Pyramidal Neuron: Deep, Thalamic Relay and Reticular, Interneuron (Destexhe et al 1998, 2001)

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Accession:3817
This package shows single-compartment models of different classes of cortical neurons, such as the "regular-spiking", "fast-spiking" and "bursting" (LTS) neurons. The mechanisms included are the Na+ and K+ currents for generating action potentials (INa, IKd), the T-type calcium current (ICaT), and a slow voltage-dependent K+ current (IM). See http://cns.fmed.ulaval.ca/alain_demos.html
References:
1 . Destexhe A, Contreras D, Steriade M (1998) Mechanisms underlying the synchronizing action of corticothalamic feedback through inhibition of thalamic relay cells. J Neurophysiol 79:999-1016 [PubMed]
2 . Destexhe A, Contreras D, Steriade M (2001) LTS cells in cerebral cortex and their role in generating spike-and-wave oscillations. Neurocomputing 38:555-563
3 . Destexhe A, Sejnowski TJ (2001) Thalamocortical Assemblies-How Ion Channels, Single Neurons and large-Scale Networks Organize Sleep
Model Information (Click on a link to find other models with that property)
Model Type: Neuron or other electrically excitable cell;
Brain Region(s)/Organism:
Cell Type(s): Thalamus geniculate nucleus/lateral principal GLU cell; Thalamus reticular nucleus GABA cell; Neocortex L5/6 pyramidal GLU cell; Neocortex spiking regular (RS) neuron; Neocortex spiking low threshold (LTS) neuron;
Channel(s): I Na,t; I T low threshold; I K; I M; I Sodium; I Calcium; I Potassium;
Gap Junctions:
Receptor(s): GabaA; GabaB; AMPA; Gaba;
Gene(s):
Transmitter(s):
Simulation Environment: NEURON;
Model Concept(s): Activity Patterns; Bursting; Action Potentials; Calcium dynamics;
Implementer(s): Destexhe, Alain [Destexhe at iaf.cnrs-gif.fr];
Search NeuronDB for information about:  Thalamus geniculate nucleus/lateral principal GLU cell; Thalamus reticular nucleus GABA cell; Neocortex L5/6 pyramidal GLU cell; GabaA; GabaB; AMPA; Gaba; I Na,t; I T low threshold; I K; I M; I Sodium; I Calcium; I Potassium;
/
cortex
README *
cadecay.mod *
hh2.mod *
IM.mod *
IT.mod *
demo_IN_FS.oc *
demo_PY_LTS.oc *
demo_PY_RS.oc *
mosinit.hoc *
rundemo.hoc *
sIN_template
sPY_template
sPYr_template
                            
/*----------------------------------------------------------------------------

	Simplified model of bursting cortical neuron
	============================================

        Single-compartment model of "rebound bursts" in pyramidal
        neurons (type of cell very common in association areas of
	cortex).  The model is based on the presence of four
        voltage-dependent currents: 
        - INa, IK: action potentials
        - IM: slow K+ current for spike-frequency adaptation
        - IT: T-type calcium currents for burst generation

This model is described in the following reference:

  Destexhe, A. Contreras, D. and Steriade, M.  LTS cells in cerebral cortex
  and their role in generating spike-and-wave oscillations.   
  Neurocomputing 38: 555-563 (2001).


        Alain Destexhe, CNRS, 2000
	http://cns.iaf.cnrs-gif.fr

----------------------------------------------------------------------------*/


batch = 0		// for batch processing (use nrniv)


//----------------------------------------------------------------------------
//  load and define general graphical procedures
//----------------------------------------------------------------------------

load_file("stdrun.hoc")

objectvar g[20]			// max 20 graphs
ngraph = 0

proc addgraph() { local ii	// define subroutine to add a new graph
				// addgraph("variable", minvalue, maxvalue)
	ngraph = ngraph+1
	ii = ngraph-1
	g[ii] = new Graph()
	g[ii].size(tstart,tstop,$2,$3)
	g[ii].xaxis()
	g[ii].yaxis()
	g[ii].addvar($s1,1,0)
	g[ii].save_name("graphList[0].")
	graphList[0].append(g[ii])
}

proc addtext() { local ii	// define subroutine to add a text graph
				// addtext("text")
	ngraph = ngraph+1
	ii = ngraph-1
	g[ii] = new Graph()
	g[ii].size(0,tstop,0,1)
	g[ii].xaxis(3)
	g[ii].yaxis(3)
	g[ii].label(0.1,0.8,$s1)
	g[ii].save_name("graphList[0].")
	graphList[0].append(g[ii])
	text_id = ii
}

proc addline() {		// to add a comment to the text window
				// addline("text")
	g[text_id].label($s1)
}


if(ismenu==0) {
  nrnmainmenu()			// create main menu
  nrncontrolmenu()		// crate control menu
}



