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Explaining Visual Cortex Phenomena using Recursive Cortical Network

Alexander Lavin, View ORCID ProfileJ. Swaroop Guntupalli, Miguel Lázaro-Gredilla, Wolfgang Lehrach, Dileep George
doi: https://doi.org/10.1101/380048
Alexander Lavin
Vicarious AI, San Francisco, USA
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J. Swaroop Guntupalli
Vicarious AI, San Francisco, USA
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Miguel Lázaro-Gredilla
Vicarious AI, San Francisco, USA
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Wolfgang Lehrach
Vicarious AI, San Francisco, USA
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Dileep George
Vicarious AI, San Francisco, USA
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Abstract

The connectivity and information pathways of visual cortex are well studied, as are observed physiological phenomena, yet a cohesive model for explaining visual cortex processes remains an open problem. For a comprehensive understanding, we need to build models of the visual cortex that are capable of robust real-world performance, while also being able to explain psychophysical and physiological observations. To this end, we demonstrate how the Recursive Cortical Network (George et al., 2017) can be used as a computational model to reproduce and explain subjective contours, neon color spreading, occlusion vs. deletion, and the border-ownership competition phenomena observed in the visual cortex.

Footnotes

  • {alex{at}vicarious.com, swaroop{at}vicarious.com, miguel{at}vicarious.com, wolfgang{at}vicarious.com, dileep{at}vicarious.com}

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-NC-ND 4.0 International license.
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Posted July 30, 2018.
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Explaining Visual Cortex Phenomena using Recursive Cortical Network
Alexander Lavin, J. Swaroop Guntupalli, Miguel Lázaro-Gredilla, Wolfgang Lehrach, Dileep George
bioRxiv 380048; doi: https://doi.org/10.1101/380048
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Explaining Visual Cortex Phenomena using Recursive Cortical Network
Alexander Lavin, J. Swaroop Guntupalli, Miguel Lázaro-Gredilla, Wolfgang Lehrach, Dileep George
bioRxiv 380048; doi: https://doi.org/10.1101/380048

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