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-...
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Language: | English |
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eLife Sciences Publications Ltd
2021-05-01
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Series: | eLife |
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Online Access: | https://elifesciences.org/articles/63711 |
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DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
The International Brain Laboratory Valeria Aguillon-Rodriguez Dora Angelaki Hannah Bayer Niccolo Bonacchi Matteo Carandini Fanny Cazettes Gaelle Chapuis Anne K Churchland Yang Dan Eric Dewitt Mayo Faulkner Hamish Forrest Laura Haetzel Michael Häusser Sonja B Hofer Fei Hu Anup Khanal Christopher Krasniak Ines Laranjeira Zachary F Mainen Guido Meijer Nathaniel J Miska Thomas D Mrsic-Flogel Masayoshi Murakami Jean-Paul Noel Alejandro Pan-Vazquez Cyrille Rossant Joshua Sanders Karolina Socha Rebecca Terry Anne E Urai Hernando Vergara Miles Wells Christian J Wilson Ilana B Witten Lauren E Wool Anthony M Zador |
spellingShingle |
The International Brain Laboratory Valeria Aguillon-Rodriguez Dora Angelaki Hannah Bayer Niccolo Bonacchi Matteo Carandini Fanny Cazettes Gaelle Chapuis Anne K Churchland Yang Dan Eric Dewitt Mayo Faulkner Hamish Forrest Laura Haetzel Michael Häusser Sonja B Hofer Fei Hu Anup Khanal Christopher Krasniak Ines Laranjeira Zachary F Mainen Guido Meijer Nathaniel J Miska Thomas D Mrsic-Flogel Masayoshi Murakami Jean-Paul Noel Alejandro Pan-Vazquez Cyrille Rossant Joshua Sanders Karolina Socha Rebecca Terry Anne E Urai Hernando Vergara Miles Wells Christian J Wilson Ilana B Witten Lauren E Wool Anthony M Zador Standardized and reproducible measurement of decision-making in mice eLife behavior reproducibility decision making |
author_facet |
The International Brain Laboratory Valeria Aguillon-Rodriguez Dora Angelaki Hannah Bayer Niccolo Bonacchi Matteo Carandini Fanny Cazettes Gaelle Chapuis Anne K Churchland Yang Dan Eric Dewitt Mayo Faulkner Hamish Forrest Laura Haetzel Michael Häusser Sonja B Hofer Fei Hu Anup Khanal Christopher Krasniak Ines Laranjeira Zachary F Mainen Guido Meijer Nathaniel J Miska Thomas D Mrsic-Flogel Masayoshi Murakami Jean-Paul Noel Alejandro Pan-Vazquez Cyrille Rossant Joshua Sanders Karolina Socha Rebecca Terry Anne E Urai Hernando Vergara Miles Wells Christian J Wilson Ilana B Witten Lauren E Wool Anthony M Zador |
author_sort |
The International Brain Laboratory |
title |
Standardized and reproducible measurement of decision-making in mice |
title_short |
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_sort |
standardized and reproducible measurement of decision-making in mice |
publisher |
eLife Sciences Publications Ltd |
series |
eLife |
issn |
2050-084X |
publishDate |
2021-05-01 |
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. |
topic |
behavior reproducibility decision making |
url |
https://elifesciences.org/articles/63711 |
work_keys_str_mv |
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doaj-0607a5000b744a54a235fb64586a4ba32021-05-26T15:00:15ZengeLife Sciences Publications LtdeLife2050-084X2021-05-011010.7554/eLife.63711Standardized and reproducible measurement of decision-making in miceThe International Brain LaboratoryValeria Aguillon-Rodriguez0Dora Angelaki1https://orcid.org/0000-0002-9650-8962Hannah Bayer2https://orcid.org/0000-0002-5644-4124Niccolo Bonacchi3Matteo Carandini4https://orcid.org/0000-0003-4880-7682Fanny Cazettes5https://orcid.org/0000-0002-9648-4761Gaelle Chapuis6Anne K Churchland7https://orcid.org/0000-0002-3205-3794Yang Dan8https://orcid.org/0000-0002-3818-877XEric Dewitt9Mayo