Model of repetitive firing in Grueneberg ganglion olfactory neurons (Liu et al., 2012)

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Accession:151817
This model is constructed based on properties of Na+ and K+ currents observed in whole-cell patch clamp recordings of mouse Grueneberg ganglion neurons in acute slices. Two distinct Na+ conductances representing the TTX-sensitive and TTX-resistant currents and one delayed rectifier K+ currrent are included. By modulating the maximal conductances of Na+ currents, one can reproduce the regular, phasic, and sporadic patterns of repetitive firing found in the patch clamp experiments.
Reference:
1 . Liu CY, Xiao C, Fraser SE, Lester HA, Koos DS (2012) Electrophysiological characterization of Grueneberg ganglion olfactory neurons: spontaneous firing, sodium conductance, and hyperpolarization-activated currents. J Neurophysiol 108:1318-34 [PubMed]
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): Olfactory receptor GLU cell; Grueneberg ganglion neuron;
Channel(s): I K; I K,leak; I Sodium;
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment: NEURON;
Model Concept(s): Action Potential Initiation; Temporal Pattern Generation; Action Potentials; Rebound firing; Recurrent Discharge; Olfaction;
Implementer(s): Liu, Cambrian [camliu at chla.usc.edu];
Search NeuronDB for information about:  Olfactory receptor GLU cell; I K; I K,leak; I Sodium;
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GG
readme.txt
code_holder.hoc
elvis.ses
elvism10.ses
elvisp10.ses
graphs.hoc
gui_controller.hoc
hvas.ses
iclamp.hoc
init.hoc
kchannels.ses
leak.ses
mosinit.hoc *
runner.hoc
soma.hoc
                            
{load_file("nrngui.hoc")}
objectvar save_window_, rvp_
objectvar scene_vector_[4]
objectvar ocbox_, ocbox_list_, scene_, scene_list_
{ocbox_list_ = new List()  scene_list_ = new List()}
{pwman_place(0,0,0)}

//Begin ChannelBuild[0] managed KSChan[0]
{
load_file("chanbild.hoc", "ChannelBuild")
}
{ocbox_ = new ChannelBuild(1)}
{object_push(ocbox_)}
{genprop.set_data("TTXR", 1, 1, -1, "NonSpecific")}
{genprop.set_defstr(0.002438, 50)}
tobj = new ChannelBuildKSGate(this)
{gatelist.append(tobj)}
{tobj.begin_restore(3)}
{tobj.set_state("m", 1, 110, 140)}
{tobj.set_trans(0, 0, 0)}
{tobj.transitions.object(0).settype(0, "")}
{tobj1 = new Vector(3)  for (i=0; i < 3; i += 1) tobj1.x[i] = fscan() }
0.552
0.43478
-64
{tobj.transitions.object(0).set_f(0, 3, tobj1)}
{tobj1 = new Vector(3)  for (i=0; i < 3; i += 1) tobj1.x[i] = fscan() }
0.61
-0.034483
-66
{tobj.transitions.object(0).set_f(1, 2, tobj1)}
{tobj.end_restore()}
tobj = new ChannelBuildKSGate(this)
{gatelist.append(tobj)}
{tobj.begin_restore(1)}
{tobj.set_state("h", 1, 110, 130)}
{tobj.set_trans(0, 0, 0)}
{tobj.transitions.object(0).settype(0, "")}
{tobj1 = new Vector(3)  for (i=0; i < 3; i += 1) tobj1.x[i] = fscan() }
0.0093
-0.095238
-65
{tobj.transitions.object(0).set_f(0, 2, tobj1)}
{tobj1 = new Vector(3)  for (i=0; i < 3; i += 1) tobj1.x[i] = fscan() }
1.6
-0.032258
-53
{tobj.transitions.object(0).set_f(1, 4, tobj1)}
{tobj.end_restore()}
end_restore()
{genprop.set_single(0)}
{set_alias(0)}
{usetable(0)}
{object_pop()}
{
ocbox_.map("ChannelBuild[0] managed KSChan[0]", 193, 193, 207, 273.6)
}
objref ocbox_
//End ChannelBuild[0] managed KSChan[0]

objectvar scene_vector_[1]
{doNotify()}

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