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Category representation in primary visual cortex after visual perceptual learning.
Liu, Zhaofan; Yan, Yin; Wang, Da-Hui.
Affiliation
  • Liu Z; School of Systems Science, Beijing Normal University, Beijing, 100875 China.
  • Yan Y; State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Xinjiekouwaidajie 19, Haidian, Beijing, 100875 China.
  • Wang DH; Chinese Institute for Brain Research, Beijing, China.
Cogn Neurodyn ; 18(1): 23-35, 2024 Feb.
Article in En | MEDLINE | ID: mdl-38406201
ABSTRACT
The visual perceptual learning (VPL) leads to long-term enhancement of visual task performance. The subjects are often trained to link different visual stimuli to several options, such as the widely used two-alternative forced choice (2AFC) task, which involves an implicit categorical decision. The enhancement of performance has been related to the specific changes of neural activities, but few studies investigate the effects of categorical responding on the changes of neural activities. Here we investigated whether the neural activities would exhibit the categorical characteristics if the subjects are requested to respond visual stimuli in a categorical manner during VPL. We analyzed the neural activities of two monkeys in a contour detection VPL. We found that the neural activities in primary visual cortex (V1) converge to one pattern if the contour can be detected by monkey and another pattern if the contour cannot be detected, exhibiting a kind of category learning that the neural representations of detectable contour become less selective for number of bars forming contour and diverge from the representations of undetectable contour. Supplementary Information The online version contains supplementary material available at 10.1007/s11571-022-09926-8.
Key words

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Cogn Neurodyn Year: 2024 Document type: Article Country of publication:

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Cogn Neurodyn Year: 2024 Document type: Article Country of publication: