// Background inputs to the 2D OB network
Tb_Start = 0 // Start time of background inputs
Tb_ISI = 10 // spike interval in background input
N_SPIKE = 1000 // number of spike in background input
Thresh = 0
Wb_MC = 1.0e3 // Synaptic weight of background inputs to MCs
Wb_PG = 0.5e3 // Synaptic weight of background inputs to PGs
Wb_GC = 0.3e3 // Synaptic weight of background inputs to GCs
objref MCbinput[nmitx][nmity], PGbinput[npgx][npgy], GCbinput[ngranx][ngrany]
objref MCb[nmitx][nmity], PGb[npgx][npgy], GCb[ngranx][ngrany]
objref RSP[nmitx][nmity]
//==============================================================================
// Spiketrigered random background inputs
//==============================================================================
// For MCs
for i = 0, nmitx1 {
for j = 0, nmity1 {
RSP[i][j] = new Vector()
MCb[i][j] = new NetStim(.5)
MCb[i][j].number = N_SPIKE
MCb[i][j].start = Tb_Start
MCb[i][j].interval = Tb_ISI
MCb[i][j].noise = 1
MCb[i][j].seed(NSSEED)
MCbinput[i][j] = new NetCon(MCb[i][j], mit[i][j].AMPA)
MCbinput[i][j].threshold = Thresh
MCbinput[i][j].delay = 0
MCbinput[i][j].weight = Wb_MC
MCbinput[i][j].record(RSP[i][j])
}
}
// For PGs
for i = 0, npgx1 {
for j = 0, npgy1 {
PGb[i][j] = new NetStim(.5)
PGb[i][j].number = N_SPIKE
PGb[i][j].start = Tb_Start
PGb[i][j].interval = Tb_ISI
PGb[i][j].noise = 1
PGb[i][j].seed(NSSEED)
PGbinput[i][j] = new NetCon(PGb[i][j], pg[i][j].AMPAr)
PGbinput[i][j].threshold = Thresh
PGbinput[i][j].delay = 0
PGbinput[i][j].weight = Wb_PG
}
}
// For GCs
for i = 0, ngranx1 {
for j = 0, ngrany1 {
GCb[i][j] = new NetStim(.5)
GCb[i][j].number = N_SPIKE
GCb[i][j].start = Tb_Start
GCb[i][j].interval = Tb_ISI
GCb[i][j].noise = 1
GCb[i][j].seed(NSSEED)
GCbinput[i][j] = new NetCon(GCb[i][j], gran[i][j].AMPAr)
GCbinput[i][j].threshold = Thresh
GCbinput[i][j].delay = 0
GCbinput[i][j].weight = Wb_GC
}
}
