Mitral cell activity gating by respiration and inhibition in an olfactory bulb NN (Short et al 2016)

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Accession:183300
To explore interactions between respiration, inhibition, and olfaction, experiments using light to active channel rhodopsin in sensory neurons expressing Olfactory Marker Protein were performed in mice and modeled in silico. This archive contains NEURON models that were run on parallel computers to explore the interactions between varying strengths of respiratory activity and olfactory sensory neuron input and the roles of periglomerular, granule, and external tufted cells in shaping mitral cell responses.
Reference:
1 . Short SM, Morse TM, McTavish TS, Shepherd GM, Verhagen JV (2016) Respiration Gates Sensory Input Responses in the Mitral Cell Layer of the Olfactory Bulb. PLoS One 11:e0168356 [PubMed]
Citations  Citation Browser
Model Information (Click on a link to find other models with that property)
Model Type: Realistic Network; Neuron or other electrically excitable cell;
Brain Region(s)/Organism: Olfactory bulb;
Cell Type(s): Olfactory bulb main mitral GLU cell; Olfactory bulb main interneuron periglomerular GABA cell; Olfactory bulb main interneuron granule MC GABA cell; Olfactory bulb main tufted cell external;
Channel(s):
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment: NEURON;
Model Concept(s): Activity Patterns; Sensory processing; Sensory coding; Bursting; Oscillations; Olfaction;
Implementer(s): Morse, Tom [Tom.Morse at Yale.edu];
Search NeuronDB for information about:  Olfactory bulb main mitral GLU cell; Olfactory bulb main interneuron periglomerular GABA cell; Olfactory bulb main interneuron granule MC GABA cell;
Files displayed below are from the implementation
/
ShortEtAl2016
early_theta_version
event_generator
import
py
run_0
run_1
run_10
run_11
run_12
run_13
run_14
run_15
run_16
run_17
run_2
run_3
run_4
run_5
run_6
run_7
run_8
run_9
run_test
saved_sim_makers
spike_output
stimulation
synaptic_activity
tdt2mat_data
tmp
VecStim
readme.html
readme.louise
readme.NSG
readme.specialcase.txt
ampanmda.mod *
cadecay.mod *
cadecay2.mod *
Caint.mod *
Can.mod *
CaPN.mod *
CaT.mod *
fi.mod
GradeAMPA.mod *
GradeGABA.mod *
GradNMDA.mod *
hpg.mod *
Ih.mod *
kamt.mod *
KCa.mod *
kdrmt.mod *
kfasttab.mod *
kM.mod *
KS.mod *
kslowtab.mod *
LCa.mod *
nafast.mod *
NaP.mod *
naxn.mod
Nicotin.mod *
nmdanet.mod *
OdorInput.mod *
thetastim.mod *
ThreshDetect.mod *
vecstim.mod *
batch_run_first_NSG.py
batch_runs.py
batch_runs.py20150708
batch_runs.py20150808gc_error
batch_runs_first_NSG.py
build_net.hoc
build_net_Shep.hoc
build_net_Shep_NSG.hoc
build_net_Shep_NSG20160825.hoc
build_net_SMS.hoc
build_net_theta.hoc
build_net20150312.hoc
build_pg_net.hoc
cell_properties_for_ET_from_standalone.txt
cells_volt_graphs.ses
cells_volt_graphs_pg.ses
create_arrays.py
documentation.txt
et.hoc
et_rig.ses
et_rig2.ses
Et_start.zip
granule.hoc *
graph_fncs.hoc
graph_fncs_pg.hoc
gui_stim.hoc
how_to_run_pre_init_on_mac.txt
inhib_study.eps
inhib_study.ps
init.hoc
init.py
make_lookup_table.sh
makelib.err
makelib.out
mct_cells.hoc
mitral.hoc
mosinit.hoc
nrnivmodl.out
num_of_columns.hoc
PG_def.hoc
pre_init.py
pre_init_first_NSG.py
pre_init_no_changes_in_weights.py
roberts_python_help.txt
run_on_serial.hoc
runcntrl.ses
sample_gc1_v_graph.ses
sample_mitral_pg_space_plots.ses
screenshot.png
screenshot0.png
tdt2mat_data.hoc
temporary_file.tmp
test_matplotlib.hoc
                            
// build_net_Shep_NSG.hoc
// builds simple model
// OSN input goes to two mitral cells
// which are connected to two granule cell and periglomerular cells
// Slightly more complicated nets are also generated with duplicated columns

load_file("mct_cells.hoc") // loads the McTavish cell templates Mitral and Granule and new ET
load_file("event_generator/gen_events.hoc")

// The num_of_columns.hoc with relative path run_X, (X=0,1,...,num of sims) set 
//  previously (NSG version sets it in init.py)
// The variable n stores the number of columns other than the first (recordings
// from the mitral cell soma for the tank defines the first) column
// note that num_of_columns.hoc can be generated from other code
xopen(num_of_columns_dot_hoc_file) //"run_X/num_of_columns.hoc") 

