Evidence map›Paper›PMID 21305061›Full record

ArticlePloS one2011

Executive decision-making in the domestic sheep.

A Jennifer Morton, Laura Avanzo

Open access · goldAbstract readEvaluation Study
In one paragraph

Article in PloS one, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed
2.1field-weighted citation impact, top 14% 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

26 citing papers in PubMed, 79 citations in OpenAlex.

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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

2 authors at 1 institution in 1 country.

A Jennifer MortonDepartment of Pharmacology, University of Cambridge, Cambridge, United Kingdom. ajm41@cam.ac.uk
Laura Avanzo
University of Cambridge · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Two new large animal models of Huntington's disease (HD) have been developed recently, an old world monkey (macaque) and a sheep. Macaques, with their large brains and complex repertoire of behaviors are the 'gold-standard' laboratory animals for testing cognitive function, but there are many practical and ethical issues that must be resolved before HD macaques can be used for pre-clinical research. By contrast, despite their comparable brain size, sheep do not enjoy a reputation for intelligence, and are not used for pre-clinical cognitive testing. Given that cognitive decline is a major therapeutic target in HD, the feasibility of testing cognitive function in sheep must be explored if they are to be considered seriously as models of HD. Here we tested the ability of sheep to perform tests of executive function (discrimination learning, reversal learning and attentional set-shifting). Significantly, we found that not only could sheep perform discrimination learning and reversals, but they could also perform the intradimensional (ID) and extradimensional (ED) set-shifting tasks that are sensitive tests of cognitive dysfunction in humans. Their performance on the ID/ED shifts mirrored that seen in humans and macaques, with significantly more errors to reach criterion in the ED than the ID shift. Thus, sheep can perform 'executive' cognitive tasks that are an important part of the primate behavioral repertoire, but which have never been shown previously to exist in any other large animal. Sheep have great potential, not only for use as a large animal model of HD, but also for studying cognitive function and the evolution of complex behaviours in normal animals.

Indexed as

CognitionModels, AnimalAnimalsAttentionDecision MakingDiscrimination LearningHuntington DiseaseReversal LearningSheep, Domestic

Identifiers

PMID21305061
PMCPMC3031539
OpenAlexW2083505668

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.