/*
Copyright (c) 2015 EPFL-BBP, All rights reserved.
THIS SOFTWARE IS PROVIDED BY THE BLUE BRAIN PROJECT ``AS IS''
AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO,
THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE BLUE BRAIN PROJECT
BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR
BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY,
WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE
OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN
IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-sa/4.0/legalcode or send a letter to Creative Commons, 171
Second Street, Suite 300, San Francisco, California, 94105, USA.
*/
/*
* @file createsimulation.hoc
* @brief Set up the simulation
* @author Werner Van Geit @ BBP
* @date 2015
*/
//modified by Fabio Simoes de Souza @ UFABC, 2016
load_file("nrngui.hoc")
load_file("import3d.hoc")
load_file("morphology.hoc")
load_file("biophysics.hoc")
load_file("template.hoc")
//======================== settings ===================================
//PARAMETERS
NUMBER_NEURONS=1 //number neurons per layer
tmax=25000 //simulation time
//Synaptic Stimulation Sequencies
//sensory, motor, or re-afference sequencies
//cond="1" //basal only -control-
//cond="2a" //sensory only 1 pulse
//cond="3a" //motor only 1 pulse
//cond="4a" //motor with sensory re-afference 1 pulse
//cond="2b" //sensory only 4 pulses
//cond="3b" //motor only 4 pulses
//cond="4b" //motor with sensory re-afference 4 pulses
strdef condi //string
condi="4b"
//set poisson random seeds for presynaptic spikes
if (strcmp(condi,"1") == 0) {
RANDOM_SEED=1
print RANDOM_SEED
} else if (strcmp(condi,"2a") == 0) {
RANDOM_SEED=2
print RANDOM_SEED
} else if (strcmp(condi,"3a") == 0) {
RANDOM_SEED=3
print RANDOM_SEED
} else if (strcmp(condi,"4a") == 0) {
RANDOM_SEED=4
print RANDOM_SEED
} else if (strcmp(condi,"2b") == 0) {
RANDOM_SEED=5
print RANDOM_SEED
} else if (strcmp(condi,"3b") == 0) {
RANDOM_SEED=6
print RANDOM_SEED
} else if (strcmp(condi,"4b") == 0) {
RANDOM_SEED=7
print RANDOM_SEED
}
//=================== creating cell object ===========================
objref semente
objref cell0[NUMBER_NEURONS] //pre synaptic cells
objref cell1[NUMBER_NEURONS] //post synaptic cells
proc create_cell() { local synapses_enabled
synapses_enabled = $1
semente = new Random($2)
semente.uniform(0,1000000000)
NUMBER_NEURONS = $3
for i=0, NUMBER_NEURONS-1 {
//print i
semente_pick=int(semente.repick())
cell0[i] = new cADpyr232_L5_TTPC1_b6836fcf6f(synapses_enabled,semente_pick)
semente_pick=int(semente.repick())
cell1[i] = new cADpyr232_L5_TTPC1_b6836fcf6f(synapses_enabled,semente_pick)
}
}
////////////////////////////////////////
//Setting up for Saving Spiking Events//
///////////////////////////////////////
//==================== recording settings ==========================
