Electrotonic transform and EPSCs for WT and Q175+/- spiny projection neurons (Goodliffe et al 2018)

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Accession:236310
This model achieves electrotonic transform and computes mean inward and outward attenuation from 0 to 500 Hz input; and randomly activates synapses along dendrites to simulate AMPAR mediated EPSCs. For electrotonic analysis, in Elec folder, the entry file is MSNelec_transform.hoc. For EPSC simulation, in Syn folder, the entry file is randomepsc.hoc. Run read_EPSCsims_mdb_alone.m next with the simulated parameter values specified to compute the mean EPSC.
Reference:
1 . Goodliffe JW, Song H, Rubakovic A, Chang W, Medalla M, Weaver CM, Luebke JI (2018) Differential changes to D1 and D2 medium spiny neurons in the 12-month-old Q175+/- mouse model of Huntington's Disease. PLoS One 13:e0200626 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Synapse;
Brain Region(s)/Organism: Striatum;
Cell Type(s): Neostriatum spiny neuron;
Channel(s):
Gap Junctions:
Receptor(s): AMPA;
Gene(s):
Transmitter(s):
Simulation Environment: NEURON;
Model Concept(s): Detailed Neuronal Models; Membrane Properties; Electrotonus; Synaptic-input statistic;
Implementer(s):
Search NeuronDB for information about:  AMPA;
/
GoodliffeEtAl2018
Syn
tau_tables
bkkca.mod
cadyn.mod *
caL.mod
caL13.mod
caldyn.mod
can.mod
caq.mod *
car.mod
cat.mod
kaf.mod
kas.mod
kdr.mod
kir.mod *
krp.mod *
linearIclamp.mod
naf.mod
nap.mod
skkca.mod
stim.mod *
actionPotentialPlayer.hoc *
all_tau_vecs.hoc
analyticFunctions.hoc *
analyze_EPSC.m
aux_procs.hoc
baseline_values.txt
basic_procs.hoc
createFit_WTD1.m
electro_procs.hoc
fixnseg.hoc *
load_scripts.hoc
msp_template.hoc
PFC-V1_AddSynapses.hoc
PFC-V1_AddSynapses_fix.hoc
PFC-V1_AddSynapses_neg.hoc
PFC-V1_AddSynapses_negexp.hoc
plot_seClamp_i.ses
ran_test.hoc
randomepsc.hoc
ranstream.hoc
read_EPSCsims_mdb_alone.m
readcell.hoc
readNRNbin_Vclamp.m
                            
//**************************************************************************
// Begin cell template for MSP_Cell
// load cell template - builds the cell topology, including inserting
// channels and synapses

begintemplate MSP_Cell
public is_art
public init, topol, basic_shape, subsets, geom, memb
public synlist, x, y, z, position, connect2target

public soma, dend1, dend2, dend3, dend4, dend1_1, dend1_2
public dend2_1, dend2_2, dend4_1, dend4_2, dend3_2, dend3_1
public dend5, dend6, dend5_1, dend6_1, dend5_2, dend6_2
public all
public Prox_Dend, Mid_Dend, Dist_Dend
public leaf
public gaba, ampa, nmda, axonal, axon_init, axon_myelin




create soma, dend1, dend2, dend3, dend4, dend1_1[3], dend1_2[3]
create dend2_1[3], dend2_2[3], dend4_1[3], dend4_2[3], dend3_2[3], dend3_1[3]
create dend5, dend5_1[3], dend5_2[3]
create dend6, dend6_1[3], dend6_2[3]


create axon[3]







objref synlist, leaf, gaba[300], ampa[300], nmda[300]

proc init() { 
	topol()
	subsets()
	geom()
	biophys()  // replaced by set_active() in setupChannels.hoc
	
	forall {Ra = $1 CM = $2}
	geom_nseg()
	compts = 0
	forall {
		print secname(), " ", nseg  compts = compts + nseg
	}
	print compts, " compartments"


	synlist = new List()
	leaf    = new List()
	
