This is the code for the CA3 hippocampal model in the paper by Sherif et al, 2020, in npj Schizophrenia.
The code has been updated to use Python3. In addition to NEURON, the following python packages are needed:
hyp5
configparser
(You can use conda or pip to install them).
After you install the required packages, compile the mod files:
nrnivmodl
To plot a figure similar to figure 1 in the paper with the control conditions, you will need first to run a control simulation. The configuraiton file with the parameters for the model are in fig1simulationConfig.cfg file. The following code will run a simulation that is 3 seconds long (it takes around one minute to run on my machine with 8 cores), and save the resulting output file in directory ./data/batch.
After the file has been generated (or if you want to plot the provided output sample file), you can run the following code:
python -i analysisPlottingCode.py
Then inside python:
simstr = 'controlSimulation' # name of simulation that just ran - set in the configuration file.
loadedSim = loadSimH5py(simstr, datadir = './data/batch/')
myfig, rastsp, lfpsp, psdsp = plotloadedsimProfiling(loadedSim, 0)
rastsp.set_xlim(2000, 3000) # plot the last 1000 ms (1 second).
# annotate y-axis of raster for the different neuronal populations
rastsp.set_ylabel('')
rastsp.set_yticklabels('')
rastsp.annotate('PYR', xy=(-0.1, 0.33), xycoords='axes fraction', color = 'red', fontsize = 12, fontweight='bold')
rastsp.annotate('PV', xy=(-0.1, 0.73), xycoords='axes fraction', color = 'green', fontsize = 12, fontweight='bold')
rastsp.annotate('OLM', xy=(-0.1, 0.88), xycoords='axes fraction', color = 'blue', fontsize = 12, fontweight='bold')
# change color of LFP voltage plot to black
lfpline = lfpsp.get_lines()[0]
lfpline.set_color('k')
# change color of PSD plot to black
psdline = psdsp.get_lines()[0]
psdline.set_color('k')
You should get a figure similar to the one below:
