Literature DB >> 34011433

Standardized and reproducible measurement of decision-making in mice.

Valeria Aguillon-Rodriguez1, Dora Angelaki2, Hannah Bayer3, Niccolo Bonacchi4, Matteo Carandini5, Fanny Cazettes4, Gaelle Chapuis6, Anne K Churchland1, Yang Dan7, Eric Dewitt4, Mayo Faulkner6, Hamish Forrest5, Laura Haetzel8, Michael Häusser6, Sonja B Hofer9, Fei Hu7, Anup Khanal1, Christopher Krasniak1,10, Ines Laranjeira4, Zachary F Mainen4, Guido Meijer4, Nathaniel J Miska9, Thomas D Mrsic-Flogel9, Masayoshi Murakami4, Jean-Paul Noel2, Alejandro Pan-Vazquez8, Cyrille Rossant11, Joshua Sanders12, Karolina Socha5, Rebecca Terry11, Anne E Urai1,13, Hernando Vergara9, Miles Wells11, Christian J Wilson2, Ilana B Witten8, Lauren E Wool11, Anthony M Zador1.   

Abstract

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.
© 2021, The International Brain Laboratory et al.

Entities:  

Keywords:  behavior; decision making; mouse; neuroscience; reproducibility

Mesh:

Year:  2021        PMID: 34011433      PMCID: PMC8137147          DOI: 10.7554/eLife.63711

Source DB:  PubMed          Journal:  Elife        ISSN: 2050-084X            Impact factor:   8.713


  62 in total

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Authors:  Elyse H Norton; Luigi Acerbi; Wei Ji Ma; Michael S Landy
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7.  Attention improves performance primarily by reducing interneuronal correlations.

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Journal:  Nat Neurosci       Date:  2009-11-15       Impact factor: 24.884

8.  Sources of noise during accumulation of evidence in unrestrained and voluntarily head-restrained rats.

Authors:  Benjamin B Scott; Christine M Constantinople; Jeffrey C Erlich; David W Tank; Carlos D Brody
Journal:  Elife       Date:  2015-12-17       Impact factor: 8.140

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Authors:  Lucas Pinto; Sue A Koay; Ben Engelhard; Alice M Yoon; Ben Deverett; Stephan Y Thiberge; Ilana B Witten; David W Tank; Carlos D Brody
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10.  The impact of learning on perceptual decisions and its implication for speed-accuracy tradeoffs.

Authors:  André G Mendonça; Jan Drugowitsch; M Inês Vicente; Eric E J DeWitt; Alexandre Pouget; Zachary F Mainen
Journal:  Nat Commun       Date:  2020-06-02       Impact factor: 14.919

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  14 in total

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6.  Neural correlates of blood flow measured by ultrasound.

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7.  Citric Acid Water as an Alternative to Water Restriction for High-Yield Mouse Behavior.

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