load_file("l4sscell.hoc")//the cell
// load_file("l4cell2.hoc")//
// load_file("l23_3.hoc")//
// load_file("layerV2.hoc")//
load_file("nrngui.hoc")
//****SYNAPTIC CONDUCTACES
//for auto run
uplimit=40 //up limit of presynaptic cells
downlimit=40 //bottom limit of presynaptic cells
countlimit=2 //counter between bottom to top
//activation parameters - netstim for Thalamo-Cortical inputs
tcnoise=1 //0-fixed ISI interval, 1-random activation times
tcdel=40 //delay to first stim
tcNspike=10 //number of presynaptic spikes
tcTspike=5 //ISI between spikes (average)
//same for Cortico-Cortical (eCC)
ccnoise=1 //0
ccdel=50 //200
ccNspike=3 //5
ccTspike=20 //
Inoise=1//0
//Inhibitory (iCC)
Idel=50 //200
INspike=5 //
ITspike=20 //
TCratio=1 //ratio between the number of TC inputs to TC (100%)
CCratio=.3 //...CC
Inhibratio=.5 //and Inhib inputs
TCsyn=1 //number of thalamic cells
CCsyn=1 //number of eCC cells
Isyn=1 //number of iCC cells
tcsynpercell=5 //number of synaptic contacts between thalamic and l4 neuron;based on cruikshank et al 2007
ccsynpercell=5 //number of synaptic contacts between l4 and l4 neuron;
Isynpercell=5 //number of inhibitory synaptic contacts to l4 cell
percentseg=0 //0-100% segregated on specific branches; 0-completetly random locations
//background synapses, random
randEnum=100 //Excitatory
randInum=100 //Inhibitory
randAMPAmax=.3 //conductances (nS)
randNMDAmax=.75 //...
randGABAmax=.5 //...
//more details of synaptic activation
risetime_gaba_net=2 //GABAA-rise time
decaytime_gaba_net=40 //GABAA-decay time
tau_ampa_glutamate=2 //decay time
tau_ampa_glutamate_old=2//decay time (not net stim synapse)
tau1_glutamate=50 //decay time
tau2_glutamate=2 //rise time
gama_glutamate=0.08 //'sharpness' of voltage IV curve
n_glutamate=0.25 //'Vhalf' of voltage IV curve
//synaptic conductances of single synapses(nS)
gampamaxcc=0.3 //based on sun et al 2006
gnmdamaxcc=.75
gampamaxtc=.3 //based on cruikshank et al 2007
gnmdamaxtc=.75
ggabamax=0.5 //conductance (nS)
//short term decay (depression)(to % of first pulse)
decaynmdatc=.6
decayampatc=.3
decaynmdacc=1
decayampacc=.5
decaygaba=.7 //GABAA-short term depression (to % of first pulse)
//OBJECTS
objref tcinputvectimes[2],ccinputvectimes[2],Iinputvectimes[2]
objref tcnetstim[2],ccnetstim[2], Inetstim[2]
objref temp,temp2
objref rall, rseg, rbg,rbgnormal,rsyndist,rrandsyn //random objects
rall= new Random()
rseg= new Random()
rbg= new Random()
rbgnormal= new Random()
rsyndist=new Random()
rrandsyn=new Random()
objref savevec,savebaseline ,fsave //saving vectors
savevec=new Vector()
savebaseline=new Vector()
//some important vectors
objref apnum,aplast,upstate,downstate,updur,cavectors[2],Vvectors[2],focV,focAMPA,focNMDA,globV,globAMPA,globNMDA
objref gNMDAcc[2],gAMPAcc[2],gNMDAtc[2],gAMPAtc[2],Vcc[2],cacc[2]
objref randElist,randIlist
objref fV,fAP ,backvec
objref conTCAMPA[2],conTCNMDA[2],conCCAMPA[2],conCCNMDA[2],conIGABA1[2],conIGABA2[2]
//*****ACTIVE CONDUCTANCES
taus_hh3=30
tausv_hh3=10
tausn_hh3=5
tausb_hh3=0.1
taun_hh3=2
taun2_hh3=40
tauh_hh3=1
soma_na=0.5//2//.3
soma_k1=.1//.03
soma_k2=0.1
dend_na=0.002
dend_k1=0.001
dend_k2=0.0001//0.001
axon_na=0
axon_k1=0
axon_k2=0
cabar=0.03
itbar=0
hbar=0.0001
//end active conductances
zeroactive=1
nmdaoff=0 //1-NMDA becomes an ohmic conductance with no v dependence
nmdaVset=-60 //set voltage of NMDA conductance when nmdaoff=1
//the cell
objref cell
cell=new l4(0,0)
savevec.record(&cell.soma.v(.5))
//****FOCAL SYNAPSE
objref synglu
synglu=new glutamate_old(0.9)
synglu.decaynmda=1
synglu.decayampa=.5
synglu.del=tcdel+tcTspike*2
synglu.Nspike=2
synglu.Tspike=tcTspike
synglu.gnmdamax=0
