ElegansBot

Newtonian Mechanics Model for C. elegans Locomotion

omega_turn.mp4

(Left: Experimental video from [1], Right: ElegansBot)

[1] Broekmans, O. D., Rodgers, J. B., Ryu, W. S., & Stephens, G. J. (2016). Resolving coiled shapes reveals new reorientation behaviors in C. elegans. ELife, 5, e17227. https://doi.org/10.7554/eLife.17227

Web Demo

• https://taegonchung.github.io/elegansbot/
  • Use the sliders to observe the worm's movement changes.
    • Water-Agar Slider: Adjust this to modify the ground's frictional coefficients.
    • Swim-Crawl Slider: This slider alters the period and linear wave number of C. elegans' locomotion.

Requirements

• Python (version 3)
• NumPy
• Numba
  • SciPy (required as a dependency of numba)
• Matplotlib

(Optional)

• FFmpeg (for saving a video.)
• Jupyter Notebook version 6 (for interactive coding. "backend_nbagg" is no longer supported in version 7.)

Tested Environment

• Windows 10
  • Python 3.8.18
  • NumPy 1.19.0
  • Numba 0.54.0
    • SciPy 1.5.0
  • Matplotlib 3.4.2

Usage

1. Install library by pip install elegansbot.
2. Use from elegansbot import Worm to import the library.
3. Refer to the detailed instructions in the docstring of the "Worm" class. Below is a brief overview of potential use-cases:
   • If you want to determine $\theta_{\mathrm{ctrl}}$ dynamically, it's advised to update "act" (equivalent to theta_ctrl) manually and then invoke the "steps" method on an instance of the "Worm" class.
   • If you wish to use ElegansBot with a pre-determined $\theta_{\mathrm{ctrl}}$ (kymogram), it's recommended to utilize the "run" method of an instance of the "Worm" class.

Examples

You may want to check out examples in the "examples/" directory.
For instance, you can execute the example code with:
python examples/example01.py

Files:

• examples/example01.py : Dynamic input
• examples/example02.py : Kymogram input
• examples/example03.py : Kymogram input (Omega-turn)
• examples/example04.py : Kymogram input (Delta-turn)
• examples/example05.py : Frictional forces, power, and behavioral classification

Local Demo

Execute the following command:

python -m elegansbot.elegansbot

File Description

• elegansbot.py : Main code
• Video_S1_omega_turn.avi : Video from the supplementary section of our paper.
• Video_S2_delta_turn.avi : Another video from the supplementary section of our paper.

Citing ElegansBot

• If ElegansBot has been significant in your research, and you would like to acknowledge this work in your academic publication, we suggest citing the following paper:

Taegon Chung, Iksoo Chang, Sangyeol Kim (2024) Development of equation of motion deciphering locomotion including omega turns of Caenorhabditis elegans eLife 12:RP92562 https://doi.org/10.7554/eLife.92562