Pyramidal neuron, fast, regular, and irregular spiking interneurons (Konstantoudaki et al 2014)

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Accession:168310
This is a model network of prefrontal cortical microcircuit based primarily on rodent data. It includes 16 pyramidal model neurons, 2 fast spiking interneuron models, 1 regular spiking interneuron model and 1 irregular spiking interneuron model. The goal of the paper was to use this model network to determine the role of specific interneuron subtypes in persistent activity
Reference:
1 . Konstantoudaki X, Papoutsi A, Chalkiadaki K, Poirazi P, Sidiropoulou K (2014) Modulatory effects of inhibition on persistent activity in a cortical microcircuit model. Front Neural Circuits 8:7 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Realistic Network; Neuron or other electrically excitable cell;
Brain Region(s)/Organism:
Cell Type(s): Neocortex fast spiking (FS) interneuron; Neocortex spiking regular (RS) neuron; Neocortex spiking low threshold (LTS) neuron; Neocortex spiking irregular interneuron;
Channel(s): I Na,p; I Na,t; I L high threshold; I T low threshold; I A; I K; I h; I_Ks; I_KD;
Gap Junctions:
Receptor(s): GabaA; GabaB; AMPA; NMDA;
Gene(s):
Transmitter(s): Gaba; Glutamate;
Simulation Environment: NEURON;
Model Concept(s): Activity Patterns; Synchronization; Active Dendrites;
Implementer(s): Sidiropoulou, Kyriaki [sidirop at imbb.forth.gr]; Konstantoudaki, Xanthippi [xeniakons at gmail.com];
Search NeuronDB for information about:  GabaA; GabaB; AMPA; NMDA; I Na,p; I Na,t; I L high threshold; I T low threshold; I A; I K; I h; I_Ks; I_KD; Gaba; Glutamate;
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KonstantoudakiEtAl2014
experiment
data
ampa.mod
ampain.mod
cadyn.mod
cadynin.mod
cal.mod
calc.mod
calcb.mod
can.mod
cancr.mod
canin.mod
car.mod
cat.mod
catcb.mod
gabaa.mod *
gabaain.mod
gabab.mod
h.mod
hcb.mod
hin.mod
ican.mod
iccb.mod
iccr.mod
icin.mod
iks.mod
ikscb.mod
ikscr.mod
iksin.mod
kadist.mod
kadistcr.mod
kadistin.mod
kaprox.mod
kaproxcb.mod
kaproxin.mod
kca.mod
kcain.mod
kct.mod
kctin.mod
kdr.mod *
kdrcb.mod
kdrcr.mod
kdrin.mod
naf.mod
nafcb.mod
nafcr.mod
nafin.mod
nafx.mod
nap.mod *
netstim.mod *
NMDA.mod
NMDAIN.mod
sinclamp.mod *
cb.hoc
cr.hoc
ExperimentControl.hoc *
final.hoc
incell.hoc
net.hoc
pfc_pc_temp.hoc
run
run_orig
                            
/* Based on Durstewitz and Gabriel 2006, "Irregular spiking in NMDA-driven prefrontal cortex neurons"
Written 18-04-08 updated 8-10-2009
This file makes connections between 16 Pcells, 2 PV and 1 CB interneuron and 1 CR interneuron. The connections are all-with-all, with the same weights for feedforward and feedback synapses, but with different for autapses. Also the number of synapses Pcells to interneuon and interneuron to Pcells are different*/ 



xopen ("incell.hoc")      		//load template for PV/FS interneuron
xopen ("pfc_pc_temp.hoc")		//load template for pyramidal neuron
xopen ("cb.hoc")			//load template for CB/LTS interneuron
xopen ("cr.hoc")		//load template for CR/IR interneuron


//----------------------------Insert variables to be used for stimulations and connections

//----------------------------Insert variable for random placement of synapses

objref r, f, fin, fpin, finp, finps, fpcb, fpcr, fcrcb, fcbp, fcrp, fa, fn



//--------------------Stimulations

total=150
objref nc1[nPcells][total], ns1, nc2[nPcells][total], ampapr[nPcells][total], nmdapr[nPcells][total], nc3[nPcells][total], ns2, nc4[nPcells][total], ampal[nPcells][total], nmdal[nPcells][total], gabaal[nPcells][total], gababl[nPcells][total]



