A content analysis of the conversational behavior of accepted and rejected children

The present study was designed to assess whether the conversational behavior of children separated into accepted, rejected, and mixed-status dyads differed along the dimensions of listening to, paying attention to, and indicating interest in their dyadic partner. Conversations of 40 third-grade dyads were analyzed as they occurred in a 2- min waiting period and a 4- min conversation period. Seventeen categories of verbal behaviors that indexed these dimensions were used as content codes. Multivariate analyses of variance performed on the observational data yielded significant main effects for status, sex, and experimental condition. Results are interpreted in terms of previous social skills research, and suggestions for future research are offered.     

August Dvorak (1894-1975): Early expressions of applied behavior analysis and precision teaching

August Dvorak is best known for his development of the Dvorak keyboard. However, Dvorak also adapted and applied many behavioral and scientific management techniques to the field of education. Taken collectively, these techniques are representative of many of the procedures currently used in applied behavior analysis, in general, and especially in precision teaching. The failure to consider Dvorak's instructional methods may explain some of the discrepant findings in studies which compare the efficiency of the Dvorak to the standard keyboard. This article presents a brief background on the development of the standard (QWERTY) and Dvorak keyboards, describes parallels between Dvorak's teaching procedures and those used in precision teaching, reviews some of the comparative research on the Dvorak keyboard, and suggests some implications for further research in applying the principles of behavior analysis.     

Conditioned taste aversions support drug discrimination learning at low dosages of morphine.

The present experiment shows that a conditioned taste aversion procedure can support discrimination learning at dosages of morphine comparable to those required to produce motivational effects. Sprague-Dawley rats were injected with 4.0 mg/kg morphine sulfate prior to a saccharin-lithium chloride pairing, and physiological saline prior to a saccharin-saline pairing. The rats avoided the saccharin solution following the administration of morphine and consumed significantly more saccharin following saline administration after four discrimination cycles. After this initial discrimination the subjects were trained with progressively lower doses of morphine. Discrimination learning was apparent at doses of 2.0, 1.5, 1.0, 0.75 and 0.5 mg/kg. Animals initially trained with 1.0 mg/kg morphine also learned the discrimination but required 10 training cycles. After this initial discrimination the subjects were trained with progressively lower dosages of morphine and showed a discrimination at a dosage of 0.5 mg/kg.     

Low-dimensional chaos maps learning in a model neuropil (olfactory bulb).

Quantification of a chaotic system can be made by calculating the correlation dimension (D2) of the data that the system generates (Packard et al., 1980). The D2 algorithm, however, requires stationarity of the generator, a feature that biological data rarely reflect (Mayer-Kress et al., 1988). So we developed the "point correlation dimension" (PD2), an algorithm that accurately tracks D2 in linked data of different dimensions (Carpeggiani et al., 1991). We now present a mathematical argument that, for stationary data, individual PD2s converge to D2 and we demonstrate that the algorithm rejects contributions made by bursts of noise. Data were obtained from the surface of the olfactory bulb of the conscious rabbit (64 electrodes, 640 Hz each, 1.3 sec epochs) before and after presentation of a novel or habituated odor. D2 could be calculated in only 1 of 10 novel-odor trials, whereas PD2 could be calculated in all. Both algorithms indicated that a novel odor evokes a spatially uniform dimensional increase. The PD2 uniquely exhibited the dimensional decreases that occur during inspiration and the gradients of mean dimension present during the nonstimulated control state. These control gradients remained unchanged without odor experience, but showed spatially specific PD2 increases following odor habituation. It is interpreted that, 1) the PD2 is sensitive, accurate, and appropriate for dimensional assessment of biological data, 2) that during analysis of unfamiliar information a single global process is transiently evoked in the neuropil, and 3) after experience multiple spatially specific processes tonically map the sites of learning.     

Myth Information and Bizarre Beliefs of Male Juvenile Sex Offenders

The author describes mythical beliefs, thinking errors, and faulty attitudes collected from a group of male juvenile sex offenders. Therapists need this information to develop effective treatment strategies for replacing distortions and misperceptions with correct and moral information as a foundation for change.     

