Keeping adolescents safe from harm: management strategies of African-American families in a high-risk community

In this study, we investigated changes in parents' use of restrictive and promotive management strategies from early to middle adolescence. We also examined the antecedents of these changes and their effects on adolescents' achievement and mental health. Longitudinal data included 50 African American adolescents and their parents living in a low-income school district. There were three major findings. First, parents, on average, used less restrictive and promotive management strategies from early to middle adolescence. Second, parents who experienced increased depressive symptoms reported using more restrictive management strategies from early to middle adolescence. Third, adolescents whose parents increased their use of restrictive management strategies experienced more anger and lower grade point averages, whereas adolescents whose parents increased their use of promotive management strategies experienced less anger, higher grade point averages, and less absences from early to middle adolescence. These findings suggest that increasing parents' use of promotive rather than restrictive management strategies may be more beneficial in supporting the academic achievement and mental health of adolescents living in high-risk neighborhoods.     

Why Higher Working Memory Capacity May Help You Learn: Sampling,Search, and Degrees of Approximation

Algorithms for approximate Bayesian inference, such as those based on sampling (i.e., Monte Carlo methods), provide a natural source of models of how people may deal with uncertainty with limited cognitive resources. Here, we consider the idea that individual differences in working memory capacity (WMC) may be usefully modeled in terms of the number of samples, or “particles,” available to perform inference. To test this idea, we focus on two recent experiments that report positive associations between WMC and two distinct aspects of categorization performance: the ability to learn novel categories, and the ability to switch between different categorization strategies (“knowledge restructuring”). In favor of the idea of modeling WMC as a number of particles, we show that a single model can reproduce both experimental results by varying the number of particles—increasing the number of particles leads to both faster category learning and improved strategy‐switching. Furthermore, when we fit the model to individual participants, we found a positive association between WMC and best‐fit number of particles for strategy switching. However, no association between WMC and best‐fit number of particles was found for category learning. These results are discussed in the context of the general challenge of disentangling the contributions of different potential sources of behavioral variability.     

Varying reinforcement magnitude on interval schedules

In Experiment 1, rats were trained on either a random-interval or a variable-interval 60-sec schedule of reinforcement, and reinforcement magnitude was varied across conditions between one and four pellets. Although the two schedules maintained different patterns of behaviour, patterns and rates of responding were not systematically affected by the variation in reinforcement magnitude. In Experiment 2, a regulated probability interval schedule that generated similar rates of reinforcement to those of the schedules of Experiment 1 was used, with the pattern of behaviour generated resembling that typical of a random-interval schedule. Changing reinforcement magnitude again produced few systematic changes in behaviour. In Experiment 3, a variable-ratio schedule was used within a procedure that otherwise resembled that of Experiments 1 and 2. Increasing the reinforcement magnitude now decreased the rates of responding, and examination of the patterns of responding showed that this came about because rates of responding were higher early in the interreinforcer interval in the one-pellet condition. These experiments demonstrate the insensitivity of behaviour under interval schedules to changes in reinforcement magnitude and suggest the operation of mechanisms different from those engaged by ratio schedules and discretetrial learning procedures.     

The Trouble with Neurobiological Explanations of Mind

Neuroist literature dresses psychological narratives up with neuroscience facts. But there are fundamental differences between the languages of the mind and the brain, so ad hoc devices paper over the gaps. These include taking words out of their proper contexts; equating the conceptual architecture of psychology with the neural architecture of the brain; mimicking the format of scientific research papers; and exalting paradox to produce a thrilling sense of mystery. In addition there are outright errors that are hard for nonneuroscientists to detect. Neuroism is a bid for status by nonnatural science disciplines such as psychoanalysis.