//--------------------PC-PC connections
objref autoampa[nPcells][total], autonmda[nPcells][total]                          //autapses
objref conautoampa[nPcells][total], conautonmda[nPcells][total]
objref ampa[nPcells][total], nmda[nPcells][total]                                 //synapses  
objref conampa[nPcells][nPcells][total], connmda[nPcells][nPcells][total]

//--------------------IN-IN connections
objref gabaain[nINcells][total],gababin[nINcells][total]
objref congabaain[nINcells][nINcells][total],congababin[nINcells][nINcells][total]

//--------------------PC-IN connections
objref ampain[nINcells][total], nmdain[nINcells][total]
objref conampain[nPcells][nINcells][total], connmdain[nPcells][nINcells][total]

//--------------------IN-PC connections-soma
objref gabaa[nPcells][total],gabab[nPcells][total]
objref congabaa[nINcells][nPcells][total], congabab[nINcells][nPcells][total]

//--------------------IN-PC connections-dend1
objref gabaas[nPcells][total],gababs[nPcells][total]
objref congabaas[nINcells][nPcells][total], congababs[nINcells][nPcells][total]

//--------------------PC-CB connections
objref ampacb[nCBcells][total], nmdacb[nCBcells][total]
objref conampacb[nPcells][nCBcells][total], connmdacb[nPcells][nCBcells][total]

//--------------------PC-CR connections
objref ampacr[nCRcells][total], nmdacr[nCRcells][total]
objref conampacr[nPcells][nCRcells][total], connmdacr[nPcells][nCRcells][total]

//--------------------CR-CB connections
objref gabaacrcb[nCBcells][total],gababcrcb[nCBcells][total]
objref congabaacrcb[nCRcells][nCBcells][total],congababcrcb[nCRcells][nCBcells][total]

//--------------------CB-PC connections
objref gabaacb[nPcells][total],gababcb[nPcells][total]
objref congabaacb[nCBcells][nPcells][total], congababcb[nCBcells][nPcells][total]

//--------------------CR-PC connections
objref gabaacrs[nPcells][total],gababcrs[nPcells][total]
objref congabaacrs[nCRcells][nPcells][total], congababcrs[nCRcells][nPcells][total]





//--------------------Others 
objref ic1, ic2, ic3, ic4, ic5, ic6, ic7, ic8, ic9, ic10                    	//IClamp
objref sinw[nPcells], w[101][nPcells], ramp              				//membrane noise
objref insinw[nINcells], inw[101][nINcells], ramp
objref cbsinw[nCBcells], cbw[101][nCBcells], ramp
objref crsinw[nCRcells], crw[101][nCRcells], ramp

//----------------------------------------------Insert noise

proc noise() {
tot=0
forsec soma_list {
w[runs][tot]=new Random(tot+$1)
w[runs][tot].poisson(0.02) 
    
sinw[tot]=new SinClamp(0.5)
sinw[tot].del=0       
sinw[tot].dur=tstop
sinw[tot].freq =100     
w[runs][tot].play(&sinw[tot].pkamp)
tot=tot+1
} 

totin=0
forsec insoma_list {
inw[runs][totin]=new Random(1000+$1)
inw[runs][totin].poisson(0.02)  

insinw[totin]=new SinClamp(0.5)
insinw[totin].del=0      
insinw[totin].dur=tstop
insinw[totin].freq =100 
   
inw[runs][totin].play(&insinw[totin].pkamp)
totin=totin+1
} 

totcb=0
forsec cbsoma_list {
cbw[runs][totcb]=new Random(800+$1)
cbw[runs][totcb].poisson(0.02)  

cbsinw[totcb]=new SinClamp(0.5)
cbsinw[totcb].del=0      
cbsinw[totcb].dur=tstop
cbsinw[totcb].freq =100 
   
cbw[runs][totcb].play(&cbsinw[totcb].pkamp)
totcb=totcb+1
} 

totcr=0
forsec crsoma_list {
crw[runs][totcr]=new Random(1500+$1)
crw[runs][totcr].poisson(0.035)  

crsinw[totcr]=new SinClamp(0.5)
crsinw[totcr].del=0      
crsinw[totcr].dur=tstop
crsinw[totcr].freq =100 
   
