Evidence map›Paper›PMID 30778072›Full record

ArticleNature communications2019

C. elegans collectively forms dynamical networks.

Takuma Sugi, Hiroshi Ito, Masaki Nishimura, Ken H Nagai

Abstract read
In one paragraph

Article in Nature communications, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing 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

22 citing papers in PubMed.

  1. Article
  2. Neuromodulation of swarming behavior inProceedings of the National Academy of Sciences of the United States of America · 2026
    Article
  3. Article
  4. Article
  5. A geometric condition for robot-swarm cohesion and cluster-flock transition.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  6. Neuromodulation of Swarming Behavior inbioRxiv : the preprint server for biology · 2025
    Article
  7. On collective behavior inFrontiers in neurorobotics · 2025
    Review
  8. microPublication biology · 2025
    Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Frontiers in neurorobotics · 2023
    Article
  15. Collective behavior and self-organization in neural rosette morphogenesis.Frontiers in cell and developmental biology · 2023
    Review
  16. Article
  17. Article
  18. Article
  19. A Keller-Segel model for C elegans L1 aggregation.PLoS computational biology · 2021
    Article
  20. Collective dynamics in entangled worm and robot blobs.Proceedings of the National Academy of Sciences of the United States of America · 2021
    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

4 authors.

Takuma SugiMolecular Neuroscience Research Center, Shiga University of Medical Science, Otsu, Shiga, 520-2192, Japan. tsugi@belle.shiga-med.ac.jp.ORCID http://orcid.org/0000-0002-8123-2895
Hiroshi ItoFaculty of Design, Kyushu University, Fukuoka, 815-8540, Japan. hito@design.kyushu-u.ac.jp.
Masaki NishimuraMolecular Neuroscience Research Center, Shiga University of Medical Science, Otsu, Shiga, 520-2192, Japan.
Ken H NagaiSchool of Materials Science, Japan Advanced Institute of Science and Technology, Nomi, Ishikawa, 923-1292, Japan. k-nagai@jasit.ac.jp.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Understanding physical rules underlying collective motions requires perturbation of controllable parameters in self-propelled particles. However, controlling parameters in animals is generally not easy, which makes collective behaviours of animals elusive. Here, we report an experimental system in which a conventional model animal, Caenorhabditis elegans, collectively forms dynamical networks of bundle-shaped aggregates. We investigate the dependence of our experimental system on various extrinsic parameters (material of substrate, ambient humidity and density of worms). Taking advantage of well-established C. elegans genetics, we also control intrinsic parameters (genetically determined motility) by mutations and by forced neural activation via optogenetics. Furthermore, we develop a minimal agent-based model that reproduces the dynamical network formation and its dependence on the parameters, suggesting that the key factors are alignment of worms after collision and smooth turning. Our findings imply that the concepts of active matter physics may help us to understand biological functions of animal groups.

Indexed as

Models, BiologicalAnimalsAnimals, Genetically ModifiedBehavior, AnimalCaenorhabditis elegansLocomotionModels, AnimalMotor SkillsMutationOptogenetics

Identifiers

PMID30778072
PMCPMC6379388

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.