// reading in the number of columns is convenient for batch running jobs
// n= 2 // num_of_columns = 1  // number of other columns than m1, n easier to type than num_of_columns

objref m1, m2[n], gc1[n], gc2[n], pg1[n], pg2[n], et1, et2[n]
// gc1's are granule cells that are close to m1 cell body, gc2's are gcs that are far from m1 cell bodies
// likewise for pg1[n] (close to m1: dendrites on m1 tuft, axon on m2[i] primary dend) and 
// pg2[n] (pg2 cell bodies far from m1 cell body: pg2[i] dendrites on m2[i] tuft, axon on m1 primary dend)
// Similarly the et1 cells excitatory connections to the m1 tuft and the pg1 dendrites while the et2 cells
// have excitatory connections to the m2 cells tufts and the pg2 cells dendrites
m1 = new Mitral()
et1 = new ET() // because the ET cells do not connect (directly) to other glomeruli we only need one per glom
// The granule cells will require multiple cells per glom because they can receive inputs from both the local
// mitral cell and one from an adjacent glom.
for i=0,n-1 {
  m2[i] = new Mitral()  // 
  gc1[i] = new Granule()
  gc2[i] = new Granule() 
  pg1[i] = new PGcell(0) // the number 0 passed to PGcell() is the nicot. current
  pg2[i] = new PGcell(0) // the number 0 passed to PGcell() is the nicot. current
  et2[i] = new ET()
}

// OSNXs will be representing breathing OSN activity while LightXs are repr. of light
// stim. OSN activity (events)
objref OSN1, OSN2[n], Light1, Light2[n]

// Located arbitrarily because where they have an
// effect is determined by the NetCon target not the 
// VecStim (source) position
breathing_period = 400 // 400 ms is typical breathing period
breath_gauss_center = 0 // 0 makes peak occur right at start (and end) of breath
breath_half_width = 10 // 10 makes for a narrow peak
breath_peak_rate = 240 // 150 // 150 or 300 OK to represent thousands of OSN's converging onto a mc

// share these parameters for mitral cell 1 and 2 except for 
// lightX_peak_rate which can be used to turn off and on each
light_period = 300 // 398 // 300 for debugging // light interval period
light_gauss_center = 0 // 0 makes peak occur right at start (and end) of light
light_half_width = 10 // 10 makes for a narrow peak

light1_peak_rate = 240 // 40 for much less // 300 // 150 or 300 OK to represent thousands of OSN's converging onto a mc

objref light2_peak_rate_vec
light2_peak_rate_vec  = new Vector(n) // will store peak rates - develop later - to do

light2_peak_rate = 0 // 150 or 300 OK to represent thousands of OSN's converging onto a mc

// OSNX provides source events for breathing synaptic events
// note that the (arbitrary) location of VecStim artificial cells when created does not determine
// what they are connected to, the NetCon's do that!
m1.tuftden OSN1 = new VecStim(0.5) // previously ThetaStim(0.5)
for i=0,n-1 {
  m1.tuftden OSN2[i] = new VecStim(0.5) // breath inputs to all the external columns
}
// LightX provides source events for light synaptic events
m1.tuftden Light1 = new VecStim(0.5) // previously ThetaStim(0.5)
for i=0,n-1 {
  m1.tuftden Light2[i] = new VecStim(0.5) // potential trains of inputs to external cols.
}
// backgroundX is representative of background activity that causes mitral cell tuft excitatory events
// at any phase of the breath cycle. The _m1 is for input to the m1 mc tuft,
// background1, background2 is for the inputs to the pg1[i] and pg2[i] cells.
// background2 also shares it's input with the m2[i] tufts

objref background_m1, background1[n], background2[n]

m1.tuftden background_m1 = new NetStim(0.5) // additional constant input onto mitral 1.
for i=0,n-1 {
  m1.tuftden background1[i] = new NetStim(0.5)
  m1.tuftden background2[i] = new NetStim(0.5)
}
// introduce synapses so they can be targets in NetCons:
// name conventions:
// cell name of post synaptic partner _ cell name of pre synaptic partner _ synapse type
// or for shared synapses
// cell name of post synaptic partner _ synapse type

objref m1_glut, m2_glut[n] // excitation of mitral tufts by osn cells
// excitation of mitral tufts by the newly added et cells will also
// take place on the m1_glut m2_glut[n] synapses

objref m1_gc1_inhib[n], m2_gc1_inhib[n] // inhibition of mitral dends by gc
objref m1_gc2_inhib[n], m2_gc2_inhib[n] // inhibition of mitral dends by gc2

objref gc1_m1_glut[n], gc1_m2_glut[n] // excitation of gc by mitral cells
objref gc2_m1_glut[n], gc2_m2_glut[n]

// pg cells:
objref pg1_glut[n], pg2_glut[n] // excitation of peri-glom cells by osn, mitral cells, light, background, et cells
objref m1_inhib[n], m2_inhib[n] // inhibition in the mitral cell tufts by both the local (same number

// et cells:
objref et1_glut, et2_glut[n] // excitation of et cells by either light (Light1, Light2) or respiratory input (OSN1, OSN2)

