Evidence map›Paper›PMID 36959336›Full record

ArticleCommunications biology2023

Quantity discrimination in newly hatched zebrafish suggests hardwired numerical abilities.

Tyrone Lucon-Xiccato, Elia Gatto, Camilla Maria Fontana, Angelo Bisazza

Open access · goldFull text read
In one paragraph

Article in Communications biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
6.1field-weighted citation impact, top 3% 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

9 citing papers in PubMed, 18 citations in OpenAlex.

  1. Article
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  4. Neural Basis of Number Sense in Larval Zebrafish.bioRxiv : the preprint server for biology · 2024
    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 at 2 institutions in 1 country.

Tyrone Lucon-Xiccato *Department of Life Sciences and Biotechnology, University of Ferrara, Ferrara, Italy. tyrone.luconxiccato@unife.it.ORCID 0000-0002-1017-9230
Elia Gatto *Department of Life Sciences and Biotechnology, University of Ferrara, Ferrara, Italy.
Camilla Maria FontanaDepartment of Biology, University of Padova, Padova, Italy.ORCID 0000-0001-7520-0814
Angelo BisazzaDepartment of General Psychology, University of Padova, Padova, Italy.ORCID 0000-0003-0209-7638
University of Ferrara · ITUniversity of Padua · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

An intriguing hypothesis to explain the ubiquity of numerical abilities is that all vertebrates are born with hardwired neuronal networks for processing numbers. To date, only studies on human foetuses have clearly supported this hypothesis. Zebrafish hatch 48-72 h after fertilisation with an embryonic nervous system, providing a unique opportunity for investigating this hypothesis. Here, we demonstrated that zebrafish larvae exposed to vertical bars at birth acquired an attraction for bar stimuli and we developed a numerical discrimination task based on this preference. When tested with a series of discriminations of increasing difficulty (1vs.4, 1vs.3, 1vs.2, and 2vs.4 bars), zebrafish larvae reliably selected the greater numerosity. The preference was significant when stimuli were matched for surface area, luminance, density, and convex hull, thereby suggesting a true capacity to process numerical information. Converging results from two phylogenetically distant species suggests that numerical abilities might be a hallmark feature of vertebrates' brains.

Indexed as

BrainZebrafishAnimalsFetusHumansInfant, NewbornLarvaNeurons

Identifiers

PMID36959336
PMCPMC10036331
OpenAlexW4360610654

What OpenQuestion holds

Textfull text, public
LicenceCC BY
measurements read48
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.