Evidence map›Paper›PMID 33349672›Full record

ArticleScientific reports2020

Efficient training of mice on the 5-choice serial reaction time task in an automated rodent training system.

Eszter Birtalan, Anita Bánhidi, Joshua I Sanders, Diána Balázsfi, Balázs Hangya

Abstract read
In one paragraph

Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing 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

15 citing papers in PubMed.

  1. Article
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  6. Review
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  8. Probing the Skin-Brain Axis: New Vistas Using Mouse Models.International journal of molecular sciences · 2022
    Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Eszter BirtalanLendület Laboratory of Systems Neuroscience, Institute of Experimental Medicine, Budapest, Hungary.
Anita BánhidiLendület Laboratory of Systems Neuroscience, Institute of Experimental Medicine, Budapest, Hungary.
Joshua I SandersSanworks LLC, Rochester, NY, USA.
Diána BalázsfiLendület Laboratory of Systems Neuroscience, Institute of Experimental Medicine, Budapest, Hungary. balazsfi.diana@koki.mta.hu.
Balázs HangyaLendület Laboratory of Systems Neuroscience, Institute of Experimental Medicine, Budapest, Hungary. hangya.balazs@koki.mta.hu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Experiments aiming to understand sensory-motor systems, cognition and behavior necessitate training animals to perform complex tasks. Traditional training protocols require lab personnel to move the animals between home cages and training chambers, to start and end training sessions, and in some cases, to hand-control each training trial. Human labor not only limits the amount of training per day, but also introduces several sources of variability and may increase animal stress. Here we present an automated training system for the 5-choice serial reaction time task (5CSRTT), a classic rodent task often used to test sensory detection, sustained attention and impulsivity. We found that full automation without human intervention allowed rapid, cost-efficient training, and decreased stress as measured by corticosterone levels. Training breaks introduced only a transient drop in performance, and mice readily generalized across training systems when transferred from automated to manual protocols. We further validated our automated training system with wireless optogenetics and pharmacology experiments, expanding the breadth of experimental needs our system may fulfill. Our automated 5CSRTT system can serve as a prototype for fully automated behavioral training, with methods and principles transferrable to a range of rodent tasks.

Indexed as

AttentionChoice BehaviorCognitionReaction TimeAnimalsMaleMice

Identifiers

PMID33349672
PMCPMC7752912

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LicenceCC BY
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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.