Faulkner10Hamish Forrest11Laura Haetzel12Michael Häusser13https://orcid.org/0000-0002-2673-8957Sonja B Hofer14Fei Hu15https://orcid.org/0000-0001-7827-9548Anup Khanal16https://orcid.org/0000-0002-8929-7984Christopher Krasniak17Ines Laranjeira18Zachary F Mainen19https://orcid.org/0000-0001-7913-9109Guido Meijer20Nathaniel J Miska21Thomas D Mrsic-Flogel22Masayoshi Murakami23Jean-Paul Noel24https://orcid.org/0000-0001-5297-3363Alejandro Pan-Vazquez25Cyrille Rossant26Joshua Sanders27Karolina Socha28Rebecca Terry29Anne E Urai30https://orcid.org/0000-0001-5270-6513Hernando Vergara31Miles Wells32Christian J Wilson33Ilana B Witten34https://orcid.org/0000-0003-0548-2160Lauren E Wool35Anthony M Zador36Cold Spring Harbor Laboratory, New York, United StatesCenter for Neural Science, New York University, New York, United StatesZuckerman Institute, Columbia University, New York, United StatesChampalimaud Centre for the Unknown, Lisbon, PortugalUCL Institute of Ophthalmology, University College London, London, United KingdomChampalimaud Centre for the Unknown, Lisbon, PortugalWolfson Institute for Biomedical Research, University College London, London, United KingdomCold Spring Harbor Laboratory, New York, United StatesDepartment of Molecular and Cell Biology, University of California, Berkeley, Berkeley, United StatesChampalimaud Centre for the Unknown, Lisbon, PortugalWolfson Institute for Biomedical Research, University College London, London, United KingdomUCL Institute of Ophthalmology, University College London, London, United KingdomPrinceton Neuroscience Institute, Princeton University, Princeton, United StatesWolfson Institute for Biomedical Research, University College London, London, United KingdomSainsbury-Wellcome Centre for Neural Circuits and Behaviour, University College London, London, United KingdomDepartment of Molecular and Cell Biology, University of California, Berkeley, Berkeley, United StatesCold Spring Harbor Laboratory, New York, United StatesCold Spring Harbor Laboratory, New York, United States; Watson School of Biological Sciences, New York, United StatesChampalimaud Centre for the Unknown, Lisbon, PortugalChampalimaud Centre for the Unknown, Lisbon, PortugalChampalimaud Centre for the Unknown, Lisbon, PortugalSainsbury-Wellcome Centre for Neural Circuits and Behaviour, University College London, London, United KingdomSainsbury-Wellcome Centre for Neural Circuits and Behaviour, University College London, London, United KingdomChampalimaud Centre for the Unknown, Lisbon, PortugalCenter for Neural Science, New York University, New York, United StatesPrinceton Neuroscience Institute, Princeton University, Princeton, United StatesUCL Queen Square Institute of Neurology, University College London, London, United KingdomSanworks LLC, New York, United StatesUCL Institute of Ophthalmology, University College London, London, United KingdomUCL Queen Square Institute of Neurology, University College London, London, United KingdomCold Spring Harbor Laboratory, New York, United States; Cognitive Psychology Unit, Leiden University, Leiden, NetherlandsSainsbury-Wellcome Centre for Neural Circuits and Behaviour, University College London, London, United KingdomUCL Queen Square Institute of Neurology, University College London, London, United KingdomCenter for Neural Science, New York University, New York, United StatesPrinceton Neuroscience Institute, Princeton University, Princeton, United StatesUCL Queen Square Institute of Neurology, University College London, London, United KingdomCold Spring Harbor Laboratory, New York, United StatesProgress 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.https://elifesciences.org/articles/63711behaviorreproducibilitydecision making |