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Th.hoc
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// Full thalamus
objref ncNRTNRT, ncNRTminisGABAaout, gapList_Th
objref nc_TCFO_NRTHO, nc_NRTHO_TCFO, nc_NRTHO_TCFO_minisGABAaout
objref nc_TCHO_NRTFO, nc_NRTFO_TCHO, nc_NRTFO_TCHO_minisGABAaout
{ load_file("section.hoc") }
if (isFO || isHO) {
if (isFO) {
createSec("FO")
}
if (isHO) {
createSec("HO")
}
}
proc initParam() {
if (isFO && isHO) {
ratio_TCFO_NRTHO = ratioTCNRT/3
ratio_NRTHO_TCFO = ratioNRTTC/3
ratio_TCHO_NRTFO = ratio_TCFO_NRTHO
ratio_NRTFO_TCHO = ratio_NRTHO_TCFO
ratioNRTNRT = ratioNRTNRT/2
}
}
proc connectSecs() {local i, gid, sgid, nCons localobj amps, cell, gapj, delayVec, weightVec
if (isFO || isHO) {
// Combine NRT lists from different sections:
if (ratioNRTNRT) {
NRTcells = new List()
nodeNRTgids = new Vector()
NRTgids = new Vector()
delNRTNRT = new Vector()
weiNRTNRT = new Vector()
if (isFO) {
for i = 0, cellLists_FO.o(4).count()-1 {
NRTcells.append(cellLists_FO.o(4).o(i))
}
nodeNRTgids = nodeNRTgids.append(nodeGidLists_FO.o(4))
NRTgids = NRTgids.append(gidLists_FO.o(4))
delNRTNRT = delNRTNRT.append(delNRTNRT_FO)
weiNRTNRT = weiNRTNRT.append(weiNRTNRT_FO)
}
if (isHO) {
for i = 0, cellLists_HO.o(4).count()-1 {
NRTcells.append(cellLists_HO.o(4).o(i))
}
nodeNRTgids = nodeNRTgids.append(nodeGidLists_HO.o(4))
NRTgids = NRTgids.append(gidLists_HO.o(4))
delNRTNRT = delNRTNRT.append(delNRTNRT_HO)
weiNRTNRT = weiNRTNRT.append(weiNRTNRT_HO)
}
// Create NRT-NRT GABAa synapses and connect them to the source:
createSyns(NRTcells, nodeNRTgids, "GABAa", P_release_Th, amps, pc)
ncNRTNRT = connectSyns(NRTcells, NRTgids, NRTcells, NRTgids, ratioNRTNRT, "GABAa", delNRTNRT, weiNRTNRT, 0, pc, randomise.x[4], synSpread_Th, P_release_Th, amps, edge)
if (randomise.x[4]) {
weight = 0.06 // 0.06: ~-0.2 mV @-65 mV and Ri = ~160 MOhms
ncNRTminisGABAaout = connectMinis(NRTcells, 0.6, weight, "GABAa")
ncNRTNRT.append(ncNRTminisGABAaout)
}
}
}
if (isFO && isHO) {
// Create TC_FO-NRT_HO GLU synapses and connect them to the source:
nc_TCFO_NRTHO = connect2pops(ratio_TCFO_NRTHO, 1, TCNRTfact, cellLists_FO.o(1), \
gidLists_FO.o(1), cellLists_HO.o(4), gidLists_HO.o(4), synSpread_Th, P_release_Th, amps, edge, "GLU")
// Create NRT_HO-TC_FO GABA synapses and connect them to the source:
nConns = round(ratio_NRTHO_TCFO*gidLists_HO.o(4).size()*gidLists_FO.o(1).size()*synSpread_Th)
delayVec = ranDel(delayNRTTC, nConns, pc, randomise.x[2])
weightVec = ranWei(NRTTCfact, nConns, pc, randomise.x[3])