objref Cell0MatrixS, Cell1MatrixS
objref Cell0MatrixV, Cell1MatrixV
objref Cell1Matrixgsyn0, Cell1Matrixgsyn1
objref Cell1Matrixpsyn0, Cell1Matrixpsyn1
objref sav_Cell0MatrixS,sav_Cell1MatrixS
objref sav_Cell0MatrixV,sav_Cell1MatrixV
objref sav_Cell1Matrixgsyn0,sav_Cell1Matrixgsyn1
objref sav_Cell1Matrixpsyn0,sav_Cell1Matrixpsyn1
objref time
objref nc0, nil0, nc1, nil1
proc create_recording() {
NUMBER_NEURONS=$1
//generate matrix and send the data to them
Cell0MatrixS=new Matrix()
Cell1MatrixS=new Matrix()
Cell0MatrixV=new Matrix()
Cell1MatrixV=new Matrix()
Cell1Matrixgsyn0=new Matrix()
Cell1Matrixgsyn1=new Matrix()
Cell1Matrixpsyn0=new Matrix()
Cell1Matrixpsyn1=new Matrix()
sav_Cell0MatrixS=new File()
sav_Cell1MatrixS=new File()
sav_Cell0MatrixV=new File()
sav_Cell1MatrixV=new File()
sav_Cell1Matrixgsyn0=new File()
sav_Cell1Matrixgsyn1=new File()
sav_Cell1Matrixpsyn0=new File()
sav_Cell1Matrixpsyn1=new File()
//Open recording Files
sav_Cell0MatrixS.wopen("hoc_recordings/Cell0MatrixS.dat")
sav_Cell1MatrixS.wopen("hoc_recordings/Cell1MatrixS.dat")
sav_Cell0MatrixV.wopen("hoc_recordings/Cell0MatrixV.dat")
sav_Cell1MatrixV.wopen("hoc_recordings/Cell1MatrixV.dat")
sav_Cell1Matrixgsyn0.wopen("hoc_recordings/Cell1Matrixgsyn0.dat")
sav_Cell1Matrixgsyn1.wopen("hoc_recordings/Cell1Matrixgsyn1.dat")
sav_Cell1Matrixpsyn0.wopen("hoc_recordings/Cell1Matrixpsyn0.dat")
sav_Cell1Matrixpsyn1.wopen("hoc_recordings/Cell1Matrixpsyn1.dat")
time = new Vector()
time.record(&t, dt)
for i=0, NUMBER_NEURONS-1 {
//set voltage recording
cell0[i].voltagem.record(&cell0[i].soma.v(0.5),dt)
cell1[i].voltagem.record(&cell1[i].soma.v(0.5),dt)
//set gsyn recording
cell1[i].gsyn0.record(&cell1[i].sinapse0[0].g,dt)
cell1[i].gsyn1.record(&cell1[i].sinapse1[0].g,dt)
//set psyn recording
cell1[i].psyn0.record(&cell1[i].sinapse0[0].peso,dt)
cell1[i].psyn1.record(&cell1[i].sinapse1[0].peso,dt)
//Fabio´s stuff
//saving spiketimes
cell0[i].soma cell0[i].nc = new NetCon(&cell0[i].soma.v(0.5),nil0)
cell1[i].soma cell1[i].nc = new NetCon(&cell1[i].soma.v(0.5),nil1)
cell0[i].nc.record(cell0[i].spiketimes)
cell1[i].nc.record(cell1[i].spiketimes)
}
}
//==================== stimulus settings ===========================
//current stimulus
objref step_stimulus[NUMBER_NEURONS]
proc create_current_stimulus() {
NUMBER_NEURONS = $1
for i=0, NUMBER_NEURONS-1 {
access cell0[i].soma
step_stimulus[i] = new IClamp(0.5)
step_stimulus[i].dur = 1000
step_stimulus[i].del = 11000+1e4
step_stimulus[i].amp = 0.5 //nA
}
}
//synaptic stimulus
proc create_synaptic_stimulus() {
//sensory, motor, or re-afference sequencies
//cond="1" //basal only -control-
//cond="2a" //sensory only 1 pulse
//cond="3a" //motor only 1 pulse
//cond="4a" //motor with sensory re-afference 1 pulse
//cond="2b" //sensory only 4 pulses
//cond="3b" //motor only 4 pulses
