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Retinal-specific category learning

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Virtually all cognitive theories of category learning (such as prototype theory1–5 and exemplar theory6–8) view this important skill as a high-level process that uses abstract representations of objects in the… Click to show full abstract

Virtually all cognitive theories of category learning (such as prototype theory1–5 and exemplar theory6–8) view this important skill as a high-level process that uses abstract representations of objects in the world. Because these representations are removed from visual characteristics of the display, such theories suggest that category learning occurs in higher-level (such as association) areas and therefore should be immune to the visual field dependencies that characterize processing of objects mediated by representations in low-level visual areas. Here we challenge that view by describing a fully controlled demonstration of visual-field dependence in category learning. Eye-tracking was used to control gaze while participants either learned rule-based categories known to recruit prefrontal-based explicit reasoning, or information-integration categories known to depend on basal-ganglia-mediated procedural learning9. Results showed that learning was visual-field dependent with information-integration categories, but we found no evidence of visual-field dependence with rule-based categories. A theoretical interpretation of this difference is offered in terms of the underlying neurobiology. Finally, these results are situated within the broad perceptual-learning literature in an attempt to motivate further research on the similarities and differences between category and perceptual learning.Category learning has been traditionally viewed as a high-level cognitive process independent of sensory systems. Rosedahl and colleagues demonstrate that procedural category learning is in fact dependent on low-level visual representations.

Keywords: category; category learning; retinal specific; level; visual field

Journal Title: Nature Human Behaviour
Year Published: 2018

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