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Deep convolutional models improve predictions of macaque V1 responses to natural images

Santiago A. Cadena, George H. Denfield, View ORCID ProfileEdgar Y. Walker, Leon A. Gatys, Andreas S. Tolias, Matthias Bethge, Alexander S. Ecker
doi: https://doi.org/10.1101/201764
Santiago A. Cadena
1Centre for Integrative Neuroscience and Institute for Theoretical Physics, University of Tübingen, 72076 Tübingen, Germany
3Bernstein Center for Computational Neuroscience, 72076 Tübingen, Germany
6Center for Neuroscience and Artificial Intelligence, BCM. 77030 Houston, TX, USA
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George H. Denfield
4Department of Neuroscience, Baylor College of Medicine, 77030 Houston, TX, USA
6Center for Neuroscience and Artificial Intelligence, BCM. 77030 Houston, TX, USA
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Edgar Y. Walker
4Department of Neuroscience, Baylor College of Medicine, 77030 Houston, TX, USA
6Center for Neuroscience and Artificial Intelligence, BCM. 77030 Houston, TX, USA
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  • ORCID record for Edgar Y. Walker
Leon A. Gatys
1Centre for Integrative Neuroscience and Institute for Theoretical Physics, University of Tübingen, 72076 Tübingen, Germany
3Bernstein Center for Computational Neuroscience, 72076 Tübingen, Germany
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Andreas S. Tolias
3Bernstein Center for Computational Neuroscience, 72076 Tübingen, Germany
4Department of Neuroscience, Baylor College of Medicine, 77030 Houston, TX, USA
5Department of Electrical and Computer Engineering, Rice University, 77030 Houston, TX, USA
6Center for Neuroscience and Artificial Intelligence, BCM. 77030 Houston, TX, USA
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Matthias Bethge
1Centre for Integrative Neuroscience and Institute for Theoretical Physics, University of Tübingen, 72076 Tübingen, Germany
2Max Planck Institute for Biological Cybernetics, 72076 Tübingen, Germany
3Bernstein Center for Computational Neuroscience, 72076 Tübingen, Germany
6Center for Neuroscience and Artificial Intelligence, BCM. 77030 Houston, TX, USA
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Alexander S. Ecker
1Centre for Integrative Neuroscience and Institute for Theoretical Physics, University of Tübingen, 72076 Tübingen, Germany
3Bernstein Center for Computational Neuroscience, 72076 Tübingen, Germany
6Center for Neuroscience and Artificial Intelligence, BCM. 77030 Houston, TX, USA
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Article Information

doi 
https://doi.org/10.1101/201764
History 
  • November 5, 2018.

Article Versions

  • Version 1 (October 11, 2017 - 14:27).
  • You are viewing Version 2, the most recent version of this article.
Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.

Author Information

  1. Santiago A. Cadena1,3,6,*,
  2. George H. Denfield4,6,
  3. Edgar Y. Walker4,6,
  4. Leon A. Gatys1,3,
  5. Andreas S. Tolias☯,3,4,5,6,
  6. Matthias Bethge☯,1,2,3,6 and
  7. Alexander S. Ecker☯,1,3,6
  1. 1Centre for Integrative Neuroscience and Institute for Theoretical Physics, University of Tübingen, 72076 Tübingen, Germany
  2. 2Max Planck Institute for Biological Cybernetics, 72076 Tübingen, Germany
  3. 3Bernstein Center for Computational Neuroscience, 72076 Tübingen, Germany
  4. 4Department of Neuroscience, Baylor College of Medicine, 77030 Houston, TX, USA
  5. 5Department of Electrical and Computer Engineering, Rice University, 77030 Houston, TX, USA
  6. 6Center for Neuroscience and Artificial Intelligence, BCM. 77030 Houston, TX, USA
  1. ↵☯ These authors contributed equally to this work.

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Posted November 05, 2018.
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Deep convolutional models improve predictions of macaque V1 responses to natural images
Santiago A. Cadena, George H. Denfield, Edgar Y. Walker, Leon A. Gatys, Andreas S. Tolias, Matthias Bethge, Alexander S. Ecker
bioRxiv 201764; doi: https://doi.org/10.1101/201764
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Deep convolutional models improve predictions of macaque V1 responses to natural images
Santiago A. Cadena, George H. Denfield, Edgar Y. Walker, Leon A. Gatys, Andreas S. Tolias, Matthias Bethge, Alexander S. Ecker
bioRxiv 201764; doi: https://doi.org/10.1101/201764

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