//cond="4b" //motor with sensory re-afference 4 pulses
strdef cond //string
cond = $s1
tmax=$2
//synapses index
id1=19 //L5_TTP1
id2=20 //L5_TTPC2
id3=3 //L23_PC
freq=2 //basal pre-synaptic firing freq
tstop=1 //1 ms
run()
print tstop
if (strcmp(cond,"1") == 0) {
print RANDOM_SEED
cell0_synapse_on_off(id2,freq,1,NUMBER_NEURONS) // basal sensory stimulus on
cell1_synapse_on_off(id2,freq,1,NUMBER_NEURONS) // basal motor stimulus on
tstop=10000
print tstop
continuerun(tstop)//t=10000
cell0_synapse_on_off(id1,50,0,NUMBER_NEURONS) // test stimulus on
tstop=11000
continuerun(tstop) //t=11000
cell0_synapse_on_off(id1,50,0,NUMBER_NEURONS) // test stimulus off
tstop=tmax //run till tmax
continuerun(tstop)
} else if (strcmp(cond,"2a") == 0) {
print RANDOM_SEED
cell0_synapse_on_off(id2,freq,1,NUMBER_NEURONS) // basal sensory stimulus on
cell1_synapse_on_off(id2,freq,1,NUMBER_NEURONS) // basal motor stimulus on
tstop=1000
continuerun(tstop) //t=1000
cell0_synapse_on_off(id1,50,1,NUMBER_NEURONS) // sensory stimulus on
tstop=2000 //run till tstop ms
continuerun(tstop) //t=2000
cell0_synapse_on_off(id1,50,0,NUMBER_NEURONS) // sensory stimulus off
tstop=10000
continuerun(tstop) //t=10000 ms
cell0_synapse_on_off(id1,50,0,NUMBER_NEURONS) // test stimulus on
tstop=11000
continuerun(tstop)//t=11000
cell0_synapse_on_off(id1,50,0,NUMBER_NEURONS) // test stimulus off
tstop=tmax //run till tmax
continuerun(tstop)
} else if (strcmp(cond,"3a") == 0) {
print RANDOM_SEED
cell0_synapse_on_off(id2,freq,1,NUMBER_NEURONS) // basal sensory stimulus on
cell1_synapse_on_off(id2,freq,1,NUMBER_NEURONS) // basal motor stimulus on
tstop=1000
continuerun(tstop) //t=1000
cell1_synapse_on_off(id2,50,1,NUMBER_NEURONS) // motor stimulus on
tstop=2000 //run till tstop ms
continuerun(tstop) //t=2000
cell1_synapse_on_off(id2,freq,1,NUMBER_NEURONS) // motor stimulus off
tstop=10000
continuerun(tstop) //t=10000 ms
cell0_synapse_on_off(id1,50,0,NUMBER_NEURONS) // test stimulus on
tstop=11000
continuerun(tstop)//t=11000
cell0_synapse_on_off(id1,50,0,NUMBER_NEURONS) // test stimulus off
tstop=tmax //run till tmax
continuerun(tstop)
} else if (strcmp(cond,"4a") == 0) {
print RANDOM_SEED
cell0_synapse_on_off(id2,freq,1,NUMBER_NEURONS) // basal sensory stimulus on
cell1_synapse_on_off(id2,freq,1,NUMBER_NEURONS) // basal motor stimulus on
tstop=1000
continuerun(tstop) //t=1000
cell1_synapse_on_off(id2,50,1,NUMBER_NEURONS) // motor stimulus on
tstop=1200
continuerun(tstop) //t=1200
cell0_synapse_on_off(id1,50,1,NUMBER_NEURONS) // re-affer sensory stimulus on
tstop=2000
continuerun(tstop) //t=2000
cell1_synapse_on_off(id2,freq,1,NUMBER_NEURONS) // motor stimulus off
tstop=2200
continuerun(tstop) //t=2200
cell0_synapse_on_off(id1,50,0,NUMBER_NEURONS) // re-affer sensory stimulus off
tstop=10000 //pause between stimulus
