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Age-dependent Dynamics of Locomotion in Caenorhabditis elegans: A Lyapunov Exponent Analysis

Age-dependent Dynamics of Locomotion in Caenorhabditis elegans: A Lyapunov Exponent Analysis

Published on: September 23, 2025

C. elegans collectively forms dynamical networks.

Takuma Sugi¹, Hiroshi Ito², Masaki Nishimura³

¹Molecular Neuroscience Research Center, Shiga University of Medical Science, Otsu, Shiga, 520-2192, Japan. tsugi@belle.shiga-med.ac.jp.

Nature Communications

|February 20, 2019

Summary

This summary is machine-generated.

Researchers studied collective motion in Caenorhabditis elegans, finding that worm alignment after collisions and smooth turning create dynamic networks. This work offers insights into animal group behavior using active matter physics principles.

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Basic Caenorhabditis elegans Methods: Synchronization and Observation

Basic Caenorhabditis elegans Methods: Synchronization and Observation

Published on: June 10, 2012

Area of Science:

Active matter physics
Collective behavior
Biophysics

Background:

Understanding collective motion in self-propelled particles requires parameter control, which is challenging in animal systems.
Collective behaviors in animals remain elusive due to difficulties in manipulating controllable parameters.

Purpose of the Study:

To experimentally investigate the collective formation of dynamical networks by Caenorhabditis elegans.
To explore the influence of extrinsic and intrinsic parameters on these collective behaviors.
To develop a model that explains the mechanisms behind network formation.

Main Methods:

Utilized Caenorhabditis elegans as a model organism.
Manipulated extrinsic parameters: substrate material, humidity, and worm density.
Controlled intrinsic parameters: genetic mutations affecting motility and optogenetic neural activation.
Developed a minimal agent-based model.

Main Results:

Observed collective formation of dynamical networks of bundle-shaped aggregates in C. elegans.
Identified dependence of network formation on extrinsic parameters (substrate, humidity, density).
Demonstrated control over collective behavior via genetic and optogenetic manipulation of worm motility.
Agent-based model reproduced network dynamics, highlighting alignment after collision and smooth turning as key factors.

Conclusions:

Worm alignment after collision and smooth turning are critical for dynamical network formation.
Active matter physics concepts can illuminate the biological functions of animal groups.
This study provides a controllable experimental system for studying collective animal behavior.