Learning reward expectations in honeybees

The aim of this study was to test whether honeybees develop reward expectations. In our experiment, bees first learned to associate colors with a sugar reward in a setting closely resembling a natural foraging situation. We then evaluated whether and how the sequence of the animals’ experiences with different reward magnitudes changed their later behavior in the absence of reinforcement and within an otherwise similar context. We found that the bees that had experienced increasing reward magnitudes during training assigned more time to flower inspection 24 and 48 h after training. Our design and behavioral measurements allowed us to uncouple the signal learning and the nutritional aspects of foraging from the effects of subjective reward values. We thus found that the animals behaved differently neither because they had more strongly associated the related predicting signals nor because they were fed more or faster. Our results document for the first time that honeybees develop long-term expectations of reward; these expectations can guide their foraging behavior after a relatively long pause and in the absence of reinforcement, and further experiments will aim toward an elucidation of the neural mechanisms involved in this form of learning.     

Testing the group polarization hypothesis by using logit models

This paper focuses on methodological aspects of group polarization research and has two well‐defined parts. The first part presents a methodological overview of group polarization research together with an examination of the inadequacy, under certain circumstances, of the traditional parametric approach usually used to test this phenomenon based on pre‐test/post‐test means comparison across groups. It is shown that this approach will produce masks effects when groups are heterogeneous with regard to the observed change from pre‐test to post‐test. The second part suggests an alternative methodological approach based on logit models for the analysis of contingency tables from a categorization of the variable ‘kind of shift’. This approach is illustrated and compared with the parametric approach with a simulated data set. Copyright © 2002 John Wiley & Sons, Ltd.     

Violence and Latin‐American preadolescents: A study of social brain function and cortisol levels

The present study investigated exposure to violence and its association with brain function and hair cortisol concentrations in Latin‐American preadolescents. Self‐reported victimization scores (JVQ‐R2), brain imaging (fMRI) indices for a social cognition task (the ‘eyes test’), and hair cortisol concentrations were investigated, for the first time, in this population. The eyes test is based on two conditions: attributing mental state or sex to pictures of pairs of eyes (Baron‐Cohen, Wheelwright, Hill, Raste, & Plumb, 2001). The results showed an association among higher victimization scores and (a) less activation of posterior temporoparietal right‐hemisphere areas, in the mental state condition only (including right temporal sulcus and fusiform gyrus); (b) higher functional connectivity indices for the Amygdala and Right Fusiform Gyrus (RFFG) pair of brain regions, also in the mental state condition only; (c) higher hair cortisol concentrations. The results suggest more exposure to violence is associated with significant differences in brain function and connectivity. A putative mechanism of less activation in posterior right‐hemisphere regions and of synchronized Amygdala: RFFG time series was identified in the mental state condition only. The results also suggest measurable effects of exposure to violence in hair cortisol concentrations, which contribute to the reliability of self‐reported scores by young adolescents. The findings are discussed in light of the effects of exposure to violence on brain function and on social‐cognitive development in the adolescent brain. A video abstract of this article can be viewed at https://www.youtube.com/watch?v=qHcXq7Y9PBk     

Overdispersion tests in count-data analysis

Count data are commonly assumed to have a Poisson distribution, especially when there is no diagnostic procedure for checking this assumption. However, count data rarely fit the restrictive assumptions of the Poisson distribution. The violation of much of such assumptions commonly results in overdispersion, which invalidates the Poisson distribution. Undetected overdispersion may entail important misleading inferences, so its detection is essential. In this study, different overdispersion diagnostic tests are evaluated through two simulation studies. In Exp. 1, the nominal error rate is compared under different sample sizes and lamda conditions. Analysis shows a remarkable performance of the chi2 df test. In Exp. 2 and 3, statistical power is compared under different sample sizes, lamda, and overdispersion conditions. Chi2 and LR tests provide the highest statistical power.     

The Social Functions and Dysfunctions of Brazilian Immigrant Congregations in “<Emphasis Type="Italic">terra incognita</Emphasis>”

Ethnic congregations are often considered safe havens for immigrants. This is supported by a large body of literature showing that many religious congregations in diasporic contexts help immigrants maintain their ethnic group identity and cohesion, build social capital, and adapt more smoothly to life in an unfamiliar society. The role of ethnic congregations in the lives of immigrants is, however, complex and multifaceted, and some recent research suggests that, in some ways, these congregations may inhibit their adaptation to the larger society and arouse tensions among the very immigrant communities they intend to help. In light of these varying observations, we seek to explore the functions—and potential dysfunctions—that ethnic congregations have among Brazilians who have immigrated to central Texas. Using data drawn in 2013 from participant observation and 16 in-depth interviews conducted in two Brazilian evangelical congregations, we find that respondents perceive that their congregations strengthen their feelings of attachment to Brazilian culture and language and foster the development of social capital within to the Brazilian immigrant community. At the same time, however, some respondents acknowledge that church members can become overly dependent on their congregations and isolated from the larger society, leaving them susceptible to potential exploitation at the hands of more established co-ethnics within the congregation.     

Does stress run through the leash? An examination of stress transmission between owners and dogs during a walk

Animal Cognition - Humans and dogs have co-evolved for over 10,000&nbsp;years. Recent research suggests that, through the domestication process, dogs have become proficient at responding to...     

Conserved: inherited beyond genes / Conservado: heredado más allá de los genes

For more than a century we have discussed the extent to which a trait is innate or acquired, but little has been discussed regarding the mechanisms through which that inheritance takes place. Based on studies by Lorenz and Neo-Darwinism, we have blindly bet on genetics as the mechanism of inheritance. However, evolution considers conserved traits, but this concept lacks a specific inheritance mechanism. We would like to restore the concept of conserved to integrate other inheritance mechanisms. As such, we analyse the inheritance of both genes and the environment, allowing us to fully explore inherited psychopathologies.     

A Latent Class Multidimensional Scaling Model for Two-Way One-Mode Continuous Rating Dissimilarity Data

In this paper, we propose a cluster-MDS model for two-way one-mode continuous rating dissimilarity data. The model aims at partitioning the objects into classes and simultaneously representing the cluster centers in a low-dimensional space. Under the normal distribution assumption, a latent class model is developed in terms of the set of dissimilarities in a maximum likelihood framework. In each iteration, the probability that a dissimilarity belongs to each of the blocks conforming to a partition of the original dissimilarity matrix, and the rest of parameters, are estimated in a simulated annealing based algorithm. A model selection strategy is used to test the number of latent classes and the dimensionality of the problem. Both simulated and classical dissimilarity data are analyzed to illustrate the model.