Evidence map›Paper›PMID 24586288›Full record

ArticlePloS one2014

Strains and stressors: an analysis of touchscreen learning in genetically diverse mouse strains.

Carolyn Graybeal, Munisa Bachu, Khyobeni Mozhui, Lisa M Saksida, Timothy J Bussey, Erica Sagalyn, Robert W Williams, Andrew Holmes

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 42 papers.

0numbers the graph read from it
0cells of the map it votes in
42citing papers in PubMed
2.6field-weighted citation impact, top 11% 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

42 citing papers in PubMed, 65 citations in OpenAlex.

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  19. Dorsolateral striatum engagement during reversal learning.Learning & memory (Cold Spring Harbor, N.Y.) · 2020
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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

8 authors at 4 institutions in 2 countries.

Carolyn GraybealLaboratory of Behavioral and Genomic Neuroscience, National Institute on Alcoholism and Alcohol Abuse, National Institutes of Health, Bethesda, Maryland, United States of America.
Munisa BachuLaboratory of Behavioral and Genomic Neuroscience, National Institute on Alcoholism and Alcohol Abuse, National Institutes of Health, Bethesda, Maryland, United States of America.
Khyobeni MozhuiDepartments of Preventive Medicine, and Department of Anatomy and Neurobiology, University of Tennessee Health Science Center, Memphis, Tennessee, United States of America.
Lisa M SaksidaDepartment of Experimental Psychology, University of Cambridge, Cambridge, Medical Research Council and Wellcome Trust Behavioral and Clinical Neuroscience Institute, Cambridge, United Kingdom.
Timothy J BusseyDepartment of Experimental Psychology, University of Cambridge, Cambridge, Medical Research Council and Wellcome Trust Behavioral and Clinical Neuroscience Institute, Cambridge, United Kingdom.
Erica SagalynLaboratory of Behavioral and Genomic Neuroscience, National Institute on Alcoholism and Alcohol Abuse, National Institutes of Health, Bethesda, Maryland, United States of America.
Robert W WilliamsDepartments of Preventive Medicine, and Department of Anatomy and Neurobiology, University of Tennessee Health Science Center, Memphis, Tennessee, United States of America.
Andrew HolmesLaboratory of Behavioral and Genomic Neuroscience, National Institute on Alcoholism and Alcohol Abuse, National Institutes of Health, Bethesda, Maryland, United States of America.
National Institute on Alcohol Abuse and Alcoholism · USNational Institutes of Health · USUniversity of Tennessee Health Science Center · USWellcome Trust · GB

Funding

Mouse models of stress disorders and addictionZIAAA000411 · NIAAA · NATIONAL INSTITUTE ON ALCOHOL ABUSE AND ALCOHOLISM · PI HOLMES, ANDREW · 2009 to 2025
$37.7M
Systems Genetics of Alcohol Response and Stress Effects in CNSU01AA013499 · NIAAA · UNIVERSITY OF TENNESSEE HEALTH SCI CTR · PI WILLIAMS, ROBERT W. · 2002 to 2016
$4.8M
INIA-STRESS: Informatics and Analysis CoreU01AA016662 · NIAAA · VIRGINIA COMMONWEALTH UNIVERSITY · PI WILLIAMS, ROBERT W. · 2007 to 2016
$2.9M
Intramural NIH HHSNIAAA NIH HHS U01 AA013499NIAAA NIH HHS U01 AA016662PHS HHS U01 11016662
6 · The paper itself

Abstract

Touchscreen-based systems are growing in popularity as a tractable, translational approach for studying learning and cognition in rodents. However, while mouse strains are well known to differ in learning across various settings, performance variation between strains in touchscreen learning has not been well described. The selection of appropriate genetic strains and backgrounds is critical to the design of touchscreen-based studies and provides a basis for elucidating genetic factors moderating behavior. Here we provide a quantitative foundation for visual discrimination and reversal learning using touchscreen assays across a total of 35 genotypes. We found significant differences in operant performance and learning, including faster reversal learning in DBA/2J compared to C57BL/6J mice. We then assessed DBA/2J and C57BL/6J for differential sensitivity to an environmental insult by testing for alterations in reversal learning following exposure to repeated swim stress. Stress facilitated reversal learning (selectively during the late stage of reversal) in C57BL/6J, but did not affect learning in DBA/2J. To dissect genetic factors underlying these differences, we phenotyped a family of 27 BXD strains generated by crossing C57BL/6J and DBA/2J. There was marked variation in discrimination, reversal and extinction learning across the BXD strains, suggesting this task may be useful for identifying underlying genetic differences. Moreover, different measures of touchscreen learning were only modestly correlated in the BXD strains, indicating that these processes are comparatively independent at both genetic and phenotypic levels. Finally, we examined the behavioral structure of learning via principal component analysis of the current data, plus an archival dataset, totaling 765 mice. This revealed 5 independent factors suggestive of "reversal learning," "motivation-related late reversal learning," "discrimination learning," "speed to respond," and "motivation during discrimination." Together, these findings provide a valuable reference to inform the choice of strains and genetic backgrounds in future studies using touchscreen-based tasks.

Indexed as

LearningTechnologyAnimalsBehavior, AnimalDiscrimination, PsychologicalInbreedingMaleMicePrincipal Component AnalysisReversal LearningSpecies SpecificityStress, Psychological

Identifiers

PMID24586288
PMCPMC3929556
OpenAlexW1973404922

What OpenQuestion holds

Textmetadata
LicenceCC0
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.