the Kondh-dominated area in Orissa. While economic considerations help to explain gender discrimination between boys and girls, we find that social and cultural factors also play a major role. Parents in a similar economic situation seem to display substantially different patterns of gender discrimination between children depending on their social and cultural content. It seems that the extent to which economic theories of the family explain family preferences and behaviour depend significantly on the social and cultural context in which they are to be applied.