// as mitral cell)
objref m1priden_inhib[n], m2priden_inhib[n]
// and the remote pg cell (different number than mitral cell)

tuft_excite_pos = 0.5
// we could study multiple dendrites in the tuft later however for now there
// is just one tuft dendrite per mitral cell
m1.tuftden m1_glut = new AmpaNmda(tuft_excite_pos)
et1.tuftden et1_glut = new AmpaNmda(tuft_excite_pos)

for i=0, n-1 {
  m2[i].tuftden m2_glut[i] = new AmpaNmda(tuft_excite_pos)
  et2[i].tuftden et2_glut[i] = new AmpaNmda(tuft_excite_pos)
}
// the two below MC GC positions are reused for m1, m2, gc1, gc2
mc_gc_close_recip_pos = 0.01
mc_gc_far_recip_pos=.75

// original reicprocal position on the secondary dendrite:
for i=0,n-1 {
  m1.secden m1_gc1_inhib[i] = new FastInhib(mc_gc_close_recip_pos)
  m1.secden m1_gc2_inhib[i] = new FastInhib(mc_gc_far_recip_pos)

  m2[i].secden m2_gc1_inhib[i] = new FastInhib(mc_gc_far_recip_pos)
  m2[i].secden m2_gc2_inhib[i] = new FastInhib(mc_gc_close_recip_pos)
}
/**/ 

// move the gc reciprocal inhibition position to mitral cell body
// for maximum effect:
// m1.soma m1_gc1_inhib = new FastInhib(0.5)
// m2.soma m2_gc2_inhib = new FastInhib(0.5)

gc_recip_pos1 = 0.55
gc_recip_pos2 = 0.65
for i=0, n-1 {
  gc1[i].priden2 gc1_m1_glut[i] = new AmpaNmda(gc_recip_pos1)
  gc1[i].priden2 gc1_m2_glut[i] = new AmpaNmda(gc_recip_pos2)

  gc2[i].priden2 gc2_m1_glut[i] = new AmpaNmda(gc_recip_pos2)
  gc2[i].priden2 gc2_m2_glut[i] = new AmpaNmda(gc_recip_pos1)
}
// these mitral cell tuft inhibitory synapses are contacted by both the local and remote pg cells
// the local pg cell is from a reciprocal synapse and the remote is from an "axon"

tuft_inhib_pos = 0.5 // for now make overlap with the tuft excitatory position
for i=0, n-1 {
  m1.tuftden m1_inhib[i] = new FastInhib(tuft_inhib_pos)
  m2[i].tuftden m2_inhib[i] = new FastInhib(tuft_inhib_pos)

  priden_inhib_pos = 0.9
  m1.priden m1priden_inhib[i] = new FastInhib(priden_inhib_pos)
  m2[i].priden m2priden_inhib[i] = new FastInhib(priden_inhib_pos)

  // pg cell excitatory synapse part of reciprocal synapses and site of OSN input
  pg1[i].gemmbody pg1_glut[i] = new AmpaNmda(0.5) // put in middle of pg spine
  pg2[i].gemmbody pg2_glut[i] = new AmpaNmda(0.5) // put in middle of pg spine
}

/////////////////////////////////////////////////////
//
//  connect the network
//
/////////////////////////////////////////////////////

num_of_netcon_types = 34
objref nc[num_of_netcon_types][n]
objref nclist
nclist = new List()

// connect the OSNs to the mcs
// breath to mc1
nc[0][0] = new NetCon(OSN1, m1_glut, 0, 1, 1)
// light to mc1
nc[6][0] = new NetCon(Light1, m1_glut, 0, 1, 1)  // arguments are source, target, threshold, delay, weight
// connect the background stimulus

nc[8][0] = new NetCon(background_m1, m1_glut, 0, 1, 1)  // arguments are source, target, threshold, delay, weight

// arguments are source, target, threshold, delay, weight
for i=0, n-1 {
  nc[1][i] = new NetCon(OSN2[i], m2_glut[i])

// connect the Lights to the mcs

  nc[7][i] = new NetCon(Light2[i], m2_glut[i])  // the 2's refer to the external col.

// connect the reciprocal synapse between m1 and gc1

  m1.secden[0] {nc[2][i] = new NetCon(&v(mc_gc_close_recip_pos), gc1_m1_glut[i], -20, 1, 1)}
  gc1[i].priden2[0] {nc[3][i] = new NetCon(&v(gc_recip_pos1), m1_gc1_inhib[i], -20, 1, 1)}

// load_file("sample_gc1_v_graph.ses")

// connect the reciprocal synapse between m2 and gc1

  m2[i].secden[0] {nc[4][i] = new NetCon(&v(mc_gc_far_recip_pos), gc1_m2_glut[i])}
  gc1[i].priden2[0] {nc[5][i] = new NetCon(&v(gc_recip_pos2), m2_gc1_inhib[i])}
print "for nc[3][i's] gc_recip_pos1 = ", gc_recip_pos1 
print " for nc[5][i's] gc_recip_pos2= ", gc_recip_pos2
// connect the reciprocal synapse between m1 and gc2

  m1.secden[0] {nc[10][i] = new NetCon(&v(mc_gc_far_recip_pos), gc2_m1_glut[i], -20, 1, 1)}
  gc2[i].priden2[0] {nc[11][i] = new NetCon(&v(gc_recip_pos2), m1_gc2_inhib[i])}
print " for nc[11] gc_recip_pos2 = ", gc_recip_pos2

