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Standardized and reproducible measurement of decision-making in mice
Progress in science requires standardized assays whose results can be readily shared, compared, and reproduced across laboratories. Reproducibility, however, has been a concern in neuroscience, particularly for measurements of mouse behavior. Here, we show that a standardized task to probe decision-...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
eLife Sciences Publications, Ltd
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8137147/ https://www.ncbi.nlm.nih.gov/pubmed/34011433 http://dx.doi.org/10.7554/eLife.63711 |
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author | Aguillon-Rodriguez, Valeria Angelaki, Dora Bayer, Hannah Bonacchi, Niccolo Carandini, Matteo Cazettes, Fanny Chapuis, Gaelle Churchland, Anne K Dan, Yang Dewitt, Eric Faulkner, Mayo Forrest, Hamish Haetzel, Laura Häusser, Michael Hofer, Sonja B Hu, Fei Khanal, Anup Krasniak, Christopher Laranjeira, Ines Mainen, Zachary F Meijer, Guido Miska, Nathaniel J Mrsic-Flogel, Thomas D Murakami, Masayoshi Noel, Jean-Paul Pan-Vazquez, Alejandro Rossant, Cyrille Sanders, Joshua Socha, Karolina Terry, Rebecca Urai, Anne E Vergara, Hernando Wells, Miles Wilson, Christian J Witten, Ilana B Wool, Lauren E Zador, Anthony M |
author_facet | Aguillon-Rodriguez, Valeria Angelaki, Dora Bayer, Hannah Bonacchi, Niccolo Carandini, Matteo Cazettes, Fanny Chapuis, Gaelle Churchland, Anne K Dan, Yang Dewitt, Eric Faulkner, Mayo Forrest, Hamish Haetzel, Laura Häusser, Michael Hofer, Sonja B Hu, Fei Khanal, Anup Krasniak, Christopher Laranjeira, Ines Mainen, Zachary F Meijer, Guido Miska, Nathaniel J Mrsic-Flogel, Thomas D Murakami, Masayoshi Noel, Jean-Paul Pan-Vazquez, Alejandro Rossant, Cyrille Sanders, Joshua Socha, Karolina Terry, Rebecca Urai, Anne E Vergara, Hernando Wells, Miles Wilson, Christian J Witten, Ilana B Wool, Lauren E Zador, Anthony M |
collection | PubMed |
description | Progress in science requires standardized assays whose results can be readily shared, compared, and reproduced across laboratories. Reproducibility, however, has been a concern in neuroscience, particularly for measurements of mouse behavior. Here, we show that a standardized task to probe decision-making in mice produces reproducible results across multiple laboratories. We adopted a task for head-fixed mice that assays perceptual and value-based decision making, and we standardized training protocol and experimental hardware, software, and procedures. We trained 140 mice across seven laboratories in three countries, and we collected 5 million mouse choices into a publicly available database. Learning speed was variable across mice and laboratories, but once training was complete there were no significant differences in behavior across laboratories. Mice in different laboratories adopted similar reliance on visual stimuli, on past successes and failures, and on estimates of stimulus prior probability to guide their choices. These results reveal that a complex mouse behavior can be reproduced across multiple laboratories. They establish a standard for reproducible rodent behavior, and provide an unprecedented dataset and open-access tools to study decision-making in mice. More generally, they indicate a path toward achieving reproducibility in neuroscience through collaborative open-science approaches. |
format | Online Article Text |
id | pubmed-8137147 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | eLife Sciences Publications, Ltd |
record_format | MEDLINE/PubMed |
spelling | pubmed-81371472021-05-21 Standardized and reproducible measurement of decision-making in mice Aguillon-Rodriguez, Valeria Angelaki, Dora Bayer, Hannah Bonacchi, Niccolo Carandini, Matteo Cazettes, Fanny Chapuis, Gaelle Churchland, Anne K Dan, Yang Dewitt, Eric Faulkner, Mayo Forrest, Hamish Haetzel, Laura Häusser, Michael Hofer, Sonja B Hu, Fei Khanal, Anup Krasniak, Christopher Laranjeira, Ines Mainen, Zachary F Meijer, Guido Miska, Nathaniel J Mrsic-Flogel, Thomas D Murakami, Masayoshi Noel, Jean-Paul Pan-Vazquez, Alejandro Rossant, Cyrille Sanders, Joshua Socha, Karolina Terry, Rebecca Urai, Anne E Vergara, Hernando Wells, Miles Wilson, Christian J Witten, Ilana B Wool, Lauren E Zador, Anthony M eLife Neuroscience Progress in science requires standardized assays whose results can be readily shared, compared, and reproduced across laboratories. Reproducibility, however, has been a concern in neuroscience, particularly for measurements of mouse behavior. Here, we show that a standardized task to probe decision-making in mice produces reproducible results across multiple laboratories. We adopted a task for head-fixed mice that assays perceptual and value-based decision making, and we standardized training protocol and experimental hardware, software, and procedures. We trained 140 mice across seven laboratories in three countries, and we collected 5 million mouse choices into a publicly available database. Learning speed was variable across mice and laboratories, but once training was complete there were no significant differences in behavior across laboratories. Mice in different laboratories adopted similar reliance on visual stimuli, on past successes and failures, and on estimates of stimulus prior probability to guide their choices. These results reveal that a complex mouse behavior can be reproduced across multiple laboratories. They establish a standard for reproducible rodent behavior, and provide an unprecedented dataset and open-access tools to study decision-making in mice. More generally, they indicate a path toward achieving reproducibility in neuroscience through collaborative open-science approaches. eLife Sciences Publications, Ltd 2021-05-20 /pmc/articles/PMC8137147/ /pubmed/34011433 http://dx.doi.org/10.7554/eLife.63711 Text en © 2021, The International Brain Laboratory et al https://creativecommons.org/licenses/by/4.0/This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited. |
spellingShingle | Neuroscience Aguillon-Rodriguez, Valeria Angelaki, Dora Bayer, Hannah Bonacchi, Niccolo Carandini, Matteo Cazettes, Fanny Chapuis, Gaelle Churchland, Anne K Dan, Yang Dewitt, Eric Faulkner, Mayo Forrest, Hamish Haetzel, Laura Häusser, Michael Hofer, Sonja B Hu, Fei Khanal, Anup Krasniak, Christopher Laranjeira, Ines Mainen, Zachary F Meijer, Guido Miska, Nathaniel J Mrsic-Flogel, Thomas D Murakami, Masayoshi Noel, Jean-Paul Pan-Vazquez, Alejandro Rossant, Cyrille Sanders, Joshua Socha, Karolina Terry, Rebecca Urai, Anne E Vergara, Hernando Wells, Miles Wilson, Christian J Witten, Ilana B Wool, Lauren E Zador, Anthony M Standardized and reproducible measurement of decision-making in mice |
title | Standardized and reproducible measurement of decision-making in mice |
title_full | Standardized and reproducible measurement of decision-making in mice |
title_fullStr | Standardized and reproducible measurement of decision-making in mice |
title_full_unstemmed | Standardized and reproducible measurement of decision-making in mice |
title_short | Standardized and reproducible measurement of decision-making in mice |
title_sort | standardized and reproducible measurement of decision-making in mice |
topic | Neuroscience |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8137147/ https://www.ncbi.nlm.nih.gov/pubmed/34011433 http://dx.doi.org/10.7554/eLife.63711 |
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