Category learning and visual perception are fundamentally interactive processes, such that successful categorization often depends on the ability to make fine visual discriminations between stimuli that vary on continuously valued dimensions. Research suggests that category learning can improve perceptual discrimination along the stimulus dimensions that predict category membership and that these perceptual enhancements are a byproduct of functional plasticity in the visual system. However, the precise mechanisms underlying learning-dependent sensory modulation in categorization are not well understood. We hypothesized that category learning leads to a representational sharpening of underlying sensory populations tuned to values at or near the category boundary. Furthermore, such sharpening should occur largely during active learning of new categories. These hypotheses were tested using fMRI and a theoretically constrained model of vision to quantify changes in the shape of orientation representations while human adult subjects learned to categorize physically identical stimuli based on either an orientation rule (
- Award ID(s):
- 1847603
- NSF-PAR ID:
- 10421956
- Date Published:
- Journal Name:
- Journal of Cognitive Neuroscience
- Volume:
- 34
- Issue:
- 10
- ISSN:
- 0898-929X
- Page Range / eLocation ID:
- 1761 to 1779
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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N = 12) or an orthogonal spatial frequency rule (N = 13). Consistent with our predictions, modeling results revealed relatively enhanced reconstructed representations of stimulus orientation in visual cortex (V1–V3) only for orientation rule learners. Moreover, these reconstructed representations varied as a function of distance from the category boundary, such that representations for challenging stimuli near the boundary were significantly sharper than those for stimuli at the category centers. These results support an efficient model of plasticity wherein only the sensory populations tuned to the most behaviorally relevant regions of feature space are enhanced during category learning. -
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1162/jocn_a_01882