	synloops()
	x = y = z = 0 // only change via position
}






proc topol() { local i
  connect dend1(0), soma(1)
  connect dend2(0), soma(1)
  connect dend3(0), soma(0)
  connect dend4(0), soma(0)
  connect dend5(0), soma(1)
  connect dend6(0), soma(0)
  
  connect axon(0), soma(0.5)
  connect axon[1](0), axon[0](1)
  connect axon[2](0), axon[1](1)
  
  
  connect dend1_1(0), dend1(1)
  for i = 1, 2 connect dend1_1[i](0), dend1_1(1)
  connect dend1_2(0), dend1(1)
  for i = 1, 2 connect dend1_2[i](0), dend1_2(1)
  connect dend2_1(0), dend2(1)
  for i = 1, 2 connect dend2_1[i](0), dend2_1(1)
  connect dend2_2(0), dend2(1)
  for i = 1, 2 connect dend2_2[i](0), dend2_2(1)
  connect dend4_1(0), dend4(1)
  for i = 1, 2 connect dend4_1[i](0), dend4_1(1)
  connect dend4_2(0), dend4(1)
  for i = 1, 2 connect dend4_2[i](0), dend4_2(1)
  connect dend3_2(0), dend3(1)
  for i = 1, 2 connect dend3_2[i](0), dend3_2(1)
  connect dend3_1(0), dend3(1)
  for i = 1, 2 connect dend3_1[i](0), dend3_1(1)

  // two more dendrites, added Jan 2017
  connect dend5_1(0), dend5(1)
  for i = 1, 2 connect dend5_1[i](0), dend5_1(1)
  connect dend5_2(0), dend5(1)
  for i = 1, 2 connect dend5_2[i](0), dend5_2(1)
  connect dend6_1(0), dend6(1)
  for i = 1, 2 connect dend6_1[i](0), dend6_1(1)
  connect dend6_2(0), dend6(1)
  for i = 1, 2 connect dend6_2[i](0), dend6_2(1)
// Above is the actual connection!!
  basic_shape()
}


proc basic_shape() {
  soma {pt3dclear() pt3dadd(0, 0, 0, 1) pt3dadd(15, 0, 0, 1)}
  dend1 {pt3dclear() pt3dadd(15, 0, 0, 1) pt3dadd(45, -29, 0, 1)}
  dend2 {pt3dclear() pt3dadd(15, 0, 0, 1) pt3dadd(45, 30, 0, 1)}
  dend3 {pt3dclear() pt3dadd(0, 0, 0, 1) pt3dadd(-29, -29, 0, 1)}
  dend4 {pt3dclear() pt3dadd(0, 0, 0, 1) pt3dadd(-29, 30, 0, 1)}
  dend1_1 {pt3dclear() pt3dadd(45, -29, 0, 1) pt3dadd(45, -59, 0, 1)}
  dend1_2 {pt3dclear() pt3dadd(45, -29, 0, 1) pt3dadd(90, -29, 0, 1)}
  dend2_1 {pt3dclear() pt3dadd(45, 30, 0, 1) pt3dadd(90, 30, 0, 1)}
  dend2_2 {pt3dclear() pt3dadd(45, 30, 0, 1) pt3dadd(60, 75, 0, 1)}
  dend4_1 {pt3dclear() pt3dadd(-29, 30, 0, 1) pt3dadd(-44, 75, 0, 1)}
  dend4_2 {pt3dclear() pt3dadd(-29, 30, 0, 1) pt3dadd(-74, 30, 0, 1)}
  dend3_2 {pt3dclear() pt3dadd(-29, -29, 0, 1) pt3dadd(-74, -29, 0, 1)}
  dend3_1 {pt3dclear() pt3dadd(-29, -29, 0, 1) pt3dadd(-44, -59, 0, 1)}
  dend1_1[1] {pt3dclear() pt3dadd(45, -59, 0, 1) pt3dadd(30, -89, 0, 1)}
  dend1_1[2] {pt3dclear() pt3dadd(45, -59, 0, 1) pt3dadd(75, -74, 0, 1)}
  dend1_2[1] {pt3dclear() pt3dadd(90, -29, 0, 1) pt3dadd(120, -14, 0, 1)}
  dend1_2[2] {pt3dclear() pt3dadd(90, -29, 0, 1) pt3dadd(120, -59, 0, 1)}
  dend2_1[1] {pt3dclear() pt3dadd(90, 30, 0, 1) pt3dadd(120, 15, 0, 1)}
  dend2_1[2] {pt3dclear() pt3dadd(90, 30, 0, 1) pt3dadd(105, 60, 0, 1)}
  dend2_2[1] {pt3dclear() pt3dadd(60, 75, 0, 1) pt3dadd(90, 90, 0, 1)}
  dend2_2[2] {pt3dclear() pt3dadd(60, 75, 0, 1) pt3dadd(45, 105, 0, 1)}
  dend4_1[1] {pt3dclear() pt3dadd(-44, 75, 0, 1) pt3dadd(-14, 105, 0, 1)}
  dend4_1[2] {pt3dclear() pt3dadd(-44, 75, 0, 1) pt3dadd(-74, 90, 0, 1)}
  dend4_2[1] {pt3dclear() pt3dadd(-74, 30, 0, 1) pt3dadd(-89, 60, 0, 1)}
  dend4_2[2] {pt3dclear() pt3dadd(-74, 30, 0, 1) pt3dadd(-104, 15, 0, 1)}
  dend3_2[1] {pt3dclear() pt3dadd(-74, -29, 0, 1) pt3dadd(-104, -14, 0, 1)}
  dend3_2[2] {pt3dclear() pt3dadd(-74, -29, 0, 1) pt3dadd(-104, -59, 0, 1)}
  dend3_1[1] {pt3dclear() pt3dadd(-44, -59, 0, 1) pt3dadd(-29, -89, 0, 1)}
  dend3_1[2] {pt3dclear() pt3dadd(-44, -59, 0, 1) pt3dadd(-89, -74, 0, 1)}

