Feature-saliency and feedback-information interactively impact visual category learning
Visual category learning (VCL) involves detecting which features are most relevant for categorization. This requires attentional learning, which allows effectively redirecting attention to object’s features most relevant for categorization while also filtering out irrelevant features. When features...
Main Authors: | Rubi eHammer, Vladimir eSloutsky, Kalanit eGrill-Spector |
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Format: | Article |
Language: | English |
Published: |
Frontiers Media S.A.
2015-02-01
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Series: | Frontiers in Psychology |
Subjects: | |
Online Access: | http://journal.frontiersin.org/Journal/10.3389/fpsyg.2015.00074/full |
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