continuerun(tstop)
cell0_synapse_on_off(id1,50,0,NUMBER_NEURONS) // test stimulus on
tstop=11000
continuerun(tstop) //t=11000
cell0_synapse_on_off(id1,50,0,NUMBER_NEURONS) // test stimulus off
tstop=tmax //run till tmax
continuerun(tstop)
} else if (strcmp(cond,"2b") == 0) {
print RANDOM_SEED
cell0_synapse_on_off(id2,freq,1,NUMBER_NEURONS) // basal sensory stimulus on
cell1_synapse_on_off(id2,freq,1,NUMBER_NEURONS) // basal motor stimulus on
tstop=1000
continuerun(tstop) //t=1000
cell0_synapse_on_off(id1,50,1,NUMBER_NEURONS) // sensory stimulus on 1
tstop=2000 //run till tstop ms
continuerun(tstop) //t=2000
cell0_synapse_on_off(id1,50,0,NUMBER_NEURONS) // sensory stimulus off
tstop=3000
continuerun(tstop) //t=10000 ms
cell0_synapse_on_off(id1,50,1,NUMBER_NEURONS) // sensory stimulus on 2
tstop=4000 //run till tstop ms
continuerun(tstop) //t=2000
cell0_synapse_on_off(id1,50,0,NUMBER_NEURONS) // sensory stimulus off
tstop=5000
continuerun(tstop) //t=10000 ms
cell0_synapse_on_off(id1,50,1,NUMBER_NEURONS) // sensory stimulus on 3
tstop=6000 //run till tstop ms
continuerun(tstop) //t=2000
cell0_synapse_on_off(id1,50,0,NUMBER_NEURONS) // sensory stimulus off
tstop=7000
continuerun(tstop) //t=10000 ms
cell0_synapse_on_off(id1,50,1,NUMBER_NEURONS) // sensory stimulus on 4
tstop=8000 //run till tstop ms
continuerun(tstop) //t=2000
cell0_synapse_on_off(id1,50,0,NUMBER_NEURONS) // sensory stimulus off
tstop=9000
continuerun(tstop) //t=10000 ms
cell0_synapse_on_off(id1,50,0,NUMBER_NEURONS) // sensory stimulus off
tstop=10000
continuerun(tstop) //t=10000 ms
cell0_synapse_on_off(id1,50,0,NUMBER_NEURONS) // test stimulus on
tstop=11000
continuerun(tstop)//t=11000
cell0_synapse_on_off(id1,50,0,NUMBER_NEURONS) // test stimulus off
tstop=tmax //run till tmax
continuerun(tstop)
} else if (strcmp(cond,"3b") == 0) {
print RANDOM_SEED
cell0_synapse_on_off(id2,freq,1,NUMBER_NEURONS) // basal sensory stimulus on
cell1_synapse_on_off(id2,freq,1,NUMBER_NEURONS) // basal motor stimulus on
tstop=1000
continuerun(tstop) //t=1000
cell1_synapse_on_off(id2,50,1,NUMBER_NEURONS) // motor stimulus on 1
tstop=2000 //run till tstop ms
continuerun(tstop) //t=2000
cell1_synapse_on_off(id2,freq,1,NUMBER_NEURONS) // motor stimulus off
tstop=3000
continuerun(tstop) //t=10000 ms
cell1_synapse_on_off(id2,50,1,NUMBER_NEURONS) // motor stimulus on 2
tstop=4000 //run till tstop ms
continuerun(tstop) //t=2000
cell1_synapse_on_off(id2,freq,1,NUMBER_NEURONS) // motor stimulus off
tstop=5000
continuerun(tstop) //t=10000 ms
cell1_synapse_on_off(id2,50,1,NUMBER_NEURONS) // motor stimulus on 3
tstop=6000 //run till tstop ms
continuerun(tstop) //t=2000
cell1_synapse_on_off(id2,freq,1,NUMBER_NEURONS) // motor stimulus off
tstop=7000
continuerun(tstop) //t=10000 ms
cell1_synapse_on_off(id2,50,1,NUMBER_NEURONS) // motor stimulus on 4
