muscle_model
Model of C elegans body wall muscle based on Boyle & Cohen 2008
Science Score: 41.0%
This score indicates how likely this project is to be science-related based on various indicators:
-
✓CITATION.cff file
Found CITATION.cff file -
✓codemeta.json file
Found codemeta.json file -
○.zenodo.json file
-
○DOI references
-
✓Academic publication links
Links to: sciencedirect.com -
○Academic email domains
-
○Institutional organization owner
-
○JOSS paper metadata
-
○Scientific vocabulary similarity
Low similarity (13.0%) to scientific vocabulary
Repository
Model of C elegans body wall muscle based on Boyle & Cohen 2008
Basic Info
- Host: GitHub
- Owner: openworm
- License: other
- Language: Jupyter Notebook
- Default Branch: master
- Homepage: http://www.opensourcebrain.org/projects/muscle_model
- Size: 1.68 MB
Statistics
- Stars: 47
- Watchers: 45
- Forks: 24
- Open Issues: 18
- Releases: 1
Metadata Files
README.md
OpenWorm muscle model
Mode of C. elegans body wall muscle from: Caenorhabditis elegans body wall muscles are simple actuators, Jordan H. Boyle & Netta Cohen, Biosystems 2008.
Authors: Mike Vella, Alex Dibert, Padraig Gleeson, Rayner Lucas email:mv333@cam.ac.uk
If you contribute to the project please add your name to the Authors field
| NOTE: while the NeuroML version of this model is still supported, the most recent work using this muscle model is taking place in the c302 repository. |
Introduction
This repository contains several different subprojects all related to the construction of a biophysically-detailed model of the dynamic properties of electrical excitation of the body wall muscle of the c. elegans.

In the figure above, you can see the basic functionality that we are seeking to reproduce. The electrical activity of a muscle cell can be recorded using an electrode that is stuck into it. Connecting the electrode to a sensitive amplifier and stimulator allows a researcher to either use a current clamp or voltage clamp mode to control and examine the dynamics of the voltage changes or current flow across the membrane.
Ultimately, we understand from Hodgkin and Huxley that these electrical dynamics of the membrane are fully determined by the dynamics of ion channels that sit across the membrane.
In 2008, Dr. Netta Cohen and Dr. Jordan Boyle at the University of Leeds published an article with their mathematical model of these dynamics based on real data.
This model was expressed as a system of equations and a set of parameters in their publication, as well as C++ and Matlab code.
Their original code has been graciously shared with the OpenWorm project under the BoyleCohen2008 directory. In addition, a Python port of key components of the model has been added by OpenWorm contributors (Rayner Lucas).
For the purposes of re-using the model as a component of the larger OpenWorm project, we have converted the mathematical model of Cohen & Boyle into NeuroML2, an XML-based description of the system of equations that make up mathematical models of biophysically-based models of excitable membranes.
This repository contains the following:
- Simulation of C.Elegans muscle cell electrical properties, based on Boyle & Cohen 2008.
- NeuroML 2/LEMS conversion of the muscle cell model
- Optimization script for the above model, utliising Optimal Neuron package. Optimizing towards sharp electrode data obtained from lab of Michael M Francis.
- C++ Module for importation of arbitrary Pyramidal model into C++ program such as Palyanov et al SPH solver.
1. Simulation of C.Elegans muscle cell electrical properties
The authoritative version of the muscle cell model from Boyle & Cohen has been shared with the project under the BoyleCohen2008/ directory. Here you will also find a Python port of some of the scripts that demonstrate the dynamics of the muscle model.
An early attempt to convert this model into the NEURON package is available in the neuron_implementation/ directory (no longer supported).
2. NeuroML 2/LEMS conversion of the muscle cell model
This version of the muscle model reflects an initial attempt to convert the model from: http://www.sciencedirect.com/science/article/pii/S0303264708001408 into NeuroML 2 (http://www.neuroml.org/neuroml2.php).
See issue: https://github.com/openworm/OpenWorm/issues/169 for the latest.
See also http://www.opensourcebrain.org/projects/muscle_model/wiki.
2.1 Simulation of muscle cell ion channels
The muscle model contains NeuroML2 descriptions of the ion channels in the muscle cell. To create and run LEMS simulations of these ion channels, first install the dependencies as follows:
INSTALLDIR=~/git
mkdir $INSTALLDIR
cd $INSTALLDIR
git clone https://github.com/openworm/muscle_model
pip install lxml
git clone https://github.com/NeuralEnsemble/libNeuroML.git
cd libNeuroML
git checkout development
python setup.py install
cd ..
git clone https://github.com/NeuroML/pyNeuroML.git
cd pyNeuroML
python setup.py install
cd ../..
