STDP and BDNF in CA1 spines (Solinas et al. 2019)

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Accession:244412
Storing memory traces in the brain is essential for learning and memory formation. Memory traces are created by joint electrical activity in neurons that are interconnected by synapses and allow transferring electrical activity from a sending (presynaptic) to a receiving (postsynaptic) neuron. During learning, neurons that are co-active can tune synapses to become more effective. This process is called synaptic plasticity or long-term potentiation (LTP). Timing-dependent LTP (t-LTP) is a physiologically relevant type of synaptic plasticity that results from repeated sequential firing of action potentials (APs) in pre- and postsynaptic neurons. T-LTP is observed during learning in vivo and is a cellular correlate of memory formation. T-LTP can be elicited by different rhythms of synaptic activity that recruit distinct synaptic growth processes underlying t-LTP. The protein brain-derived neurotrophic factor (BDNF) is released at synapses and mediates synaptic growth in response to specific rhythms of t-LTP stimulation, while other rhythms mediate BDNF-independent t-LTP. Here, we developed a realistic computational model that accounts for our previously published experimental results of BDNF-independent 1:1 t-LTP (pairing of 1 presynaptic with 1 postsynaptic AP) and BDNF-dependent 1:4 t-LTP (pairing of 1 presynaptic with 4 postsynaptic APs). The model explains the magnitude and time course of both t-LTP forms and allows predicting t-LTP properties that result from altered BDNF turnover. Since BDNF levels are decreased in demented patients, understanding the function of BDNF in memory processes is of utmost importance to counteract Alzheimer’s disease.
Reference:
1 . Solinas SMG, Edelmann E, Leßmann V, Migliore M (2019) A kinetic model for Brain-Derived Neurotrophic Factor mediated spike timing-dependent LTP. PLoS Comput Biol 15:e1006975 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Neuron or other electrically excitable cell; Synapse; Dendrite;
Brain Region(s)/Organism: Hippocampus;
Cell Type(s): Hippocampus CA1 pyramidal GLU cell;
Channel(s): I Na,t; I_KD; I K; I h; I A; I Calcium;
Gap Junctions:
Receptor(s): AMPA; NMDA;
Gene(s):
Transmitter(s): Glutamate;
Simulation Environment: NEURON;
Model Concept(s): Facilitation; Long-term Synaptic Plasticity; Short-term Synaptic Plasticity; STDP;
Implementer(s): Solinas, Sergio [solinas at unipv.it]; Migliore, Michele [Michele.Migliore at Yale.edu];
Search NeuronDB for information about:  Hippocampus CA1 pyramidal GLU cell; AMPA; NMDA; I Na,t; I A; I K; I h; I Calcium; I_KD; Glutamate;
load_file("nrngui.hoc")
cvode_active(1)

numaxon=1
numsoma=1
numbasal=52
numapical=70
numtrunk=49

xopen("geo5038804.hoc")             // geometry file
xopen("fixnseg.hoc")           

Rm = 28000
RmDend = Rm
RmSoma = Rm
RmAx = Rm

Cm    = 1
CmSoma= Cm
CmAx  = Cm
CmDend = Cm

RaAll= 150
RaSoma=150  
RaAx = 50

Vrest = -70
gna =  .025
AXONM = 5
gkdr = 0.01
celsius = 35.0  
KMULT =  0.04
KMULTP = 0.04

ghd=0.00005

objref g, b,c, stim, distrx, distry, cdistry, p

forsec "axon" {insert pas e_pas=Vrest g_pas = 1/RmAx Ra=RaAx cm=CmAx}
forsec "soma" {insert pas e_pas=Vrest g_pas = 1/RmSoma Ra=RaSoma cm=CmSoma}
forsec "dendrite"{insert pas e_pas=Vrest g_pas = 1/RmDend Ra=RaAll cm=CmDend}
forsec "user5" {insert pas e_pas=Vrest g_pas = 1/RmDend Ra=RaAll cm=CmDend}

access soma

freq=50
geom_nseg()
tot=0
forall {tot=tot+nseg}
distance()

// tstop=20

// b = new VBox()
// b.intercept(1)
// g = new Graph()
// g.size(0,tstop,-70,30)
// g.addvar("soma.v(0.5)",1,1,2*tstop,0,2)
// g.xaxis(1)
// c = new Graph()
// c.size(0,740,0,100)
// c.xaxis(1)
// c.exec_menu("10% Zoom out")
// c.color(1)
// c.label(0.4,0.8," peak AP")
// xpanel("")
// xbutton("runm ", "runp()")
// xpanel()
// b.intercept(0)
// b.map()

// p = new PlotShape()
// p.exec_menu("Shape Plot")
// p.size(-194.658,304.758,-223.667,609.667)
// p.variable("v")
// p.show(0)

