ArticleiScience2024
Profiles of visual perceptual learning in feature space.
Article in iScience, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- The curriculum effect in visual learning: The role of readout dimensionality.PLoS computational biology · 2026Article
- Article
- Category-specific perceptual learning of robust object recognition modelled using deep neural networks.PLoS computational biology · 2025Article
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8 authors.
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Abstract
Visual perceptual learning (VPL), experience-induced gains in discriminating visual features, has been studied extensively and intensively for many years, its profile in feature space, however, remains unclear. Here, human subjects were trained to perform either a simple low-level feature (grating orientation) or a complex high-level object (face view) discrimination task over a long-time course. During, immediately after, and one month after training, all results showed that in feature space VPL in grating orientation discrimination was a center-surround profile; VPL in face view discrimination, however, was a monotonic gradient profile. Importantly, these two profiles can be emerged by a deep convolutional neural network with a modified AlexNet consisted of 7 and 12 layers, respectively. Altogether, our study reveals for the first time a feature hierarchy-dependent profile of VPL in feature space, placing a necessary constraint on our understanding of the neural computation of VPL.
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