My_template.hoc

load_file("nrngui.hoc")
load_file("cell.hoc")
cvode_active(1) 

objref NeuroCell[2], stim[2]
objref synD[2][400], nsD[2][400], ncD[2][400], ns, nt[2]
objref syn[3], nt[2]
objref fseq
double  DistSD[2][400], DistSDm[2], ds[2]

N = 2
for j=0, N-1{
	NeuroCell[j] = new CA1_PC_cAC_sig() 
	NeuroCell[j].init()
}

forall print secname() //elenca tutti i segmenti e i loro nomi

celsius=34


aI = 200
Nsyn=20
ws=5e-4
wi = 0
ds0=50
ds1=150
Dsd=40
FreqInp = 100
chnoise = 0

	xpanel("variables")
//	xvalue("Istim Amplitude - aI","aI",0,"wca()")
	xvalue("Synaptic Conduptance - ws","ws",0,"wca()")
	xvalue("Inhibition weight - wi","wi",0,"wca()")
	xvalue("d0","ds0",0,"wca()")
	xvalue("d1","ds1",0,"wca()")
	xvalue("f (Hz)","FreqInp",0,"wca()")
	xvalue("Stoch (0/1)","chnoise",0,"wca()")
	xpanel()

ds[0] = ds0
ds[1] = ds1

fseq = new File("seq.txt")
fseq.ropen()
xseed=fseq.scanvar()
fseq.close()

mcell_ran4_init(xseed)
rrr = mcell_ran4(&xseed)
print rrr

//********************************************

/*
forall {
        print secname()
        for i=0,n3d()-1 print i, x3d(i), y3d(i), z3d(i), diam3d(i)
}
*/

for j=1, N-1 {
	NeuroCell[j].soma {
	    print secname(), " Nsecs: ", n3d()
    	for i=0,n3d()-1 { 
//    		print "BEFORE: ", i, x3d(i), y3d(i), z3d(i), diam3d(i)
	    	pt3dchange(i, x3d(i)+400, y3d(i), z3d(i), diam3d(i))
//    		print "AFTER : ", i, x3d(i), y3d(i), z3d(i), diam3d(i)
		}
	}
}

/*
for j=0, N-1{
	NeuroCell[j].soma {
		stim[j] = new IClamp(0.5)
		stim[j].del=20
		stim[j].dur=100
		stim[j].amp=aI
	}
}
*/

ns = new NetStim(0.5)       //Unico impulso di corrente per tutte le sinapsi
ns.number = 1000000
//ns.interval = 20          //20ms -> 1/(20e-3) = 50 Hz
ns.interval = 1000/FreqInp  //interval in ms
ns.start = 10
ns.noise = chnoise

for m = 0, (N-1) NeuroCell[m].soma {
    syn[m]     = new ExpSyn(0.5)
	syn[m].tau = 30
	syn[m].e   = -80
}

for m = 0, (N-1) {
	k = m+1
	if ( m==(N-1) ) k=0
	NeuroCell[m].soma nt[m] = new NetCon(&v(.5), syn[k], 0, 0, wi)
}


proc wca() {

	for j=0, N-1{
		NeuroCell[j].soma {
//			stim[j].amp=aI
			for ll=0,Nsyn-1 {
		    	ncD[j][ll].weight = ws
			}
		}
		nt[j].weight = wi
	}
	ds[0] = ds0
	ds[1] = ds1
    ns.noise = chnoise
	ns.interval = 1000/FreqInp    //interval in ms
	
//    CreateShuffleSyn()
}


proc CreateShuffleSyn() {

if (Dsd == 0) Dsd = 50  //max 400

for m=0,N-1 {
	access NeuroCell[m].soma
	distance()
	dm=0
	for j=0,(Nsyn-1)  {

		k=0
		while(k==0){
    		indAD = int(189*mcell_ran4(&xseed)) 
 			rrr = mcell_ran4(&xseed)

 			NeuroCell[m].apic[indAD] {
 				if ( (distance(rrr) > ds[m] && distance(rrr) < (ds[m]+Dsd) ) ) {
					k=1
//  				print indAD, distance(rrr) 
    	    	}
			}
		}
	    access NeuroCell[m].apic[indAD] // dendriti random

	   	synD[m][j] = new Exp2Syn(rrr)     // nuova sinapsi a due tempi
   		synD[m][j].tau1 = 0.5             // costante di attivazione   (ms)
	   	synD[m][j].tau2 = 3               // costante di inattivazione (ms)
   		synD[m][j].e    = 0               // sinapsi di tipo eccitatorio
   		ncD[m][j] = new NetCon(ns,synD[m][j],0,0,ws) //Unico impulso di corrente per tutte le sinapsi

		print m, j, indAD, synD[m][j].get_loc(),rrr

	    DistSD[m][j] = distance(rrr)
		dm = dm + DistSD[m][j]
	}
	DistSDm[m] = dm/Nsyn
}
print "      Synapsis shuffling - dSm[0] = ",DistSDm[0], " - dSm[1] = ",DistSDm[1] 
print "                   Frequency (Hz) = ",1000/ns.interval, " - ISI (ms) = ",ns.interval
print "                               ws = ",ws, " - wi = ",wi
}

CreateShuffleSyn()

load_file("Ses.ses")