This will install the muscle model and all their dependencies into the directory defined by INSTALLDIR.
To create and run the LEMS simulations, there is a script for each of the NeuroML2 ion channel models. For example,
to create and run a simulation to analyse the fast potassium channel, go to the muscle_model/NeuroML2/ subdirectory and run the command:
./analyse_k_fast.sh
In this directory, you can run:
pynml LEMS_NeuronMuscle.xml
to run a simulation of a presynaptic neuron causing the muscle cell to spike:

Note: neither the presynaptic neuron (modelled as an Integrate and Fire neuron) nor the synapse model are physiologically constrained.
3. Optimization script for the above model
Note: see https://github.com/openworm/muscle_model/issues/18 for details on the current status of these subprojects.
See https://github.com/openworm/musclemodel/blob/master/pyramidalimplementation/README.md
4. C++ Module for SPH/muscle_model integration
Note: see https://github.com/openworm/muscle_model/issues/18 for details on the current status of these subprojects.
This is still at an alpha stage, but has been demonstrated to function as expected.
to compile and run (temp notes with hardcoded paths - replace with your own path) run the following commands from inside curdir:
$ export PYTHONPATH="/home/mike/dev/cpppyramidalintegration/" OR export PYTHONPATH=$PYTHONPATH:/home/mike/dev/musclemodel/pyramidalimplementation/ $ g++ main.cpp -l python2.7 -o sim -I /usr/include/python2.7/ $ ./sim
The resultant so file will then be importable in any c++ module and present a PyramidalSimulation class with a run() method which will return the membrane potential at the end of execution of a fixed timestep.
Reusing this model
The code in this repository is provided under the terms of the software license included with it. If you use this model in your research, we respectfully ask you to cite the references outlined in the CITATION file.
Owner
- Name: OpenWorm
- Login: openworm
- Kind: organization
- Email: info@openworm.org
- Location: International
- Website: http://openworm.org
- Repositories: 95
- Profile: https://github.com/openworm
An open-source project dedicated to creating a virtual C. elegans nematode in a computer.
Citation (CITATION.md)
## Citing this model The software in this repository is provided under the terms of the [software license](LICENSE) included with it. If you use this model in your research, we respectfully ask you to cite: **The original publication upon which this model is based** - Boyle JH, Cohen N. Caenorhabditis elegans body wall muscles are simple actuators. Biosystems. 2008;94: 170–181. **The latest release of this Open Source Brain repository** - This link should provide a DOI/citation for the latest version released: https://zenodo.org/badge/latestdoi/4203900. If you would like us to make a new release, please [open an issue](../../issues).
GitHub Events
Total
- Push event: 2
- Pull request event: 2
Last Year
- Push event: 2
- Pull request event: 2
Issues and Pull Requests
Last synced: over 1 year ago
All Time
- Total issues: 39
- Total pull requests: 31
- Average time to close issues: 5 months
- Average time to close pull requests: 7 days
- Total issue authors: 10
- Total pull request authors: 13
- Average comments per issue: 5.03
- Average comments per pull request: 0.77
- Merged pull requests: 30
- Bot issues: 0
- Bot pull requests: 0
Past Year
- Issues: 0
- Pull requests: 2
- Average time to close issues: N/A
- Average time to close pull requests: 13 minutes
- Issue authors: 0
- Pull request authors: 1
- Average comments per issue: 0
- Average comments per pull request: 0.0
- Merged pull requests: 2
- Bot issues: 0
- Bot pull requests: 0
Top Authors
Issue Authors
- travs (12)
- slarson (11)
- VahidGh (4)
- gsarma (4)
- rgerkin (2)
- shah-n (1)
- pgleeson (1)
- jaidhyani (1)
- vellamike (1)
- rayner (1)
Pull Request Authors
- pgleeson (8)
- rayner (8)
- VahidGh (3)
- gsarma (2)
- slarson (2)
- gitter-badger (1)
- brijeshmodi12 (1)
- souravsingh (1)
- borismarin (1)
- adrianq (1)
- msasinski (1)
- rgerkin (1)
- RobbySimpson (1)
Top Labels
Issue Labels
Pull Request Labels
Dependencies
- PyOSB *
- pyNeuroML *
- actions/checkout v2 composite
- actions/setup-python v2 composite
- actions/checkout v2 composite
- actions/setup-python v2 composite