Stochastic layer V pyramidal neuron: interpulse interval coding and noise (Singh & Levy 2017)

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Accession:237594
Layer V pyramidal neuron with stochastic Na channels. Supports evidence for interpulse interval coding and has very detailed AIS with Nav1.2 and Nav1.6 channels.
Reference:
1 . Singh C, Levy WB (2017) A consensus layer V pyramidal neuron can sustain interpulse-interval coding. PLoS One 12:e0180839 [PubMed]
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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: Neocortex;
Cell Type(s): Neocortex L5/6 pyramidal GLU cell;
Channel(s):
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment: NEURON;
Model Concept(s): Action Potential Initiation;
Implementer(s): Singh, Chandan [chandan_singh at berkeley.edu];
Search NeuronDB for information about:  Neocortex L5/6 pyramidal GLU cell;
{load_file("nrngui.hoc")}
objectvar save_window_, rvp_
objectvar scene_vector_[5]
objectvar ocbox_, ocbox_list_, scene_, scene_list_
{ocbox_list_ = new List()  scene_list_ = new List()}
{pwman_place(0,0,0)}
{
xpanel("RunControl", 0)
xvalue("Init","v_init", 1,"stdinit()", 1, 1 )
xbutton("Init & Run","run()")
xbutton("Stop","stoprun=1")
runStopAt = 5
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()")
xvalue("t","t", 2 )
xvalue("Tstop","tstop", 1,"tstop_changed()", 0, 1 )
xvalue("dt","dt", 1,"setdt()", 0, 1 )
steps_per_ms = 100
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 = 4.83
xvalue("Real Time","realtime", 0,"", 0, 1 )
xpanel(410,963)
}
{
save_window_ = new Graph(0)
save_window_.size(0,30,-80,50)
scene_vector_[4] = save_window_
{save_window_.view(50, -80, 50, 130, 771, 971, 612.48, 440.32)}
graphList[0].append(save_window_)
save_window_.save_name("graphList[0].")
save_window_.addvar("node[0].v(.5)", 3, 3, 0, 1, 2)
save_window_.addvar("soma.v(.5)", 1, 3, 0, 1, 2)
save_window_.addvar("ais[5].v(1)", 2, 3, 0, 1, 2)
}
objectvar scene_vector_[1]
{doNotify()}