//----------------------------------------------------------------------------
//  transient time
//----------------------------------------------------------------------------

trans = 0000

print " "
print ">> Transient time of ",trans," ms"
print " "









//----------------------------------------------------------------------------
//  create PY cells
//----------------------------------------------------------------------------

print " "
print "<<==================================>>"
print "<<            CREATE CELLS          >>"
print "<<==================================>>"
print " "

load_file("sPYr_template")		// read geometry file

ncells = 1			// nb of cells in each layer <<>>

objectvar PY[ncells]
for i=0,ncells-1 {
  PY[i] = new sPYr()
}









//----------------------------------------------------------------------------
//  Rebound parameters
//----------------------------------------------------------------------------

// T-current density adjusted to delaPena & Geigo-Barrientos

PY[0].soma {
	gcabar_it = 4e-4
	gkbar_im = 3e-5
	g_pas = 1e-5
	e_pas = -85
	gnabar_hh2 = 0.05
	gkbar_hh2 = 0.005
}

// this parameter set (above) is for bursting behavior; for 
// regular spiking:
//   e_pas = -75
//   El[0].stim.amp = 0.12
// LTS:
//   e_pas = -60
//   El[0].stim.amp = -0.075
// bursting:
//   e_pas = -85
//   El[0].stim.amp = 0.15

// classic RS and FS behavior are obtained by blocking IT and IM successively







//----------------------------------------------------------------------------
//  insert electrode in each PY cell
//----------------------------------------------------------------------------

if(ismenu==0) {
  load_file("electrod.hoc")	// electrode template
  ismenu = 1
}

objectvar El[ncells]			// create electrodes

CURR_AMP = 0.15

for i=0,ncells-1 {			// insert one in each cell
	PY[i].soma El[i] = new Electrode()
	PY[i].soma El[i].stim.loc(0.5)
	El[i].stim.del = 400
	El[i].stim.dur = 400
	El[i].stim.amp = CURR_AMP
}

electrodes_present=1


//----------------------------------------------------------------------------
//  setup simulation parameters
//----------------------------------------------------------------------------

Dt = .1				// macroscopic time step <<>>
npoints = 10000

dt = 0.1			// must be submultiple of Dt
tstart = trans
tstop = trans + npoints * Dt
runStopAt = tstop
steps_per_ms = 5
celsius = 36
v_init = -84






//----------------------------------------------------------------------------
//  add graphs
//----------------------------------------------------------------------------

strdef gtxt

if(batch == 0) {
  addgraph("PY[0].soma.m_im",0,1)
//  addgraph("PY[0].soma.m_iahp",0,1)
  for i=0,ncells-1 {
	sprint(gtxt,"PY[%d].soma.v(0.5)",i)
	addgraph(gtxt,-120,40)
  }
}





//----------------------------------------------------------------------------
//  add text
//----------------------------------------------------------------------------

access PY[0].soma

proc text() {
  sprint(gtxt,"%d PY cells",ncells)
  addtext(gtxt)
  sprint(gtxt,"Passive: gleak=%g Eleak=%g",PY.soma.g_pas,PY.soma.e_pas)
  addline(gtxt)
  sprint(gtxt,"HH: gNa=%g, gK=%g, vtraub=%g",PY.soma.gnabar_hh2,\
  PY.soma.gkbar_hh2,PY.soma.vtraub_hh2)
  addline(gtxt)
  sprint(gtxt,"IM: g=%g, taumax=%g",PY.soma.gkbar_im,taumax_im)
  addline(gtxt)
  sprint(gtxt,"Ca++: tau=%g, depth=%g, cainf=%g",taur_cad,depth_cad,cainf_cad)
  addline(gtxt)
  sprint(gtxt,"IT: g=%g",PY.soma.gcabar_it)
  addline(gtxt)
}


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