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The formation of linked perceptual classes.
Lanny Fields1, Priya Matneja, Antonios Varelas
1Department of Psychology, Queens College and The Graduate School and University Center of the City University of New York, Flushing 11367, USA.
Journal of the Experimental Analysis of Behavior
|January 1, 2003
Summary
Multiple-exemplar training established new perceptual classes. Linked perceptual classes emerged immediately or after a delay, demonstrating similarities with other learned categories and informing intersensory perception.
Area of Science:
- Psychology
- Cognitive Science
- Behavioral Science
Background:
- Perceptual learning is crucial for categorization.
- Understanding how novel perceptual classes form and link is key to cognitive development.
- Existing research explores stimulus generalization and class formation.
Purpose of the Study:
- To investigate the emergence of linked perceptual classes using multiple-exemplar training.
- To determine if training on different stimulus domains (fill-based and satellite-image-based) leads to linked classes.
- To assess the timing of linked class emergence (immediate vs. delayed).
Main Methods:
- Multiple-exemplar training across four domains.
- Establishing conditional discriminations between specific perceptual classes (A1'/B1' and A2'/B2').
- Evaluating linked class emergence through serial and concurrent cross-class probes.
Main Results:
- Two new fill-based (A1', A2') and satellite-image-based (B1', B2') perceptual classes were induced.
- Conditional discriminations were successfully established.
- 70% of linked perceptual classes emerged during the serial test, with an additional 20% emerging during the concurrent test.
Conclusions:
- Linked perceptual classes can emerge on an immediate or delayed basis following training.
- The findings suggest shared structural and functional similarities between these emergent classes and other known categories like equivalence classes.
- This research may offer insights into the mechanisms underlying intersensory perception and complex categorization.