// connect the reciprocal synapse between m2 and gc2

  m2[i].secden[0] {nc[12][i] = new NetCon(&v(mc_gc_close_recip_pos), gc2_m2_glut[i])}
// gc1.priden2[0] {nc[13] = new NetCon(&v(gc_recip_pos1), m2_gc2_inhib)} // typo of providing gc1.priden2[0]
// location seems to take away from nc[3]?  Is that the intended behavior for NEURON?

  gc2[i].priden2[0] {nc[13][i] = new NetCon(&v(gc_recip_pos1), m2_gc2_inhib[i])}
print " for nc[13] gc_recip_pos1 = ", gc_recip_pos1

// connect the background stimulus

  nc[9][i] = new NetCon(background2[i], m2_glut[i])

// connect the periglomerular cells

// all the connections to periglom 1:
// excited by background, OSN1, Light1, mitral cell 1
// output inhibits mitral cell 1 with dendro-dendritic reciprocal synapse
// and inhibits mitral cell 2 with axonal synapse

////////////////// 20150508 stopping place: keep going here later - finish loop - test - fix gui.

  nc[14][i] = new NetCon(background1[i], pg1_glut[i])
  nc[15][i] = new NetCon(OSN1, pg1_glut[i]) // makes it possible to connect the breath to all the pg1_glut[i]
  nc[16][i] = new NetCon(Light1, pg1_glut[i]) // makes it possible to connect Light1 to all the pg1_glut[i]

  m1.tuftden {nc[17][i] = new NetCon(&v(0.5), pg1_glut[i])} // excitatory connections from m1 onto pg1 dends
  pg1[i].gemmbody {nc[18][i] = new NetCon(&v(0.5), m1_inhib)} // reciprocal connections from pg1 dends back to m1
  pg2[i].soma {nc[19][i] = new NetCon(&v(0.5), m1priden_inhib) } // pg2's axon connections to m1

// all the connections to periglom 2:
// excited by background, OSN2, Light2, mitral cell 2
// output inhibits mitral cell 2 with dendro-dendritic reciprocal synapse
// and inhibits mitral cell 1 with axonal synapse

  nc[20][i] = new NetCon(background2[i], pg2_glut[i])  // background2 input onto pg2's
  nc[21][i] = new NetCon(OSN2[i], pg2_glut[i]) // breathing inputs onto pg2
  nc[22][i] = new NetCon(Light2[i], pg2_glut[i]) // light inputs onto pg2

  m2[i].tuftden {nc[23][i] = new NetCon(&v(0.5), pg2_glut[i])} // m2 inputs onto pg2
  pg2[i].gemmbody {nc[24][i] = new NetCon(&v(0.5), m2_inhib[i])} // pg2 recip connections back to m2
  pg1[i].soma {nc[25][i] = new NetCon(&v(0.5), m2priden_inhib[i]) } // pg1 axon connections to m2 pri dends
}

// new connections for et cells
// nc index, description
// 26 Light1 -> et1
// 27 OSN1 -> et1
// 28 et1 -> mc1 tuft
// 29 et1 -> pg1 tuft
// 30 Light2 -> et2
// 31 OSN2 -> et2
// 32 et2 -> mc2 tuft
// 33 et2 -> pg2 tuft

nc[26][0] = new NetCon(Light1, et1_glut, 0, 1, 1)  // arguments are source, target, threshold, delay, weight
nc[27][0] = new NetCon(OSN1, et1_glut, 0, 1, 1)
et1.soma nc[28][0] = new NetCon(&v(0.5), m1_glut, 0, 1, 1) // note that the soma connections are a proxy for the axons

for i=0,n-1 { // i is index over additional columns
  et1.soma {nc[29][i] = new NetCon(&v(0.5), pg1_glut[i], 0, 1, 1)} // excitatory connections from et1 onto pg1 dends
  nc[30][i] = new NetCon(Light2[i], et2_glut[i], 0, 1, 1) // light inputs onto et2
  nc[31][i] = new NetCon(OSN2[i], et2_glut[i], 0, 1, 1) // breathing inputs onto et2
  et2[i].soma {nc[32][i] = new NetCon(&v(0.5), m2_glut[i], 0, 1, 1)}
  et2[i].soma {nc[33][i] = new NetCon(&v(0.5), pg2_glut[i], 0, 1, 1)}
}

// store all netcons in a list for easy access
for columns=0,n-1 {
  for i=0,num_of_netcon_types-1 {
    nclist.append(nc[i][columns])
  }
}

/////////////////////////////////////////////////////
//
// Adjust plasticity of FastInhib and AmpaNmda
//
/////////////////////////////////////////////////////

// it was decided the easiest thing to do was turn off
// plasticity in the AmpaNmda and FastInhib mod files
/*
// test section
objref test_gc
m1.tuftden test_gc = new ThetaStim(0.5) // stimulate granule cell synapse directly
objref test_nc
test_nc = new NetCon(test_gc, gc1_m1_glut)

objref test_gc2
m1.tuftden test_gc2 = new ThetaStim(0.5) // stimulate granule cell synapse directly
objref test_nc2
test_nc2 = new NetCon(test_gc2, gc1_m1_glut)

nclist.append(test_nc)
nclist.append(test_nc2)

