Files included in the NEURON implementation:
 CaDynamics_E2.mod: Ca2+ dynamics mod file
 Ca_HVA.mod                 #High-voltage activated Ca2+ current mod file
 Ca_LVAst.mod               #Low-voltage activated Ca2+ current mod file
 Ih.mod                     #HCN channel current mod file
 Im.mod                     #Muscarinic K+ current mod file
 K_Pst.mod                  #Persistent K+ current mod file
 K_Tst.mod                  #Transient K+ current mod file
 NaTa_t.mod                 #Transient Na+ current mod file
 Nap_Et2.mod                #Persistent Na+ current mod file
 SK_E2.mod                  #SK current mod file
 SKv3_1.mod                 #Kv3.1 channel (K+) current mod file
 epsp.mod                   #EPSC-like synaptic current mod file
 fullhay_run_1.dat          #Reference simulation results of the full model
                            #  using a somatic stimulus
 fullhay_run_2.dat          #Reference simulation results of the full model
                            #  using a synaptic stimulus
 fullhay_run_3.dat          #Reference simulation results of the full model
                            #  using a somatic+synaptic stimulus
 fullhay_run_3a.dat         #Reference simulation results of the full model
                            #  using a somatic stimulus
 models/fourcompartment.hoc #The model template
 runmodel.hoc               #The hoc file for running the simulations 1, 2, 3 and 3a
                            #  (this creates run_1.dat, run_2.dat, run_3.dat data files
                            #  that you plot later)
 runmodel.py                #The python file for running the simulations 1, 2, 3 and
                            #  3a and plotting the results 

Mod and hoc-files are based on the ModelDB entry 139653
(http://modeldb.yale.edu/139653).

Run the NEURON implementation and plot the results (runs.eps) by
running commands:


nrnivmodl
python runmodel.py
This script reproduces data showed in (Mäki-Marttunen et al.: "Step-wise model fitting
                                       accounting for high-resolution spatial measurements:
                                       construction of a layer V pyramidal cell model with
                                       reduced morphology", BMC Neuroscience 2016,
                                       17(Suppl 1), p. 165):



Alternatively, run without python and save the results to files run_1.dat, run_2.dat, run_3.dat and run_3a.dat:


nrnivmodl
nrniv runmodel.hoc