Visual Cortex Neurons: Dendritic computations (Archie, Mel 2000)

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Accession:3682
Neuron and C program files from Archie, K.A. and Mel, B.W. A model of intradendritic computation of binocular disparity. Nature Neuroscience 3:54-63, 2000 The original files for this model are located at the web site http://www-lnc.usc.edu/~karchie/synmap
Reference:
1 . Archie KA, Mel BW (2000) A model for intradendritic computation of binocular disparity. Nat Neurosci 3:54-63 [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): Neocortex L5/6 pyramidal GLU cell;
Channel(s): I Na,t; I K;
Gap Junctions:
Receptor(s): AMPA;
Gene(s):
Transmitter(s):
Simulation Environment: NEURON;
Model Concept(s): Spatio-temporal Activity Patterns; Active Dendrites; Vision;
Implementer(s): Hines, Michael [Michael.Hines at Yale.edu]; Archie, Kevin A [karchie at lnc.usc.edu];
Search NeuronDB for information about:  Neocortex L5/6 pyramidal GLU cell; AMPA; I Na,t; I K;
objectvar save_window_, rvp_
objectvar scene_vector_[4]
objectvar ocbox_, ocbox_list_, scene_, scene_list_
{ocbox_list_ = new List()  scene_list_ = new List()}
{
xpanel("RunControl", 0)
v_init = -65
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()")
t = 0
xvalue("t","t", 2 )
tstop = 250
xvalue("Tstop","tstop", 1,"tstop_changed()", 0, 1 )
dt = 0.025
xvalue("dt","dt", 1,"setdt()", 0, 1 )
steps_per_ms = 40
xvalue("Points plotted/ms","steps_per_ms", 1,"setdt()", 0, 1 )
xcheckbox("Quiet",&stdrun_quiet,"")
realtime = 0
xvalue("Real Time","realtime", 0,"", 0, 1 )
xpanel(82,116)
}
{
save_window_ = new Graph(0)
save_window_.size(0,250,-80,40)
scene_vector_[2] = save_window_
{save_window_.view(0, -80, 250, 120, 385, 24, 300.48, 200.32)}
graphList[0].append(save_window_)
save_window_.save_name("graphList[0].")
save_window_.addexpr("v(.5)", 1, 1, 0.8, 0.9, 2)
}
{
xpanel("Parameters", 0)
xbutton("Passive Properties","passive_menu()")
xbutton("Active Channels","active_menu()")
xbutton("Synapses","synapses_menu()")
xpanel(388,292)
}
{
save_window_ = new Shape(0)
save_window_.size(-47.0031,494.869,-175.449,366.424)
scene_vector_[3] = save_window_
{save_window_.view(-47.0031, -175.449, 541.872, 541.872, 384, 442, 200.64, 200.32)}
}
objectvar scene_vector_[1]
{doNotify()}

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