Evidence map›Paper›PMID 32994566›Full record

ArticleNature methods2020

EthoLoop: automated closed-loop neuroethology in naturalistic environments.

Ali Nourizonoz, Robert Zimmermann, Chun Lum Andy Ho, Sebastien Pellat, Yannick Ormen, Clément Prévost-Solié, Gilles Reymond, Fabien Pifferi, Fabienne Aujard, Anthony Herrel and 1 more

Open access · greenAbstract read
PubMed Publisher
In one paragraph

Article in Nature methods, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers.

0numbers the graph read from it
0cells of the map it votes in
38citing papers in PubMed
10.3field-weighted citation impact, top 1% 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

38 citing papers in PubMed, 126 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Primate neuroethology: a new synthesis.Trends in cognitive sciences · 2026
    Review
  6. Neural Bases of Collective Social Behavior and Group Interactions across Species.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2026
    Review
  7. Review
  8. Mouse lemurs.Nature methods · 2025
    Article
  9. Article
  10. Article
  11. Article
  12. The impact of machine learning on ethological neuroscience.Frontiers in behavioral neuroscience · 2025
    Review
  13. Article
  14. eLemur: A cellular-resolution 3D atlas of the mouse lemur brain.Proceedings of the National Academy of Sciences of the United States of America · 2024
    Article
  15. Article
  16. A perspective on neuroethology: what the past teaches us about the future of neuroethology.Journal of comparative physiology. A, Neuroethology, sensory, neural, and behavioral physiology · 2024
    Review
  17. Article
  18. Article
  19. Article
  20. 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

11 authors at 2 institutions in 3 countries.

Ali NourizonozUniversity of Geneva, Department of Basic Neurosciences, Geneva, Switzerland.ORCID http://orcid.org/0000-0001-8906-6345
Robert ZimmermannUniversity of Geneva, Department of Basic Neurosciences, Geneva, Switzerland.
Chun Lum Andy HoUniversity of Geneva, Department of Basic Neurosciences, Geneva, Switzerland.
Sebastien PellatUniversity of Geneva, Department of Basic Neurosciences, Geneva, Switzerland.
Yannick OrmenUniversity of Geneva, Department of Basic Neurosciences, Geneva, Switzerland.
Clément Prévost-SoliéUniversity of Geneva, Department of Basic Neurosciences, Geneva, Switzerland.ORCID http://orcid.org/0000-0002-9519-0171
Gilles ReymondUniversity of Geneva, Department of Basic Neurosciences, Geneva, Switzerland.
Fabien PifferiMusée National d'Histoire Naturelle, Adaptive Mechanisms and Evolution, UMR7179-CNRS, Paris, France.
Fabienne AujardMusée National d'Histoire Naturelle, Adaptive Mechanisms and Evolution, UMR7179-CNRS, Paris, France.
Anthony HerrelMusée National d'Histoire Naturelle, Adaptive Mechanisms and Evolution, UMR7179-CNRS, Paris, France.ORCID http://orcid.org/0000-0003-0991-4434
Daniel HuberUniversity of Geneva, Department of Basic Neurosciences, Geneva, Switzerland. daniel.huber@unige.ch.ORCID http://orcid.org/0000-0002-0744-7679
University of Geneva · CHCentre National de la Recherche Scientifique · FR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Accurate tracking and analysis of animal behavior is crucial for modern systems neuroscience. However, following freely moving animals in naturalistic, three-dimensional (3D) or nocturnal environments remains a major challenge. Here, we present EthoLoop, a framework for studying the neuroethology of freely roaming animals. Combining real-time optical tracking and behavioral analysis with remote-controlled stimulus-reward boxes, this system allows direct interactions with animals in their habitat. EthoLoop continuously provides close-up views of the tracked individuals and thus allows high-resolution behavioral analysis using deep-learning methods. The behaviors detected on the fly can be automatically reinforced either by classical conditioning or by optogenetic stimulation via wirelessly controlled portable devices. Finally, by combining 3D tracking with wireless neurophysiology we demonstrate the existence of place-cell-like activity in the hippocampus of freely moving primates. Taken together, we show that the EthoLoop framework enables interactive, well-controlled and reproducible neuroethological studies in large-field naturalistic settings.

Indexed as

AnimalsAutomationBehavior, AnimalBrainConditioning, OperantLemuridaeMiceMonitoring, PhysiologicNeurophysiologyOptogeneticsWireless Technology

Identifiers

PMID32994566
OpenAlexW3090861299

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.