Evidence map›Paper›PMID 31920577›Full record

ArticleFrontiers in behavioral neuroscience2019

High-Throughput Automated Olfactory Phenotyping of Group-Housed Mice.

Janine K Reinert, Andreas T Schaefer, Thomas Kuner

Open access · goldAbstract read
In one paragraph

Article in Frontiers in behavioral neuroscience, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
1.4field-weighted citation impact, top 22% of its field
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

13 citing papers in PubMed, 17 citations in OpenAlex.

  1. Article
  2. Article
  3. Constructing an Olfactometer for Rodent Olfactory Behavior Studies.Journal of visualized experiments : JoVE · 2025
    Article
  4. Article
  5. A novel approach to the assessment of higher-order rule learning in male mice.Learning & memory (Cold Spring Harbor, N.Y.) · 2023
    Article
  6. Review
  7. Review
  8. Article
  9. Article
  10. Article
  11. Behavior Individuality: A Focus onFrontiers in physiology · 2021
    Review
  12. Article
  13. Article
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

3 authors at 2 institutions in 2 countries.

Janine K ReinertInstitute of Anatomy and Cell Biology, Heidelberg University, Heidelberg, Germany.
Andreas T SchaeferInstitute of Anatomy and Cell Biology, Heidelberg University, Heidelberg, Germany.
Thomas KunerInstitute of Anatomy and Cell Biology, Heidelberg University, Heidelberg, Germany.
Heidelberg University · DEUniversity College London · GB

Funding

Medical Research Council MC_UP_1202/5Wellcome Trust FC001153
6 · The paper itself

Abstract

Behavioral phenotyping of mice is often compromised by manual interventions of the experimenter and limited throughput. Here, we describe a fully automated behavior setup that allows for quantitative analysis of mouse olfaction with minimized experimenter involvement. Mice are group-housed and tagged with unique RFID chips. They can freely initiate trials and are automatically trained on a go/no-go task, learning to distinguish a rewarded from an unrewarded odor. Further, odor discrimination tasks and detailed training aspects can be set for each animal individually for automated execution without direct experimenter intervention. The procedure described here, from initial RFID implantation to discrimination of complex odor mixtures at high accuracy, can be completed within <2 months with cohorts of up to 25 male mice. Apart from the presentation of monomolecular odors, the setup can generate arbitrary mixtures and dilutions from any set of odors to create complex stimuli, enabling demanding behavioral analyses at high-throughput.

Indexed as

automatedbehavior assayolfactionolfactory testingoperant conditioning

Identifiers

PMID31920577
PMCPMC6927946
OpenAlexW2996081259

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.