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Network: Computation in Neural Systems Volume 14, 2003 - Issue 2
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Original Article

Nonlinear ideal observation and recurrent preprocessing in perceptual learning

L Zhaoping Department of Psychology, University College, London, WC1E 6BT, UK
,
Michael H Herzog Human Neurobiology, Argonnenstrasse 3, 28211, Bremen, Germany
&
Peter Dayan Gatsby Computational Neuroscience Unit, University College, London, WC1N 3AR, UK
Pages 233-247 | Received 24 Apr 2002, Published online: 09 Jul 2009

Citations (18)

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Reza Moazzezi & Peter Dayan. (2008) Change-based inference for invariant discrimination. Network: Computation in Neural Systems 19:3, pages 236-252.
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Articles from other publishers (17)

Giorgio L. Manenti, Aslan S. Dizaji & Caspar M. Schwiedrzik. (2023) Variability in training unlocks generalization in visual perceptual learning through invariant representations. Current Biology 33:5, pages 817-826.e3.
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Zhong-Lin Lu & Barbara Anne Dosher. (2022) Current directions in visual perceptual learning. Nature Reviews Psychology 1:11, pages 654-668.
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Ryo Tani & Yoshiki Kashimori. (2021) Coordination of top-down influence on V1 responses by interneurons and brain rhythms. Biosystems 207, pages 104452.
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Aaron R. Seitz. (2020) Perceptual Learning: How Does the Visual Circuit Change through Experience?. Current Biology 30:21, pages R1309-R1311.
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C. Shawn Green, Karen Banai, Zhong‐Lin Lu & Daphne Bavelier. 2018. Stevens' Handbook of Experimental Psychology and Cognitive Neuroscience. Stevens' Handbook of Experimental Psychology and Cognitive Neuroscience 1 47 .
Barbara DosherZhong-Lin Lu. (2017) Visual Perceptual Learning and Models. Annual Review of Vision Science 3:1, pages 343-363.
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Fang Wang, Jing Huang, Yaping Lv, Xiaoli Ma, Bin Yang, Encong Wang, Boqi Du, Wu Li & Yan Song. (2016) Predicting perceptual learning from higher-order cortical processing. NeuroImage 124, pages 682-692.
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Zhe Qu, You Wang, Yanfen Zhen, Liping Hu, Yan Song & Yulong Ding. (2014) Brain mechanisms underlying behavioral specificity and generalization of short-term texture discrimination learning. Vision Research 105, pages 166-176.
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Han Yan, Lei ZhaoLiang HuXidi Wang, Erkang WangJin Wang. (2013) Nonequilibrium landscape theory of neural networks. Proceedings of the National Academy of Sciences 110:45.
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Barbara Anne Dosher, Pamela Jeter, Jiajuan Liu & Zhong-Lin Lu. (2013) An integrated reweighting theory of perceptual learning. Proceedings of the National Academy of Sciences 110:33, pages 13678-13683.
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Roland Schäfer, Eleni Vasilaki & Walter Senn. (2009) Adaptive Gain Modulation in V1 Explains Contextual Modifications during Bisection Learning. PLoS Computational Biology 5:12, pages e1000617.
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Elisa M. Tartaglia, Kristoffer C. Aberg & Michael H. Herzog. (2009) Modeling perceptual learning: Why mice do not play backgammon. Learning & Perception 1:1, pages 155-163.
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Roland Schäfer, Eleni Vasilaki & Walter Senn. (2007) Perceptual Learning via Modification of Cortical Top-Down Signals. PLoS Computational Biology 3:8, pages e165.
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Alexander A. Petrov, Barbara Anne Dosher & Zhong-Lin Lu. (2006) Perceptual learning without feedback in non-stationary contexts: Data and model. Vision Research 46:19, pages 3177-3197.
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Thomas U. Otto, Michael H. Herzog, Manfred Fahle & Li Zhaoping. (2006) Perceptual learning with spatial uncertainties. Vision Research 46:19, pages 3223-3233.
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Aaron R. Seitz, Noriko Yamagishi, Birgit Werner, Naokazu Goda, Mitsuo Kawato & Takeo Watanabe. (2005) Task-specific disruption of perceptual learning. Proceedings of the National Academy of Sciences 102:41, pages 14895-14900.
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Misha Tsodyks & Charles Gilbert. (2004) Neural networks and perceptual learning. Nature 431:7010, pages 775-781.
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