Recurrent discharge in a reduced model of cat spinal motoneuron (Balbi et al, 2013)

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Accession:151443
Following a distal stimulation of a motor fibre, only a fraction of spinal motoneurons are able to produce a re-excitation of the initial segment leading to an orthodromically conducted action potential, known as recurrent discharge. In order to show the reciprocal interplay of the axonal initial segment and the soma leading to recurrent discharge in detail, a reduced model of a cat spinal motoneuron was developed.
Reference:
1 . Balbi P, Martinoia S, Colombo R, Massobrio P (2014) Modelling recurrent discharge in the spinal a-motoneuron: reappraisal of the F wave. Clin Neurophysiol 125:427-9 [PubMed]
Citations  Citation Browser
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): Spinal cord lumbar motor neuron alpha ACh cell;
Channel(s): I Na,p; I Na,t; I K; I K,Ca;
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment: NEURON;
Model Concept(s): Recurrent Discharge;
Implementer(s): Balbi, Pietro [piero.balbi at fsm.it];
Search NeuronDB for information about:  Spinal cord lumbar motor neuron alpha ACh cell; I Na,p; I Na,t; I K; I K,Ca;
{load_file("nrngui.hoc")}
objectvar save_window_, rvp_
objectvar scene_vector_[7]
objectvar ocbox_, ocbox_list_, scene_, scene_list_
{ocbox_list_ = new List()  scene_list_ = new List()}
{pwman_place(0,0,0)}

//Begin PointProcessManager
{
load_file("pointman.hoc")
}
{
soma ocbox_ = new PointProcessManager(0)
}
{object_push(ocbox_)}
{
mt.select("IClamp") i = mt.selected()
ms[i] = new MechanismStandard("IClamp")
ms[i].set("del", 0.5, 0)
ms[i].set("dur", 0.5, 0)
ms[i].set("amp", 40, 0)
mt.select("IClamp") i = mt.selected() maction(i)
hoc_ac_ = 0.5
sec.sec move() d1.flip_to(0)
}
{object_pop() doNotify()}
{
ocbox_ = ocbox_.v1
ocbox_.map("PointProcessManager", 34, 426, 208, 298)
}
objref ocbox_
//End PointProcessManager

{
xpanel("RunControl", 0)
v_init = -70
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 = 20
xvalue("t","t", 2 )
tstop = 20
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 )
screen_update_invl = 0.05
xvalue("Scrn update invl","screen_update_invl", 1,"", 0, 1 )
realtime = 0.57
xvalue("Real Time","realtime", 0,"", 0, 1 )
xpanel(7,80)
}
{
save_window_ = new Graph(0)
save_window_.size(0,20,-80,40)
scene_vector_[3] = save_window_
{save_window_.view(0, -80, 20, 120, 270, 84, 300, 200)}
graphList[0].append(save_window_)
save_window_.save_name("graphList[0].")
save_window_.addexpr("v(.5)", 1, 1, 0.8, 0.9, 2)
}
{
save_window_ = new Graph(0)
save_window_.size(0,20,-80,40)
scene_vector_[4] = save_window_
{save_window_.view(0, -80, 20, 120, 272, 312, 300, 200)}
graphList[0].append(save_window_)
save_window_.save_name("graphList[0].")
save_window_.addexpr("v(.5)", 1, 1, 0.8, 0.9, 2)
save_window_.addexpr("IS.v(.5)", 2, 1, 0.8, 0.9, 2)
save_window_.addexpr("node[30].v(.5)", 3, 1, 0.8, 0.9, 2)
}
{
save_window_ = new Graph(0)
save_window_.size(0,20,0,1)
scene_vector_[5] = save_window_
{save_window_.view(0, 0, 20, 1, 576, 84, 300, 200)}
graphList[2].append(save_window_)
save_window_.save_name("graphList[2].")
save_window_.addexpr("soma.h_Naf_So(.5)", 2, 1, 0.633333, 1.01, 2)
save_window_.addexpr("soma.m_Naf_So(.5)", 3, 1, 0.62, 1.02, 2)
save_window_.addexpr("soma.n_Kdr(.5)", 1, 1, 0.703333, 1.03, 2)
save_window_.addexpr("soma.n_mAHP(.5)", 4, 1, 0.653333, 1.035, 2)
}
{
save_window_ = new Graph(0)
save_window_.size(-1,20,-1.4,1.7)
scene_vector_[6] = save_window_
{save_window_.view(-1, -1.4, 21, 3.1, 579, 314, 300, 200)}
graphList[1].append(save_window_)
save_window_.save_name("graphList[1].")
save_window_.addexpr("soma.ik(.5)", 1, 1, 0.8, 0.9, 2)
save_window_.addexpr("soma.ina(.5)", 2, 1, 0.8, 0.9, 2)
}
objectvar scene_vector_[1]
{doNotify()}