ACQUISITION OF EXPRESSIVE SIGNING BY AUTISTIC CHILDREN: AN EVALUATION OF THE RELATIVE EFFECTS OF SIMULTANEOUS COMMUNICATION AND SIGN-ALONE TRAINING

Two methods of training autistic children to use manual signs were compared. Two children, one mute and one capable of some verbal imitation, were taught to use signs as expressive labels for pictures of objects. Using an alternating treatments design, speed of sign acquisition was compared across two training conditions in which signs were presented either accompanied by, or without, the corresponding verbal label. In both conditions, the training procedure incorporated reinforcement, modeling, prompting, fading, and stimulus rotation. The efficacy of training in both treatment conditions was demonstrated by the use of a multiple baseline control across signs, but no clear differences in acquisition speed across conditions were apparent. Posttests conducted to assess stimulus control of signing, and learning of verbal labels when these were present in training, showed that the behavior of the imitative, but not the mute, child was controlled by the verbal stimuli. The implications of the results both for understanding deficits characteristic of autistic children and for developing appropriate language training procedures are discussed.     

Physiologic reactivity to startling tones in women with posttraumatic stress disorder.

Autonomic and eyeblink reactivity to startling tones were investigated in women with histories of childhood sexual abuse (CSA). Twenty-one women with current posttraumatic stress disorder (PTSD), 23 with lifetime but not current PTSD, and 13 women who never had PTSD listened to 15 95-dB, 500-ms, 1000-Hz tones with a 0-ms rise time while heart rate (HR), skin conductance (SC), and orbicularis oculi electromyogram (EMG) responses were measured. Participants in the current and lifetime PTSD groups produced larger HR responses across tones and showed slower absolute habituation of SC response magnitude compared with the never PTSD group. EMG response magnitudes did not differ among groups. Women with CSA-related PTSD showed increased autonomic reactivity and slower habituation to high-intensity tones similar to that observed in primarily male, combat PTSD samples. This suggests that heightened autonomic responsivity to startling stimuli in PTSD is not gender or event specific.     

Cognitive Behavioral Mobile Applications: Clinical Studies,Marketplace Overview,and Research Agenda

Objective

To review the current literature for evidence regarding the feasibility and efficacy of smartphone-based cognitive-behavioral intervention mobile applications, compare such to the number of applications on the commercial marketplaces, and explore potential steps forward for research in the field.

How causal knowledge affects classification: A generative theory of categorization

Several theories have been proposed regarding how causal relations among features of objects affect how those objects are classified. The assumptions of these theories were tested in 3 experiments that manipulated the causal knowledge associated with novel categories. There were 3 results. The 1st was a multiple cause effect in which a feature's importance increases with its number of causes. The 2nd was a coherence effect in which good category members are those whose features jointly corroborate the category's causal knowledge. These 2 effects can be accounted for by assuming that good category members are those likely to be generated by a category's causal laws. The 3rd result was a primary cause effect, in which primary causes are more important to category membership. This effect can also be explained by a generative account with an additional assumption: that categories often are perceived to have hidden generative causes.     

A knowledge-resonance (KRES) model of category learning

This article introduces a connectionist model of category learning that takes into account the prior knowledge that people bring to new learning situations. In contrast to connectionist learning models that assume a feedforward network and learn by the delta rule or backpropagation, this model, the knowledge-resonance model, or KRES, employs a recurrent network with bidirectional symmetric connection whose weights are updated according to a contrastive Hebbian learning rule. We demonstrate that when prior knowledge is represented in the network, KRES accounts for a considerable range of empirical results regarding the effects of prior knowledge on category learning, including (1) the accelerated learning that occurs in the presence of knowledge, (2) the better learning in the presence of knowledge of category features that are not related to prior knowledge, (3) the reinterpretation of features with ambiguous interpretations in light of error-corrective feedback, and (4) the unlearning of prior knowledge when that knowledge is inappropriate in the context of a particular category.     

How prior knowledge affects selective attention during category learning: An eyetracking study

Research has shown that category learning is affected by (a) attention, which selects which aspects of stimuli are available for further processing, and (b) the existing semantic knowledge that learners bring to the task. However, little is known about how knowledge affects what is attended. Using eyetracking, we found that (a) knowledge indeed changes what features are attended, with knowledge-relevant features being fixated more often than irrelevant ones, (b) this effect was not due to an initial attentional bias toward relevant dimensions but rather emerged gradually as a result of observing category members, and (c) this effect grew even after a learning criterion was reached, that is, despite the absence of negative feedback. We argue that models of knowledge-based learning will remain incomplete until they specify mechanisms that dynamically select prior knowledge in response to observed category members and which then directs attention to knowledge-relevant dimensions and away from irrelevant ones.     

What's new? Children prefer novelty in referent selection

Determining the referent of a novel name is a critical task for young language learners. The majority of studies on children’s referent selection focus on manipulating the sources of information (linguistic, contextual and pragmatic) that children can use to solve the referent mapping problem. Here, we take a step back and explore how children’s endogenous biases towards novelty and their own familiarity with novel objects influence their performance in such a task. We familiarized 2-year-old children with previously novel objects. Then, on novel name referent selection trials children were asked to select the referent from three novel objects: two previously seen and one completely novel object. Children demonstrated a clear bias to select the most novel object. A second experiment controls for pragmatic responding and replicates this finding. We conclude, therefore, that children’s referent selection is biased by previous exposure and children’s endogenous bias to novelty.     

Thirty-something categorization results explained: selective attention, eyetracking, and models of category learning

An eyetracking study testing D. L. Medin and M. M. Schaffer's (1978) 5-4 category structure was conducted. Over 30 studies have shown that the exemplar-based generalized context model (GCM) usually provides a better quantitative account of 5-4 learning data as compared with the prototype model. However, J. D. Smith and J. P. Minda (2000) argued that the GCM is a psychologically implausible account of 5-4 learning because it implies suboptimal attention weights. To test this claim, the authors recorded undergraduates' eye movements while the students learned the 5-4 category structure. Eye fixations matched the attention weights estimated by the GCM but not those of the prototype model. This result confirms that the GCM is a realistic model of the processes involved in learning the 5-4 structure and that learners do not always optimize attention, as commonly supposed. The conditions under which learners are likely to optimize attention during category learning are discussed.