An implementation of the NEURON models created for the article: "BK channels have opposite effects on sodium versus calcium mediated action potentials in endocrine pituitary cells.", and all analysis of the models.

The content of this folder is:

• medaka.py - contains the Medaka model.
• burstines.py - contains the functions for calculating the burstiness.
• uq.py - contains the uncertainty quantification and sensitivity analysis of the models.
• *.mod - NEURON files that implements the various ion channels.
• platform_information.py - prints platform information.

We have created a Docker environment with all dependencies installed. This Docker environment can be started by running the bash script run_docker.sh from within this directory. All results have been created in this Docker environment.

The required dependencies are:

• numpy
• matplotlib
• uncertainpy
• chaospy
• NEURON

These can be installed with:

pip install numpy
pip install matplotlib
pip install uncertainpy
pip install chaospy

Additionally, the Neuron simulator with the Python interface is required. NEURON must be manually installed by the user.

To perform the uncertainty quantification and sensitivity analysis of the model run:

python uq.py

The uncertainty quantification and sensitivity analysis results have been generated inside a Docker environment with:

Platform: linux
Python: 3.7.1 (default, Dec 14 2018, 19:28:38)
[GCC 7.3.0]
Machine and architecture x86_64 64bit
NumPy: 1.15.2
matplotlib: 3.0.0
Chaospy: 2.3.5
Uncertainpy: 1.1.4
NEURON: 7.6.6