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A lightweight data-driven spiking neural network model of Drosophila olfactory nervous system with dedicated hardware support

Takuya Nanami, Daichi Yamada, Makoto Someya, Toshihide Hige, Hokto Kazama, Takashi Kohno
doi: https://doi.org/10.1101/2023.10.12.560618

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doi 
https://doi.org/10.1101/2023.10.12.560618
History 
  • October 13, 2023.
Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. All rights reserved. No reuse allowed without permission.

Author Information

  1. Takuya Nanami1,*,
  2. Daichi Yamada2,
  3. Makoto Someya5,
  4. Toshihide Hige2,3,4,
  5. Hokto Kazama5 and
  6. Takashi Kohno1
  1. 1Institute of Industrial Science, The University of Tokyo, Tokyo, Japan
  2. 2Department of Biology, University of North Carolina at Chapel Hill, Chapel Hill, United States
  3. 3Department of Cell Biology and Physiology, University of North Carolina at Chapel Hill, Chapel Hill, United States
  4. 4Integrative Program for Biological and Genome Sciences, University of North Carolina at Chapel Hill, Chapel Hill, United States
  5. 5RIKEN Center for Brain Science, Saitama, Japan
  1. ↵*Corresponding authors
    Correspondence to Takuya Nanami; email: nanami{at}iis.u-tokyo.ac.jp
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Posted October 13, 2023.
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A lightweight data-driven spiking neural network model of Drosophila olfactory nervous system with dedicated hardware support
Takuya Nanami, Daichi Yamada, Makoto Someya, Toshihide Hige, Hokto Kazama, Takashi Kohno
bioRxiv 2023.10.12.560618; doi: https://doi.org/10.1101/2023.10.12.560618
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