Adaptation aftereffects reveal how categorization training changes the encoding of face identity

Area of Science:

• Cognitive Psychology
• Neuroscience
• Computational Vision

Background:

• Categorization learning is thought to create novel perceptual dimensions.
• Previous studies suggest categorization training alters face representation.

Purpose of the Study:

• To investigate whether face categorization training creates novel dimensions or enhances existing ones.
• To explore the impact of training on face identity encoding.

Main Methods:

• Participants categorized faces varying along relevant and irrelevant dimensions.
• Face adaptation aftereffects were used to probe perceptual changes.
• Comparison between trained and untrained groups.

Main Results:

• Categorization training did not create novel representations.
• Existing norm-based coding of face identity was enhanced.
• The category-relevant dimension was not encoded as a preferred direction.

Conclusions:

• Face categorization training strengthens existing norm-based coding mechanisms.
• Novel perceptual dimensions are not created through this type of training.
• A computational model was developed to explain these findings.