synglu.gampamax=0
//end focal syn
strdef st
forall {nseg=9}
proc init_active(){
// voltage gated conductances
zero=0
if (zeroactive==0){zero=1}
access cell.soma
insert hh3
vshift_hh3=-10
gnabar_hh3=soma_na//*(zero)
gkbar_hh3=soma_k1//*(zero)
gkbar2_hh3=soma_k2//*(zero)
forsec cell.all{
insert hh3
gnabar_hh3=dend_na//*(zero)
gkbar_hh3=dend_k1//*(zero)
gkbar2_hh3=dend_k2//*(zero)
vshift_hh3=-10
gl_hh3=0
ena=70
insert pas
g_pas=1/16000
e_pas=-70
insert cad
insert cah
//insert it
gbar_cah=cabar
//gbar_it=itbar
}
} //init active
proc calc(){ //the procedure for making new run
objref backvec //compares to the background activity
backvec=new Vector()
countrun= downlimit //sim counter
while (countrun<= uplimit){ //chnange in the number of synaptic inputs
TCsyn=int(countrun*TCratio) //new number of synapses
CCsyn=int(countrun*CCratio) //...
Isyn=int(countrun*Inhibratio)//...
if (TCsyn<1){TCsyn=1} //range check
if (CCsyn<1){CCsyn=1} //...
if (Isyn<1){Isyn=1} //...
loclocation()
//recording of synaptic conductances
objref conTCAMPA[cell.tcsyn.count()],conTCNMDA[cell.tcsyn.count()],conCCAMPA[cell.ccsyn.count()],conCCNMDA[cell.ccsyn.count()],conIGABA1[cell.Isyn.count()],conIGABA2[cell.Isyn.count()]
for j=0,cell.tcsyn.count()-1{ //tc connections
conTCAMPA[j]=new Vector()
conTCNMDA[j]=new Vector()
conTCAMPA[j].record(&cell.tcsyn.object(j).gampa)
conTCNMDA[j].record(&cell.tcsyn.object(j).gnmda)
}
for j=0,cell.ccsyn.count()-1{ //cc connections
conCCAMPA[j]=new Vector()
conCCNMDA[j]=new Vector()
conCCAMPA[j].record(&cell.ccsyn.object(j).gampa)
conCCNMDA[j].record(&cell.ccsyn.object(j).gnmda)
}
for j=0,cell.Isyn.count()-1{ //gaba connections
conIGABA1[j]=new Vector()
conIGABA1[j].record(&cell.Isyn.object(j).D)
conIGABA2[j]=new Vector()
conIGABA2[j].record(&cell.Isyn.object(j).R)
} //end recording conductances
for runcount=1,1{//# repeats , first run in each repeat is control, second run is just the background activity
stdinit() //control
run()
for j=1,cell.tcsyn.count()-1{
conTCAMPA[0].add(conTCAMPA[j])
conTCNMDA[0].add(conTCNMDA[j])
}
for j=1,cell.ccsyn.count()-1{
conCCAMPA[0].add(conCCAMPA[j])
conCCNMDA[0].add(conCCNMDA[j])
}
for j=1,cell.Isyn.count()-1{
conIGABA1[0].add(conIGABA1[j])
conIGABA1[0].sub(conIGABA2[j])
}
backvec=savevec.c
for tccount=0,int((TCsyn-1)/tcsynpercell){
tcnetstim[tccount].start=1000
}
for count=0,int((CCsyn-1)/ccsynpercell){
ccnetstim[count].start=1000
}
for count=0,int((Isyn-1)/Isynpercell){
Inetstim[count].start=1000
}
//****saving conductance vectors can be done from here, for example:
print conCCAMPA[0].max() //optional print of peak amplitude, can print to a file
//background run
stdinit()
run()
print backvec.sub(savevec).max() //optional print of peak amplitude, can print to a file
}
countrun=countrun+countlimit //goes over synaptic numbers
}
} //end calc run
load_file("l4ss.ses")
xpanel("Params")
xlabel("Axon") //default-no active conductances
xvalue("Na","axon_na",1,"init_active()")
xvalue("K1","axon_k1",1,"init_active()")
xvalue("K2","axon_k2",1,"init_active()")
xlabel("Soma") //AP generation site
xvalue("Na","soma_na",1,"init_active()")
xvalue("K1","soma_k1",1,"init_active()")
xvalue("K2","soma_k2",1,"init_active()")
xlabel("Dends")
xvalue("Na","dend_na",1,"init_active()")
xvalue("K1","dend_k1",1,"init_active()")
xvalue("K2","dend_k2",1,"init_active()")
xlabel("All")
xvalue("CaL","cabar",1,"init_active()")
//xvalue("CaT","itbar",1,"init_active()")
xlabel("Iterations")
xvalue("% Seg","percentseg",1,"loclocation()")//location of synaptic inputs (0-random)
xvalue("DownLimit","downlimit",1,"") //top number of presynaptic TC cells
xvalue("UPLimit","uplimit",1,"") //bottom...