  // added two more dendrites, 1/11/17
  dend5 {pt3dclear() pt3dadd(15, 0, 0, 1) pt3dadd(45, 0, 0, 1)}
  dend6 {pt3dclear() pt3dadd(0, 0, 0, 1) pt3dadd(-30, 0, 0, 1)}
  dend5_1 {pt3dclear() pt3dadd(45,  0, 0, 1) pt3dadd(75, 15, 0, 1)}
  dend5_1[1] {pt3dclear() pt3dadd(75, 15, 0, 0, 1) pt3dadd(90, 15, 0, 1)}
  dend5_1[2] {pt3dclear() pt3dadd(75, 15, 0, 1) pt3dadd(90, 30, 0, 1)}
  dend5_2 {pt3dclear() pt3dadd(45,  0, 0, 1) pt3dadd(75, -15, 0, 1)}
  dend5_2[1] {pt3dclear() pt3dadd(75, -15, 0, 1) pt3dadd(90, -15, 0, 1)}
  dend5_2[2] {pt3dclear() pt3dadd(75, -15, 0, 1) pt3dadd(90, -30, 0, 1)}
  dend6_1 {pt3dclear() pt3dadd(-30, 0, 0, 1) pt3dadd(-60, 15, 0, 1)}
  dend6_1[1] {pt3dclear() pt3dadd(-40, 15, 0, 1) pt3dadd(-63, 18, 0, 1)}
  dend6_1[2] {pt3dclear() pt3dadd(-60, 15, 0, 1) pt3dadd(-75, 30, 0, 1)}
  dend6_2 {pt3dclear() pt3dadd(-30, 0, 0, 1) pt3dadd(-60, -15, 0, 1)}
  dend6_2[1] {pt3dclear() pt3dadd(-40, 0, 0, 1) pt3dadd(-63, -12, 0, 1)}
  dend6_2[2] {pt3dclear() pt3dadd(-40, 0, 0, 1) pt3dadd(-63, -18, 0, 1)}

