CA1 pyramidal neuron: nonlinear a5-GABAAR controls synaptic NMDAR activation (Schulz et al 2018)

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Accession:258867
The study shows that IPSCs mediated by a5-subunit containing GABAA receptors are strongly outward-rectifying generating 4-fold larger conductances above -50?mV than at rest. Experiments and modeling show that synaptic activation of these receptors can very effectively control voltage-dependent NMDA-receptor activation in a spatiotemporally controlled manner in fine dendrites of CA1 pyramidal cells. The files contain the NEURON code for Fig.8, Fig.S8 and Fig.S9 of the paper. The model is based on the model published by Bloss et al., 2017. Physiological properties of GABA synapses were modified as determined by optogenetic activation of inputs during voltage-clamp recordings in Schulz et al. 2018. Other changes include stochastic synaptic release and short-term synaptic plasticity. All changes of mechanisms and parameters are detailed in the Methods of the paper. Simulation can be run by starting start_simulation.hoc after running mknrndll. The files that model the individual figures have to be uncommented in start_simulation.hoc beforehand.
Reference:
1 . Schulz JM, Knoflach F, Hernandez MC, Bischofberger J (2018) Dendrite-targeting interneurons control synaptic NMDA-receptor activation via nonlinear a5-GABAA receptors. Nat Commun 9:3576 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Neuron or other electrically excitable cell; Dendrite; Synapse;
Brain Region(s)/Organism: Hippocampus; Mouse;
Cell Type(s): Hippocampus CA1 pyramidal GLU cell;
Channel(s): I h; I A;
Gap Junctions:
Receptor(s): GabaA; GabaB; AMPA; NMDA;
Gene(s):
Transmitter(s): Gaba; Glutamate;
Simulation Environment: NEURON;
Model Concept(s):
Implementer(s): Schulz, Jan M [j.schulz at unibas.ch];
Search NeuronDB for information about:  Hippocampus CA1 pyramidal GLU cell; GabaA; GabaB; AMPA; NMDA; I A; I h; Gaba; Glutamate;
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Alpha5_NMDA_CA1_pyr
README.html
dists.mod *
eff.mod *
exc.mod *
gabab.mod
h.mod
id.mod *
inh.mod
kad.mod *
kap.mod *
kdr.mod *
na3.mod *
nmdaSyn.mod
syns.mod *
tonic.mod
activateExcitation.hoc
activateInhibition_JMS.hoc
addChannels_JMS.hoc
addExcitation_JMS.hoc
addVgatInhibition_JMS.hoc
channelParameters.hoc
Connect_Stimulator2ExcSyn.hoc
Connect_Stimulator2InhSyn.hoc
Fig8_tuft_NMDA_spike.hoc
FigS8_SR_SLM_burst_stim.hoc
FigS9_test_TI.hoc
flagVgatInhibition_JMS.hoc
Generate_Stimulator.hoc
getBranchOrder.hoc *
idMorph.hoc
inhibitionBiophysics_JMS.hoc
initializationAndRun.hoc *
loadMorph.hoc *
mosinit.hoc
naceaxon.nrn *
Print-to-File.hoc
processMorph.hoc *
proofreadMorph.hoc *
resetNSeg.hoc *
screenshot.png
start_simulation.hoc
synHelperScripts.hoc
SynStim_SR_SLM_control.hoc
SynStim_SR_SLM_noInh.hoc
SynStim_SR_SLM_redInh.hoc
SynStim_SR_SLM_TI.hoc
tuft_NMDA_spike_fast.hoc
tuft_NMDA_spike_noRect.hoc
twinApical.swc *
update_Synapses.hoc
                            
// DECLARE OBJECTS TO BE ASSIGNED DURING initChannels() CALL
objref osec[10]


