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Mice in a labyrinth show rapid learning, sudden insight, and efficient exploration

Rosenberg, Matthew and Zhang, Tony and Perona, Pietro and Meister, Markus (2021) Mice in a labyrinth show rapid learning, sudden insight, and efficient exploration. eLife, 10 . Art. No. e66175. ISSN 2050-084X. PMCID PMC8294850. doi:10.7554/eLife.66175. https://resolver.caltech.edu/CaltechAUTHORS:20210119-130811113

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Abstract

Animals learn certain complex tasks remarkably fast, sometimes after a single experience. What behavioral algorithms support this efficiency? Many contemporary studies based on two-alternative-forced-choice (2AFC) tasks observe only slow or incomplete learning. As an alternative, we study the unconstrained behavior of mice in a complex labyrinth and measure the dynamics of learning and the behaviors that enable it. A mouse in the labyrinth makes ~2000 navigation decisions per hour. The animal explores the maze, quickly discovers the location of a reward, and executes correct 10-bit choices after only 10 reward experiences — a learning rate 1000-fold higher than in 2AFC experiments. Many mice improve discontinuously from one minute to the next, suggesting moments of sudden insight about the structure of the labyrinth. The underlying search algorithm does not require a global memory of places visited and is largely explained by purely local turning rules.


Item Type:Article
Related URLs:
URLURL TypeDescription
https://doi.org/10.7554/eLife.66175DOIArticle
https://doi.org/10.1101/2021.01.14.426746DOIDiscussion Paper
https://github.com/markusmeister/Rosenberg-2021-RepositoryRelated ItemCode
https://archive.softwareheritage.org/swh:1:rev:224141473e53d6e8963a77fbe625f570b0903ef1Related ItemCode
https://data.caltech.edu/badge/latestdoi/329740227Related ItemCode
http://www.ncbi.nlm.nih.gov/pmc/articles/pmc8294850/PubMed CentralArticle
ORCID:
AuthorORCID
Zhang, Tony0000-0002-5198-499X
Perona, Pietro0000-0002-7583-5809
Meister, Markus0000-0003-2136-6506
Alternate Title:Mice in a labyrinth: Rapid learning, sudden insight, and efficient exploration
Additional Information:© 2021 Rosenberg et al. 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. Received: 31 December 2020; Accepted: 30 June 2021; Published: 01 July 2021. Funding: This work was supported by the Simons Collaboration on the Global Brain (grant 543015 to MM and 543025 to PP), by NSF award 1564330 to PP, and by a gift from Google to PP. The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication. Author contributions: Matthew Rosenberg, Tony Zhang, Conceptualization, Data curation, Software, Formal analysis, Validation, Investigation, Visualization, Methodology, Writing - review and editing; Pietro Perona, Conceptualization, Software, Formal analysis, Supervision, Funding acquisition, Validation, Visualization, Methodology, Project administration, Writing - review and editing; Markus Meister, Conceptualization, Software, Formal analysis, Supervision, Funding acquisition, Validation, Visualization, Methodology, Writing - original draft, Project administration, Writing - review and editing. Competing interests: Markus Meister: Reviewing editor, eLife. The other authors declare that no competing interests exist. Ethics: Animal experimentation: This study was performed in strict accordance with the recommendations in the Guide for the Care and Use of Laboratory Animals of the National Institutes of Health. All of the animals were handled according to animal protocol 1656 approved by the institutional animal care and use committee (IACUC) at Caltech. Data Availability: The behavioral data and code that produced the figures are available in a public Github repository cited in the article https://github.com/markusmeister/Rosenberg-2021-Repository (copy archived at https://archive.softwareheritage.org/swh:1:rev:224141473e53d6e8963a77fbe625f570b0903ef1). We also prepared a permanent institutional repository at https://data.caltech.edu/badge/latestdoi/329740227.
Funders:
Funding AgencyGrant Number
Simons Foundation543015
Simons Foundation543025
NSFIIS-1564330
GoogleUNSPECIFIED
PubMed Central ID:PMC8294850
DOI:10.7554/eLife.66175
Record Number:CaltechAUTHORS:20210119-130811113
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20210119-130811113
Official Citation:Mice in a labyrinth show rapid learning, sudden insight, and efficient exploration. Rosenberg, Zhang, et al. eLife 2021;10:e66175. DOI: https://doi.org/10.7554/eLife.66175
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:107545
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:19 Jan 2021 21:34
Last Modified:26 Jul 2021 22:13

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