Discharge hysteresis in motoneurons (Powers & Heckman 2015)

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Accession:183949
"Motoneuron activity is strongly influenced by the activation of persistent inward currents (PICs) mediated by voltage-gated sodium and calcium channels. ... It has recently been suggested that a number of factors other than PIC can contribute to delta F (firing rate differences between motoneurons) values, including mechanisms underlying spike frequency adaptation and spike threshold accommodation. In the present study, we used a set of compartmental models representing a sample of 20 motoneurons with a range of thresholds to investigate how several different intrinsic motoneuron properties can potentially contribute to variations in F values. ... Our results indicate that, although other factors can contribute, variations in discharge hysteresis and delta F values primarily reflect the contribution of dendritic PICs to motoneuron activation.
Reference:
1 . Powers RK, Heckman CJ (2015) Contribution of intrinsic motoneuron properties to discharge hysteresis and its estimation based on paired motor unit recordings. A simulation study. J Neurophysiol 114:184-198 [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): Spinal cord lumbar motor neuron alpha cell;
Channel(s): I Na,p; I Na,t; I L high threshold; I K; I M; I K,Ca; I_AHP; I Calcium; I Sodium;
Gap Junctions:
Receptor(s):
Gene(s): Kv1.2 KCNA2; Kv1.9 Kv7.1 KCNQ1;
Transmitter(s):
Simulation Environment: NEURON;
Model Concept(s): Spike Frequency Adaptation;
Implementer(s): Powers, Randy [rkpowers at u.washington.edu];
Search NeuronDB for information about:  Spinal cord lumbar motor neuron alpha cell; I Na,p; I Na,t; I L high threshold; I K; I M; I K,Ca; I Sodium; I Calcium; I_AHP;
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Discharge_hysteresis
Model hoc files and output
README.txt
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ghchan.mod *
kca2.mod *
KCNQ.mod *
kdrRL.mod *
km_hu.mod
kv1_gp.mod *
L_Ca.mod *
L_Ca_inact.mod *
mAHP.mod *
mAHPvt.mod
na3rp.mod *
naps.mod *
napsi.mod *
AHPlen.csv
FasterMis.csv
FR3cablepas.hoc
FRMot3dendNaHH.hoc
gramp.ses
HiDKCa.csv
init_3dend_gramp.hoc
LCai.csv
Napi.csv
pars2manyhocs.py *
ProxCa.csv
SetConductances2.hoc *
SlowM.csv
standard.csv
twobirampsdel.hoc *
                            
{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)
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 = 16696.3
xvalue("t","t", 2 )
tstop = 22000
xvalue("Tstop","tstop", 1,"tstop_changed()", 0, 1 )
dt = 0.025
xvalue("dt","dt", 1,"setdt()", 0, 1 )
steps_per_ms = 10
xvalue("Points plotted/ms","steps_per_ms", 1,"setdt()", 0, 1 )
screen_update_invl = 0.5
xvalue("Scrn update invl","screen_update_invl", 1,"", 0, 1 )
realtime = 43.59
xvalue("Real Time","realtime", 0,"", 0, 1 )
xpanel(11,104)
}
{
xpanel("APCount[0] at soma(0.5)", 0)
xlabel("APCount[0] at soma(0.5)")
apc.n = 109
xvalue("n","apc.n", 1,"", 0, 1 )
apc.thresh = -20
xvalue("thresh","apc.thresh", 1,"", 0, 1 )
apc.time = 10996.6
xvalue("time","apc.time", 1,"", 0, 1 )
apc.firing = 0
xvalue("firing","apc.firing", 0,"", 0, 1 )
xpanel(11,500)
}
{
save_window_ = new Graph(0)
save_window_.size(0,22000,-80,40)
scene_vector_[2] = save_window_
{save_window_.view(0, -80, 22000, 120, 351, 371, 572.16, 349.12)}
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("dendrite.v(0.5)", 2, 1, 0.8, 0.9, 2)
}
{
save_window_ = new Graph(0)
save_window_.size(0,22000,0,1)
scene_vector_[3] = save_window_
{save_window_.view(0, 0, 22000, 1, 503, 157, 300.48, 200.32)}
graphList[2].append(save_window_)
save_window_.save_name("graphList[2].")
save_window_.addexpr("dendrite.m_L_Ca( 0.5 )", 1, 1, 0.8, 0.9, 2)
}
{
save_window_ = new Graph(0)
save_window_.size(0,22000,0,1)
scene_vector_[4] = save_window_
{save_window_.view(0, 0, 22000, 1, 355, 75, 565.44, 232.96)}
graphList[2].append(save_window_)
save_window_.save_name("graphList[2].")
save_window_.addexpr("soma.s_na3rp( 0.5 )", 3, 1, 0.797522, 0.997245, 2)
save_window_.addexpr("dendrite.m_L_Ca( 0.5 )", 2, 1, 0.793804, 0.817342, 2)
}
objectvar scene_vector_[1]
{doNotify()}

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