tstop=8000 //run till tstop ms
continuerun(tstop) //t=2000
cell1_synapse_on_off(id2,freq,1,NUMBER_NEURONS) // motor stimulus off
tstop=9000
continuerun(tstop) //t=10000 ms
cell1_synapse_on_off(id2,freq,1,NUMBER_NEURONS) // motor stimulus off
tstop=10000
continuerun(tstop) //t=10000 ms
cell0_synapse_on_off(id1,50,0,NUMBER_NEURONS) // test stimulus on
tstop=11000
continuerun(tstop)//t=11000
cell0_synapse_on_off(id1,50,0,NUMBER_NEURONS) // test stimulus off
tstop=tmax //run till tmax
continuerun(tstop)
} else (strcmp(cond,"4b") == 0) {
print RANDOM_SEED
cell0_synapse_on_off(id2,freq,1,NUMBER_NEURONS) // basal sensory stimulus on
cell1_synapse_on_off(id2,freq,1,NUMBER_NEURONS) // basal motor stimulus on
tstop=1000+1e4
continuerun(tstop) //t=1000
cell1_synapse_on_off(id2,50,1,NUMBER_NEURONS) // motor stimulus on 1
tstop=1200+1e4
continuerun(tstop) //t=1200
cell0_synapse_on_off(id1,50,1,NUMBER_NEURONS) // re-affer sensory stimulus on
tstop=2000+1e4
continuerun(tstop) //t=2000
cell1_synapse_on_off(id2,freq,1,NUMBER_NEURONS) // motor stimulus off
tstop=2200+1e4
continuerun(tstop) //t=2200
cell0_synapse_on_off(id1,50,0,NUMBER_NEURONS) // re-affer sensory stimulus off
tstop=3000+1e4 //pause between stimulus
continuerun(tstop)
cell1_synapse_on_off(id2,50,1,NUMBER_NEURONS) // motor stimulus on 2
tstop=3200+1e4
continuerun(tstop) //t=1200
cell0_synapse_on_off(id1,50,1,NUMBER_NEURONS) // re-affer sensory stimulus on
tstop=4000+1e4
continuerun(tstop) //t=2000
cell1_synapse_on_off(id2,freq,1,NUMBER_NEURONS) // motor stimulus off
tstop=4200+1e4
continuerun(tstop) //t=2200
cell0_synapse_on_off(id1,50,0,NUMBER_NEURONS) // re-affer sensory stimulus off
tstop=5000+1e4 //pause between stimulus
continuerun(tstop)
cell1_synapse_on_off(id2,50,1,NUMBER_NEURONS) // motor stimulus on 3
tstop=5200+1e4
continuerun(tstop) //t=1200
cell0_synapse_on_off(id1,50,1,NUMBER_NEURONS) // re-affer sensory stimulus on
tstop=6000+1e4
continuerun(tstop) //t=2000
cell1_synapse_on_off(id2,freq,1,NUMBER_NEURONS) // motor stimulus off
tstop=6200+1e4
continuerun(tstop) //t=2200
cell0_synapse_on_off(id1,50,0,NUMBER_NEURONS) // re-affer sensory stimulus off
tstop=7000+1e4 //pause between stimulus
continuerun(tstop)
cell1_synapse_on_off(id2,50,1,NUMBER_NEURONS) // motor stimulus on 4
tstop=7200+1e4
continuerun(tstop) //t=1200
cell0_synapse_on_off(id1,50,1,NUMBER_NEURONS) // re-affer sensory stimulus on
tstop=8000+1e4
continuerun(tstop) //t=2000
cell1_synapse_on_off(id2,freq,1,NUMBER_NEURONS) // motor stimulus off
tstop=8200+1e4
continuerun(tstop) //t=2200
cell0_synapse_on_off(id1,50,0,NUMBER_NEURONS) // re-affer sensory stimulus off
tstop=9000+1e4 //pause between stimulus
continuerun(tstop)
cell0_synapse_on_off(id1,50,0,NUMBER_NEURONS) // re-affer sensory stimulus off
tstop=10000+1e4 //pause between stimulus