crw[runs][totcr].play(&crsinw[totcr].pkamp)
totcr=totcr+1
} 
}

//---------------------------Initial stimulation (proximal dendrite)(Kuroda, 1998, Constantinides, 2001)

ns1=new NetStim(0.5)
ns1.interval=50 
ns1.number=10
ns1.start=0
ns1.noise=0

proc stimulation() {

r = new Random($1+165)
PID = r.uniform(0, 1)

for i=0, (nPcells-1) {
	for j=0, (inmaxsyn-1) {
PID=r.repick()
Pcells[i].dend[1] ampapr[i][j]=new GLU(PID)
Pcells[i].dend[1] nmdapr[i][j]=new NMDA(PID)

nc1[i][j]=new NetCon(ns1, ampapr[i][j])
nc1[i][j].delay=500
nc1[i][j].weight=ampaweightpr 
nc1[i][j].threshold=-20 
	
nc2[i][j]=new NetCon(ns1, nmdapr[i][j])
nc2[i][j].delay=500
nc2[i][j].weight=ampaweightpr*5                        
nc2[i][j].threshold=-20 
		
		}

	}

}

// --------------------------------PC-PC connections, basal dendrite(Thomson, 1997)

proc pyramidals() {
fa = new Random($1+3)
//FIDa=fa.normal(1.5,0.15)			//According to Thomson(2007)
FIDa=fa.normal(0.96,0.11)
fn=new Random($1+124)
FIDn=fn.normal(1.33, 0.13)

//---------------------------------------------------Insert Autapses(Lubke, 1996)
for i=0, (nPcells-1) {
	for j=0, (automaxsyn-1) {

//PID=r.repick()

Pcells[i].dend[0] autoampa[i][j] = new GLU(0.5)
Pcells[i].dend[0] autonmda[i][j] = new NMDA(0.5)
	}
}
//----------------------Connect autapses
for i=0, (nPcells-1) {
	for j=0, (automaxsyn-1) {

FIDa=fa.repick()
if (FIDa<0) FIDa=FIDa*(-1)
FIDn=fn.repick()
if (FIDn<0) FIDn=FIDn*(-1)

Pcells[i].axon conautoampa [i][j] = new NetCon(&v(1), autoampa[i][j], -20, FIDa, ampaweight)
Pcells[i].axon conautonmda [i][j] = new NetCon(&v(1), autonmda[i][j], -20, FIDn, nmdaweight) 
	}
}
//---------------------------------------------------------Insert Synapses
 
//The connections between Pcells are all-with-all, with the same strength (#of synapses)

for i=0, (nPcells-1) {
	for j=0, (maxsyn-1) {

//PID=r.repick()

Pcells[i].dend[0] ampa[i][j] = new GLU(0.5)
Pcells[i].dend[0] nmda[i][j] = new NMDA(0.5)
	}
}

///---------------------Connect synapses
for i=0, (nPcells-1) {
	for j=0, (nPcells-1) {
			if (i !=j) {
				for k=0, (maxsyn-1) {
//FID=f.repick()
//if (FID<0) FID=FID*(-1)
FIDa=fa.repick()
if (FIDa<0) FIDa=FIDa*(-1)
FIDn=fn.repick()
if (FIDn<0) FIDn=FIDn*(-1)

Pcells[i].axon conampa[i][j][k]=new NetCon(&v(1), ampa[j][k], -20, FIDa, ampaweight)
Pcells[i].axon connmda[i][j][k]=new NetCon(&v(1), nmda[j][k], -20, FIDn, nmdaweight)
			}
		}
	}
}

}

///---------------------------------------------IN-IN connections--------------------------------------------------------//
proc interneurons() {
fin = new Random($1-100)
delstimin=fin.normal(1.76,0.07)		//latency from IN-IN, according to Bacci (2003)   
//delstimin=1.8
// delstimin=0.5
//----------------------Insert synapses

for i=0, (nINcells-1) {
	for j=0,(maxsyn1-1) {

//PID = r.repick ()

INcells[i].soma gabaain[i][j] = new GABAain(0.5)
	}
}
//----------------------Connect
for i=0, (nINcells-1) {
	for j=0, (nINcells-1) {
		for k=0, (maxsyn1-1) {


delstimin=fin.repick()
if (delstimin<0) delstimin=delstimin*(-1)

