// This hoc file reproduces the simulation of a grid cell in a circular environment from Fig. 7F of Welday et al.
//
// Before running this simulation, the theta cell spike trains from which the grid cell is formed must first be created
// and saved in files. This is done by running the MATLAB script 'grid_thetaspikes.m' from within the simulation directory.
//
// Since we are modeling a 1 hour recording session (3600 seconds), the simulation runs for a long time. To maximize speed
// and performance, you may wish to close the graph windows that plot the voltage trace (Graph[2]) and the spike raster
// (SpikePlot[0] for NetData[0]) before hitting the 'Init & Run' button to start the simulation.
//
// To save the glace cell's spike times when the simulation finishes, type:
//
// >>load_file("savespikes.hoc")
//
// at the interpreter prompt after the simulation has finished running. Spikes will be saved in a file called 'SPIKOUT.dat',
// and you can then create a path plot of the simulated grid cell's spike output by running the MATLAB script 'plotnrn.m'.
//
// The grid cell is formed by a target neuron that receives inhibitory input from three theta cells.
load_file("nrngui.hoc")
// -----------------------------------------------------------------
// read theta cell spike trains from disk files into NEURON vectors
// -----------------------------------------------------------------
load_file("grid_vecstims.ses") //create vecstim objects for delivering theta spike trains to the model neuron
numinputs = 3 //number of inhibitory theta inputs to the model neuron
objref evec[numinputs] //array of event vectors (VecStim.mod) for reading theta spike trains
objref spikefile //file object through which to read in theta cell spike times from disk
objref pplist //list of point processes containing theta spike trains
spikefile = new File()
pplist = new List()
load_file("read_grid_cell_theta_spikes.hoc") //read in theta cell spike timestamps from files
simlength=1000*3600
// --------------------------------------------------------------
// build a single-compartment postsynaptic cell
// --------------------------------------------------------------
ra = 150 // axial resistance through cytoplasm (ohms)
global_ra = ra
rm = 15000 // passive membrane resistance (ohms)
c_m = 1 // membrane capacitance (microFarads per centimeter squared, uF/cm^2)
create soma //single somatic compartment
access soma
PI=3.14159
{L=10/PI diam=10}
nseg=1
Ra = ra
cm = c_m
//Insert voltage-activated persistent sodium current (Nap.mod)
insert nap
gbar_nap=.00005 //Nap conductance
sh_nap=-2 //Nap voltage activation threshold shift parameter (mV)
//Insert Hodgkin-Huxley kinetics (hh.mod, standard NEURON mechanism)
insert hh
gkbar_hh=.005 //delayed rectifier K+ conductance
gnabar_hh=.05 //voltage-gated Na+ conductance
el_hh=-65 //leak reversal potential
gl_hh=1/rm //leak conductance
// --------------------------------------------------------------
// connect theta spike train inputs to the model neuron
// --------------------------------------------------------------
objref nclist //list of netcon objects for synaptic connections
nclist = new List()
load_file("gridcell_GABA_inputs.ses") //GABA-A synapses are simulated by modifying an AMPA current (found in ampa.mod)
//Convert AMPA currents to GABA
Erev_AMPA_S=-80 //set reversal potential to -80 mV to convert the AMPA synapse to GABA
Beta_AMPA_S=.12 //slow down the decay time a little bit for GABA currents
synw=.001 //conductance of GABA synapses
for i=0,numinputs-1 {
nclist.append(new NetCon(pplist.o(i), AMPA_S[i], -20, 1, synw)) //make the input connections
}
tstop=simlength
// ------------------------------------------------------------------------
// store model neuron's spike times in a vector to be saved later if needed
// ------------------------------------------------------------------------
objref spiketimes //vector in which to store timestamps of spikes generated by the model neuron
objref spikenc //netcon object through which spikes are passed into the 'spiketimes' vector
objref null //null object
spiketimes = new Vector()
spikenc = new NetCon(&v(0.5), null)
spikenc.threshold = -25 // store a spike timestamp if the postsynaptic membrane voltage exceeds -20 mV
spikenc.record(spiketimes) // record the spike times to the 'spiketimes' vector
//To save the postsynaptic neuron's spike times, type:
//
// >>load_file("savespikes.hoc")
//
//at the interpreter prompt after the simulation has finished running.
//Spikes will be saved in a file called 'SPIKOUT.dat'. MATLAB code
//(plotnrn.m) is provided for generating a "path plot" of the model
//neuron's spatial tuning function from the 'SPIKEOUT.dat' file. | 