// end test section
*/
/////////////////////////////////////////////////////
//
// Graphical control of VecStims
//
/////////////////////////////////////////////////////
objref breath_events_for_mc1,  breath_events_for_mc2[n]
objref breath_poisson_rate_for_mc1, breath_poisson_rate_for_mc2[n]

proc generate_mc1_breath_events() {
  breath_events_for_mc1 = gen_events(tstop, breathing_period, breath_gauss_center, breath_half_width, breath_peak_rate)
  OSN1.play(breath_events_for_mc1)
  breath_poisson_rate_for_mc1 = _poisson_rate // global vector set by gen_events
  print "completed generating ",breath_events_for_mc1.size()," mc1 breath events"
}
proc generate_mc2_breath_events() { local i
  for i=0, n-1 {
    breath_events_for_mc2[i] = gen_events(tstop, breathing_period, breath_gauss_center, breath_half_width, breath_peak_rate)
    OSN2[i].play(breath_events_for_mc2[i])
    breath_poisson_rate_for_mc2[i] = _poisson_rate // global vector set by gen_events
    print "completed generating ", breath_events_for_mc2[i].size()," m2[",i,"] breath events"
  }
}
proc generate_breath_events() {
  generate_mc1_breath_events()
  generate_mc2_breath_events()
}
strdef stim_file_name

proc save_mc1_breath_events() { // writes a file
  sprint(stim_file_name, "stimulation/breath_for_mc1_%f_%f_%f_%f_%f.dat",breathing_period, breath_gauss_center, breath_half_width, breath_peak_rate, tstop)
  write_vec(stim_file_name, breath_events_for_mc1)
}
proc save_mc2_breath_events() { // writes a file 
  sprint(stim_file_name, "stimulation/breath_for_mc2_%f_%f_%f_%f_%f.dat",breathing_period, breath_gauss_center, breath_half_width, breath_peak_rate, tstop)
  write_vec(stim_file_name, breath_events_for_mc2)
}
proc save_breath_events() { // writes two files
  save_mc1_breath_events()
  save_mc2_breath_events()
}

chdir("py")
nrnpython("import utilities")
nrnpython("import os.path as path")
chdir("..")
objref p
p=new PythonObject()

proc load_mc1_breath_events() { // reads a file
  sprint(stim_file_name, "stimulation/breath_for_mc1_%f_%f_%f_%f_%f.dat",breathing_period, breath_gauss_center, breath_half_width, breath_peak_rate, tstop)
  breath_events_for_mc1=p.utilities.read_nrn_vec(stim_file_name)
  OSN1.play(breath_events_for_mc1)
}
proc load_mc2_breath_events() { // reads a file
  sprint(stim_file_name, "stimulation/breath_for_mc2_%f_%f_%f_%f_%f.dat",breathing_period, breath_gauss_center, breath_half_width, breath_peak_rate, tstop)
  breath_events_for_mc2=p.utilities.read_nrn_vec(stim_file_name)
  OSN2.play(breath_events_for_mc2)

}
proc load_breath_events() { // reads two files
  load_mc1_breath_events()
  load_mc2_breath_events()
}

objref light_events_for_mc1,  light_events_for_mc2
objref light_poisson_rate_for_mc1, light_poisson_rate_for_mc2

proc generate_mc1_light_events() {
  light_events_for_mc1 = gen_events(tstop, light_period, light_gauss_center, light_half_width, light1_peak_rate)
  Light1.play(light_events_for_mc1)
  light_poisson_rate_for_mc1 = _poisson_rate // global vector set by gen_events
  print "completed generating ", light_events_for_mc1.size()," mc1 light events"
}
proc generate_mc2_light_events() {
  light_events_for_mc2 = gen_events(tstop, light_period, light_gauss_center, light_half_width, light2_peak_rate)
  Light2.play(light_events_for_mc2)
  light_poisson_rate_for_mc2 = _poisson_rate // global vector set by gen_events
  print "completed generating ",light_events_for_mc2.size()," mc2 light events"
}
proc generate_light_events() {
  generate_mc1_light_events()
  generate_mc2_light_events()
}

proc save_mc1_light_events() { // writes a file
  sprint(stim_file_name, "stimulation/light_for_mc1_%f_%f_%f_%f_%f.dat",light_period, light_gauss_center, light_half_width, light1_peak_rate, tstop)
  write_vec(stim_file_name, light_events_for_mc1)
}
proc save_mc2_light_events() { // writes a file
  sprint(stim_file_name, "stimulation/light_for_mc2_%f_%f_%f_%f_%f.dat",light_period, light_gauss_center, light_half_width, light2_peak_rate, tstop)
  write_vec(stim_file_name, light_events_for_mc2)
}
proc save_light_events() { // writes two files
  save_mc1_light_events()
  save_mc2_light_events()
}

proc load_mc1_light_events() { // writes a file that is 
  sprint(stim_file_name, "stimulation/light_for_mc1_%f_%f_%f_%f_%f.dat",light_period, light_gauss_center, light_half_width, light1_peak_rate, tstop)
  light_events_for_mc1=p.utilities.read_nrn_vec(stim_file_name)
  Light1.play(light_events_for_mc1)
}
proc load_mc2_light_events() { // writes a file that is 
  sprint(stim_file_name, "stimulation/light_for_mc2_%f_%f_%f_%f_%f.dat",light_period, light_gauss_center, light_half_width, light2_peak_rate, tstop)
  light_events_for_mc2=p.utilities.read_nrn_vec(stim_file_name)
  Light2.play(light_events_for_mc2)
}
proc load_light_events() { // writes a file that is 
  load_mc1_light_events()
  load_mc2_light_events()
}

proc adjust_tstop() {
    tstop=breathing_period*((breathing_period)/abs(breathing_period-light_period))+100
}
proc do_everything() {
  print "Doing everything: load or regenerate input trains, run simulation, and store results in tdt2mat dir"
  adjust_tstop() // tstop=breathing_period*((breathing_period)/abs(breathing_period-light_period))+100
  print "First set tstop =",tstop," to accomdate all phase differences between breathing and light periods, plus arbitrary 100 ms"

