/*
Copyright (c) 2015 EPFL-BBP, All rights reserved.
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*/
/*
* @file init.hoc
* @brief Initialisation
* @author Werner Van Geit @ BBP
* @date 2015
*/
//modified by Fabio Simoes de Souza @ UFABC, 2016
//----------------------------------------------------------------------------
// define a panel to run the different demos
//----------------------------------------------------------------------------
load_file("nrngui.hoc")
load_file("constants.hoc")
load_file("creategui.hoc")
load_file("createsimulation.hoc")
// By default, enable synapses
synapses_enabled = 1
use_mcell_ran4(1) //MCell random number generator
// Set up simulation
create_cell(synapses_enabled,RANDOM_SEED,NUMBER_NEURONS) //create cells (100 pre_synaptic and 100 post_synaptic cells)
//Move cell location
XORIGIN0 = 0
YORIGIN0 = 0
ZORIGIN0 = 0
XORIGIN1 = 0
YORIGIN1 = -3000
ZORIGIN1 = 0
for i=0, NUMBER_NEURONS-1 {
//Move cell location
cell0[i].position(XORIGIN0+1000*i,YORIGIN0,ZORIGIN0)
cell1[i].position(XORIGIN1+1000*i,YORIGIN1,ZORIGIN1)
}
// Start the GUI
make_mainwindow(cell1[0])
//Create Current Stimulus to Presynaptic neurons
create_current_stimulus(NUMBER_NEURONS)
// Save the windows that already exist before this initialisation
pwmcnt = PWManager[0].count
//Create synapses
objectvar sinapse0[1] //[NUMBER_NEURONS] //STDP1
objectvar sinapse1[1] //[NUMBER_NEURONS] //STDP2
objectvar sinapse2[1] //[NUMBER_NEURONS] //ExpSyn
//parameters
fator= 10
CONNECTION_THRESHOLD=0
CONNECTION_DELAY=6.7 // ms
CONNECTION_WEIGHT=fator*5e-6 // max conductance uS
for i=0, NUMBER_NEURONS-1 {
access cell1[i].apic(0.5)
cell1[i].sinapse0[0]=new ExpSynSTDP_triplet(0)
cell1[i].sinapse0[0].e=0
cell1[i].sinapse0[0].tau=10
cell1[i].sinapse0[0].factor=1e3//potentiation depotentiation factor
cell1[i].sinapse0[0].gw=fator*5e-6 //uS max conductance
cell1[i].sinapse1[0]=new ExpSynSTDP_triplet(0)
cell1[i].sinapse1[0].e=0
cell1[i].sinapse1[0].tau=10
cell1[i].sinapse1[0].factor=1e3//potentiation depotentiation factor
cell1[i].sinapse1[0].gw=fator*5e-6 //uS max conductance
cell1[i].sinapse2[0]=new ExpSyn(0.5)
cell1[i].sinapse2[0].tau=10
cell1[i].sinapse2[0].e=0
//STDP parameters (Pfister)
cell1[i].sinapse0[0].A2mais=4.6e-3 /1
cell1[i].sinapse0[0].A2menos=3e-3 /1
cell1[i].sinapse0[0].A3mais=9.1e-3 /1
cell1[i].sinapse0[0].A3menos=7.5e-9 /1
cell1[i].sinapse0[0].Taumais=16.8
cell1[i].sinapse0[0].Taumenos= 33.7
cell1[i].sinapse0[0].Tauy=47
cell1[i].sinapse0[0].Taux=575
//STDP parameters (Abbott)
cell1[i].sinapse1[0].A2mais=5e-3 /1
cell1[i].sinapse1[0].A2menos=5.1e-3 /1
cell1[i].sinapse1[0].A3mais=2e-4 /1
cell1[i].sinapse1[0].A3menos=1e-3 /1
cell1[i].sinapse1[0].Taumais=16.8
cell1[i].sinapse1[0].Taumenos= 33.7
cell1[i].sinapse1[0].Tauy=47
cell1[i].sinapse1[0].Taux=575
//synaptic connections
access cell0[i].soma
cell0[i].soma cell1[i].nclist.append(new NetCon(&cell0[i].soma.v(0.5),cell1[i].sinapse0[0],CONNECTION_THRESHOLD,CONNECTION_DELAY,CONNECTION_WEIGHT))
cell0[i].soma cell1[i].nclist.append(new NetCon(&cell0[i].soma.v(0.5),cell1[i].sinapse1[0],CONNECTION_THRESHOLD,CONNECTION_DELAY,CONNECTION_WEIGHT))
}
//Show results
objref grafico[7]
grafico[0]=new Graph()
grafico[0].size(0,tmax ,-100,50)
grafico[0].beginline()
grafico[0].addvar("Pre",&cell0[0].soma.v(0.5),1,1)
grafico[0].addvar("Post",&cell1[0].soma.v(0.5),3,1)
grafico[0].flush()
graphList[0].append(grafico[0])
objref graficoshape
graficoshape=new PlotShape()
graficoshape.variable("soma","v(0.5)")
//graficoshape.view(-594.956, -98.0373, 1260.25, 1188.42, 573, 0, 505.92, 592)
graficoshape.exec_menu("Show Diam")
graficoshape.exec_menu("Shape Plot")
fast_flush_list.append(graficoshape)
//Synapse control menu
nrncontrolmenu()
//setting up to save data to file
create_recording(NUMBER_NEURONS)
//Start Simulation
//simulate()
cvode.active(0)
init()
//Synaptic Stimulation Sequencies
create_synaptic_stimulus(condi, tmax)
///////////////////////
//Save Data to Files//
//////////////////////
save_recording()
/*
/** Procedure linked to the Init & Run button */
proc restart() {
cleanup()
// make_plottingpanel()
create_stimulus(stepcurrent)
cell.synapses.update_synapses(synapse_plot)
simulate()
save_recording()
}