xvalue("CountLimit","countlimit",1,"") //counter...
xvalue("TC Ratio","TCratio",1,"") //TC to TC (can differ from 1 for preffered vs. non preferred cases
xvalue("CC Ratio","CCratio",1,"") //eCC to TC ratio
xvalue("Inhib Ratio","Inhibratio",1,"") //iCC to TC ratio
xbutton("Calc","calc()") //runs the simulation
xbutton("New Loc","loclocation() ") //new distribution of synapses
xpanel()
xpanel("Synapses")
xlabel("Thalamic Synapses")
xvalue("Delay","tcdel",1,"c_gmax(2)")
xvalue("AMPA Amp","gampamaxtc",1,"c_gmax(2)")
xvalue("NMDA Amp","gnmdamaxtc",1,"c_gmax(2)")
// xvalue("AMPA Decay","decayampatc",1,"c_gmax(2)")
// xvalue("NMDA Decay","decaynmdatc",1,"c_gmax(2)")
xvalue("Tspike","tcTspike",1,"c_gmax(2)")
xvalue("Nspike","tcNspike",1,"c_gmax(2)")
xvalue("Nnoise","tcnoise",1,"c_gmax(2)")
xvalue("Syn #","TCsyn",1,"loclocation()")
xlabel("CC Synapses")
xvalue("Delay","ccdel",1,"c_gmax(2)")
xvalue("AMPA Amp","gampamaxcc",1,"c_gmax(2)")
xvalue("NMDA Amp","gnmdamaxcc",1,"c_gmax(2)")
//xvalue("AMPA Decay","decayampacc",1,"c_gmax(2)")
//xvalue("NMDA Decay","decaynmdacc",1,"c_gmax(2)")
xvalue("Tspike","ccTspike",1,"c_gmax(2)")
xvalue("Nspike","ccNspike",1,"c_gmax(2)")
xvalue("Nnoise","ccnoise",1,"c_gmax(2)")
xvalue("Syn #","CCsyn",1,"loclocation()")
xlabel("Inhibitory Synapses")
xvalue("Delay","Idel",1,"c_gmax(2)")
xvalue("GABAA Amp","ggabamax",1,"c_gmax(2)")
xvalue("Tspike","ITspike",1,"c_gmax(2)")
xvalue("Nspike","INspike",1,"c_gmax(2)")
xvalue("Nnoise","Inoise",1,"c_gmax(2)")
xvalue("Syn #","Isyn",1,"loclocation()")
xlabel("Random Synapses")
xvalue("E#","randEnum",1,"loclocation()")
xvalue("I#","randInum",1,"loclocation()")
xvalue("AMPA Amp","randAMPAmax",1,"c_gmax(2)")
xvalue("NMDA Amp","randNMDAmax",1,"c_gmax(2)")
xvalue("GABA Amp","randGABAmax",1,"c_gmax(2)")
xpanel()
//GUI
objref shape
shape=new Shape(0)
shape.view(-200, -200, 400, 400, 900, 200, 300.48, 300.32)
shape.show(0)
proc make_shape_plot(){//DRAWS THE POINTS ON THE CELL
shape.point_mark_remove()
for j=0,cell.tcsyn.count()-1{
shape.point_mark(cell.tcsyn.object(j), 3, 4, 5)
}
for j=0,cell.ccsyn.count()-1{
shape.point_mark(cell.ccsyn.object(j), 2, 4, 5)
}
for j=0,cell.Isyn.count()-1{
shape.point_mark(cell.Isyn.object(j), 4, 4, 5)
}
for j=0,randElist.count()-1{
shape.point_mark(randElist.object(j), 2, 2, 4)
}
for j=0,randIlist.count()-1{
shape.point_mark(randIlist.object(j), 4, 2, 4)
}
}//END SHAPE
//end GUI
proc loclocation(){ //automatic placement of synapses
objref tcnetstim[int(TCsyn/tcsynpercell)+1],ccnetstim[int(CCsyn/ccsynpercell)+1], Inetstim[int(Isyn/Isynpercell)+1]
objref tcinputvectimes[int(TCsyn/tcsynpercell)+1],ccinputvectimes[int(CCsyn/ccsynpercell)+1],Iinputvectimes[int(Isyn/Isynpercell)+1]
objref randElist,randIlist,rrandsyn