  // methodically check that each of the breath and light files (mc1 and mc2) (4 files total) are available
  // breath for mc1
  // breath for mc2
  // light for mc1
  // light for mc2
  
  sprint(stim_file_name, "stimulation/breath_for_mc1_%f_%f_%f_%f_%f.dat",breathing_period, breath_gauss_center, breath_half_width, breath_peak_rate, tstop)
/*  if (p.path.isfile(stim_file_name)) {
    load_mc1_breath_events()
  } else {
    generate_mc1_breath_events()
    save_mc1_breath_events()
  }
*/
    // for now always generate: (can add file writing for columns later if desired)
    generate_mc1_breath_events()  // always just generate the breath events

  sprint(stim_file_name, "stimulation/breath_for_mc2_%f_%f_%f_%f_%f.dat",breathing_period, breath_gauss_center, breath_half_width, breath_peak_rate, tstop)
/*  if (p.path.isfile(stim_file_name)) {
    load_mc2_breath_events()
  } else {
    generate_mc2_breath_events()
    save_mc2_breath_events()
  }
*/
    generate_mc2_breath_events() // always generate

  sprint(stim_file_name, "stimulation/light_for_mc1_%f_%f_%f_%f_%f.dat",light_period, light_gauss_center, light_half_width, light1_peak_rate, tstop)
/*  if (p.path.isfile(stim_file_name)) {
    load_mc1_light_events()
  } else {
    generate_mc1_light_events()
    save_mc1_light_events()
  }
*/
    generate_mc1_light_events()  // always generate


  sprint(stim_file_name, "stimulation/light_for_mc2_%f_%f_%f_%f_%f.dat",light_period, light_gauss_center, light_half_width, light2_peak_rate, tstop)

/*
  if (p.path.isfile(stim_file_name)) {
    load_mc2_light_events()
  } else {
    generate_mc2_light_events()
    save_mc2_light_events()
  }
*/
    generate_mc2_light_events() // always generate

  print "running simulation"
  print "hide graphs for faster run"
  init()
  run()
  print "saving tank"
  save_tank()
  print "Done everything!"
}

gc_connection_state=0
gc_on = 4 // can use for particular global levels of gc connectivity strength
proc toggle_gc_connection() {

  if (gc_connection_state) {
    for i=0, n-1 {
      nc[2][i].weight = 0
      nc[3][i].weight = 0
      nc[4][i].weight = 0
      nc[5][i].weight = 0
      nc[10][i].weight = 0
      nc[11][i].weight = 0
      nc[12][i].weight = 0
      nc[13][i].weight = 0
    }
    // automaticaly xstatebutton sets gc_connection_state=0
  } else {
    for i=0, n-1 {
      nc[2][i].weight = gc_on
      nc[3][i].weight = gc_on
      nc[4][i].weight = gc_on
      nc[5][i].weight = gc_on
      nc[10][i].weight = gc_on
      nc[11][i].weight = gc_on
      nc[12][i].weight = gc_on
      nc[13][i].weight = gc_on
    }
    // automatically xbuttonstate sets gc_connection_state=1
  }
}

pg_connection_state=0
pg_on = 1 // can use for particular global levels of pg connectivity strength
proc toggle_pg_connection() {
  if (pg_connection_state) {
    for i=0, n-1 {
      nc[14][i].weight = 0
      nc[15][i].weight = 0
      nc[16][i].weight = 0
      nc[17][i].weight = 0
      nc[18][i].weight = 0
      nc[19][i].weight = 0
      nc[20][i].weight = 0
      nc[21][i].weight = 0
      nc[22][i].weight = 0
      nc[23][i].weight = 0
      nc[24][i].weight = 0
      nc[25][i].weight = 0
    // xstatebutton automatically sets pg_connection_state=0
    }
  } else {
    for i=0, i-1 {
      nc[14][i].weight = pg_on
      nc[15][i].weight = pg_on
      nc[16][i].weight = pg_on
      nc[17][i].weight = pg_on
      nc[18][i].weight = pg_on
      nc[19][i].weight = pg_on
      nc[20][i].weight = pg_on
      nc[21][i].weight = pg_on
      nc[22][i].weight = pg_on
      nc[23][i].weight = pg_on
      nc[24][i].weight = pg_on
      nc[25][i].weight = pg_on
    // xstatebutton automatically sets pg_connection_state=1
    }
  }
}

objref hbox
hbox = new HBox()
hbox.intercept(1)

xpanel("Seperate BREATHING inputs generated for each of two mitral cells.")
xbutton("tstop=breathing_period*((breathing_period)/abs(breathing_period-light_period))+100","{ adjust_tstop() tstop_changed() }")
// what the formula does above is compute how long the simulation needs to run to allow the breathing period and light
// period to completly overlap and then adds 100 ms for good measure.

