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Open Access
Peer-reviewed
Research Article
Deep convolutional models improve predictions of macaque V1 responses to natural images
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Santiago A. Cadena ,
Roles Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration, Software, Validation, Visualization, Writing – original draft, Writing – review & editing
* E-mail: santiago.cadena@uni-tuebingen.de
Affiliations Centre for Integrative Neuroscience and Institute for Theoretical Physics, University of Tübingen, Tübingen, Germany, Bernstein Center for Computational Neuroscience, Tübingen, Germany, Center for Neuroscience and Artificial Intelligence, Baylor College of Medicine, Houston, Texas, United States of America
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George H. Denfield,
Roles Formal analysis, Investigation, Methodology, Writing – review & editing
Affiliations Center for Neuroscience and Artificial Intelligence, Baylor College of Medicine, Houston, Texas, United States of America, Department of Neuroscience, Baylor College of Medicine, Houston, Houston, Texas, United States of America
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Edgar Y. Walker,
Roles Formal analysis, Investigation, Methodology, Resources, Software
Affiliations Center for Neuroscience and Artificial Intelligence, Baylor College of Medicine, Houston, Texas, United States of America, Department of Neuroscience, Baylor College of Medicine, Houston, Houston, Texas, United States of America
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Leon A. Gatys,
Roles Investigation, Methodology, Software, Writing – review & editing
Affiliations Centre for Integrative Neuroscience and Institute for Theoretical Physics, University of Tübingen, Tübingen, Germany, Bernstein Center for Computational Neuroscience, Tübingen, Germany
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Andreas S. Tolias ,
Contributed equally to this work with: Andreas S. Tolias, Matthias Bethge, Alexander S. Ecker
Roles Conceptualization, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Supervision, Writing – original draft, Writing – review & editing
Affiliations Bernstein Center for Computational Neuroscience, Tübingen, Germany, Center for Neuroscience and Artificial Intelligence, Baylor College of Medicine, Houston, Texas, United States of America, Department of Neuroscience, Baylor College of Medicine, Houston, Houston, Texas, United States of America, Department of Electrical and Computer Engineering, Rice University, Houston, Houston, Texas, United States of America
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Matthias Bethge ,
Contributed equally to this work with: Andreas S. Tolias, Matthias Bethge, Alexander S. Ecker
Roles Conceptualization, Funding acquisition, Investigation, Methodology, Resources, Supervision, Validation, Writing – original draft, Writing – review & editing
Affiliations Centre for Integrative Neuroscience and Institute for Theoretical Physics, University of Tübingen, Tübingen, Germany, Bernstein Center for Computational Neuroscience, Tübingen, Germany, Center for Neuroscience and Artificial Intelligence, Baylor College of Medicine, Houston, Texas, United States of America, Max Planck Institute for Biological Cybernetics, Tübingen, Germany
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Alexander S. Ecker
Contributed equally to this work with: Andreas S. Tolias, Matthias Bethge, Alexander S. Ecker
Roles Conceptualization, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Writing – original draft, Writing – review & editing
Affiliations Centre for Integrative Neuroscience and Institute for Theoretical Physics, University of Tübingen, Tübingen, Germany, Bernstein Center for Computational Neuroscience, Tübingen, Germany, Center for Neuroscience and Artificial Intelligence, Baylor College of Medicine, Houston, Texas, United States of America
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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
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- Published: April 23, 2019
- https://doi.org/10.1371/journal.pcbi.1006897
- See the preprint