// rel=0.5
// soma {
// stim= new IClamp(rel)
// stim.amp=2.5
// stim.dur=1.5
// stim.del=1
// }

// objref tvec, dvdt
// tvec = new Vector()
// dvdt = new Vector(0)
// distrx=new Vector()
// distry=new Vector()


// soma{
// distry.record(&v(0.5))
// tvec.record(&t)
// }

forsec "axon" {   
                insert nax gbar_nax=gna * AXONM
                insert kdr gkdrbar_kdr=gkdr
                insert kap gkabar_kap = KMULTP
}

forsec "soma" {   
		insert hd ghdbar_hd=ghd	vhalfl_hd=-73
                insert na3 gbar_na3=gna
                insert kdr gkdrbar_kdr=gkdr
                insert kap gkabar_kap = KMULTP
}

for i=0, numbasal-1 dendrite[i] {
		insert hd ghdbar_hd=ghd vhalfl_hd=-73
                insert na3 gbar_na3=gna
                insert kdr gkdrbar_kdr=gkdr
		insert kap gkabar_kap=0
		insert kad gkabar_kad=0

		for (x) if (x>0 && x<1) { xdist = distance(x)
                	ghdbar_hd(x) = ghd*(1+3*xdist/100)
                		if (xdist > 100){
					vhalfl_hd=-81
                        		gkabar_kad(x) = KMULT*(1+xdist/100)
                			} else {
					vhalfl_hd=-73
                        		gkabar_kap(x) = KMULTP*(1+xdist/100)
               				}
		}
}
                
forsec "apical_dendrite" {
	insert ds
		insert hd ghdbar_hd=ghd
                insert na3 gbar_na3=gna
                insert kdr gkdrbar_kdr=gkdr
		insert kap gkabar_kap=0
		insert kad gkabar_kad=0

		for (x) if (x>0 && x<1) { xdist = distance(x)
                	ghdbar_hd(x) = ghd*(1+3*xdist/100)
                		if (xdist > 100){
					vhalfl_hd=-81
                        		gkabar_kad(x) = KMULT*(1+xdist/100)
                			} else {
					vhalfl_hd=-73
                        		gkabar_kap(x) = KMULTP*(1+xdist/100)
               				}
		}
}

forsec "user5" {
	insert ds
		insert hd ghdbar_hd=ghd
                insert na3 gbar_na3=gna
                insert kdr gkdrbar_kdr=gkdr
		insert kap gkabar_kap=0
		insert kad gkabar_kad=0

		for (x) if (x>0 && x<1) { xdist = distance(x)
                	ghdbar_hd(x) = ghd*(1+3*xdist/100)
                		if (xdist > 100){
					vhalfl_hd=-81
                        		gkabar_kad(x) = KMULT*(1+xdist/100)
                			} else {
					vhalfl_hd=-73
                        		gkabar_kap(x) = KMULTP*(1+xdist/100)
               				}
		}
}

proc init() {
	t=0
        forall {
        v=Vrest
        if (ismembrane("nax") || ismembrane("na3")) {ena=55}
        if (ismembrane("kdr") || ismembrane("kap") || ismembrane("kad")) {ek=-90}
        if (ismembrane("hd") ) {ehd_hd=-30}
	}
	finitialize(Vrest)
        fcurrent()

        forall {
	for (x) {
	if (ismembrane("na3")||ismembrane("nax")){e_pas(x)=v(x)+(ina(x)+ik(x))/g_pas(x)}
	if (ismembrane("hd")) {e_pas(x)=e_pas(x)+i_hd(x)/g_pas(x)}
		}
	}
	cvode.re_init()
	cvode.event(tstop)
	access soma
	// g.begin()
		// dvdt.resize(0)
		// tvec.resize(0)
	    }
	    
init()

// proc advance() {
// 	fadvance()
// 	g.plot(t)
// 	g.flush()
// 	p.flush()
// 	doNotify()
// }

// proc runp() {
// run()

// 	distrx=new Vector()
// 	distry=new Vector()
// 	forsec "apical_dendrite" {
// 		for (x) if (x>0 && x<1) {
// 			if (diam>=0.) {
// 			distrx.append(distance(x)) 
// 			distry.append(vmax_ds(x)-Vrest)
// 			}
// }
// }
// }
/*
proc loop() {
		c.beginline()
		for index=0, tvec.size()-2 {
			if (tvec.x[index+1]>tvec.x[index]) {dvdt.append((distry.x[index]-distry.x[index+1])/(tvec.x[index]-tvec.x[index+1]))}
			}
		for index=0, dvdt.size()-1 {
			c.line(distry.x[index],dvdt.x[index])
			}
		c.flush()
		doNotify()
}
*/

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