objref temp,temp2
length=0
forsec cell.all{length=length+L}
rall.uniform(10, length-10)
length=0
forsec cell.segdends{length=length+L}
rseg.uniform(10, length-10)
length=0
rbgnormal.normal(1000,100)
cell.tcsyn=new List()
cell.tcnetcon=new List()
cell.ccsyn=new List()
cell.ccnetcon=new List()
cell.Isyn=new List()
cell.Inetcon=new List()
randElist=new List()
randIlist=new List()
rrandsyn=new Random()
rrandsyn.uniform(0,100)
//background synapses
for count=0,randEnum-1{
length=0
dendcount=0
newloc=rall.repick()
forsec cell.dends{
dendcount=dendcount+1
if( (length<=newloc)&&(length+L>=newloc)){ //put synapse
temp=new glutamate_old((newloc-length)/L)
temp.Tspike=100
temp.Nspike=5
temp.del= rrandsyn.repick()
randElist.append(temp)
}
length=length+L
}
}
for count=0,randInum-1{
length=0
dendcount=0
forsec cell.dends{
dendcount=dendcount+1
newloc=rall.repick()
if( (length<=newloc)&&(length+L>=newloc)){ //put synapse
temp=new gaba((newloc-length)/L)
temp.e=-60
temp.Tspike=100
temp.Nspike=5
temp.del= rrandsyn.repick()
randIlist.append(temp)
}
length=length+L
}
}
//thalamocortical synapses
prenum=-1
precounter=0
for count=0,TCsyn-1{
if (precounter==0){
prenum=prenum+1
tcnetstim[prenum]=new NetStim(.5)
tcinputvectimes[prenum]=new Vector()
}
precounter=precounter+1
if (precounter==tcsynpercell){
precounter=0
}
cell.dends =new SectionList()
//the whole tree is connected
newloc=rall.repick()
forsec cell.all{cell.dends.append()}
length=0
dendcount=0
forsec cell.dends{
dendcount=dendcount+1
if( (length<=newloc)&&(length+L>=newloc)){ //put synapse
temp=new glutamate((newloc-length)/L)
temp.xloc=x3d(((newloc-length)/L)*(n3d()-1))
temp.yloc=y3d(((newloc-length)/L)*(n3d()-1))
temp.tag1=dendcount-1
temp.tag2=(newloc-length)/L
cell.tcsyn.append(temp)
temp2=new NetCon(tcnetstim[prenum],temp)
if (precounter==1){
temp2.record(tcinputvectimes[prenum])
}
cell.tcnetcon.append(temp2)
}
length=length+L
}
}
//corticocortical synapses
prenum=-1
precounter=0
for count=0,CCsyn-1{
if (precounter==0){
prenum=prenum+1
ccnetstim[prenum]=new NetStim(.5)
ccinputvectimes[prenum]=new Vector()
}
precounter=precounter+1
if (precounter==ccsynpercell){
precounter=0
}
cell.dends =new SectionList()
//the whole tree is connected
newloc=rall.repick()
forsec cell.all{cell.dends.append()}
length=0
dendcount=0
forsec cell.dends{
dendcount=dendcount+1
if( (length<=newloc)&&(length+L>=newloc)){ //put synapse
temp=new glutamate((newloc-length)/L)
temp.xloc=x3d(((newloc-length)/L)*(n3d()-1))
temp.yloc=y3d(((newloc-length)/L)*(n3d()-1))
temp.tag1=dendcount-1
temp.tag2=(newloc-length)/L
cell.ccsyn.append(temp)
temp2=new NetCon(ccnetstim[prenum],temp)
if (precounter==1){
temp2.record(ccinputvectimes[prenum])
}
cell.ccnetcon.append(temp2)
}
