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At least 73 records · Page 4Linked to original sources
PubMed1983

Probability learning in pigeons (Columba livia) is not impaired by hyperstriatal lesions.

Three experiments investigated the effects of hyperstriatal lesions on spatial and visual probability learning in pigeons. The lesions did not affect choice accuracy although they did reduce positional responding on error trials in the visual task. The results gave support to a perseverative, as opposed to an attentional, interpretation of the lesion effects. Increasing intertrial interval in the visual task resulted in decreased accuracy in both lesion and control groups, and the absence of a differential effect on the lesioned birds ran counter to an earlier suggestion that increased perseveration might be due to increased frustration. A fourth experiment confirmed that the lesions disrupted both acquisition and reversal of a conventional orientation discrimination; the deficits again appeared to be due to increased perseveration rather than to shifts in attention.

Analysis of Variance↗
PubMed2002

Web-based experiments controlled by JavaScript: an example from probability learning.

JavaScript programs can be used to control Web experiments. This technique is illustrated by an experiment that tested the effects of advice on performance in the classic probability-learning paradigm. Previous research reported that people tested via the Web or in the lab tended to match the probabilities of their responses to the probabilities that those responses would be reinforced. The optimal strategy, however, is to consistently choose the more frequent event; probability matching produces suboptimal performance. We investigated manipulations we reasoned should improve performance. A horse race scenario in which participants predicted the winner in each of a series of races between two horses was compared with an abstract scenario used previously. Ten groups of learners received different amounts of advice, including all combinations of (1) explicit instructions concerning the optimal strategy, (2) explicit instructions concerning a monetary sum to maximize, and (3) accurate information concerning the probabilities of events. The results showed minimal effects of horse race versus abstract scenario. Both advice concerning the optimal strategy and probability information contributed significantly to performance in the task. This paper includes a brief tutorial on JavaScript, explaining with simple examples how to assemble a browser-based experiment.

Computer-Assisted Instruction↗
PubMed1978

Effects of low concentrations of enflurane on probability learning.

The effects of controlled subanaesthetic concentrations of enflurane on learning behaviour and on ability to change previously developed decision strategies were studied in 10 male volunteers, using a probability learning task. Subjects were instructed to predict on each of 200 consecutive trials, whether a left or a right light would appear. The appearance of lights was pre-determined by a set relative frequency unknown to the subject. The relative frequency was automatically changed at the end of the first 100 trials, from 8/10 lights in the left side to 4/10. It was found that enflurane at subanaesthetic concentration of 0.25% (end-tidal) slowed the rate of learning, and increased the number of trials required for readjusting the prediction strategy to the changed situation.

Adult↗
PubMed1976

Spatial probability learning by alcoholic Korsakoff patients.

Performance of 10 alcoholic Korsakoff patients was compared to that of 10 normal and 10 alcoholic control subjects on each of three different schedules of spatial probability learning (50:50, 70:30, and 30:70) using monetary reinforcement and a correction procedure. There was some evidence that the Korsakoff patients were less sensitive than normals to the effects of reward: Although on all three schedules, choice ratios by normal subjects approximated the reinforcement ratios, the choice ratios of Korsakoffs on the second and third schedules remained close to the reinforcement ratio acquired with the first schedule. In addition, the Korsakoffs made an abnormal number of perseverative errors early in training. On most measures, performance by alcoholic controls fell between that of the other two groups.

Adult↗
PubMed1976

Spatial probability learning by alcoholic Korsakoff patients.

Performance of 10 alcoholic Korsakoff patients was compared to that of 10 normal and 10 alcoholic control subjects on each of three different schedules of spatial probability learning (50:50, 70:30, and 30:70) using monetary reinforcement and a correction procedure. There was some evidence that the Korsakoff patients were less sensitive than normals to the effects of reward: Although on all three schedules, choice ratios by normal subjects approximated the reinforcement ratios, the choice ratios of Korsakoffs on the second and third schedules remained close to the reinforcement ratio acquired with the first schedule. In addition, the Korsakoffs made an abnormal number of perseverative errors early in training. On most measures, performance by alcoholic controls fell between that of the other two groups.

Adult↗
PubMed1980

Probability learning and aging.

The performance of 48 young (ages 18--20) and 48 old (mean age = 78) adult Ss was studied in a probability learning task which used different reinforcement procedures and material rewards. In the course of learning, the noncorrection procedure was associated with a greater tendency to choose the majority stimulus than was the correction procedure, but this difference was not maintained. All Ss chose the majority stimulus less often than did rats despite the fact that the experimental procedure was based on that used in animal experiments. An interaction effect was found between age level and sex, such that the young women and the old men chose the majority stimulus more than the young men and old women, respectively. It was suggested that the results could imply an increase in rigidity and cautiousness with age in men and a decrease in these qualities with age in women. This suggestion was shown to be consistent with findings reported by other psychologists showing sex differences in personality change associated with aging.

Adolescent↗
PubMed1984

Curiosity and demographic factors as determinants of children's probability-learning strategies.

Children's curiosity, gender, activity level, and socioeconomic status (SES) were related to their performance on a partially reinforced discrimination-learning task. The 38 boys and 37 girls were in the first grade and were all white. Three factors of curiosity (manipulatory, conceptual, and about the complex) were assessed. Performance on the learning task was scored for the number of correct responses (maximizing) and for the frequency of three-step sequences reflecting variability, systematic patterning, and perseveration. In general, the three curiosity factors related negatively to maximizing and perseveration and positively to variability. (The same effects were found for activity level.) Systematic patterning related positively to one curiosity type and negatively to another. Girls used less maximizing and more systematic patterning than boys. The response choices of girls were affected more by differences in conceptual curiosity and those of boys by differences in curiosity about the complex. Activity level was unrelated to gender but differed with SES. The findings demonstrate the role of different curiosity factors in shaping response sequences and suggest some reasons for children's choice of probability-learning strategies.

Child↗