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A standardized and reproducible method to measure decision-making in mice

The International Brain Laboratory, Valeria Aguillon-Rodriguez, View ORCID ProfileDora E. Angelaki, View ORCID ProfileHannah M. Bayer, View ORCID ProfileNiccolò Bonacchi, View ORCID ProfileMatteo Carandini, View ORCID ProfileFanny Cazettes, View ORCID ProfileGaelle A. Chapuis, View ORCID ProfileAnne K. Churchland, View ORCID ProfileYang Dan, Eric E. Dewitt, Mayo Faulkner, Hamish Forrest, View ORCID ProfileLaura M. Haetzel, View ORCID ProfileMichael Hausser, View ORCID ProfileSonja B. Hofer, View ORCID ProfileFei Hu, View ORCID ProfileAnup Khanal, View ORCID ProfileChristopher S. Krasniak, Inês Laranjeira, View ORCID ProfileZachary F. Mainen, View ORCID ProfileGuido T. Meijer, View ORCID ProfileNathaniel J. Miska, View ORCID ProfileThomas D. Mrsic-Flogel, Masayoshi Murakami, View ORCID ProfileJean-Paul Noel, View ORCID ProfileAlejandro Pan-Vazquez, Josh I. Sanders, View ORCID ProfileKarolina Z. Socha, Rebecca Terry, View ORCID ProfileAnne E. Urai, View ORCID ProfileHernando M. Vergara, View ORCID ProfileMiles J. Wells, Christian J. Wilson, View ORCID ProfileIlana B. Witten, View ORCID ProfileLauren E. Wool, View ORCID ProfileAnthony Zador
doi: https://doi.org/10.1101/2020.01.17.909838
Dept. of Molecular and Cell Biology, University of California, Berkeley, CA, USA
  • For correspondence: info+behavior@internationalbrainlab.org
Valeria Aguillon-Rodriguez
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Dora E. Angelaki
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Hannah M. Bayer
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Niccolò Bonacchi
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Matteo Carandini
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Fanny Cazettes
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Gaelle A. Chapuis
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Anne K. Churchland
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Yang Dan
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Eric E. Dewitt
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Mayo Faulkner
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Hamish Forrest
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Laura M. Haetzel
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Michael Hausser
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Sonja B. Hofer
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Fei Hu
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Anup Khanal
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Christopher S. Krasniak
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Inês Laranjeira
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Zachary F. Mainen
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Guido T. Meijer
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Nathaniel J. Miska
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Thomas D. Mrsic-Flogel
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Masayoshi Murakami
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Jean-Paul Noel
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Alejandro Pan-Vazquez
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Josh I. Sanders
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Karolina Z. Socha
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Rebecca Terry
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Anne E. Urai
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Hernando M. Vergara
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Miles J. Wells
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Christian J. Wilson
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Ilana B. Witten
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Lauren E. Wool
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Anthony Zador
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Abstract

Progress in neuroscience is hindered by poor reproducibility of mouse behavior. Here we show that in a visual decision making task, reproducibility can be achieved by automating the training protocol and by standardizing experimental hardware, software, and procedures. We trained 101 mice in this task across seven laboratories at six different research institutions in three countries, and obtained 3 million mouse choices. In trained mice, variability in behavior between labs was indistinguishable from variability within labs. Psychometric curves showed no significant differences in visual threshold, bias, or lapse rates across labs. Moreover, mice across laboratories adopted similar strategies when stimulus location had asymmetrical probability that changed over time. We provide detailed instructions and open-source tools to set up and implement our method in other laboratories. These results establish a new standard for reproducibility of rodent behavior and provide accessible tools for the study of decision making in mice.

Footnotes

  • ↵1 Authors are listed alphabetically.

  • Edited to include links to additional online resources

  • https://doi.org/10.6084/m9.figshare.11636748

  • https://data.internationalbrainlab.org

  • https://github.com/int-brain-lab

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 4.0 International license.
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Posted January 19, 2020.
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A standardized and reproducible method to measure decision-making in mice
The International Brain Laboratory, Valeria Aguillon-Rodriguez, Dora E. Angelaki, Hannah M. Bayer, Niccolò Bonacchi, Matteo Carandini, Fanny Cazettes, Gaelle A. Chapuis, Anne K. Churchland, Yang Dan, Eric E. Dewitt, Mayo Faulkner, Hamish Forrest, Laura M. Haetzel, Michael Hausser, Sonja B. Hofer, Fei Hu, Anup Khanal, Christopher S. Krasniak, Inês Laranjeira, Zachary F. Mainen, Guido T. Meijer, Nathaniel J. Miska, Thomas D. Mrsic-Flogel, Masayoshi Murakami, Jean-Paul Noel, Alejandro Pan-Vazquez, Josh I. Sanders, Karolina Z. Socha, Rebecca Terry, Anne E. Urai, Hernando M. Vergara, Miles J. Wells, Christian J. Wilson, Ilana B. Witten, Lauren E. Wool, Anthony Zador
bioRxiv 2020.01.17.909838; doi: https://doi.org/10.1101/2020.01.17.909838
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A standardized and reproducible method to measure decision-making in mice
The International Brain Laboratory, Valeria Aguillon-Rodriguez, Dora E. Angelaki, Hannah M. Bayer, Niccolò Bonacchi, Matteo Carandini, Fanny Cazettes, Gaelle A. Chapuis, Anne K. Churchland, Yang Dan, Eric E. Dewitt, Mayo Faulkner, Hamish Forrest, Laura M. Haetzel, Michael Hausser, Sonja B. Hofer, Fei Hu, Anup Khanal, Christopher S. Krasniak, Inês Laranjeira, Zachary F. Mainen, Guido T. Meijer, Nathaniel J. Miska, Thomas D. Mrsic-Flogel, Masayoshi Murakami, Jean-Paul Noel, Alejandro Pan-Vazquez, Josh I. Sanders, Karolina Z. Socha, Rebecca Terry, Anne E. Urai, Hernando M. Vergara, Miles J. Wells, Christian J. Wilson, Ilana B. Witten, Lauren E. Wool, Anthony Zador
bioRxiv 2020.01.17.909838; doi: https://doi.org/10.1101/2020.01.17.909838

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