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
Gfluctdv.mod *
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")}
{xopen("FRMot3dendNaHH.hoc")}
forsec dend {insert Gfluctdv}
access soma
insert Gfluctdv

{load_file("SetConductances2.hoc")}


tstop=22000

simple2del()
grampon()

proc batchrun20pool(){local i,ii,trun,gLCa
trun=startsw()
for ii = 0,19 {
sprint(filename,"%s/%s_%d/%s_%d.hoc",$s1,$s1,ii,$s1,ii)
xopen(filename)
forsec dend {gLCa=$2*gcabar_L_Ca(0.4)
gcabar_L_Ca(0.2:0.5) = gLCa:gLCa}
forall {ar_na3rp=$3 ar_naps=$3}
apc.record()
apc.record(spiketimes)
sprint(filename,"t%s_%d_%.2fgLCa_ar%.1f.txt",$s1,ii,$2,$3)
spikeout.wopen(filename)
run()
spiketimes.printf(spikeout,"%8.4f\n")
spikeout.close()
}
print startsw()-trun, "seconds"
}

proc batchrun20poolprox(){local i,ii,trun,gLCa
trun=startsw()
for ii = 0,19 {
sprint(filename,"%s/%s_%d/%s_%d.hoc",$s1,$s1,ii,$s1,ii)
xopen(filename)
forsec dend {gLCa=$2*gcabar_L_Ca(0.2)
gcabar_L_Ca(0:0.3) = gLCa:gLCa}
forall {ar_na3rp=$3 ar_naps=$3}
apc.record()
apc.record(spiketimes)
sprint(filename,"t%s_%d_%.2fgLCa_ar%.1f.txt",$s1,ii,$2,$3)
spikeout.wopen(filename)
run()
spiketimes.printf(spikeout,"%8.4f\n")
spikeout.close()
}
print startsw()-trun, "seconds"
}

proc batchrun20poolnasi(){local i,ii,trun,gLCa
trun=startsw()
for ii = 0,19 {
sprint(filename,"%s/%s_%d/%s_%d.hoc",$s1,$s1,ii,$s1,ii)
xopen(filename)
forsec dend {gLCa=$2*gcabar_L_Ca(0.4)
gcabar_L_Ca(0.2:0.5) = gLCa:gLCa}
forall {ar_na3rp=$3 ar_napsi=$3}
apc.record()
apc.record(spiketimes)
sprint(filename,"t%s_%d_%.2fgLCa_ar%.1f.txt",$s1,ii,$2,$3)
spikeout.wopen(filename)
run()
spiketimes.printf(spikeout,"%8.4f\n")
spikeout.close()
}
print startsw()-trun, "seconds"
}

proc batchrun20poolLCainact(){local i,ii,trun,gLCa
trun=startsw()
for ii = 0,19 {
sprint(filename,"%s/%s_%d/%s_%d.hoc",$s1,$s1,ii,$s1,ii)
xopen(filename)
forsec dend {gLCa=$2*gcabar_L_Ca_inact(0.4)
gcabar_L_Ca_inact(0.2:0.5) = gLCa:gLCa}
forall {ar_na3rp=$3 ar_naps=$3}
apc.record()
apc.record(spiketimes)
sprint(filename,"t%s_%d_%.2fgLCa_ar%.1f.txt",$s1,ii,$2,$3)
spikeout.wopen(filename)
run()
spiketimes.printf(spikeout,"%8.4f\n")
spikeout.close()
}
print startsw()-trun, "seconds"
}


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