}

objref all, Prox_Dend, Mid_Dend, Dist_Dend, axonal, axon_init, axon_myelin


proc subsets() { local i
  objref all, Prox_Dend, Mid_Dend, Dist_Dend, axonal, axon_init, axon_myelin

  all = new SectionList()
  axonal = new SectionList()
  axon_init = new SectionList()
  axon_myelin = new SectionList()
  forsec axonal { all.append() }
    soma all.append()
    dend1 all.append()
    dend2 all.append()
    dend3 all.append()
    dend4 all.append()
    dend5 all.append()
    dend6 all.append()
    for i=0, 2 dend1_1[i] all.append()
    for i=0, 2 dend1_2[i] all.append()
    for i=0, 2 dend2_1[i] all.append()
    for i=0, 2 dend2_2[i] all.append()
    for i=0, 2 dend4_1[i] all.append()
    for i=0, 2 dend4_2[i] all.append()
    for i=0, 2 dend3_2[i] all.append()
    for i=0, 2 dend3_1[i] all.append()
    for i=0, 2 dend5_1[i] all.append()
    for i=0, 2 dend5_2[i] all.append()
    for i=0, 2 dend6_1[i] all.append()
    for i=0, 2 dend6_2[i] all.append()


  Prox_Dend = new SectionList()
    dend1 Prox_Dend.append()
    dend2 Prox_Dend.append()
    dend3 Prox_Dend.append()
    dend4 Prox_Dend.append()
    dend5 Prox_Dend.append()
    dend6 Prox_Dend.append()

  Mid_Dend = new SectionList()
    dend1_1 Mid_Dend.append()
    dend1_2 Mid_Dend.append()
    dend2_1 Mid_Dend.append()
    dend2_2 Mid_Dend.append()
    dend4_1 Mid_Dend.append()
    dend4_2 Mid_Dend.append()
    dend3_2 Mid_Dend.append()
    dend3_1 Mid_Dend.append()
    dend5_1 Mid_Dend.append()
    dend5_2 Mid_Dend.append()
    dend6_1 Mid_Dend.append()
    dend6_2 Mid_Dend.append()

  Dist_Dend = new SectionList()
    for i=1, 2 dend1_1[i] Dist_Dend.append()
    for i=1, 2 dend1_2[i] Dist_Dend.append()
    for i=1, 2 dend2_1[i] Dist_Dend.append()
    for i=1, 2 dend2_2[i] Dist_Dend.append()
    for i=1, 2 dend4_1[i] Dist_Dend.append()
    for i=1, 2 dend4_2[i] Dist_Dend.append()
    for i=1, 2 dend3_2[i] Dist_Dend.append()
    for i=1, 2 dend3_1[i] Dist_Dend.append()
    for i=1, 2 dend5_1[i] Dist_Dend.append()
    for i=1, 2 dend5_2[i] Dist_Dend.append()
    for i=1, 2 dend6_1[i] Dist_Dend.append()
    for i=1, 2 dend6_2[i] Dist_Dend.append()
    axon[0] {
    	axon_init.append()
    	axonal.append()
    	}
    axon[1] {
    	axon_init.append()
    	axonal.append()
    	}
    axon[2] {
    	axon_myelin.append()
    	axonal.append()
    	}
    
}




// Wilson 1992 Single Neuron Computation
// dendritic diam(um) * (1+spine/dend ratio)
// also O'Donnell 1993 Synapse
// Koch/Segev Methods in Neuronal Modeling pg 122-3, 1998
proc geom() {
  soma {  L = 11.2753  diam = 9.99  }
  forsec Prox_Dend {L = 22.514153 diam = 1.428774}	
  forsec Mid_Dend  {L = 29.491451 diam = 1.2244817}	// { L = 20		diam = 1 * (1+0.3) }	
  forsec Dist_Dend {L = 114.68304	diam = 0.77782643}	// { L = 190	diam = 0.5 * (1+2) } 
  dend6_2[1] {L=39.447277 diam = 0.77782643}
  dend6_2[2] {L=39.447277 diam = 0.77782643}
  dend6_1[1] {L=39.447277 diam = 0.77782643}  

