Regularity of unit length boosts statistical learning in verbal and nonverbal artificial languages

Humans have remarkable statistical learning abilities for verbal speech-like materials and for nonverbal music-like materials. Statistical learning has been shown with artificial languages (AL) that consist of the concatenation of nonsense word-like units into a continuous stream. These ALs contain no cues to unit boundaries other than the transitional probabilities between events, which are high within a unit and low between units. Most AL studies have used units of regular lengths. In the present study, the ALs were based on the same statistical structures but differed in unit length regularity (i.e., whether they were made out of units of regular vs. irregular lengths) and in materials (i.e., syllables vs. musical timbres), to allow us to investigate the influence of unit length regularity on domain-general statistical learning. In addition to better performance for verbal than for nonverbal materials, the findings revealed an effect of unit length regularity, with better performance for languages with regular- (vs. irregular-) length units. This unit length regularity effect suggests the influence of dynamic attentional processes (as proposed by the dynamic attending theory; Large & Jones (Psychological Review 106: 119–159, 1999)) on domain-general statistical learning.     

Towards a distributed account of conceptual knowledge

How is conceptual knowledge organized and represented? Are domains (such as living things) and categories (such as tools, fruit) represented explicitly or can domain and category structure emerge out of a distributed system? Taken at face value, evidence from brain-damaged patients and neuroimaging studies suggests that conceptual knowledge is explicitly structured in independent content-based stores. However, recent analyses of the fine-grained details of semantic impairments, combined with research using connectionist modelling, suggest a different picture - one in which concepts are represented as patterns of activation over multiple semantic properties within a unitary distributed system. Within this context, category-specific deficits emerge as a result of differences in the structure and content of concepts rather than from explicit divisions of conceptual knowledge in separate stores.     

Latent variable assessment of outcomes in a nurse-managed intervention to increase latent tuberculosis treatment completion in homeless adults.

OBJECTIVE: To assess predictors of latent tuberculosis infection (LTBI) completion by using structural equation modeling (SEM) among homeless adults, a group at great risk for LTBI and active tuberculosis (TB). LTBI therapy is effective in stemming the progression to active TB, yet treatment adherence among homeless persons is difficult to attain. DESIGN: By using SEM, the authors assessed predictors of LTBI completion among a sample of 494 homeless adults in Los Angeles, CA, who received either a nurse case-managed program (NCM) or a usual care program. MAIN OUTCOME MEASURES: Latent variables were created with the baseline variables of site type, age, intervention status, dissatisfaction with health care, depression, TB risk assessment, alcohol use, heroin or cocaine use, and TB knowledge. Outcome variables included many of the same baseline variables as well as treatment completion. RESULTS: LTBI treatment completion (100% adherence) was significantly and positively associated with participation in NCM, older age, and less heroin or cocaine use. NCM also predicted greater TB knowledge, greater ease of treatment, and more satisfaction with treatment (NCM completion rate = 64%, control rate = 42%). CONCLUSION: The culturally competent NCM program, combined with active tracking and incentives, was successful in a difficult-to-treat and highly transient population.     

Dynamic Motivational Processing of Antimarijuana Messages: Coactivation Begets Attention

In the theoretical framework of dynamic motivational activation, this study reveals the dynamics of antimarijuana public service announcement (PSA) processing, especially the processing of co‐occurring positive and negative content. It specifies the important role of endogenous feedback dynamics of the information processing system and teases them apart from exogenous message effects. As suggested by real‐time psychophysiological responses (heart rate, skin conductance level, and facial electromyography), the copresence of positive and negative content is most attention eliciting and is not moderated by individuals' marijuana experience. Marijuana experience, however, increases attention to arousing content in the PSAs, increases smiling responses to positive content, and escalates arousal to the PSAs in general. Implications for designing and evaluating PSAs and health campaigns are discussed.     

Modification of behavior problems in the home with a parent as observer and experimenter

Four parents enrolled in a Responsive Teaching class carried out experiments using procedures they had devised for alleviating their children's problem behaviors. The techniques used involved different types of reinforcement, extinction, and punishment. One parent increased the frequency of the wearing of an orthodontic device during five daily time checks by making an immediate monetary payoff contingent on wearing the device. A second parent increased the number of points earned for doing daily household tasks by providing back-ups for which the points could be exchanged. The parents of a 4-yr-old boy decreased the frequency of whines, cries, and complaints by removing social attention when such behavior occurred. A mother decreased the duration of time it took for her 5-yr-old daughter to get dressed by making permission to watch television contingent on dressing within 30 min of the time she got up in the morning. Brief reversals of contingencies were used to show causal relationships between the procedures used and the changes in behavior. Checks on the reliability of measurement were made by persons present in the home.