Evidence map›Paper›PMID 34326540›Full record

ArticleNature neuroscience2021

Mice learn multi-step routes by memorizing subgoal locations.

Philip Shamash, Sarah F Olesen, Panagiota Iordanidou, Dario Campagner, Nabhojit Banerjee, Tiago Branco

Abstract read
In one paragraph

Article in Nature neuroscience, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

19 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Vector-Based Navigation Inspired by Directional Place Cells.From animals to animats : proceedings of the ... International Conference on Simulation of Adaptive Behavior. International Conference on Simulation of Adaptive Behavior · 2025
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  10. Review
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  19. A step-by-step guide home.Nature neuroscience · 2021
    Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors.

Philip ShamashUCL Sainsbury Wellcome Centre for Neural Circuits and Behaviour, London, UK.ORCID http://orcid.org/0000-0002-7152-3496
Sarah F OlesenUCL Sainsbury Wellcome Centre for Neural Circuits and Behaviour, London, UK.
Panagiota IordanidouUCL Sainsbury Wellcome Centre for Neural Circuits and Behaviour, London, UK.
Dario CampagnerUCL Sainsbury Wellcome Centre for Neural Circuits and Behaviour, London, UK.
Nabhojit BanerjeeUCL Sainsbury Wellcome Centre for Neural Circuits and Behaviour, London, UK.
Tiago BrancoUCL Sainsbury Wellcome Centre for Neural Circuits and Behaviour, London, UK. t.branco@ucl.ac.uk.ORCID http://orcid.org/0000-0001-5087-3465

Funding

Wellcome Trust 090843Wellcome Trust 090843/F/09/ZWellcome Trust 214352Wellcome Trust 214352/Z/18/Z
6 · The paper itself

Abstract

The behavioral strategies that mammals use to learn multi-step routes are unknown. In this study, we investigated how mice navigate to shelter in response to threats when the direct path is blocked. Initially, they fled toward the shelter and negotiated obstacles using sensory cues. Within 20 min, they spontaneously adopted a subgoal strategy, initiating escapes by running directly to the obstacle's edge. Mice continued to escape in this manner even after the obstacle had been removed, indicating use of spatial memory. However, standard models of spatial learning-habitual movement repetition and internal map building-did not explain how subgoal memories formed. Instead, mice used a hybrid approach: memorizing salient locations encountered during spontaneous 'practice runs' to the shelter. This strategy was also used during a geometrically identical food-seeking task. These results suggest that subgoal memorization is a fundamental strategy by which rodents learn efficient multi-step routes in new environments.

Indexed as

AnimalsCuesMaleMiceMice, Inbred C57BLSpatial LearningSpatial MemorySpatial Navigation

Identifiers

PMID34326540
PMCPMC7617975

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.