Attentional mechanisms in learned predictiveness

Cues that reliably predict an outcome in an initial phase of training (Phase 1) are learned faster in a second phase of training (Phase 2) than cues that were unreliable in Phase 1. This result is observed despite objectively equal relationships between the cues and the outcomes in Phase 2, and consequently constitutes a nonnormative bias in learning. The present experiments sought to confirm that this learned predictiveness effect is the product of attentional processes (Experiment 1), and to test further whether these processes are under voluntary control or are automatic in nature (Experiment 2). In addition to the usual outcome prediction measure, eye-gaze behavior was also monitored. The results indicated an important role for top-down strategic attentional processes in the learned predictiveness task. In contrast, no evidence for an automatic attentional bias was found.     

Spreading Activation in an Attractor Network With Latching Dynamics: Automatic Semantic Priming Revisited

Localist models of spreading activation (SA) and models assuming distributed representations offer very different takes on semantic priming, a widely investigated paradigm in word recognition and semantic memory research. In this study, we implemented SA in an attractor neural network model with distributed representations and created a unified framework for the two approaches. Our models assume a synaptic depression mechanism leading to autonomous transitions between encoded memory patterns (latching dynamics), which account for the major characteristics of automatic semantic priming in humans. Using computer simulations, we demonstrated how findings that challenged attractor‐based networks in the past, such as mediated and asymmetric priming, are a natural consequence of our present model’s dynamics. Puzzling results regarding backward priming were also given a straightforward explanation. In addition, the current model addresses some of the differences between semantic and associative relatedness and explains how these differences interact with stimulus onset asynchrony in priming experiments.     

Positive and negative affect produce opposing task-irrelevant stimulus preexposure effects

In three experiments, groups were exposed to either positive or negative affect video clips, after which they were presented with a series of task-irrelevant stimuli. In the subsequent test task, subjects were required to learn an association between the previously irrelevant stimulus and a consequence, and between a new stimulus and a consequence. Induced positive affect produced a latent inhibition effect (poorer evidence of learning with the previously irrelevant stimulus than with the novel stimulus). In opposition to this, induced negative affect resulted in better evidence of learning with a previously irrelevant stimulus than with a novel stimulus. In general, the opposing effects also were present in participants scoring high on self-report questionnaires of depression (Experiments 2 and 3). These unique findings were predicted and accounted for on the basis of two principles: (a) positive affect broadens the attentional field and negative affect contracts it; and (b) task-irrelevant stimuli are processed in two successive stages, the first encodes stimulus properties, and the second encodes stimulus relationships. The opposing influences of negative and positive mood on the processing of irrelevant stimuli have implications for the role of emotion in general theories of cognition, and possibly for resolving some of the inconsistent findings in research with schizophrenia patients.     

Reviews of current books

Pastoral Psychology -     

Quality of life of men and women with borderline intelligence and attention deficit disorders living in community residences: a comparative study

The research studies the quality of life (QOL) of 127 men and women diagnosed as having a borderline IQ and ADHD living in two major residential programs of the Sharon region in central Israel in respect to their personal, disability, and social ecological variables. Core findings indicate that men and women differ significantly according to their educational background. Among those who studied in a regular educational environment, the main predictor of men's QOL is their monthly income, whereas the main predictor for women is their level of attention deficit symptoms. The only predictor of QOL among men who studied in a special education program is the quality of contact with their mothers, whereas no significant predictor is observed among women.     

Is seasonal affective disorder a disorder of circadian rhythms?

Seasonal affective disorder (SAD) is a form of depression that starts in the fall and ends in the spring. This article reviews existing theories about the relationship between circadian rhythms and the disorder. Recent research indicates that as with pharmacologic antidepressants, at least 2-4 weeks are needed to demonstrate the effectiveness of bright-light therapy compared to placebo. The response to such treatment is strongest with precisely timed light exposure: treatment is optimal during the morning hours when the circadian system is susceptible to phase advance. Such clinical improvement is correlated with the magnitude of the phase shift induced. These observations suggest a model of circadian function in SAD and provide important guidelines for its treatment.     

Reviews of current books

Pastoral Psychology -     

Learning a Generative Probabilistic Grammar of Experience: A Process‐Level Model of Language Acquisition

We introduce a set of biologically and computationally motivated design choices for modeling the learning of language, or of other types of sequential, hierarchically structured experience and behavior, and describe an implemented system that conforms to these choices and is capable of unsupervised learning from raw natural‐language corpora. Given a stream of linguistic input, our model incrementally learns a grammar that captures its statistical patterns, which can then be used to parse or generate new data. The grammar constructed in this manner takes the form of a directed weighted graph, whose nodes are recursively (hierarchically) defined patterns over the elements of the input stream. We evaluated the model in seventeen experiments, grouped into five studies, which examined, respectively, (a) the generative ability of grammar learned from a corpus of natural language, (b) the characteristics of the learned representation, (c) sequence segmentation and chunking, (d) artificial grammar learning, and (e) certain types of structure dependence. The model's performance largely vindicates our design choices, suggesting that progress in modeling language acquisition can be made on a broad front—ranging from issues of generativity to the replication of human experimental findings—by bringing biological and computational considerations, as well as lessons from prior efforts, to bear on the modeling approach.