continuerun(tstop)
cell0_synapse_on_off(id1,50,0,NUMBER_NEURONS) // test stimulus on
tstop=11000+1e4
continuerun(tstop) //t=11000
cell0_synapse_on_off(id1,50,0,NUMBER_NEURONS) // test stimulus off
tstop=tmax //run till tmax
continuerun(tstop)
}
}
//turn synapses on-off
//id, freq, 0 (on) or 1(off)
proc cell0_synapse_on_off() {local id
NUMBER_NEURONS=$4
for i=0, NUMBER_NEURONS-1 {
id=cell0[i].synapses.pre_mtypes.x[$1]
cell0[i].synapses.active_pre_mtypes.x[id]=$3
cell0[i].synapses.pre_mtype_freqs.x[id]=$2
cell0[i].synapses.update_synapses(synapse_plot)
}
}
//id, freq, 0 (on) or 1(off)
proc cell1_synapse_on_off() {local id
NUMBER_NEURONS=$4
for i=0, NUMBER_NEURONS-1 {
id=cell1[i].synapses.pre_mtypes.x[$1]
cell1[i].synapses.active_pre_mtypes.x[id]=$3
cell1[i].synapses.pre_mtype_freqs.x[id]=$2
cell1[i].synapses.update_synapses(synapse_plot)
}
}
//============================= simulation ================================
proc simulate() {
cvode.active(0)
run()
}
//============================= saving results ============================
objref tempo
objref savtime
proc save_recording() {
///////////////////////
//Save Data to Files//
//////////////////////
//save time
savtime=new File()
savtime.wopen("hoc_recordings/time.dat")
time.printf(savtime)
savtime.close()
//save spikes and voltage
Cell0MatrixS.resize(time.size(),NUMBER_NEURONS)
Cell1MatrixS.resize(time.size(),NUMBER_NEURONS)
Cell0MatrixV.resize(time.size(),NUMBER_NEURONS)
Cell1MatrixV.resize(time.size(),NUMBER_NEURONS)
for i = 0, NUMBER_NEURONS-1 {
Cell0MatrixS.setcol(i,cell0[i].spiketimes)
Cell1MatrixS.setcol(i,cell1[i].spiketimes)
Cell0MatrixV.setcol(i,cell0[i].voltagem)
Cell1MatrixV.setcol(i,cell1[i].voltagem)
}
//record Vectors to File
Cell0MatrixS.fprint(sav_Cell0MatrixS," %g")
Cell1MatrixS.fprint(sav_Cell1MatrixS," %g")
Cell0MatrixV.fprint(sav_Cell0MatrixV," %g")
Cell1MatrixV.fprint(sav_Cell1MatrixV," %g")
//Close Files
sav_Cell0MatrixS.close()
sav_Cell1MatrixS.close()
sav_Cell0MatrixV.close()
sav_Cell1MatrixV.close()
//save synaptic conductances and weights
Cell1Matrixgsyn0.resize(time.size(),NUMBER_NEURONS)
Cell1Matrixgsyn1.resize(time.size(),NUMBER_NEURONS)
Cell1Matrixpsyn0.resize(time.size(),NUMBER_NEURONS)
Cell1Matrixpsyn1.resize(time.size(),NUMBER_NEURONS)
for i = 0, NUMBER_NEURONS-1 {
Cell1Matrixgsyn0.setcol(i,cell1[i].gsyn0)
Cell1Matrixgsyn1.setcol(i,cell1[i].gsyn1)
Cell1Matrixpsyn0.setcol(i,cell1[i].psyn0)
Cell1Matrixpsyn1.setcol(i,cell1[i].psyn1)
}
//record Vectors to File
Cell1Matrixgsyn0.fprint(sav_Cell1Matrixgsyn0," %g")
Cell1Matrixgsyn1.fprint(sav_Cell1Matrixgsyn1," %g")
Cell1Matrixpsyn0.fprint(sav_Cell1Matrixpsyn0," %g")
Cell1Matrixpsyn1.fprint(sav_Cell1Matrixpsyn1," %g")
//Close Files
sav_Cell1Matrixgsyn0.close()
sav_Cell1Matrixgsyn1.close()
sav_Cell1Matrixpsyn0.close()
sav_Cell1Matrixpsyn1.close()
}
