AGL StimSelect: Software for automated selection of stimuli for artificial grammar learning

Artificial grammar learning (AGL) is an experimental paradigm that has been used extensively incognitive research for many years to study implicit learning, associative learning, and generalization on the basis of either similarity or rules. Without computer assistance, it is virtually impossible to generate appropriate grammatical training stimuli along with grammatical or nongrammatical test stimuli that control relevant psychological variables. We present the first flexible, fully automated software for selecting AGL stimuli. The software allows users to specify a grammar of interest, and to manipulate characteristics of training and test sequences, and their relationship to each other. The user therefore has direct control over stimulus features that may influence learning and generalization in AGL tasks. The software, AGL StimSelect, enables researchers to develop AGL designs that would not be feasible without automatic stimulus selection. It is implemented in MATLAB.     

How Science Is Applied in Technology

Unlike basic sciences, scientific research in advanced technologies aims to explain, predict, and (mathematically) describe not phenomena in nature, but phenomena in technological artefacts, thereby producing knowledge that is utilized in technological design. This article first explains why the covering‐law view of applying science is inadequate for characterizing this research practice. Instead, the covering‐law approach and causal explanation are integrated in this practice. Ludwig Prandtl’s approach to concrete fluid flows is used as an example of scientific research in the engineering sciences. A methodology of distinguishing between regions in space and/or phases in time that show distinct physical behaviours is specific to this research practice. Accordingly, two types of models specific to the engineering sciences are introduced. The diagrammatic model represents the causal explanation of physical behaviour in distinct spatial regions or time phases; the nomo‐mathematical model represents the phenomenon in terms of a set of mathematically formulated laws.     

Theories of artificial grammar learning

Artificial grammar learning (AGL) is one of the most commonly used paradigms for the study of implicit learning and the contrast between rules, similarity, and associative learning. Despite five decades of extensive research, however, a satisfactory theoretical consensus has not been forthcoming. Theoretical accounts of AGL are reviewed, together with relevant human experimental and neuroscience data. The author concludes that satisfactory understanding of AGL requires (a) an understanding of implicit knowledge as knowledge that is not consciously activated at the time of a cognitive operation; this could be because the corresponding representations are impoverished or they cannot be concurrently supported in working memory with other representations or operations, and (b) adopting a frequency-independent view of rule knowledge and contrasting rule knowledge with specific similarity and associative learning (co-occurrence) knowledge.     

Comparing measures of cognitive bias relating to eating behaviour

Consumption of and/or abstinence from substances with a high reward value (e.g. heroin, marijuana, alcohol, nicotine, certain foods) are associated with cognitive biases for information related to the substance. Such cognitive biases are important since they may contribute to difficulties in controlling intake of the substance. We examine cognitive biases for stimuli related to food. For the first time, we concurrently employ and compare five conceptually distinct measures of cognitive bias (dot probe, emotional Stroop, recognition, EAST, explicit attitudes). Contrary to expectations from current theory, the relation between the cognitive measures was weak and evident only in certain subsets of the population sample, as defined by gender and emotional‐, restrained‐ and external‐eating characteristics of our participants. We discuss some methodological implications of our findings. Copyright © 2008 John Wiley & Sons, Ltd.     

Acceptance and Commitment Therapy for Anxiety Disorders: Three Case Studies Exemplifying a Unified Treatment Protocol

Acceptance and Commitment Therapy (ACT) is an innovative acceptance-based behavior therapy that has been applied broadly and successfully to treat a variety of clinical problems, including the anxiety disorders. Throughout treatment ACT balances acceptance and mindfulness processes with commitment and behavior change processes. As applied to anxiety disorders, ACT seeks to undermine excessive struggle with anxiety and experiential avoidance––attempts to down-regulate and control unwanted private events (thoughts, images, bodily sensations). The goal is to foster more flexible and mindful ways of relating to anxiety so individuals can pursue life goals important to them. This article describes in some detail a unified ACT protocol that can be adapted for use with persons presenting with any of the major anxiety disorders. To exemplify this approach, we present pre- and posttreatment data from three individuals with different anxiety disorders who underwent treatment over a 12-week period. The results showed positive pre- to posttreatment changes in ACT-relevant process measures (e.g., reductions in experiential avoidance, increases in acceptance and mindfulness skills), increases in quality of life, as well as significant reductions in traditional anxiety and distress measures. All three clients reported maintaining or improving on their posttreatment level of functioning.     

Language‐specific stress perception by 9‐month‐old French and Spanish infants

During the first year of life, infants begin to have difficulties perceiving non‐native vowel and consonant contrasts, thus adapting their perception to the phonetic categories of the target language. In this paper, we examine the perception of a non‐segmental feature, i.e. stress. Previous research with adults has shown that speakers of French (a language with fixed stress) have great difficulties in perceiving stress contrasts ( Dupoux, Pallier, Sebastián & Mehler, 1997 ), whereas speakers of Spanish (a language with lexically contrastive stress) perceive these contrasts as accurately as segmental contrasts. We show that language‐specific differences in the perception of stress likewise arise during the first year of life. Specifically, 9‐month‐old Spanish infants successfully distinguish between stress‐initial and stress‐final pseudo‐words, while French infants of this age show no sign of discrimination. In a second experiment using multiple tokens of a single pseudo‐word, French infants of the same age successfully discriminate between the two stress patterns, showing that they are able to perceive the acoustic correlates of stress. Their failure to discriminate stress patterns in the first experiment thus reflects an inability to process stress at an abstract, phonological level.