Differential modulation of pattern and rate in a dopamine neuron model (Canavier and Landry 2006)

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Accession:84612
"A stylized, symmetric, compartmental model of a dopamine neuron in vivo shows how rate and pattern can be modulated either concurrently or differentially. If two or more parameters in the model are varied concurrently, the baseline firing rate and the extent of bursting become decorrelated, which provides an explanation for the lack of a tight correlation in vivo and is consistent with some independence of the mechanisms that generate baseline firing rates versus bursting. ..." See paper for more and details.
Reference:
1 . Canavier CC, Landry RS (2006) An increase in AMPA and a decrease in SK conductance increase burst firing by different mechanisms in a model of a dopamine neuron in vivo. J Neurophysiol 96:2549-63 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Neuron or other electrically excitable cell; Electrogenic pump;
Brain Region(s)/Organism:
Cell Type(s): Substantia nigra pars compacta DA cell;
Channel(s): I L high threshold; I N; I T low threshold; I A; I K; I K,Ca; I Sodium; I Calcium; Na/K pump;
Gap Junctions:
Receptor(s): AMPA; NMDA; Gaba;
Gene(s):
Transmitter(s):
Simulation Environment: NEURON;
Model Concept(s): Activity Patterns; Bursting; Detailed Neuronal Models; Intrinsic plasticity; Calcium dynamics; Sodium pump;
Implementer(s): Kuznetsova, Anna [anna.kuznetsova at utsa.edu];
Search NeuronDB for information about:  Substantia nigra pars compacta DA cell; AMPA; NMDA; Gaba; I L high threshold; I N; I T low threshold; I A; I K; I K,Ca; I Sodium; I Calcium; Na/K pump;
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CanavierLandry2006
in_vitro
ampa.mod
cabalan.mod *
cachan.mod *
capump.mod *
hh3.mod *
kca.mod *
leak.mod *
nabalan.mod *
nmdaL.mod
pump.mod *
stim.mod *
fig4a.hoc
fig4a1.hoc
fig4a1.ses
fig4a2.hoc
fig4a2.ses
fig4a3.hoc
fig4a3.ses
                            
TITLE NMDA receptor as a distributed mechanism as in Canavier and Landry, 2006

COMMENT
Landry did not multiply the calcium current by z squared,
hence the effective permeability ratio is not 10.6 but 2.65.
(To make this file equivalent to Komendantov's nmda.mod 
(see Komendantov et al. 2004 ModelDB entry),
the 91st line here should be ica = 4*10.6*power*numerca/denom2).
Also Landry used the somatic calcium concentration
to drive the dendritic calcium component of the NMDA current, while
in Komendantov et al. 2004, a constant calcium concentration cai
is used in the dendrites instead.
Other than there two discrepancies, the description of the current
is identical despite the different formulations.
ENDCOMMENT

UNITS {
        (pA) = (picoamp)
        (molar) = (1/liter)
	(mV) =	(millivolt)
	(mA) =	(milliamp)
	(mM) =	(millimolar)
}


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

NEURON {
	SUFFIX nmda
	USEION ca WRITE ica
	USEION na READ nai WRITE ina
	USEION k WRITE ik
	RANGE  ica,ina,ik,inmda,Pbar,mg,km,nai,pr
        GLOBAL pinf
        POINTER caisoma  :will take calcium concentration from the soma
       
}

UNITS {
	:FARADAY = 96520 (coul)
	:R = 8.3134 (joule/degC)
	FARADAY = (faraday) (coulomb)
	R = (k-mole) (joule/degC)
}

PARAMETER {
        v (mV)
	celsius= 35  	(degC)
	Pbar = 0.0	(cm/s)	: Maximum Permeability PNMDA in Laundry
	cao = 2.0	(mM)
	lamdaca = 0.3 
        lamda = 0.75
        pr = 0.0225
	nao = 145	(mM)
	ki =  140	(mM)
	ko = 2.5	(mM)
        dt (ms)
        q=9 (mV)
        km=50.7 (mM)
        mg = 1.2 (mM)
}

STATE {
         p <1e-4>
}

ASSIGNED { 
	   nai          (mM)
           ica		(mA/cm2)
           ina		(mA/cm2)
           ik		(mA/cm2)
           inmda 	(mA/cm2)
           pinf
           caisoma      (mM)
}

LOCAL arg, power, numerna, numerk, numerca, denom, denom2

BREAKPOINT {
     SOLVE states METHOD cnexp
	pinf = pr + (1.0 - pr)/(1 + (mg/km)*exp(-v/q))
        arg = v*FARADAY /((1000)*R*(celsius+273.15))
	power =  Pbar*(0.000001)*v*p*FARADAY*FARADAY/(R*(celsius+273.15))
	numerna = lamda*nai - lamda*nao*exp(-arg)
	numerk = lamda*ki - lamda*ko*exp(-arg)
	numerca = caisoma - lamdaca*cao*exp(-2*arg)
	denom = 1 - exp(-arg)
	denom2 = 1 - exp(-2*arg)
	
        ina = power*numerna/denom
	ik = power*numerk/denom
	ica = 10.6*power*numerca/denom2
	inmda = ina + ik + ica
}
UNITSOFF
DERIVATIVE states {
	pinf = pr + (1.0 - pr)/(1 + (mg/km)*exp(-v/q))
	p' = pinf - p 
	}
UNITSON

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