Evidence map›Paper›PMID 42315678›Full record

ArticleAnimal cognition2026

Variation in song structure does not predict associative learning performance in zebra finches (Taeniopygia castanotis) raised under controlled cultural conditions.

Sébastien Derégnaucourt, Lucille Le Maguer, Nicole Geberzahn

Abstract read
In one paragraph

Article in Animal cognition, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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.

Sébastien DerégnaucourtLaboratoire Éthologie Cognition Développement, Université Paris Nanterre, 200 Avenue de la République, Nanterre, Cedex F92001, France. sebastien.deregnaucourt@parisnanterre.fr.ORCID http://orcid.org/0000-0003-0160-1986
Lucille Le MaguerLaboratoire Éthologie Cognition Développement, Université Paris Nanterre, 200 Avenue de la République, Nanterre, Cedex F92001, France.ORCID http://orcid.org/0000-0002-2478-9697
Nicole GeberzahnLaboratoire Éthologie Cognition Développement, Université Paris Nanterre, 200 Avenue de la République, Nanterre, Cedex F92001, France.ORCID http://orcid.org/0000-0001-9945-7067

Funding

Agence Nationale de la Recherche ANR-12-BSH2-0009
6 · The paper itself

Abstract

Vocal learning in songbirds requires the integration of auditory perception, sensorimotor learning, and performance monitoring, yet its relationship to general cognitive abilities remains unclear. We tested whether interindividual variation in song structure predicts performance in associative learning and reversal learning tasks in domesticated zebra finches (Taeniopygia castanotis) raised under controlled cultural conditions, in a colony founded with males trained to sing an identical song. We quantified variation in song phenotype using a composite measure summarizing motif duration, syllable number, motif elements, and similarity to the colony song model, and assessed performance in a foraging task across three phases: training, initial learning, and reversal learning. We found that this composite measure of song structure did not predict performance in any phase. Together, these results are consistent with evidence from multiple songbird species showing that individual variation in song structure is not tightly linked to individual differences in other cognitive abilities.

Indexed as

Association LearningFinchesVocalization, AnimalAnimalsMaleReversal LearningAcoustic communicationBirdsongDomain-specific cognitionIndividual variationReversal learningVocal learning

Identifiers

PMID42315678
PMCPMC13529891

What OpenQuestion holds

Textmetadata
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.