Reproduction of: Fast-Activating Voltage- and Calcium-Dependent Potassium (BK) Conductance Promotes Bursting in Pituitary Cells: A Dynamic Clamp Study

A reference implementation of "Fast-Activating Voltage- and Calcium-Dependent Potassium (BK) Conductance Promotes Bursting in Pituitary Cells: A Dynamic Clamp Study, J. Tabak, M. Tomaiuolo, A. Gonzalez-Iglesias, L. Milescu and R. Bertram, Journal of Neuroscience 31.46 (2011), 10.1523/JNEUROSCI.3235-11.2011"

Docker environment

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

Dependencies

The required dependencies are:

• numpy
• matplotlib
• uncertainpy
• chaospy
• tqdm
• NEURON

These can be installed with:

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

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

Content

The content is:

• article/ - Contains the description of the reproduction.
• code/ - Contains the code for reproducing the results.

Running the code

The code is found in the code/ directory. To create Figure 1 and Figure 2 in Tabak et al. run from code/:

python analysis.py

This runs in parallel and takes around 10 hours on a workstation computer.

This reproduction can be speed up by increasing the time step dt in tabak.py. Setting dt = 0.25 gives results similar to the results in the paper, and only takes around 23 minutes.

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

python uq.py

This takes around 20 minutes on a workstation computer.