Passive properties and Ih properties are all fitted from experimental data from the same cells from which morphology data was derived. Thus, passive, Ih, and morphological data are matched for each given model. Each model then represents one cell. The remaining active conductances, however, are tuned to reproduce firing characteristics as best as possible for the same cells. However, the channel properties are derived from previous OLM (and non-OLM) cells and thus are not experimentally constrained by recordings from the same cell. They can thus be varied to explore parameter spaces or fit new experimental data.
However, the passive and Ih properties (for the latter this includes Ih steady state activation function, time dependency of activation and deactivation, and reversal potential) should remain fixed as they have been determined directly from recordings.
In the init_model.hoc file there are three parameters to define the model:
cell - one of 1, 2, or 3, corresponding to the three reconstructed cells in the paper
paramtype - one of 1 (passive), 2 (passive + Ih), or 3 (passive + Ih + spiking currents)
modeltype - only used by the spiking model cells (1 and 2), corresponding to the five different spiking parameter sets to choose from (i.e. the top five models from the multi-objective optimization). To specify which spiking model, set the "modelnum" parameter to any value between 1 and 5 (in order from highest ranked to fifth-ranked).
Use nrngui or nrniv as follows:
nrngui init_model.hoc
The parameters specified in the previous section can also be commented out and provided during model invocation on the command-line using the -c switches for nrngui or nrniv, e.g.,
nrngui -c 'cell=1' -c 'paramtype=3' -c 'modelnum=1' init_model.hoc
Use python and as follows:
python init.py
Most parameters are found in either the sim_params.hoc file or in the per-cell parameter files within the "param_files" directory. The ones in sim_params.hoc are particularly relevant for global aspects of operation such as length of simulation, integration method, current clamp injection parameters, etc.
Current-clamp traces under synaptic blocker wash-in conditions for cells 1 and 2 can be found in the respective CellX_exp_data/ directories. These traces are needed for init.py to run for the spiking models, but can be commented out if only running init.py to obtain the currentscape plots. The injected current amplitude is included in the filename.