xvalue("Tstop","tstop", 1,"tstop_changed()", 0, 1 ) // from standard run control window
xlabel("Far above sets tstop. Below OSN breathing input gauss. params. for mc1, mc2")
xlabel("The breath period in milliseconds (ms):")
xvalue("breathing_period")
xlabel("The number of ms from the start of a breath to the peak fr:")
xvalue("breath_gauss_center")
xlabel("The half width of the gaussian:")
xvalue("breath_half_width")
xlabel("max firing rate")
xvalue("breath_peak_rate")
xbutton("regenerate and save breath event trains","{ generate_breath_events() save_breath_events() }")
//xbutton("load stimulation file into breath events","load_breath_events()") // These will read or save breath events in a
//xbutton("save breath events as stimulation","save_breath_events()")        // reusable format in the stimulation folder
xlabel("   -   -   -   -   -   -   -   -   -")

xlabel("LIGHT input to both mitral cells")
xlabel("Light input gaussian parameters for mitral cell 1 and 2:")
xlabel("parameters are shared except for lightX_peak_rate")
xlabel("The light period in milliseconds (ms):")
xvalue("light_period")
xlabel("ms from the start of a light period to the peak fr:")
xvalue("light_gauss_center")
xlabel("The half width of the gaussian:")
xvalue("light_half_width")
xlabel("max firing rates (0 is off)")
xvalue("light1_peak_rate")
xvalue("light2_peak_rate")
xbutton("regenerate light input trains","{ generate_light_events() save_light_events() }")
// xbutton("load stimulation file into light events","load_light_events()") // These will read or save breath events in a
// xbutton("save light events as stimulation","save_light_events()")        // reusable format in the stimulation folder
xbutton("Everything!: regenerate any missing input events/run sim/store","do_everything()")
xpanel()
global_weight=1

//xvalue("prompt", "variable" [, boolean_deflt, "action" [, boolean_canrun, boolean_usepointer]])
//xvalue("global_weight","global_weight",2,"readjust_weights()",1, 0)
xpanel("Synapse weights")
xlabel("Synapse weights")
xvalue("global_weight")
xbutton("readjust_weights()")
xlabel("OSN1 (breath1)->m1:")
xvalue("nc[0][0].weight")
xlabel("OSN2 (breath2)->m2:")
xvalue("nc[1][0].weight")

// background stimulation panel
xlabel("background1 and 2")
xlabel("background input to mitral cell 1:")
xvalue("background1[0].interval")
xvalue("background1[0].start")
xvalue("background1[0].number")
xvalue("background1[0].noise")
// assign some default values
background1[0].interval=100 // mean synaptic period in ms 
background1[0].start=25
background1[0].number=0 // 1e9 // (forever)
background1[0].noise=1   // completely noisy

xlabel("background input to mitral cell 2:")
xvalue("background2[0].interval")
xvalue("background2[0].start")
xvalue("background2[0].number")
xvalue("background2[0].noise")
// assign some default values
background2[0].interval=100
background2[0].start=25
background2[0].number=0 // 1e9 // (forever)
background2[0].noise=1   // completely noisy

xlabel("Below graphs stimulation events and poisson")
xlabel("Note: poisson rates not shown to scale")
xbutton("red - breath, purple-light","{graph_poisson()}") // see graph_fncs.hoc for details
xlabel("click below to save selected data or save tank")
xbutton("save event and voltage data","write_selected_vecs()")
xbutton("save simulation to tank","save_tank()")

xpanel()
xpanel("connections that involve gc cells")
xlabel("m1 to gc:")
xvalue("nc[2][0].weight")
xlabel("gc1 back to m1:")
xvalue("nc[3][0].weight")
xlabel("m2 to gc1")
xvalue("nc[4][0].weight")
xlabel("gc1 back to m2")
xvalue("nc[5][0].weight")
xlabel("m1 to gc2")
xvalue("nc[10][0].weight")
xlabel("gc2 to m1")
xvalue("nc[11][0].weight")
xlabel("m2 to gc2")
xvalue("nc[12][0].weight")
xlabel("gc2 to m2")
xvalue("nc[13][0].weight")
xstatebutton("toggle gc cell connection", &gc_connection_state, "toggle_gc_connection()")

xlabel(" ")
xlabel(" - - - - - - - - ")
xlabel(" ")
xbutton("Set weights, etc. from 0th column to all columns","adjust_netcons_from_top()")
xpanel()

// pg cell panel

xpanel("connections to/from pg cells")
xlabel("  pg1  ")
xlabel("background1(14), OSN1(15), and Light1(16) to pg1")
xvalue("nc[14][0].weight")
xvalue("nc[15][0].weight")
xvalue("nc[16][0].weight")
xlabel("recip syn m1 tuft->pg1(17),<-(18)")
xvalue("nc[17][0].weight")
xvalue("nc[18][0].weight")
xlabel("pg1 axon->m2 priden")
xvalue("nc[25][0].weight")
xlabel("  pg2  ")

