CellML Models for Cardiac Cellular Electrophysiological Modelling

We here present the CellML models referenced in the book chapter: Cardiac Cellular Electrophysiological Modelling. This notebook requires the OpenCOR Phython environment to run, as described here: https://opencor.github.io/userInterfaces/commandLineInterfacePythonRelatedScripts.html

import opencor as opencor
import matplotlib.pyplot as plt

Figure 4

First we load the SED-ML files which define the single stimulus simulation experiments that we want to run with the original FHN model and each of the Rogers & McCulloch and Aliev & Panfilov modified versions of the FHN model.

fhn = opencor.open_simulation('models/1961_fitzhugh/experiments/single-stimulus.sedml')
rogers = opencor.open_simulation('models/1994_rogers/experiments/single-stimulus.sedml')
aliev = opencor.open_simulation('models/1996_aliev/experiments/single-stimulus.sedml')

We can now run each of the simulations and grabthe results that we wish to plot.

# reset and clear any existing results
fhn.reset(True)
fhn.clear_results()
rogers.reset(True)
rogers.clear_results()
aliev.reset(True)
aliev.clear_results()

# decalare our results dictionaries
fhn_data = {}
rogers_data = {}
aliev_data = {}

fhn.run()
ds = fhn.results().data_store()
# membrane potential
fhn_data['Vm'] = ds.voi_and_variables()['output_variables/Vm'].values()
# activation variable
fhn_data['v'] = ds.voi_and_variables()['output_variables/v'].values()
# Total current
fhn_data['Iion'] = ds.voi_and_variables()['output_variables/Iion'].values()

rogers.run()
ds = rogers.results().data_store()
# membrane potential
rogers_data['Vm'] = ds.voi_and_variables()['output_variables/Vm'].values()
# activation variable
rogers_data['v'] = ds.voi_and_variables()['output_variables/v'].values()
# Total current
rogers_data['Iion'] = ds.voi_and_variables()['output_variables/Iion'].values()

aliev.run()
ds = aliev.results().data_store()
# membrane potential
aliev_data['Vm'] = ds.voi_and_variables()['output_variables/Vm'].values()
# activation variable
aliev_data['v'] = ds.voi_and_variables()['output_variables/v'].values()
# Total current
aliev_data['Iion'] = ds.voi_and_variables()['output_variables/Iion'].values()

Now that we have the data, we can generate the desired plots

time = range(0,801)
plt.figure(figsize=(8,4))
plt.plot(time, fhn_data['Vm'], label='FHN', color='red', linewidth=2)
plt.plot(time, rogers_data['Vm'], label='Rogers', color='blue', linewidth=2)
plt.plot(time, aliev_data['Vm'], label='Aliev', color='green', linewidth=2)
plt.legend()
plt.ylabel('Potential (mV)')
plt.xlabel('Time (ms)')
plt.figure(figsize=(8,4))
plt.plot(time, fhn_data['v'], label='FHN', color='red', linewidth=2)
plt.plot(time, rogers_data['v'], label='Rogers', color='blue', linewidth=2)
plt.plot(time, aliev_data['v'], label='Aliev', color='green', linewidth=2)
plt.legend()
plt.ylabel('Activation variable ()')
plt.xlabel('Time (ms)')
plt.figure(figsize=(8,4))
plt.plot(time, fhn_data['Iion'], label='FHN', color='red', linewidth=2)
plt.plot(time, rogers_data['Iion'], label='Rogers', color='blue', linewidth=2)
plt.plot(time, aliev_data['Iion'], label='Aliev', color='green', linewidth=2)
plt.legend()
plt.ylabel('Membrane current (uA/mm2)')
plt.xlabel('Time (ms)')
plt.show()