GPi/GPe neuron models (Johnson and McIntyre 2008)

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Accession:114685
Model files for two types of non-human primate neurons used in the paper: simplified versions of 1) a GPi neuron and 2) a GPe axon collateralizing in GPi en route to STN.
Reference:
1 . Johnson MD, McIntyre CC (2008) Quantifying the neural elements activated and inhibited by globus pallidus deep brain stimulation. J Neurophysiol 100:2549-63 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Neuron or other electrically excitable cell; Axon;
Brain Region(s)/Organism:
Cell Type(s): Globus pallidus neuron;
Channel(s): I Sodium; I Calcium; I Potassium;
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment: NEURON;
Model Concept(s): Simplified Models; Axonal Action Potentials; Parkinson's; Extracellular Fields;
Implementer(s): Johnson, Matthew D [johnsom11 at ccf.org];
Search NeuronDB for information about:  I Sodium; I Calcium; I Potassium;
{load_file("nrngui.hoc")}
objectvar save_window_, rvp_
objectvar scene_vector_[6]
objectvar ocbox_, ocbox_list_, scene_, scene_list_
{ocbox_list_ = new List()  scene_list_ = new List()}
{pwman_place(0,0,0)}
{
xpanel("RunControl", 0)
v_init = -60
xvalue("Init","v_init", 1,"stdinit()", 1, 1 )
xbutton("Init & Run","run()")
xbutton("Stop","stoprun=1")
runStopAt = 1000
xvalue("Continue til","runStopAt", 1,"{continuerun(runStopAt) stoprun=1}", 1, 1 )
runStopIn = 1
xvalue("Continue for","runStopIn", 1,"{continuerun(t + runStopIn) stoprun=1}", 1, 1 )
xbutton("Single Step","steprun()")
t = 1000
xvalue("t","t", 2 )
tstop = 1000
xvalue("Tstop","tstop", 1,"tstop_changed()", 0, 1 )
dt = 0.01
xvalue("dt","dt", 1,"setdt()", 0, 1 )
steps_per_ms = 50
xvalue("Points plotted/ms","steps_per_ms", 1,"setdt()", 0, 1 )
screen_update_invl = 0.05
xvalue("Scrn update invl","screen_update_invl", 1,"", 0, 1 )
realtime = 227.25
xvalue("Real Time","realtime", 0,"", 0, 1 )
xpanel(3,121)
}
{
save_window_ = new Graph(0)
save_window_.size(0,2000,-100,80)
scene_vector_[2] = save_window_
{save_window_.view(0, -100, 1000, 180, 350, 370, 700, 240)}
graphList[0].append(save_window_)
save_window_.save_name("graphList[0].")

save_window_.addvar("soma[0].v( 0.5 )", 1, 1, 0.8, 0.9, 2)
save_window_.addvar("dend[30].v( 0.5 )", 2, 1, 0.8, 0.9, 2)
save_window_.addvar("node[26].v( 0.5 )", 3, 1, 0.8, 0.9, 2)

/*
save_window_.addvar("node[0].v( 0.5 )", 1, 1, 0.8, 0.9, 2)
save_window_.addvar("node[1].v( 0.5 )", 1, 1, 0.8, 0.9, 2)
save_window_.addvar("node[2].v( 0.5 )", 1, 1, 0.8, 0.9, 2)
save_window_.addvar("node[3].v( 0.5 )", 1, 1, 0.8, 0.9, 2)
save_window_.addvar("node[4].v( 0.5 )", 1, 1, 0.8, 0.9, 2)
save_window_.addvar("node[5].v( 0.5 )", 2, 1, 0.8, 0.9, 2)
save_window_.addvar("node[6].v( 0.5 )", 2, 1, 0.8, 0.9, 2)
save_window_.addvar("node[7].v( 0.5 )", 2, 1, 0.8, 0.9, 2)
save_window_.addvar("node[8].v( 0.5 )", 2, 1, 0.8, 0.9, 2)
save_window_.addvar("node[9].v( 0.5 )", 2, 1, 0.8, 0.9, 2)
save_window_.addvar("node[10].v( 0.5 )", 3, 1, 0.8, 0.9, 2)
save_window_.addvar("node[11].v( 0.5 )", 3, 1, 0.8, 0.9, 2)
save_window_.addvar("node[12].v( 0.5 )", 3, 1, 0.8, 0.9, 2)
save_window_.addvar("node[13].v( 0.5 )", 3, 1, 0.8, 0.9, 2)
save_window_.addvar("node[14].v( 0.5 )", 3, 1, 0.8, 0.9, 2)
save_window_.addvar("node[15].v( 0.5 )", 4, 1, 0.8, 0.9, 2)
save_window_.addvar("node[16].v( 0.5 )", 4, 1, 0.8, 0.9, 2)
save_window_.addvar("node[17].v( 0.5 )", 4, 1, 0.8, 0.9, 2)
save_window_.addvar("node[18].v( 0.5 )", 4, 1, 0.8, 0.9, 2)
save_window_.addvar("node[19].v( 0.5 )", 4, 1, 0.8, 0.9, 2)
save_window_.addvar("node[20].v( 0.5 )", 5, 1, 0.8, 0.9, 2)
save_window_.addvar("node[21].v( 0.5 )", 5, 1, 0.8, 0.9, 2)
save_window_.addvar("node[22].v( 0.5 )", 5, 1, 0.8, 0.9, 2)
save_window_.addvar("node[23].v( 0.5 )", 5, 1, 0.8, 0.9, 2)
save_window_.addvar("node[24].v( 0.5 )", 5, 1, 0.8, 0.9, 2)
save_window_.addvar("node[25].v( 0.5 )", 6, 1, 0.8, 0.9, 2)
save_window_.addvar("node[26].v( 0.5 )", 6, 1, 0.8, 0.9, 2)
*/
}

objectvar scene_vector_[1]
{doNotify()}

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