Application of chaos theory to biology and medicine

The application of “chaos theory” to the physical and chemical sciences has resolved some long-standing problems, such as how to calculate a turbulent event in fluid dynamics or how to quantify the pathway of a molecule during Brownian motion. Biology and medicine also have unresolved problems, such as how to predict the occurrence of lethal arrhythmias or epileptic seizures. The quantification of a chaotic system, such as the nervous system, can occur by calculating the correlation dimension (D2) of a sample of the data that the system generates. For biological systems, the point correlation dimension (PD2) has an advantage in that it does not presume stationarity of the data, as the D2 algorithm must, and thus can track the transient non-stationarities that occur when the systems changes state. Such non-stationarities arise during normal functioning (e.g., during an event-related potential) or in pathology (e.g., in epilepsy or cardiac arrhythmogenesis). When stochastic analyses, such as the standard deviation or power spectrum, are performed on the same data they often have a reduced sensitivity and specifity compared to the dimensional measures. For example, a reduced standard deviation of heartbeat intervals can predict increased mortality in a group of cardiac subjects, each of which has a reduced standard deviation, but it cannot specify which individuals will or will not manifest lethal arrhythmogenesis; in contrast, the PD2 of the very same data can specify which patients will manifest sudden death. The explanation for the greater sensitivity and specificity of the dimensional measures is that they aredeterministic, and thus are moreaccurate in quantifying the time-series. This accuracy appears to be significant in detecting pathology in biological systems, and thus the use of deterministic measures may lead to breakthroughs in the diagnosis and treatment of some medical disorders.     

Low-dimensional chaos maps learning in a model neuropil (olfactory bulb)

Quantification of a chaotic system can be made by calculating the correlation dimension (D2) of the data that the system generates (Packard et al., 1980). The D2 algorithm, however, requires stationarity of the generator, a feature that biological data rarely reflect (Mayer-Kress et al., 1988). So we developed the “point correlation dimension” (PD2), an algorithm that accurately tracks D2 in linked data of different dimensions (Carpeggiani et al., 1991). We now present a mathematical argument that, for stationary data, individual PD2s converge to D2 and we demonstrate that the algorithm rejects contributions made by bursts of noise. Data were obtained from the surface of the olfactory bulb of the conscious rabbit (64 electrodes, 640 Hz each, 1.3 sec epochs) before and after presentation of a novel or habituated odor. D2 could be calculated in only 1 of 10 novel-odor trials, whereas PD2 could be calculated in all. Both algorithms indicated that a novel odor evokes a spatially uniform dimensional increase. The PD2 uniquely exhibited the dimensional decreases that occur during inspiration and the gradients of mean dimension present during the nonstimulated control state. These control gradients remained unchanged without odor experience, but showed spatially specific PD2 increases following odor habituation. It is interpreted that, 1) the PD2 issensitive, accurate, and appropriate for dimensional assessment of biological data, 2) that during analysis of unfamiliar information a singleglobal process is transiently evoked in the neuropil, and 3) after experience multiplespatially specific processes tonically map the sites of learning. Grant Support: National Institutes of Health, HL 31164 and NS27745     

Countering perfectionism in research on clinical practice I: Surveying rationality changes after a single intensive ret intervention

The failure of controlled experimental research on therapy out-come to produce findings of clinical as well as statistical significance seems at least partly due to irrational, perfectionistic, beliefs about how research can be used to infer causes of therapeutic change. Irrational beliefs about controlled experimental designs and about incomplete sampling, in particular, appear to prevent appropriate consideration of probatively valuable quasi-experimental research. Models of more rational alternatives are identified, and an example of the functional advantages of adopting these rational beliefs is explicated. The example demonstrates that single-shot pre-post survey data from self-selected catch-as-catch-can samples can permit legitimate, but not absolutely certain, conclusions about the efficacy and efficiency of RET.Albert Ellis, Ph.D. is executive director of the Institute for Rational-Emotive Therapy in New York City.