  

  axon[0]{
    L = 20
    diam(0:1) = 1.5:0.875
    }

    axon[1]{
    L = 30
    diam(0:1) = 0.875:0.5	
    }

    axon[2]{
    L = 400			
    diam = 0.5
    }

}





//**********
// use d_lambda function (see neuron website) to assign segments/nodes

func lambda_f() { local i, x1, x2, d1, d2, lam
        if (n3d() < 2) {
                return 1e5*sqrt(diam/(4*PI*$1*Ra*cm))
        }
		// above was too inaccurate with large variation in 3d diameter
		// so now we use all 3-d points to get a better approximate lambda

        x1 = arc3d(0)
        d1 = diam3d(0)
        lam = 0
        for i=1, n3d()-1 {
                x2 = arc3d(i)
                d2 = diam3d(i)
                lam += (x2 - x1)/sqrt(d1 + d2)
                x1 = x2   d1 = d2
        }

        //  length of the section in units of lambda
        lam *= sqrt(2) * 1e-5*sqrt(4*PI*$1*Ra*cm)

        return L/lam
}

proc geom_nseg() {
	freq = 100      // Hz, frequency at which AC length constant will be computed
	d_lambda = 0.1

	forall { nseg = int((L/(d_lambda*lambda_f(freq))+0.9)/2)*2 + 1  }
}
//**********



proc biophys() {
  
  forsec Prox_Dend {
	insert pas

	insert naf
	insert nap

	insert kir
	insert kas
	insert kaf
	insert bkkca
	insert skkca
	insert kdr

	insert caldyn
	insert caL
	insert caL13

	insert cadyn
	insert can
	insert caq
	insert car
	insert cat
  }

  forsec Mid_Dend {
	insert pas

	insert naf
	insert nap

	insert kir
	insert kas
	insert kaf
	insert bkkca
	insert skkca
	insert kdr

	insert caldyn
	insert caL
   	insert caL13

	insert cadyn
	insert can
	insert caq
	insert car
	insert cat
}

  forsec Dist_Dend {
	insert pas

	insert naf
	insert nap

	insert kir
	insert kas
	insert kaf
	insert bkkca
	insert skkca
	insert kdr

	insert caldyn
	insert caL
   	insert caL13

	insert cadyn
	insert can
	insert caq
	insert car
	insert cat
  }

  soma {
	insert pas

	insert naf
	insert nap

	insert kir
	insert kas
	insert kaf
	insert bkkca
	insert skkca
	insert kdr
	
	insert caldyn
	insert caL
	insert caL13

	insert cadyn
	insert can
	insert caq
	insert car	
	insert cat
 
	
  }

  forsec axon_init {
        // Hay et al (2013) pyramidal cell had more channels - stay simple here.
	insert naf
	insert kaf
	insert kas
	insert nap
	insert kdr
  }
  
}


  
proc position() { local i
  soma for i = 0, n3d()-1 {
    pt3dchange(i, $1-x+x3d(i), $2-y+y3d(i), $3-z+z3d(i), diam3d(i))
  }
  x = $1  y = $2  z = $3
}

proc connect2target() { //$o1 target point process, $o2 returned NetCon
  soma $o2 = new NetCon(&v(1), $o1)
}

func is_art() { return 0 }




proc synloops() {
	//***************************
	//Build AMPA synapses
	// Inner dends AMPA
	for i = 0, 0  {		// 0 in soma, 1 in each prox dend
			dend1 ampa[i] = new AMPAt(0.5)    synlist.append(ampa[i]) 
	}
	