INcells[i].axon congabaain[i][j][k] = new NetCon(&v(1), gabaain[j][k],-20,delstimin,autogabaweight)
		}
	}
}

}

//----------------------------------------------PC-IN connections-------------------------------------------------------//
proc pyrin() {
fpin = new Random($1*2)
delstim=fpin.normal(0.6, 0.2)		
//delstim=0.6
//----------------------------------Insert synapses

for i=0, (nINcells-1) {
       for j=0, (maxsyn2-1) {

INcells[i].dend ampain[i][j] = new GLUIN(0.5)
INcells[i].dend nmdain[i][j] = new NMDAIN(0.5)
    }
}
//-----------------------------------Connect
for i=0, (nPcells-1) {
	for j=0, (nINcells-1) {
		for k=0, (maxsyn2-1) {

delstim=fpin.repick()
if (delstim<0) delstim=delstim*(-1)

Pcells[i].axon conampain[i][j][k] = new NetCon(&v(1), ampain[j][k], -20, delstim, ampaweightin)
Pcells[i].axon connmdain[i][j][k] = new NetCon(&v(1), nmdain[j][k], -20, delstim, nmdaweightin)   
		}
	}
}

}
//------------------------------------------------IN-PC connections-----------------------------------------------------//
proc inpyr() {
finp = new Random($1*8)
delstiminp=finp.normal(1.8, 0.8)	//latency from IN-Pc, according to Thomson(2007)
//delstiminp=1.8
//----------------------------Insert synapses
for i=0, (nPcells-1) {
	for j=0,(maxsyn3-1) { 

Pcells[i].soma gabaa[i][j] = new GABAa(0.5)
Pcells[i].soma gabab[i][j] = new GABAb(0.5)
	}
}
//-----------------------------Connect
for i=0, (nINcells-1) {
	for j=0,(nPcells-1) {
		for k=0, (maxsyn3-1) {

delstiminp=finp.repick()
if (delstiminp<0) delstiminp=delstiminp*(-1)

INcells[i].axon congabaa[i][j][k] = new NetCon(&v(1), gabaa[j][k], -20, delstiminp, gabaweight)
INcells[i].axon congabab[i][j][k] = new NetCon(&v(1), gabab[j][k], -20, delstiminp, gabaweightb)
		}
	}
}

}


//-----------------------------------------------IN-PC connections-dend1

proc inpyrs() {
finp = new Random($1*8)
delstiminp=finp.normal(1.8, 0.8)	//latency from IN-Pc, according to Thomson(2007)
//delstiminp=1.8
//----------------------------Insert synapses
for i=0, (nPcells-1) {
	for j=0,(maxsyn3-1) { 

Pcells[i].dend[1] gabaas[i][j] = new GABAa(0.5)
Pcells[i].dend[1] gababs[i][j] = new GABAb(0.5)
	}
}
//-----------------------------Connect
for i=0, (nINcells-1) {
	for j=0,(nPcells-1) {
		for k=0, (maxsyn3-1) {

delstiminp=finp.repick()
if (delstiminp<0) delstiminp=delstiminp*(-1)

INcells[i].axon congabaas[i][j][k] = new NetCon(&v(1), gabaas[j][k], -20, delstiminp, gabaweight)
INcells[i].axon congababs[i][j][k] = new NetCon(&v(1), gababs[j][k], -20, delstiminp, gabaweightb)
		}
	}
}

}



//----------------------------------------------PC-CB connections-------------------------------------------------------//
proc pyrcb() {
fpcb = new Random($1*2)
delstim=fpcb.normal(0.6, 0.2)		//latency from Pc-Cb, according to Thomson(2007), also Angulo,Audinat(1999)
//delstim=0.6
//----------------------------------Insert synapses

for i=0, (nCBcells-1) {
       for j=0, (maxsyn5-1) {

CBcells[i].dend ampacb[i][j] = new GLUIN(0.5)
CBcells[i].dend nmdacb[i][j] = new NMDA(0.5)
    }
}
//-----------------------------------Connect
for i=0, (nPcells-1) {
	for j=0, (nCBcells-1) {
		for k=0, (maxsyn5-1) {

delstim=fpcb.repick()
if (delstim<0) delstim=delstim*(-1)

