Frog second-order vestibular neuron models (Rossert et al. 2011)

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Accession:139654
This implements spiking Hodgkin-Huxley type models of tonic and phasic second-order vestibular neurons. Models fitted to intracellular spike and membrane potential recordings from frog (Rana temporaria). The models can be stimulated by intracellular step current, frequency current (ZAP) or synaptic stimulation.
Reference:
1 . Rössert C, Moore LE, Straka H, Glasauer S (2011) Cellular and network contributions to vestibular signal processing: impact of ion conductances, synaptic inhibition, and noise. J Neurosci 31:8359-72 [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): Vestibular neuron; Abstract Morris-Lecar neuron;
Channel(s): I T low threshold; I K,Ca; I Sodium; I Potassium;
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s): Glycine; Gaba; Glutamate;
Simulation Environment: NEURON;
Model Concept(s): Simplified Models; Action Potentials; Sensory processing; Vestibular;
Implementer(s): Roessert, Christian [christian.a at roessert.de];
Search NeuronDB for information about:  I T low threshold; I K,Ca; I Sodium; I Potassium; Glycine; Gaba; Glutamate;
celsius=14

load_file("nparams.hoc")
load_file("custominit.hoc")
load_file("cell_d.hoc")

cell_nr = cell_nr-1

// PHASIC CELL
if(cell_type == 1){
    rho=vp_rho.x(cell_nr)
    Le=vp_Le.x(cell_nr)
    CS=vp_CS.x(cell_nr) 
    GS=vp_GS.x(cell_nr)
    GSh=vp_GSh.x(cell_nr)
    GNa=p_GNa
    GK=p_GK
    GKCa=p_GKCa
    tn=p_tn
    tca=p_tca
    N=p_N 
    GKd=vp_GKd.x(cell_nr)
    tfac=p_tfac
    El=p_El
    Els=p_Els
    bn=p_bn
    gn=p_gn
}

// TONIC CELL
if(cell_type == 2){
    rho=vt_rho.x(cell_nr)
    Le=vt_Le.x(cell_nr)
    CS=vt_CS.x(cell_nr) 
    GS=vt_GS.x(cell_nr)
    GSh=vt_GSh.x(cell_nr)
    GNa=vt_GNa.x(cell_nr)
    GK=vt_GK.x(cell_nr)
    GKCa=vt_GKCa.x(cell_nr)
    tn=vt_tn.x(cell_nr)
    tca=vt_tca.x(cell_nr)
    N=t_N 
    GKd=t_GKd
    tfac=t_tfac
    El=t_El
    Els=t_Els
    bn=t_bn
    gn=t_gn
}

objectvar currcell
currcell = new cell(N, rho, Le, CS, GS, GSh, GNa, GK, GKd, tfac, GKCa, El, Els, bn, gn, tn, tca)

access currcell.soma

objref stim
objref stimvec, f, ivec, tvec
objectvar window



if(stim_type == 1){

tstop = 1200

stim = new IClamp(0.5)
stim.del = 100
stim.dur = 1000
stim.amp = amp

window = new Graph(0)
window.size(0,1200,-80,40)
window.view(0, -80, 1200, 120, 325, 127, 699.84, 250.24)
graphList[0].append(window)
window.addexpr("v(.5)", 1, 1, 0.8, 0.9, 2)

}

if(stim_type == 2){

dt = 0.1
steps_per_ms = 1/dt // or steps_per_ms = 1/dt/N if you prefer 1 point per N fadvances

tstop = 30000

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

f = new File("zapstim.txt")
f.ropen()
stimvec = new Matrix()
stimvec.scanf(f)
tvec = stimvec.getcol(0)
ivec = stimvec.getcol(1)

ivec = ivec.mul(amp)

// third argument == 1 means play with interpolation
ivec.play(&stim.amp, tvec, 1)

window = new Graph(0)
window.size(0,30000,-90,40)
window.view(0, -90, 30000, 120, 325, 127, 699.84, 250.24)
graphList[0].append(window)
window.addexpr("v(.5)", 1, 1, 0.8, 0.9, 2)

}


run()


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