Sympathetic Preganglionic Neurone (Briant et al. 2014)

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Accession:151482
A model of a sympathetic preganglionic neurone of muscle vasoconstrictor-type.
Reference:
1 . Briant LJ, Stalbovskiy AO, Nolan MF, Champneys AR, Pickering AE (2014) Increased intrinsic excitability of muscle vasoconstrictor preganglionic neurons may contribute to the elevated sympathetic activity in hypertensive rats. J Neurophysiol 112:2756-78 [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 ACh cell; Spinal cord sympathetic preganglionic neuron;
Channel(s): I Na,t; I L high threshold; I N; I A; I K; I K,Ca; I_AHP;
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment: NEURON; MATLAB;
Model Concept(s): Action Potential Initiation; Activity Patterns; Bursting; Ion Channel Kinetics; Temporal Pattern Generation; Parameter Fitting; Action Potentials; Parameter sensitivity;
Implementer(s):
Search NeuronDB for information about:  Spinal cord lumbar motor neuron alpha ACh cell; I Na,t; I L high threshold; I N; I A; I K; I K,Ca; I_AHP;
// I-V curve of cell
// Figure 3B from Briant and Stalbovskiy et al. 2014
// Created Linford Briant October 2013

load_file("Cell.hoc")

tstop=3000
steps_per_ms=1
dt=1

objectvar clamp
clamp=new IClamp(0.5)
clamp.amp=0
clamp.dur=tstop
clamp.del=0

nvrec=25

proc init() {
finitialize(-55.05)
/*
if (cvode.active()) {
cvode.re_init()
} else {fcurrent()
}
frecord_init()
*/
}

nstim=1
objectvar stim[nstim]
stim[0]=new IClamp(0.5)
stim[0].amp=0
stim[0].dur=1000
stim[0].del=1000

objectvar vrec[nvrec]
for i=0, nvrec-1 vrec[i]=new Vector()

objectvar M
M=new Matrix()
objectvar DataV
DataV=new File()

vrec[0].record(&SPNcells[0].soma.v(0.5))

gkabar_borgka=0.005
run()

objectvar DeltaV
DeltaV=new Vector(25)
DeltaV.x[0]=vrec[0].x[2000]
print DeltaV.x[0]

objectvar stimamp
stimamp=new Vector(25)
stimamp.x[0]=stim[0].amp*1e3
print stimamp.x[0]

M.resize(vrec[0].size(),26)

M.setcol(1,vrec[0])

objectvar vdt
vdt = new Vector()
vdt.resize(vrec[0].size())
vdt.indgen(dt)

M.setcol(0,vdt)

objref vrec_graph_handle
vrec_graph_handle = new Graph()
vrec[0].line(vrec_graph_handle,vdt,1,1)
vrec_graph_handle.size(0,tstop,-90,-50)
vrec_graph_handle.exec_menu("Keep Lines")
vrec_graph_handle.exec_menu("View = plot")
vrec_graph_handle.exec_menu("10% Zoom out")
vrec_graph_handle.label(.4,.9,"Voltage graph")


objref DeltaV_graph_handle
DeltaV_graph_handle = new Graph()
DeltaV_graph_handle.size(-60,0,-70,-54)
DeltaV_graph_handle.exec_menu("10% Zoom out")
DeltaV_graph_handle.label(.4,.9,"I-V Curve; Figure 3B")

for i=1, nvrec-1 {

stim[0].amp=0-(0.0025*i)

vrec[i].record(&SPNcells[0].soma.v(0.5))

run()

vrec[i].line(vrec_graph_handle,vdt,2,1)
vrec_graph_handle.size(0,tstop,-70,-50)
DeltaV.x[i]=vrec[i].x[2000]
stimamp.x[i]=stim[0].amp*1e3

M.setcol(i+1,vrec[i])

print i, stimamp.x[i]

DeltaV.c(0,i).line(DeltaV_graph_handle,stimamp.c(0,i),2,1)

}

DataV.wopen("I-V_V.dat")

M.fprint(DataV, " %g")

DataV.close("I-V_V.dat")


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