A multivariate investigation of the reinforcer structure of occupations

Earlier research based on 81 Occupational Reinforcer Patterns (ORPs) suggested a nine-category classification of occupations. The present research, based on 148 ORPs, investigated the ability of that classificatory system to assimilate new information. Cluster analysis of the 148 ORPs yielded an eight-category classification of occupations in which five of the original occupational clusters appeared virtually unchanged; the other four original clusters were combined into two occupational clusters. One new cluster was identified. Principal factors analysis was employed to study the factor structure of the occupational reinforcers and to highlight the essential nature of the classificatory system. Five reinforcer factors were identified.     

The attentional demands of negation in a memory-scanning task

Subjects were run in a Sternberg recognition memory task modified to occasionally require a transformation prior to response. The transformation was similar to logical negation since onplus or nontransformed trials subjects responded "yes" if the probe was from the current memory set and "no" otherwise, while onminus or transformed trials subjects responded "no" to memory set probes and "yes" to nonmemory set probes. Two models proposed to account for the effects of logical negation were compared: The encoding and comparison model predicts that logical negation requires an additional processing stage, while the capacity sharing model argues that negation adds a processing stage and also retards the rate of memory search. The results indicated that minus probes had 50% larger mean reaction time by set size slopes than the corresponding plus probes. This finding offers clear support for the capacity sharing model.     

Individual differences in the verbal coding of familiar visual stimuli

Two experiments were performed both of which involved the same-different comparison of pairs of alphabet letters. "Same" reaction times were obtained for both physical matches (e.g., AA) and name matches (e.g., aA). The results of both experiments supported the hypothesis that individual subjects would differ with respect to whether or not they based their physical matches on a comparison of verbal codes. In Experiment I, subjects differed in the size of their reaction time difference between physical and name matches, and in Experiment II, individuals differed with respect to whether or not the frequency of usage of the letters affected their reaction time for physical matches. In both experiments, the individual differences in verbally coding physical matches were related to Hock's (1973) individual differences distinction between subjects emphasizing analytic processes and subjects emphasizing structural processes.     

Stimulus compatibility effects of an accessory visual stimulus on auditory sensitivity

Studies have reported that an accessory stimulus in a second modality can have a facilitative effect on sensory detection in a primary modality. However, performance declines when the subject has the additional task of reporting on the accessory stimulus. The facilitative effect has been attributed to an arousal or warning process, while the interference effect has been characterized as a result of limited channel capacity. Auditory sensitivity was assessed under accessory visual stimulation. Visual stimulus intensity (arousal), processing demand, and interstimulus compatibility (same or opposite direction of change of primary and secondary stimuli) were manipulated. The results indicated that interstimulus compatibility, not arousal, accounted for the obtained facilitation effect. Interference due to additional task demands was not observed. It was proposed that the facilitation effect was due to selective sensory encoding.     

Verbal interference with perceptual classification: The effect of semantic structure

In a task of the same form as the standard Stroop test, the relevant attribute was ellipse size and the required responses were the numbers 1 through 6 assigned to each of the ellipses in order of increasing size. The irrelevant attribute consisted of either alphabet letters or the numerical symbols 1 through 6 displayed in the center of each ellipse. The numerals produced more interference with the classification of the relevant attribute than the alphabet letters, supporting Klein’s (1964) results. In addition, the interference due to the irrelevant numerical symbols increased as the distance between the values of the relevant and irrelevant attributes was decreased. Since “distance” is a structural property of the number system, this indicated that the competing response tendencies aroused by the irrelevant numericals involved the semantic structure for numbers. The same results were obtained when numerical quantity, rather than ellipse size, was the relevant attribute.     

Stimulus averaging and the context for judgment

Loudness judgments of stimulus sets composed of four bursts of noise were analyzed for two types of contextual effects: between-set and within-set. Experiment I demonstrated between-set effects for these four-component stimuli; they were shown to be similar to those found in previous work with single stimuli. Experiment 2 tested an averaging model for within-set contextual effects. The results were inconsistent with the model. One interpretation is that there are within-set effects and that these are caused by shifts in the effective range of stimuli. Alternative interpretations attribute the apparent contextual effects either to an averaging of physical values or to an inappropriate scale of judgment.     

An inexpensive circuit for beta,alpha, theta,or delta EEG biofeedback

An inexpensive circuit is described for EEG biofeedback or measurement. The circuit is designed to interface easily with most basic EEG machines. It taps the output from a single recording channel of the basic EEG instrument and provides the following for each EEG band (beta, alpha, theta, and delta): (a) very selective bandpass discrimination, (b) variable center frequency, (c) variable threshold at which feedback will be provided, or the measurement made, and (d) use with any biofeedback stimulus or measurement device that one wishes to switch contingent with S’s EEG rhythms.