Fast AMPA receptor signaling (Geiger et al 1997)

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Accession:19022
Glutamatergic transmission at a principal neuron-interneuron synapse was investigated by dual whole-cell patch-clamp recording in rat hippocampal slices combined with morphological analysis and modeling. Simulations based on a compartmental model of the interneuron indicated that the rapid postsynaptic conductance change determines the shape and the somatodendritic integration of EPSPs, thus enabling interneurons to detect synchronous principal neuron activity.
Reference:
1 . Geiger JR, Lübke J, Roth A, Frotscher M, Jonas P (1997) Submillisecond AMPA receptor-mediated signaling at a principal neuron-interneuron synapse. Neuron 18:1009-23 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Synapse;
Brain Region(s)/Organism:
Cell Type(s):
Channel(s):
Gap Junctions:
Receptor(s): AMPA;
Gene(s):
Transmitter(s): Glutamate;
Simulation Environment: NEURON;
Model Concept(s): Influence of Dendritic Geometry; Detailed Neuronal Models;
Implementer(s): Roth, Arnd ;
Search NeuronDB for information about:  AMPA; Glutamate;
// generates fig 8d from
// Geiger JR, Lubke J, Roth A, Frotscher M, Jonas P.
// Submillisecond AMPA receptor-mediated signaling at a principal neuron-interneuron synapse.
// Neuron. 1997 Jun;18(6):1009-23.

objref volt_vec, slow_peaks, fast_peaks, offset, g


proc set_synapses_slow() {
	mySynapse[2].onset = relat + 20
	mySynapse[2].tau0 = 0.08	// ms
	mySynapse[2].tau1 = 1.20	// ms
	mySynapse[2].gmax = 0.0032	// microSiemens
	
	mySynapse[0].onset = 20		// fixed time that other synapse changes relative too
	mySynapse[0].tau0 = 0.08
	mySynapse[0].tau1 = 1.20
	mySynapse[0].gmax = 0.0032
}

proc set_synapses_fast() {
	mySynapse[2].onset = relat + 20
	mySynapse[2].tau0 = 0.08	// ms
	mySynapse[2].tau1 = 0.20	// ms
	mySynapse[2].gmax = 0.008	// microSiemens
	
	mySynapse[0].onset = 20		// fixed time that other synapse changes relative too
	mySynapse[0].tau0 = 0.08
	mySynapse[0].tau1 = 0.20
	mySynapse[0].gmax = 0.008
}

// turn off other synapses for this
	mySynapse[1].gmax = 0.0


volt_vec = new Vector()
volt_vec.record(&soma.v(0.5))

slow_peaks = new Vector()
fast_peaks = new Vector()
offset = new Vector()

steps_per_ms =2
dt = 0.5
tstop = 43
// change the 4 in the relat = relat + 4 to have a different offset step size
for (relat = -20; relat <= 20; relat =relat + 4) {	//loop over relative times between synapses

	set_synapses_slow()
	init()
	run()
	slow_peaks.append(volt_vec.max-volt_vec.min)
	
	set_synapses_fast()
	init()
	run()
	fast_peaks.append(volt_vec.max-volt_vec.min)
	
	offset.append(relat)
}

// renormalize peak peaks to one

slow_peaks.div(slow_peaks.max)
fast_peaks.div(fast_peaks.max)

g = new Graph(0)

fast_peaks.label("Fast Synapses")
slow_peaks.label("Slow Synapses")

slow_peaks.line(g, offset, 1, 0)
fast_peaks.line(g, offset, 2, 1)

g.view(-20,0.4,40,.6, 40,40,200,150)


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