	for i = 0, 0  {
			dend2 ampa[i] = new AMPAt(0.5)  synlist.append(ampa[i]) 
	}
	
	for i = 0, 0 {
			dend3 ampa[i] = new AMPAt(0.5)  synlist.append(ampa[i]) 
	}
	
	for i = 0, 0  {
			dend4 ampa[i] = new AMPAt(0.5)  synlist.append(ampa[i]) 
	}
	
	for i = 0, 0 {
			dend5 ampa[i] = new AMPAt(0.5)  synlist.append(ampa[i]) 
	}
	
	for i = 0, 0  {
			dend6 ampa[i] = new AMPAt(0.5)  synlist.append(ampa[i]) 
	}
	
	//Second level dends
	for i = 0, 1  {				// 2 in each mid dend
			onode = (i+1)/3		// 0.33, 0.66
			dend1_1 ampa[i] = new AMPAt(onode)  synlist.append(ampa[i]) 
	}
	
	for i = 0, 1  {
			onode = (i+1)/3
			dend1_2 ampa[i] = new AMPAt(onode)  synlist.append(ampa[i]) 
	}
	
	for i = 0, 1  {
			onode = (i+1)/3
			dend2_1 ampa[i] = new AMPAt(onode)  synlist.append(ampa[i]) 
	}
	
	for i = 0, 1  {
			onode = (i+1)/3
			dend2_2 ampa[i] = new AMPAt(onode)  synlist.append(ampa[i]) 
	}
	
	for i = 0, 1  {
			onode = (i+1)/3
			dend3_1 ampa[i] = new AMPAt(onode)  synlist.append(ampa[i]) 
	}
	
	for i = 0, 1  {
			onode = (i+1)/3
			dend3_2 ampa[i] = new AMPAt(onode)  synlist.append(ampa[i]) 
	}
	
	for i = 0, 1  {
			onode = (i+1)/3
			dend4_1 ampa[i] = new AMPAt(onode)  synlist.append(ampa[i]) 
	}
	
	for i = 0, 1  {
			onode = (i+1)/3
			dend4_2 ampa[i] = new AMPAt(onode)  synlist.append(ampa[i]) 
	}
	
	for i = 0, 1  {
			onode = (i+1)/3
			dend5_1 ampa[i] = new AMPAt(onode)  synlist.append(ampa[i]) 
	}
	
	for i = 0, 1  {
			onode = (i+1)/3
			dend5_2 ampa[i] = new AMPAt(onode)  synlist.append(ampa[i]) 
	}
	for i = 0, 1  {
			onode = (i+1)/3
			dend6_1 ampa[i] = new AMPAt(onode)  synlist.append(ampa[i]) 
	}
	
	for i = 0, 1  {
			onode = (i+1)/3
			dend6_2 ampa[i] = new AMPAt(onode)  synlist.append(ampa[i]) 
	}
	
	//Outer_level Dends
	
	for i = 0, 3  {				// 4 in each Dist_Dend dend
			onode = (i+1)/5		// 0.2, 0.4, 0.6, 0.8
			dend1_1[1] ampa[i] = new AMPAt(onode)   synlist.append(ampa[i]) 
	}
	
	for i = 0, 3  {
			onode = (i+1)/5
			dend1_1[2] ampa[i] = new AMPAt(onode)   synlist.append(ampa[i]) 
	}
	
	for i = 0, 3  {
			onode = (i+1)/5
			dend1_2[1] ampa[i] = new AMPAt(onode)   synlist.append(ampa[i]) 
	}
	
	for i = 0, 3  {
			onode = (i+1)/5
			dend1_2[2] ampa[i] = new AMPAt(onode)   synlist.append(ampa[i]) 
	}
	
	for i = 0, 3  {
			onode = (i+1)/5
			dend2_1[1] ampa[i] = new AMPAt(onode)   synlist.append(ampa[i]) 
	}
	
	for i = 0, 3  {
			onode = (i+1)/5
			dend2_1[2] ampa[i] = new AMPAt(onode)   synlist.append(ampa[i]) 
	}
	
	for i = 0, 3  {
			onode = (i+1)/5
			dend2_2[1] ampa[i] = new AMPAt(onode)   synlist.append(ampa[i]) 
	}
	
	for i = 0, 3  {
			onode = (i+1)/5
			dend2_2[2] ampa[i] = new AMPAt(onode)   synlist.append(ampa[i]) 
	}
	
