Oscillating neurons in the cochlear nucleus (Bahmer Langner 2006a, b, and 2007)

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Accession:87454
"Based on the physiological and anatomical data, we propose a model consisting of a minimum network of two choppers that are interconnected with a synaptic delay of 0.4 ms (Bahmer and Langner 2006a) . Such minimum delays have been found in different systems and in various animals (e.g. Hackett, Jackson, and Rubel 1982; Borst, Helmchen, and Sakmann 1995). The choppers receive input from both the auditory nerve and an onset neuron. This model can reproduce the mean, standard deviation, and coefficient of variation of the ISI and the dynamic features of AM coding of choppers."
Reference:
1 . Bahmer A, Langner G (2006) Oscillating neurons in the cochlear nucleus: II. Simulation results. Biol Cybern 95:381-92 [PubMed]
2 . Bahmer A, Langner G (2006) Oscillating neurons in the cochlear nucleus: I. Experimental basis of a simulation paradigm. Biol Cybern 95:371-9 [PubMed]
3 . Bahmer A, Langner G (2007) Simulation of oscillating neurons in the cochlear nucleus: a possible role for neural nets, onset cells, and synaptic delays Hearing - from basic research to applications (Proc. of International Symp. of Hearing), Kollmeier B, Klump G, Hohmann V, Langemann U, Mauermann M, Uppenkamp S, Verhey J, ed.
4 . Bahmer A, Langner G (2009) A simulation of chopper neurons in the cochlear nucleus with wideband input from onset neurons. Biol Cybern 100:21-33 [PubMed]
5 . Bahmer A, Langner G (2010) Parameters for a model of an oscillating neuronal network in the cochlear nucleus defined by genetic algorithms. Biol Cybern 102:81-93 [PubMed]
Citations  Citation Browser
Model Information (Click on a link to find other models with that property)
Model Type: Realistic Network;
Brain Region(s)/Organism:
Cell Type(s): Cochlear ganglion cell Type II; CN stellate cell; Ventral cochlear nucleus T stellate (chopper) neuron; Abstract integrate-and-fire leaky neuron;
Channel(s):
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment: NEURON; MATLAB;
Model Concept(s): Audition;
Implementer(s): Bahmer, Andreas [Andreas.Bahmer at kgu.de];
TITLE jsr.mod  VCN conductances

COMMENT
Ih for VCN neurons - average from several studies in auditory neurons


Implementation by Paul B. Manis, April (JHU) and Sept, (UNC)1999.
revised 2/28/04 pbm

pmanis@med.unc.edu

ENDCOMMENT

UNITS {
        (mA) = (milliamp)
        (mV) = (millivolt)
        (nA) = (nanoamp)
}

NEURON {
        SUFFIX ih
        NONSPECIFIC_CURRENT i
        RANGE ghbar, gh, ih
        GLOBAL rinf, rtau
	RANGE eh
}

INDEPENDENT {t FROM 0 TO 1 WITH 1 (ms)}

PARAMETER {
        v (mV)
        celsius = 22 (degC)
        dt (ms)
        ghbar = 0.00318 (mho/cm2) <0,1e9>
        eh = -43 (mV)
}

STATE {
        r
}

ASSIGNED {
	gh (mho/cm2)
	i (mA/cm2)
	rinf
    rtau (ms)
}

LOCAL rexp

BREAKPOINT {
	SOLVE states
    
	gh = ghbar*r
    i = gh*(v - eh)
    }

UNITSOFF

INITIAL {
    trates(v)
    r = rinf
}

PROCEDURE states() {  :Computes state variables m, h, and n
	trates(v)      :             at the current v and dt.
	r = r + rexp*(rinf-r)
VERBATIM
	return 0;
ENDVERBATIM
}

LOCAL q10
PROCEDURE rates(v) {  :Computes rate and other constants at current v.
                      :Call once from HOC to initialize inf at resting v.

	q10 = 3^((celsius - 22)/10)
    rinf = 1 / (1+exp((v + 76) / 7))
    rtau = (100000 / (237*exp((v+60) / 12) + 17*exp(-(v+60) / 14))) + 25

}

PROCEDURE trates(v) {  :Computes rate and other constants at current v.
                      :Call once from HOC to initialize inf at resting v.
	LOCAL tinc
	TABLE rinf, rexp
	DEPEND dt, celsius FROM -200 TO 150 WITH 350

    rates(v)    : not consistently executed from here if usetable_hh == 1
        : so don't expect the tau values to be tracking along with
        : the inf values in hoc

	tinc = -dt * q10
	rexp = 1 - exp(tinc/rtau)
}

FUNCTION vtrap(x,y) {  :Traps for 0 in denominator of rate eqns.
        if (fabs(x/y) < 1e-6) {
                vtrap = y*(1 - x/y/2)
        }else{
                vtrap = x/(exp(x/y) - 1)
        }
}

UNITSON