// LOAD PARAMETERS FOR CHANNELS
{
	load_file("channelParameters.hoc")
}

proc initChannels(){
	// add in voltage-gated channels
	{
		forall {
			insert pas  g_pas=1/(Rm)  Ra=global_ra  e_pas=Vleak
			insert id
		}
		
		soma.sec { 
            insert hd ghdbar_hd=ghd 
            //insert h gbar_h=ghd
			insert nax  gbar_nax=gnaSoma  
			insert kdr  gkdrbar_kdr=gkdr
			insert kap  gkabar_kap=gkap
			insert kad  gkabar_kad=0
			insert pas	e_pas=Vleak  g_pas=1/Rm   Ra=global_ra  cm=Cm
		}
		

		forsec basalList {
			insert pas	e_pas=Vleak  Ra=global_ra 
			for (x) {
				xdist=distance(x)
				if (xdist <= spinelimit) {
					g_pas(x) = 1/Rm
					cm(x) = Cm
				} else {
					g_pas(x) = spinefactor/Rm
					cm(x) = spinefactor*Cm
				}
			}
            insert tonic gtonic_tonic=gtonic 
            insert hd ghdbar_hd=ghd
			insert nax	
			insert kdr	gkdrbar_kdr=0 //gkdr //very low according to Kirizs et al., 2014
			insert kap
			insert kad
			gkabar_kap = 0
			gkabar_kad = 0
			
			for (x) {
				xdist = distance(x)
				xdistNoLimit = xdist
				if (xdist > dlimit) {
					xdist = dlimit
				}
				gkabar_kap(x) = 0
				gkabar_kad(x) = 0
				if (xdist > dprox) {
					gkabar_kad(x) = gkad*(1+xdist*dslope)
				} else {
					gkabar_kap(x) = gkap*(1+xdist*dslope)
				}
			}
			
		}
		
		soma.sec {
			area(0.5)
			distance()
		}
			
		forsec apicalList {
			insert pas	e_pas=Vleak  Ra=global_ra 
			for (x) {
				xdist=distance(x)
				if (xdist <= spinelimit) {
					g_pas(x) = 1/Rm
					cm(x) = Cm
				} else {
					g_pas(x) = spinefactor/Rm
					cm(x) = spinefactor*Cm
				}
			}
            insert tonic gtonic_tonic=gtonic 
            insert hd ghdbar_hd=ghd
			insert nax	
			insert kdr	gkdrbar_kdr= 0 //very low according to Kirizs et al., 2014
			insert kap
			insert kad
			gkabar_kap = 0
			gkabar_kad = 0
			
            for (x) {
				xdist = distance(x)
				xdistNoLimit = xdist
                if (xdist <= spinelimit) {
                    insert kdr	gkdrbar_kdr=gkdr //very low else where according to Kirizs et al., 2014
                }
                if (xdist>500) {xdist=500}
                ghdbar_hd(x) = ghd*(1+3*xdist/100)
                if (xdist > dlimit) {
					xdist = dlimit
				}
                gtonic_tonic(x) = gtonic*(1+3*xdist/100)
				gkabar_kap(x) = 0
				gkabar_kad(x) = 0
				if (xdist > dprox) {
					gkabar_kad(x) = gkad*(1+xdist*dslope)
				} else {
					gkabar_kap(x) = gkap*(1+xdist*dslope)
				}
			}
		}
		
		
		
		
		forsec obliqueList {
				for (x) {
					odist = distance(x) 	// odist is the distance of each segment along the oblique branch
					pdist_k = dlimit
					gkabar_kap(x) = gkap*(1+pdist_k*dslope+odist*okslope)
					gkabar_kad(x) = gkad*(1+pdist_k*dslope+odist*okslope)
				}
		}
		

		forsec tuftList {
			gbar_nax = gnaSlm
		}
		forsec ca3List {
			gbar_nax = gnaSr
		}
		soma.sec {
			gbar_nax = gnaSoma
		}
        
        forall {
        v=Vrest
        if (ismembrane("nax")) {ena=55}
        if (ismembrane("kdr") || ismembrane("kap") || ismembrane("kad")) {ek=-95}
        if (ismembrane("hd") ) {ehd_hd=-30 }
        if (ismembrane("tonic") ) {e_tonic=inhRev }
		}
        
		soma.sec { 
			distance()
		}

	}
}


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