length=length+L
}
}
//inhibitory synapses
prenum=-1
precounter=0
for count=0,Isyn-1{
if (precounter==0){
prenum=prenum+1
Inetstim[prenum]=new NetStim(.5)
Iinputvectimes[prenum]=new Vector()
}
precounter=precounter+1
if (precounter==Isynpercell){
precounter=0
}
cell.dends =new SectionList()
//the whole tree is connected
newloc=rall.repick()
forsec cell.all{cell.dends.append()}
length=0
dendcount=0
forsec cell.dends{
dendcount=dendcount+1
if( (length<=newloc)&&(length+L>=newloc)){ //put synapse
temp=new gaba_net((newloc-length)/L)
temp.xloc=x3d(((newloc-length)/L)*(n3d()-1))
temp.yloc=y3d(((newloc-length)/L)*(n3d()-1))
temp.tag1=dendcount-1
temp.tag2=(newloc-length)/L
cell.Isyn.append(temp)
temp2=new NetCon(Inetstim[prenum],temp)
if (precounter==1){
temp2.record(Iinputvectimes[prenum])
}
cell.Inetcon.append(temp2)
}
length=length+L
}
}
make_shape_plot()
c_gmax()
}//loclocation
proc c_gmax(){ //changes in synaptic conducatnces or activation parameters
//TC synapses
for tccount=0,int((TCsyn-1)/tcsynpercell){
tcnetstim[tccount].interval=tcTspike
tcnetstim[tccount].number=tcNspike
tcnetstim[tccount].start=tcdel
tcnetstim[tccount].noise=tcnoise
}
//CC synapses
for count=0,int((CCsyn-1)/ccsynpercell){
ccnetstim[count].interval=ccTspike
ccnetstim[count].number=ccNspike
ccnetstim[count].start=ccdel
ccnetstim[count].noise=ccnoise
}
//Inhib synapses
for count=0,int((Isyn-1)/Isynpercell){
Inetstim[count].interval=ITspike
Inetstim[count].number=INspike
Inetstim[count].start=Idel
Inetstim[count].noise=Inoise
}
for j=0,cell.tcsyn.count()-1{ //tc connections
cell.tcsyn.object(j).gampamax=rsyndist.lognormal(gampamaxtc,(gampamaxtc)^4)
cell.tcsyn.object(j).gnmdamax=rsyndist.lognormal(gnmdamaxtc,(gnmdamaxtc)^4)
cell.tcsyn.object(j).decaynmda=decaynmdatc
cell.tcsyn.object(j).decayampa=decayampatc
cell.tcsyn.object(j).Voff=nmdaoff
cell.tcsyn.object(j).Vset=nmdaVset
}
for j=0,cell.ccsyn.count()-1{ //cc connections
cell.ccsyn.object(j).gampamax=rsyndist.lognormal(gampamaxcc,(gampamaxcc)^4)
cell.ccsyn.object(j).gnmdamax=rsyndist.lognormal(gnmdamaxcc,(gnmdamaxcc)^4)
cell.ccsyn.object(j).decaynmda=decaynmdacc
cell.ccsyn.object(j).decayampa=decayampacc
cell.ccsyn.object(j).Voff=nmdaoff
cell.ccsyn.object(j).Vset=nmdaVset
}
for j=0,cell.Isyn.count()-1{ //Inhib connections
cell.Isyn.object(j).gmax=rsyndist.lognormal(ggabamax,(ggabamax)^4)
}
//background
for j=0,randElist.count()-1{ //E connections
randElist.object(j).gampamax=rsyndist.lognormal(randAMPAmax,(randAMPAmax)^4)
randElist.object(j).gnmdamax=rsyndist.lognormal(randNMDAmax,(randNMDAmax)^4)
}
for j=0,randIlist.count()-1{ //I connections
randIlist.object(j).gmax=rsyndist.lognormal(randGABAmax,(randGABAmax)^4)
}
}
init_active()
loclocation()
forall{
Ra=100//***//
}
