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."
References:
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]
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 klt.mod  The low threshold conductance of cochlear nucleus neurons

COMMENT

NEURON implementation of Jason Rothman's measurements of VCN conductances.

This file implements the average brain sodium current used in the Rothman model.
In the absence of direct measurements in the VCN, this is a fair assumption.
The model differs from the one used in Rothman et al, (1993) in that the steep
voltage dependence of recovery from inactivation in that model is missing. This
may affect the refractory period. To use the other model, use najsr.mod instead.

Original implementation by Paul B. Manis, April (JHU) and Sept, (UNC)1999.

File split implementaiton, April 1, 2004.

Contact: pmanis@med.unc.edu

ENDCOMMENT

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

NEURON {
        SUFFIX na
:        USEION na READ ena WRITE ina
        USEION na WRITE ina
        RANGE gnabar, gna, ina
        GLOBAL hinf, minf, htau, mtau
	RANGE ena
}

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

PARAMETER {
        v (mV)
        celsius = 22 (degC)  : model is defined on measurements made at room temp in Baltimore
        dt (ms)
        ena (mV)
        gnabar =  0.07958 (mho/cm2) <0,1e9>
}

STATE {
        m h
}

ASSIGNED {
    ina (mA/cm2) 
    gna (mho/cm2)
    minf hinf
    mtau (ms) htau (ms)
    }

LOCAL mexp, hexp

BREAKPOINT {
	SOLVE states
    
    gna = gnabar*(m^3)*h
    ina = gna*(v - ena)

}

UNITSOFF

INITIAL {
    trates(v)
    m = minf
    h = hinf
}

PROCEDURE states() {  :Computes state variables m, h, and n
	trates(v)      :             at the current v and dt.
	m = m + mexp*(minf-m)
	h = h + hexp*(hinf-h)
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) : if you don't like room temp, it can be changed!

: average sodium channel
    minf = 1 / (1+exp(-(v + 38) / 7))
    hinf = 1 / (1+exp((v + 65) / 6))

    mtau =  (10 / (5*exp((v+60) / 18) + 36*exp(-(v+60) / 25))) + 0.04
    htau =  (100 / (7*exp((v+60) / 11) + 10*exp(-(v+60) / 25))) + 0.6
}

PROCEDURE trates(v) {  :Computes rate and other constants at current v.
                      :Call once from HOC to initialize inf at resting v.
	LOCAL tinc
	TABLE minf, mexp, hinf, hexp
	DEPEND dt, celsius FROM -150 TO 150 WITH 300

    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
	mexp = 1 - exp(tinc/mtau)
	hexp = 1 - exp(tinc/htau)
	}

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

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