Evidence map›Paper›PMID 31143103›Full record

ArticleFrontiers in behavioral neuroscience2019

Impaired Reversal Learning in APPPS1-21 Mice in the Touchscreen Visual Discrimination Task.

Lore Van den Broeck, Pierre Hansquine, Zsuzsanna Callaerts-Vegh, Rudi D'Hooge

Abstract 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
–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

13 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Serial reversal learning in an olfactory discrimination task in 3xTg-AD mice.Learning & memory (Cold Spring Harbor, N.Y.) · 2023
    Article
  8. Article
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  10. Article
  11. Review
  12. Article
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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

4 authors.

Lore Van den BroeckLaboratory of Biological Psychology, KU Leuven, Leuven, Belgium.
Pierre HansquineLaboratory of Biological Psychology, KU Leuven, Leuven, Belgium.
Zsuzsanna Callaerts-VeghLaboratory of Biological Psychology, KU Leuven, Leuven, Belgium.
Rudi D'HoogeLaboratory of Biological Psychology, KU Leuven, Leuven, Belgium.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Preclinical-clinical translation of cognitive functions has been difficult in Alzheimer's disease (AD) research but is crucial to the (predictive) validity of AD animal models. Reversal learning, a representation of flexibility and adaptability to a changing environment, might represent such a translatable feature of human cognition. We, therefore, examined visual discrimination (VD) and reversal learning in the APPPS1-21 mouse model of amyloid-based AD pathology. We used touchscreen operant cages in novel and translationally valid, as well as objective testing methodology that minimizes within- or between-trial handling. Mice were trained to associate a visual cue with a food reward (VD learning), and subsequently learned to adjust their response when this rule changed (reversal learning). We assessed performance at two different ages, namely at 6 months of age, considered an early disease stage, and at 9 months, a stage of established pathology. Both at 6 and 9 months, transgenic animals needed more sessions to reach criterion performance, compared to wild-type controls. Overall, transgenic animals do not show a general cognitive, motivational or motor deficit, but experience specific difficulties to adapt to reward contingency changes, already at an early pathology stage.

Indexed as

Alzheimer’s diseasebehavioral phenotypingmouse modelsreversal learningtouchscreen operant cages

Identifiers

PMID31143103
PMCPMC6521801

What OpenQuestion holds

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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.