Deep convolutional models improve predictions of macaque V1 responses to natural images.
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| Title: | Deep convolutional models improve predictions of macaque V1 responses to natural images. |
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| Authors: | Cadena SA; 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., Denfield GH; 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., Walker EY; 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., Gatys LA; Centre for Integrative Neuroscience and Institute for Theoretical Physics, University of Tübingen, Tübingen, Germany.; Bernstein Center for Computational Neuroscience, Tübingen, Germany., Tolias AS; 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., Bethge M; 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., Ecker AS; 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. |
| Source: | PLoS computational biology [PLoS Comput Biol] 2019 Apr 23; Vol. 15 (4), pp. e1006897. Date of Electronic Publication: 2019 Apr 23 (Print Publication: 2019). |
| Publication Type: | Journal Article; Research Support, N.I.H., Extramural; Research Support, Non-U.S. Gov't; Research Support, U.S. Gov't, Non-P.H.S. |
| Journal Info: | Publisher: Public Library of Science Country of Publication: United States NLM ID: 101238922 Publication Model: eCollection Cited Medium: Internet ISSN: 1553-7358 (Electronic) Linking ISSN: 1553734X NLM ISO Abbreviation: PLoS Comput Biol Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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| ISSN: | 1553-7358 |
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| DOI: | 10.1371/journal.pcbi.1006897 |
