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A model for a nociceptor terminal and terminal tree (Barkai et al., 2020)

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Accession:266850
This model was used to study how the architecture of the nociceptor terminal tree affects the input-output relation of the primary nociceptive neurons. The model shows that the input-output properties of the nociceptive neurons depend on the length, the axial resistance, and location of individual terminals and that activation of multiple terminals by a capsaicin-like current allows summation of the responses from individual terminals, thus leading to increased nociceptive output.
Reference:
1 . Barkai O, Butterman R, Katz B, Lev S, Binshtok AM (2020) The Input-Output Relation of Primary Nociceptive Neurons is Determined by the Morphology of the Peripheral Nociceptive Terminals. J Neurosci 40:9346-9363 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type:
Brain Region(s)/Organism:
Cell Type(s): Dorsal Root Ganglion (DRG) cell;
Channel(s): I Potassium; I Calcium; I Sodium; I h;
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment: NEURON;
Model Concept(s): Action Potentials; Axonal Action Potentials; Nociception;
Implementer(s):
Search NeuronDB for information about:  I h; I Sodium; I Calcium; I Potassium;
{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 PointProcessGroupManager
{
load_file("pointgrp.hoc")
}
{
ocbox_ = new PointProcessGroupManager(0)
}
{object_push(ocbox_)}
{
ms = new MechanismStandard("Caps_Puff")
ms.set("onset", 500, 0)
ms.set("tau_act", 1e+006, 0)
ms.set("tau_inact", 6500, 0)
ms.set("gmax", 150, 0)
ms.set("X", 1e-006, 0)
ms.set("pump", 500, 0)
mnews("Caps_Puff", ms)
select(0)
execute("NavLess[0] ocbox_.move(0.05)")
}
{object_pop() doNotify()}
{
ocbox_ = ocbox_.v1
ocbox_.map("PointProcessGroupManager", 759, 146, 550.8, 317.7)
}
objref ocbox_
//End PointProcessGroupManager

{
save_window_ = new Graph(0)
save_window_.size(0,3000,-80,40)
scene_vector_[2] = save_window_
{save_window_.view(0, -80, 3000, 120, 313, 134, 300.6, 200.8)}
graphList[0].append(save_window_)
save_window_.save_name("graphList[0].")
save_window_.addexpr("v(.5)", 1, 1, 0.8, 0.9, 2)
}
{
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 = 3000
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
xvalue("Real Time","realtime", 0,"", 0, 1 )
xpanel(10,133)
}
objectvar scene_vector_[1]
{doNotify()}

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