pre-Bötzinger complex variability (Fietkiewicz et al. 2016)

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Accession:184732
" ... Based on experimental observations, we developed a computational model that can be embedded in more comprehensive models of respiratory and cardiovascular autonomic control. Our simulation results successfully reproduce the variability we observed experimentally. The in silico model suggests that age-dependent variability may be due to a developmental increase in mean synaptic conductance between preBötC neurons. We also used simulations to explore the effects of stochastic spiking in sensory relay neurons. Our results suggest that stochastic spiking may actually stabilize modulation of both respiratory rate and its variability when the rate changes due to physiological demand. "
Reference:
1 . Fietkiewicz C, Shafer GO, Platt EA, Wilson CG (2016) Variability in respiratory rhythm generation: In vitro and in silico models Communications in Nonlinear Science and Numerical Simulation 32:158-168
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Model Information (Click on a link to find other models with that property)
Model Type: Realistic Network;
Brain Region(s)/Organism:
Cell Type(s): Respiratory column neuron;
Channel(s):
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment: NEURON;
Model Concept(s): Noise Sensitivity; Development;
Implementer(s):
TITLE Sodium Density Mechanism

UNITS {
	(mV) = (millivolts)
	(mA) = (milliamp)
	(S) = (siemens)
}

NEURON {
	SUFFIX na
	USEION na WRITE ina
	RANGE gmax, e
}

PARAMETER {
	gmax = 0.0009333 (S/cm2)
	e = 50 (millivolt)
}

ASSIGNED {
	v (mV)
	ena (mA)
	ina (mA/cm2)
	g (S/cm2)
}

STATE { m h }

BREAKPOINT {
	SOLVE states METHOD cnexp
	g = gmax * h * m^3
	ina = g * (v - e)
}

INITIAL {
	m = alpham(v)/(alpham(v) + betam(v))
    h = alphah(v)/(alphah(v) + betah(v))
}

DERIVATIVE states {
	m' = alpham(v) * (1-m) - betam(v) * m
	h' = alphah(v) * (1-h) - betah(v) * h
}

FUNCTION alpham(Vm (mV)) (/ms) {
	UNITSOFF
	alpham = 10 * exp(0.1 * (Vm + 34)) 
	UNITSON
}

FUNCTION betam(Vm (mV)) (/ms) {
	UNITSOFF
	betam = 10 * exp(-0.1 * (Vm + 34))
	UNITSON
}

FUNCTION alphah(Vm (mV)) (/ms) {
	UNITSOFF
	alphah = 0.05 * exp(-0.125 * (Vm + 29)) 	
	UNITSON
}

FUNCTION betah(Vm (mV)) (/ms) {
	UNITSOFF
	betah = 0.05 * exp(0.125 * (Vm + 29))
	UNITSON
}