// all the connections to periglom 2:
// excited by background, OSN2, Light2, mitral cell 2
// output inhibits mitral cell 2 with dendro-dendritic reciprocal synapse
// and inhibits mitral cell 1 with axonal synapse

xlabel("background2(20), OSN2(21), and Light2(22) to pg2")
xvalue("nc[20][0].weight")
xvalue("nc[21][0].weight")
xvalue("nc[22][0].weight")
xlabel("m2 tuft->pg2(23),<-(24)")
xvalue("nc[23][0].weight")
xvalue("nc[24][0].weight")
xlabel("pg2 axon->m1 priden")
xvalue("nc[19][0].weight")
xstatebutton("toggle pg cell connection", &pg_connection_state, "toggle_pg_connection()")
xpanel()

// note that background omitted in the below because ended up not using it in simulations
// before the et cells were added
xpanel("connections to/from et cells")
xlabel("  et1  ")
xlabel("Light1(26), OSN1(27) to et1")
xvalue("nc[26][0].weight")
xvalue("nc[27][0].weight")
xlabel("et1 axon->m1 tuft")
xvalue("nc[28][0].weight")
xlabel("token connections to/from column replicated") // just the [0]'th connection is editable/displayed
// the zeroth is all there is if there is 1 additional columns however if there are more than 2 total columns
// then the weights of those greater the 1 additional columns are not displayed/editable in this xpanel
xlabel("et1 axon -> pg1[i] dends")
xvalue("nc[29][0].weight")
xlabel("Light2[i] -> et2 tuft[i]")
xvalue("nc[30][0].weight")
xlabel("OSN2[i] -> et2 tuft[i]")
xvalue("nc[31][0].weight")
xlabel("et2 axon[i] -> m2 tuft[i]")
xvalue("nc[32][0].weight")
xlabel("et2 axon[i]->pg2 tuft[i]")
xvalue("nc[33][0].weight")
xpanel()


/*
// spacer so scroll bars are OK in other panels
for i=1,10 {
xlabel(" ")
}
*/

hbox.intercept(0)
hbox.map()

/////////////////////////////////////////////////////
//
// Setup vector and event recording for graphing/analysis
//
/////////////////////////////////////////////////////
objref t_vec, m1_v_vec, m2_v_vec

t_vec = new Vector()
m1_v_vec = new Vector()
m2_v_vec = new Vector()

t_vec.record(&t)
m1_v_vec.record(&m1.soma.v(0.5))
m2_v_vec.record(&m2.soma.v(0.5))

// create vectors to record synaptic events of the inputs and between cells
objref light1_events, light2_events[i]
objref OSN1_events, OSN2_events[i], m1_events, m2_events[i], gc1_events1[i], gc1_events2[i]
objref gc2_events1[i], gc2_events2[i] // from gc2 to mc1 and mc2 respectively

OSN1_events = new Vector()
m1_events = new Vector()
light1_events = new Vector()
for i=0, n-1 {
  OSN2_events[i] = new Vector()
  m2_events[i] = new Vector()
  gc1_events1[i] = new Vector()
  gc1_events2[i] = new Vector()

  light2_events[i] = new Vector()

  gc2_events1[i] = new Vector()
  gc2_events2 [i]= new Vector()
}
nc[2][0].record(m1_events)
nc[0][0].record(OSN1_events)
nc[6][0].record(light1_events)
for i=0, n-1 {
  nc[1][i].record(OSN2_events[i])
  nc[3][i].record(gc1_events1[i]) // source position gc_recip_pos1 on granule priden2[0]

  nc[4][i].record(m2_events[i])
  nc[5][i].record(gc1_events2[i]) // source position gc_recip_pos2 on granule priden2[0]
  nc[7][i].record(light2_events[i]) //for these connects the events are recorded into vectors here

  nc[11][i].record(gc2_events1[i])
  nc[13][i].record(gc2_events2[i])
}
//  activate all the synapses
proc readjust_weights() {
  for i=0,nclist.count-1 {
      nclist.o[i].weight=global_weight
  }
}

readjust_weights()
// test_nc.weight=global_weight
// test_nc2.weight=global_weight

proc adjust_netcons_from_top() {
// procedure will set appropriate netcons[X][Y>0} from netcons[X][0]
  for i=0, num_of_netcon_types-1 {
    if ((i!=0)&&(i!=6)&&(i!=8)) {
      for j=0, n-1 {  //extend the values into all the columns from the first column
        nc[i][j].weight = nc[i][0].weight
        nc[i][j].threshold = nc[i][0].threshold
        nc[i][j].delay = nc[i][0].delay
      }
    }
  }
}
load_file("cells_volt_graphs.ses")
load_file("runcntrl.ses")
load_file("graph_fncs.hoc")

// moved below to parameters_dot_hoc file so that pg recording objects are
// defined: load_file("tdt2mat_data.hoc")

// for the NSG this filename which looks like "run_X/parameters.hoc" was 
// set in init.py.  The contents of parameters.hoc was set by pre_init.py
/// print "parameters_dot_hoc_file=",parameters_dot_hoc_file
/// system("pwd; echo above before load_file parameters_dot ")

load_file(parameters_dot_hoc_file) // set parameters for a batch run of the job