Measuring anxious responses to predictable and unpredictable threat in children and adolescents.

Research has highlighted the need for new methods to assess emotions in children on multiple levels to gain better insight into the complex processes of emotional development. The startle reflex is a unique translational tool that has been used to study physiological processes during fear and anxiety in rodents and in human participants. However, it has been challenging to implement developmentally appropriate startle experiments in children. This article describes a procedure that uses predictable and unpredictable aversive events to distinguish between phasic fear and sustained anxiety in children and adolescents. We investigated anxious responses, as measured with the startle reflex, in youths (N=36, mean age=12.63 years, range=7-17) across three conditions: no aversive events (N), predictable aversive events (P), and unpredictable aversive events (U). Short-duration cues were presented several times in each condition. Aversive events were signaled by the cues in the P condition but were presented randomly in the U condition. Participants showed fear-potentiated startle to the threat cue in the P condition. Startle responses were also elevated between cues in the U condition compared with the N condition, suggesting that unpredictable aversive events can evoke a sustained state of anxiety in youths. This latter effect was influenced by sex, being greater in girls than in boys. These findings indicate the feasibility of this experimental induction of the startle reflex in response to predictable and unpredictable events in children and adolescents, enabling future research on interindividual differences in fear and anxiety and their development in youths.

Inductive reasoning.

Inductive reasoning entails using existing knowledge or observations to make predictions about novel cases. We review recent findings in research on category-based induction as well as theoretical models of these results, including similarity-based models, connectionist networks, an account based on relevance theory, Bayesian models, and other mathematical models. A number of touchstone empirical phenomena that involve taxonomic similarity are described. We also examine phenomena involving more complex background knowledge about premises and conclusions of inductive arguments and the properties referenced. Earlier models are shown to give a good account of similarity-based phenomena but not knowledge-based phenomena. Recent models that aim to account for both similarity-based and knowledge-based phenomena are reviewed and evaluated. Among the most important new directions in induction research are a focus on induction with uncertain premise categories, the modeling of the relationship between inductive and deductive reasoning, and examination of the neural substrates of induction. A common theme in both the well-established and emerging lines of induction research is the need to develop well-articulated and empirically testable formal models of induction. Copyright © 2010 John Wiley & Sons, Ltd. For further resources related to this article, please visit the WIREs website.