Pcells[i].axon conampacb[i][j][k] = new NetCon(&v(1), ampacb[j][k], -20, delstim, ampaweightcb)
Pcells[i].axon connmdacb[i][j][k] = new NetCon(&v(1), nmdacb[j][k], -20, delstim, nmdaweightcb)   
		}
	}
}

}



//----------------------------------------------PC-CR connections-------------------------------------------------------//
proc pyrcr() {
fpcr = new Random($1*2)
delstim=fpcr.normal(0.6, 0.2)		
//----------------------------------Insert synapses

for i=0, (nCRcells-1) {
       for j=0, (maxsyn6-1) {

CRcells[i].dend[0] ampacr[i][j] = new GLUIN(0.5)
CRcells[i].dend[0] nmdacr[i][j] = new NMDA(0.5)
    }
}
//-----------------------------------Connect
for i=0, (nPcells-1) {
	for j=0, (nCRcells-1) {
		for k=0, (maxsyn6-1) {

delstim=fpcr.repick()
if (delstim<0) delstim=delstim*(-1)

Pcells[i].axon conampacr[i][j][k] = new NetCon(&v(1), ampacr[j][k], -20, delstim, ampaweightcr)
Pcells[i].axon connmdacr[i][j][k] = new NetCon(&v(1), nmdacr[j][k], -20, delstim, nmdaweightcr)   
		}
	}
}

}


//------------------------------------------------CR-CB connections-----------------------------------------------------//
proc crcb() {
fcrcb = new Random($1*9)
delstimcrcb=fcrcb.normal(1.8, 0.8)	
//delstimcbp=1.8
//----------------------------Insert synapses
for i=0, (nCBcells-1) {
	for j=0,(maxsyn7-1) { 

//PID = r.repick()
//print delstimcbp
CBcells[i].dend gabaacrcb[i][j] = new GABAa(0.5)

	}
}
//-----------------------------Connect
for i=0, (nCRcells-1) {
	for j=0,(nCBcells-1) {
		for k=0, (maxsyn7-1) {

delstimcrcb=fcrcb.repick()
if (delstimcrcb<0) delstimcrcb=delstimcrcb*(-1)

CRcells[i].axon congabaacrcb[i][j][k] = new NetCon(&v(1), gabaacrcb[j][k], -20, delstimcrcb, gabaweightcrcb)
		}
	}
}

}

//------------------------------------------------CB-PC connections-----------------------------------------------------//
proc cbpyr() {
fcbp = new Random($1*9)
delstimcbp=fcbp.normal(1.8, 0.8)	

//----------------------------Insert synapses
for i=0, (nPcells-1) {
	for j=0,(maxsyn8-1) { 

Pcells[i].dend[2] gabaacb[i][j] = new GABAa(0.5)
	}
}
//-----------------------------Connect
for i=0, (nCBcells-1) {
	for j=0,(nPcells-1) {
		for k=0, (maxsyn8-1) {

delstimcbp=fcbp.repick()
if (delstimcbp<0) delstimcbp=delstimcbp*(-1)

CBcells[i].axon congabaacb[i][j][k] = new NetCon(&v(1), gabaacb[j][k], -20, delstimcbp, gabaweightcb)
		}
	}
}

}


//------------------------------------------------CR-PC connections-----------------------------------------------------//
proc crpyr() {
fcrp = new Random($1*9)
delstimcrp=fcrp.normal(1.8, 0.8)	

//----------------------------Insert synapses
for i=0, (nPcells-1) {
	for j=0,(maxsyn9-1) { 

Pcells[i].dend[2] gabaacrs[i][j] = new GABAa(0.5)
	}
}
//-----------------------------Connect
for i=0, (nCRcells-1) {
	for j=0,(nPcells-1) {
		for k=0, (maxsyn9-1) {

delstimcrp=fcrp.repick()
if (delstimcrp<0) delstimcrp=delstimcrp*(-1)

CRcells[i].axon congabaacrs[i][j][k] = new NetCon(&v(1), gabaacrs[j][k], -20, delstimcrp, gabaweightcr)
		}
	}
}

}

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