A two-layer biophysical olfactory bulb model of cholinergic neuromodulation (Li and Cleland 2013)

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Accession:149739
This is a two-layer biophysical olfactory bulb (OB) network model to study cholinergic neuromodulation. Simulations show that nicotinic receptor activation sharpens mitral cell receptive field, while muscarinic receptor activation enhances network synchrony and gamma oscillations. This general model suggests that the roles of nicotinic and muscarinic receptors in OB are both distinct and complementary to one another, together regulating the effects of ascending cholinergic inputs on olfactory bulb transformations.
Reference:
1 . Li G, Cleland TA (2013) A two-layer biophysical model of cholinergic neuromodulation in olfactory bulb. J Neurosci 33:3037-58 [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): Olfactory bulb main mitral cell; Olfactory bulb main interneuron periglomerular cell; Olfactory bulb main interneuron granule MC cell;
Channel(s): I Na,p; I L high threshold; I T low threshold; I A; I M; I h; I K,Ca; I CAN; I Sodium; I Calcium; I Potassium; I_Ks; I Cl, leak; I Ca,p;
Gap Junctions:
Receptor(s): Nicotinic; GabaA; Muscarinic; AMPA; NMDA;
Gene(s):
Transmitter(s): Acetylcholine;
Simulation Environment: NEURON; MATLAB;
Model Concept(s): Sensory processing; Sensory coding; Neuromodulation; Olfaction;
Implementer(s): Li, Guoshi [guoshi_li at med.unc.edu];
Search NeuronDB for information about:  Olfactory bulb main mitral cell; Olfactory bulb main interneuron periglomerular cell; Olfactory bulb main interneuron granule MC cell; Nicotinic; GabaA; Muscarinic; AMPA; NMDA; I Na,p; I L high threshold; I T low threshold; I A; I M; I h; I K,Ca; I CAN; I Sodium; I Calcium; I Potassium; I_Ks; I Cl, leak; I Ca,p; Acetylcholine;
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ACh_ModelDB
celldata
Connection
data
Input
SP
Readme.txt
cadecay.mod *
cadecay2.mod *
Caint.mod *
Can.mod *
CaPN.mod *
CaT.mod *
GradeAMPA.mod *
GradeGABA.mod *
GradNMDA.mod *
hpg.mod *
kAmt.mod *
KCa.mod *
KDRmt.mod *
kfasttab.mod *
kM.mod *
KS.mod *
kslowtab.mod *
LCa.mod *
nafast.mod *
NaP.mod *
Naxn.mod *
Nicotin.mod *
nmdanet.mod *
OdorInput.mod *
Background.hoc
Connect.hoc
GC_def.hoc
GC_save.hoc *
GC_Stim.hoc
Input.hoc
MC_def.hoc
MC_save.hoc
MC_Stim.hoc
mod_func.c
mosinit.hoc
OB.hoc
Parameter.hoc
PG_def.hoc
PG_save.hoc *
PG_Stim.hoc
SaveData.hoc
tabchannels.dat *
tabchannels.hoc
                            
TITLE HH KM channel
: Hodgkin - Huxley KM channel with parameters from
: US Bhalla and JM Bower, J. Neurophysiol. 69:1948-1983 (1993)
: Andrew Davison, The Babraham Institute, 1998.

NEURON {
	SUFFIX kM
	USEION k READ ek WRITE ik
	RANGE gkbar, ik
	GLOBAL xinf, xtau
}

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

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

PARAMETER {
	v (mV)
	dt (ms)
	gkbar=.036 (mho/cm2) <0,1e9>
	ek = -70 (mV)
}
STATE {
	x
}
ASSIGNED {
	ik (mA/cm2)
	xinf
	xtau (ms)
}

INITIAL {
	rates(v)
	x = xinf
}

BREAKPOINT {
	SOLVE states METHOD cnexp
	ik = gkbar*x*(v - ek)
}

DERIVATIVE states {
	rates(v)
	x' = (xinf - x)/xtau
}

PROCEDURE rates(v(mV)) {
	TABLE xinf, xtau FROM -100 TO 100 WITH 200
	xinf = 1/(1 + exp(-(v*1(/mV) + 35)/5))
	xtau = 1000(ms)/(3.3*exp((v*1(/mV) + 35)/40) + exp(-(v*1(/mV) + 35)/20))
}


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