Category effects on stimulus estimation: shifting and skewed frequency distributions

Area of Science:

• Cognitive Psychology
• Memory Research
• Perceptual Learning

Background:

• The category adjustment model (CAM) suggests memory estimates shift towards a category's central value.
• Previous CAM research used symmetrical distributions, where the central value and mean align.
• The model's predictions in asymmetric distributions remain under-explored.

Purpose of the Study:

• To test the category adjustment model (CAM) with asymmetric (skewed) frequency distributions.
• To determine if memory estimates adjust towards the category's mean or another central value under skewed conditions.

Main Methods:

• Two experiments were conducted using asymmetric stimulus distributions.
• Experiment 1 involved a shifting frequency distribution over time.
• Experiment 2 utilized a static, skewed frequency distribution.

Main Results:

• Participants consistently adjusted their estimates towards the running mean of the category.
• This adjustment pattern was observed in both shifting and skewed distribution experiments.
• Findings support the CAM's prediction of adjustment towards the mean, even in asymmetric distributions.

Conclusions:

• Memory estimates are adjusted towards the category's running mean, even when distributions are asymmetric.
• This supports the category adjustment model (CAM) over alternative explanations.
• The CAM effectively predicts memory adjustments in more complex, real-world scenarios.