// run simulation without inhibition
activateInhibition(cellList,-1,1) // clear inhibition
for(jj=1; jj<simul_iter+1; jj=jj+1){
print jj
// Clear excitation and then turn on select synapses.
activateExcitation(cellList,-1,1) // clear excitation
curExc_SR = activateExcitation(radiatumList,jj*nExcAct_SR,randShift) // activate excitatory synapses
curExc_SLM = activateExcitation(tuftList,jj*nExcAct_SLM,randShift) // activate excitatory synapses
shape_no=(jj/2)-1
if (jj%2==1){shape_no=(jj-1)/2}
ActSyn = set_gluSyn(curExc_SR, randShift, 0.1, norm_Pr_exc, shapeExc[shape_no])
print "In SR, the number of activated synapses at each pulse are: ",ActSyn.x[0], ", " , ActSyn.x[1], ", " , ActSyn.x[2], ", " , ActSyn.x[3], ", " , ActSyn.x[4]
ActSyn = set_gluSyn(curExc_SLM, randShift/2, 0.1, norm_Pr_exc, shapeExc[shape_no])
print "In SLM, the number of activated synapses at each pulse are: ",ActSyn.x[0], ", " , ActSyn.x[1], ", " , ActSyn.x[2], ", " , ActSyn.x[3], ", " , ActSyn.x[4]
if (jj%2==1){curGr = graphList[0].append(voltBL) }
init()
run()
if (jj%2==1){graphList[0].remove(curGr-1)}
storeM_noInh.setcol(jj-1,recv_soma)
storeM_noInh.setcol(jj-1+simul_iter,recv_tuft1)
storeM_noInh.setcol(jj-1+2*simul_iter,recv_tuft2)
storeM_noInh.setcol(jj-1+3*simul_iter,recv_tuft3)
storeM_noInh.setcol(jj-1+4*simul_iter,recv_obl1)
storeM_noInh.setcol(jj-1+5*simul_iter,recv_obl2)
storeM_noInh.setcol(jj-1+6*simul_iter,recv_obl3)
// Wash-in AP5, block NMDA conductance
reset_NMDASyn()
if (jj%2==1){curGr =graphList[0].append(voltAMPA)}
init()
run()
if (jj%2==1){graphList[0].remove(curGr-1)}
storeM_noInh.setcol(jj-1+7*simul_iter,recv_soma)
storeM_noInh.setcol(jj-1+8*simul_iter,recv_tuft1)
storeM_noInh.setcol(jj-1+9*simul_iter,recv_tuft2)
storeM_noInh.setcol(jj-1+10*simul_iter,recv_tuft3)
storeM_noInh.setcol(jj-1+11*simul_iter,recv_obl1)
storeM_noInh.setcol(jj-1+12*simul_iter,recv_obl2)
storeM_noInh.setcol(jj-1+13*simul_iter,recv_obl3)
reset_AMPASyn()
}
// SAVE OUTPUT
//print2file(storeM_noInh,file_name1,ColLabel)