Olfactory Bulb Network (Davison et al 2003)

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A biologically-detailed model of the mammalian olfactory bulb, incorporating the mitral and granule cells and the dendrodendritic synapses between them. The results of simulation experiments with electrical stimulation agree closely in most details with published experimental data. The model predicts that the time course of dendrodendritic inhibition is dependent on the network connectivity as well as on the intrinsic parameters of the synapses. In response to simulated odor stimulation, strongly activated mitral cells tend to suppress neighboring cells, the mitral cells readily synchronize their firing, and increasing the stimulus intensity increases the degree of synchronization. For more details, see the reference below.
1 . Davison AP, Feng J, Brown D (2003) Dendrodendritic inhibition and simulated odor responses in a detailed olfactory bulb network model. J Neurophysiol 90:1921-1935 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Realistic Network;
Brain Region(s)/Organism: Olfactory bulb;
Cell Type(s): Olfactory bulb main mitral cell; Olfactory bulb main interneuron granule MC cell;
Channel(s): I Na,t; I L high threshold; I A; I K; I K,leak; I M; I K,Ca; I Sodium; I Calcium; I Potassium;
Gap Junctions:
Receptor(s): GabaA; AMPA; NMDA;
Transmitter(s): Gaba; Glutamate;
Simulation Environment: NEURON;
Model Concept(s): Oscillations; Synchronization; Spatio-temporal Activity Patterns;
Implementer(s): Davison, Andrew [Andrew.Davison at iaf.cnrs-gif.fr];
Search NeuronDB for information about:  Olfactory bulb main mitral cell; Olfactory bulb main interneuron granule MC cell; GabaA; AMPA; NMDA; I Na,t; I L high threshold; I A; I K; I K,leak; I M; I K,Ca; I Sodium; I Calcium; I Potassium; Gaba; Glutamate;
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nmdanet.mod *
calcisilag.hoc *
ddi_baseline.gnu *
ddi_baseline.ses *
experiment_ddi_baseline.hoc *
experiment_odour_baseline.hoc *
granule.tem *
init.hoc *
input.hoc *
input1 *
mathslib.hoc *
mitral.tem *
mosinit.hoc *
odour_baseline.gnu *
odour_baseline.ses *
parameters_ddi_baseline.hoc *
parameters_odour_baseline.hoc *
screenshot.png *
tabchannels.dat *
tabchannels.hoc *
TITLE simple NMDA receptors


Essentially the same as /examples/nrniv/netcon/ampa.mod in the NEURON
distribution - i.e. Alain Destexhe's simple AMPA model - but with
different binding and unbinding rates and with a magnesium block.
Modified by Andrew Davison, The Babraham Institute, May 2000

	Simple model for glutamate AMPA receptors


    Whole-cell recorded postsynaptic currents mediated by AMPA/Kainate
    receptors (Xiang et al., J. Neurophysiol. 71: 2552-2556, 1994) were used
    to estimate the parameters of the present model; the fit was performed
    using a simplex algorithm (see Destexhe et al., J. Computational Neurosci.
    1: 195-230, 1994).


    The simplified model was obtained from a detailed synaptic model that 
    included the release of transmitter in adjacent terminals, its lateral 
    diffusion and uptake, and its binding on postsynaptic receptors (Destexhe
    and Sejnowski, 1995).  Short pulses of transmitter with first-order
    kinetics were found to be the best fast alternative to represent the more
    detailed models.


    The first-order model can be solved analytically, leading to a very fast
    mechanism for simulating synapses, since no differential equation must be
    solved (see references below).


   Destexhe, A., Mainen, Z.F. and Sejnowski, T.J.  An efficient method for
   computing synaptic conductances based on a kinetic model of receptor binding
   Neural Computation 6: 10-14, 1994.  

   Destexhe, A., Mainen, Z.F. and Sejnowski, T.J. Synthesis of models for
   excitable membranes, synaptic transmission and neuromodulation using a 
   common kinetic formalism, Journal of Computational Neuroscience 1: 
   195-230, 1994.


	RANGE g, Alpha, Beta, e
	GLOBAL Cdur, mg, Cmax
	(nA) = (nanoamp)
	(mV) = (millivolt)
	(umho) = (micromho)
	(mM) = (milli/liter)

	Cmax	= 1	 (mM)           : max transmitter concentration
	Cdur	= 30	 (ms)		: transmitter duration (rising phase)
	Alpha	= 0.072	 (/ms /mM)	: forward (binding) rate
	Beta	= 0.0066 (/ms)		: backward (unbinding) rate
	e	= 45	 (mV)		: reversal potential
        mg      = 1      (mM)           : external magnesium concentration

	v		(mV)		: postsynaptic voltage
	i 		(nA)		: current = g*(v - e)
	g 		(umho)		: conductance
	Rinf				: steady state channels open
	Rtau		(ms)		: time constant of channel binding
        B                               : magnesium block

STATE {Ron Roff}

	Rinf = Cmax*Alpha / (Cmax*Alpha + Beta)
	Rtau = 1 / (Cmax*Alpha + Beta)
	synon = 0

	SOLVE release METHOD cnexp
        B = mgblock(v)
	g = (Ron + Roff)*1(umho) * B
	i = g*(v - e)

DERIVATIVE release {
	Ron' = (synon*Rinf - Ron)/Rtau
	Roff' = -Beta*Roff

FUNCTION mgblock(v(mV)) {
        DEPEND mg
        FROM -140 TO 80 WITH 1000

        : from Jahr & Stevens

        mgblock = 1 / (1 + exp(0.062 (/mV) * -v) * (mg / 3.57 (mM)))

: following supports both saturation from single input and
: summation from multiple inputs
: if spike occurs during CDur then new off time is t + CDur
: ie. transmitter concatenates but does not summate
: Note: automatic initialization of all reference args to 0 except first

NET_RECEIVE(weight, on, nspike, r0, t0 (ms)) {
	: flag is an implicit argument of NET_RECEIVE and  normally 0
        if (flag == 0) { : a spike, so turn on if not already in a Cdur pulse
		nspike = nspike + 1
		if (!on) {
			r0 = r0*exp(-Beta*(t - t0))
			t0 = t
			on = 1
			synon = synon + weight
			state_discontinuity(Ron, Ron + r0)
			state_discontinuity(Roff, Roff - r0)
		: come again in Cdur with flag = current value of nspike
		net_send(Cdur, nspike)
	if (flag == nspike) { : if this associated with last spike then turn off
		r0 = weight*Rinf + (r0 - weight*Rinf)*exp(-(t - t0)/Rtau)
		t0 = t
		synon = synon - weight
		state_discontinuity(Ron, Ron - r0)
		state_discontinuity(Roff, Roff + r0)
		on = 0

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