nc_NRTHO_TCFO = connectSyns(cellLists_HO.o(4), gidLists_HO.o(4), cellLists_FO.o(1), gidLists_FO.o(1), ratio_NRTHO_TCFO, "GABAfull", delayVec, weightVec, 1, pc, randomise.x[4], synSpread_Th, P_release_Th, amps, edge)
if (randomise.x[4]) {
weight = 0.375 // 0.375: ~-0.2 mV @-65 mV, Ri = ~160 MOhms, and GABAarev = -70 mV
nc_NRTHO_TCFO_minisGABAaout = connectMinis(cellLists_FO.o(1), 0.6, weight, "GABAa")
nc_NRTHO_TCFO.append(nc_NRTHO_TCFO_minisGABAaout)
}
// Create TC_HO-NRT_FO GLU synapses and connect them to the source:
nc_TCHO_NRTFO = connect2pops(ratio_TCHO_NRTFO, 1, TCNRTfact, cellLists_HO.o(1), \
gidLists_HO.o(1), cellLists_FO.o(4), gidLists_FO.o(4), synSpread_Th, P_release_Th, amps, edge, "GLU")
// Create NRT_FO-TC_HO GABA synapses and connect them to the source:
delayVec = ranDel(delayNRTTC, nConns, pc, randomise.x[2])
weightVec = ranWei(NRTTCfact, nConns, pc, randomise.x[3])
nc_NRTFO_TCHO = connectSyns(cellLists_FO.o(4), gidLists_FO.o(4), cellLists_HO.o(1), gidLists_HO.o(1), ratio_NRTFO_TCHO, "GABAfull", delayVec, weightVec, 1, pc, randomise.x[4], synSpread_Th, P_release_Th, amps, edge)
if (randomise.x[4]) {
weight = 0.375 // 0.375: ~-0.2 mV @-65 mV, Ri = ~160 MOhms, and GABAarev = -70 mV
nc_NRTFO_TCHO_minisGABAaout = connectMinis(cellLists_HO.o(1), 0.6, weight, "GABAa")
nc_NRTFO_TCHO.append(nc_NRTFO_TCHO_minisGABAaout)
}
}
// Create gap junctions:
if (gaps && isFO && isHO) {
gapList_Th = new List()
for i = 0,1 {
if (i) { gid = gidLists_HO.o(4).min()
} else { gid = gidLists_FO.o(4).max() }
sgid = gidLists_FO.o(4).size() - i
if (pc.gid_exists(gid)) {
cell = pc.gid2cell(gid)
cell.soma {
gapj = new HalfGap(.5)
gapj.r = gapr
gapList_Th.append(gapj)
cell.appendGapList(gapj)
pc.target_var(gapj, &gapj.vgap, sgid)
}
}
}
for i = 0,1 {
if (i) { gid = gidLists_HO.o(4).min()+1
} else { gid = gidLists_FO.o(4).max()-1 }
sgid = gidLists_FO.o(4).size() +1 - i*2
if (pc.gid_exists(gid)) {
cell = pc.gid2cell(gid)
cell.soma {
gapj = new HalfGap(.5)
//gapj.r = 2*gapr
gapj.r = gapr
gapList_Th.append(gapj)
cell.appendGapList(gapj)
pc.target_var(gapj, &gapj.vgap, sgid)
}
}
}
varDt_local = 0
}
}
proc adjMinis() {
if (isFO && isHO) {
// TC:
converge_TC = gidLists_HO.o(4).size()*(ratioNRTTC+ratio_NRTHO_TCFO)*synSpread_Th*P_release_Th
adjLayerMinis(cellLists_FO.o(1), converge_TC)
adjLayerMinis(cellLists_HO.o(1), converge_TC)
// NRT:
converge_NRT = converge_NRT + gidLists_FO.o(1).size()*ratio_TCFO_NRTHO*synSpread_Th*P_release_Th
adjLayerMinis(cellLists_FO.o(4), converge_NRT)
adjLayerMinis(cellLists_HO.o(4), converge_NRT)
}
}
initParam()
connectSecs()
if (randomise.x[4]) {
adjMinis()
}