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Robust-fit to nature: an evolutionary perspective on biological (and artificial) neural networks

View ORCID ProfileUri Hasson, View ORCID ProfileSamuel A. Nastase, Ariel Goldstein
doi: https://doi.org/10.1101/764258
Uri Hasson
1Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA
2Department of Psychology, Princeton University, Princeton, NJ, USA
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  • ORCID record for Uri Hasson
  • For correspondence: hasson@princeton.edu
Samuel A. Nastase
1Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA
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Ariel Goldstein
1Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA
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Article Information

doi 
https://doi.org/10.1101/764258
History 
  • September 10, 2019.

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  • You are currently viewing Version 1 of this article (September 10, 2019 - 11:14).
  • Version 2 (October 4, 2019 - 12:31).
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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. Uri Hasson1,2,*,
  2. Samuel A. Nastase1 and
  3. Ariel Goldstein1
  1. 1Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA
  2. 2Department of Psychology, Princeton University, Princeton, NJ, USA
  1. ↵*Corresponding author: hasson{at}princeton.edu
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Posted September 10, 2019.
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Robust-fit to nature: an evolutionary perspective on biological (and artificial) neural networks
Uri Hasson, Samuel A. Nastase, Ariel Goldstein
bioRxiv 764258; doi: https://doi.org/10.1101/764258
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Robust-fit to nature: an evolutionary perspective on biological (and artificial) neural networks
Uri Hasson, Samuel A. Nastase, Ariel Goldstein
bioRxiv 764258; doi: https://doi.org/10.1101/764258

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