Evidence map›Paper›PMID 41563960›Full record

ArticlePloS one2026

An open-source closed-loop Virtual Reality system to investigate social interactions and collective behavior in fish.

Stéphane Sanchez, Ramón Escobedo, Renaud Bastien, Boris Lenseigne, Audrey Denis, Mathieu Moreau, Maud Combe, Andrew D Straw, Clément Sire, Guy Theraulaz

Erratum issuedAbstract read
In one paragraph

Article in PloS one, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

10 authors.

Stéphane SanchezInstitut de Recherche en Informatique de Toulouse (IRIT), Université Toulouse Capitole, Toulouse, France.
Ramón EscobedoInstitut de Recherche en Informatique de Toulouse (IRIT), Université Toulouse Capitole, Toulouse, France.
Renaud BastienInstitut de Recherche en Informatique de Toulouse (IRIT), Université Toulouse Capitole, Toulouse, France.
Boris LenseigneIzital BV, Delft, The Netherlands.
Audrey DenisCentre de Recherches sur la Cognition Animale, Centre de Biologie Intégrative, CNRS, Université de Toulouse III - Paul Sabatier Toulouse, France.
Mathieu MoreauCentre de Recherches sur la Cognition Animale, Centre de Biologie Intégrative, CNRS, Université de Toulouse III - Paul Sabatier Toulouse, France.
Maud CombeCentre de Recherches sur la Cognition Animale, Centre de Biologie Intégrative, CNRS, Université de Toulouse III - Paul Sabatier Toulouse, France.
Andrew D StrawInstitute of Biology I, Faculty of Biology, Albert-Ludwigs-Universität Freiburg, Freiburg, Germany.
Clément SireDepartamento de Matemáticas, Universidad Carlos III de Madrid Leganés, Madrid, Spain.
Guy TheraulazCentre de Recherches sur la Cognition Animale, Centre de Biologie Intégrative, CNRS, Université de Toulouse III - Paul Sabatier Toulouse, France.ORCID https://orcid.org/0000-0002-3062-4215

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study introduces a low-cost, open-source, immersive Virtual Reality (VR) system designed to investigate real-time social interactions and collective behaviors in fish. Understanding collective animal behaviors, such as schooling in fish, presents significant observational challenges due to rapid and complex interactions. To address these difficulties, we developed an innovative closed-loop VR environment allowing precise control and measurement of interactions between real and virtual fish. This setup incorporates high-speed 3D tracking, real-time visual feedback, and automated data processing, creating realistic and interactive scenarios. We present experimental results, obtained with rummy-nose tetras (Hemigrammus rhodostomus), showing that freely moving real fish consistently adjusted their speed, depth, and spatial positioning to follow virtual fish effectively. Fish matched moderate virtual speeds comfortably, struggled slightly at higher speeds, and actively maintained vertical positioning to sustain group cohesion. The implementation of this VR system provides critical insights into sensory and cognitive processes underlying collective movement and decision-making in fish. By revealing both flexibility and constraints in fish behavior, our findings underscore the potential of VR technology to study social interactions in controlled yet realistic settings. Ultimately, this VR system advances our understanding of collective animal behavior, providing a foundation for cross-species studies linking neural processes, behavioral interactions, and group dynamics.

Indexed as

Behavior, AnimalCharacidaeFishesSocial BehaviorVirtual RealityAnimals

Identifiers

PMID41563960
PMCPMC12823003

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.