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  Distributed Neural Plasticity for Shape Learning in the Human Visual Cortex

Kourtzi, Z., Betts, L., Sarkheil, P., & Welchman, A. (2005). Distributed Neural Plasticity for Shape Learning in the Human Visual Cortex. PLoS Biology, 3(7), 1317-1327. doi:10.1371/journal.pbio.0030204.

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Item Permalink: http://hdl.handle.net/11858/00-001M-0000-0013-D549-7 Version Permalink: http://hdl.handle.net/21.11116/0000-0004-D7B1-1
Genre: Journal Article

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Kourtzi, Z1, 2, 3, Author              
Betts, LR, Author              
Sarkheil, P1, 2, 3, Author              
Welchman, AE1, 3, Author              
Affiliations:
1Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497797              
2Department Physiology of Cognitive Processes, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497798              
3Max Planck Institute for Biological Cybernetics, Max Planck Society, Spemannstrasse 38, 72076 Tübingen, DE, ou_1497794              

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 Abstract: Expertise in recognizing objects in cluttered scenes is a critical skill for our interactions in complex environments and is thought to develop with learning. However, the neural implementation of object learning across stages of visual analysis in the human brain remains largely unknown. Using combined psychophysics and functional magnetic resonance imaging (fMRI), we show a link between shape-specific learning in cluttered scenes and distributed neuronal plasticity in the human visual cortex. We report stronger fMRI responses for trained than untrained shapes across early and higher visual areas when observers learned to detect low-salience shapes in noisy backgrounds. However, training with high-salience pop-out targets resulted in lower fMRI responses for trained than untrained shapes in higher occipitotemporal areas. These findings suggest that learning of camouflaged shapes is mediated by increasing neural sensitivity across visual areas to bolster target segmentation and feature integration. In contrast, learning of prominent pop-out shapes is mediated by associations at higher occipitotemporal areas that support sparser coding of the critical features for target recognition. We propose that the human brain learns novel objects in complex scenes by reorganizing shape processing across visual areas, while taking advantage of natural image correlations that determine the distinctiveness of target shapes.

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 Dates: 2005-06
 Publication Status: Published in print
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 Table of Contents: -
 Rev. Type: -
 Identifiers: DOI: 10.1371/journal.pbio.0030204
BibTex Citekey: 3474
eDoc: e204
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Title: PLoS Biology
  Other : PLoS Biol.
Source Genre: Journal
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Publ. Info: San Francisco, California, US : Public Library of Science
Pages: - Volume / Issue: 3 (7) Sequence Number: - Start / End Page: 1317 - 1327 Identifier: ISSN: 1544-9173
CoNE: https://pure.mpg.de/cone/journals/resource/111056649444170