	for i = 0, 3  {
			onode = (i+1)/5
			dend3_1[1] ampa[i] = new AMPAt(onode)   synlist.append(ampa[i]) 
	}
	
	for i = 0, 3  {
			onode = (i+1)/5
			dend3_1[2] ampa[i] = new AMPAt(onode)   synlist.append(ampa[i]) 
	}
	
	for i = 0, 3  {
			onode = (i+1)/5
			dend3_2[1] ampa[i] = new AMPAt(onode)   synlist.append(ampa[i])
	}
	
	for i = 0, 3  {
			onode = (i+1)/5
			dend3_2[2] ampa[i] = new AMPAt(onode)  synlist.append(ampa[i])
	}
	 
	for i = 0, 3  {
			onode = (i+1)/5
			dend5_1[1] ampa[i] = new AMPAt(onode)   synlist.append(ampa[i])
	}
	
	for i = 0, 3  {
			onode = (i+1)/5
			dend5_1[2] ampa[i] = new AMPAt(onode)   synlist.append(ampa[i])
	}
	
	for i = 0, 3  {
			onode = (i+1)/5
			dend5_2[1] ampa[i] = new AMPAt(onode)   synlist.append(ampa[i])
	}
	
	for i = 0, 3  {
			onode = (i+1)/5
			dend5_2[2] ampa[i] = new AMPAt(onode)   synlist.append(ampa[i])
	} 
	for i = 0, 3  {
			onode = (i+1)/5
			dend6_1[1] ampa[i] = new AMPAt(onode)   synlist.append(ampa[i])
	}
	
	for i = 0, 3  {
			onode = (i+1)/5
			dend6_1[2] ampa[i] = new AMPAt(onode)   synlist.append(ampa[i])
	}
	
	for i = 0, 3  {
			onode = (i+1)/5
			dend6_2[1] ampa[i] = new AMPAt(onode)   synlist.append(ampa[i])
	}
	
	for i = 0, 3  {
			onode = (i+1)/5
			dend6_2[2] ampa[i] = new AMPAt(onode)   synlist.append(ampa[i])
	} 
	for i = 0, 3  {
			onode = (i+1)/5
			dend4_1[1] ampa[i] = new AMPAt(onode)   synlist.append(ampa[i])
	}
	
	for i = 0, 3  {
			onode = (i+1)/5
			dend4_1[2] ampa[i] = new AMPAt(onode)   synlist.append(ampa[i])
	}
	
	for i = 0, 3  {
			onode = (i+1)/5
			dend4_2[1] ampa[i] = new AMPAt(onode)   synlist.append(ampa[i])
	}
	
	for i = 0, 3  {
			onode = (i+1)/5
			dend4_2[2] ampa[i] = new AMPAt(onode)   synlist.append(ampa[i])
	}
	//***************************
	
	
	
	
	//***************************
	//Build NMDA synapses
	// Inner dends NMDA
	for i = 0, 0  { 	// 0 in soma, 1 in each prox dend
			dend1 nmda[i] = new NMDAt(0.5)    synlist.append(nmda[i]) 
	}
	
	for i = 0, 0  { 
			dend2 nmda[i] = new NMDAt(0.5)  synlist.append(nmda[i]) 
	}
	
	for i = 0, 0  {
			dend3 nmda[i] = new NMDAt(0.5)  synlist.append(nmda[i]) 
	}
	
	for i = 0, 0  {
			dend4 nmda[i] = new NMDAt(0.5)  synlist.append(nmda[i]) 
	}
	
	for i = 0, 0  {
			dend5 nmda[i] = new NMDAt(0.5)  synlist.append(nmda[i]) 
	}
	
	for i = 0, 0  {
			dend6 nmda[i] = new NMDAt(0.5)  synlist.append(nmda[i]) 
	}
	
	//Second level dends
	
	for i = 0, 1  {		// 2 in each mid dend
			onode = (i+1)/3	
			dend1_1 nmda[i] = new NMDAt(onode)  synlist.append(nmda[i]) 
	}
	
	for i = 0, 1  {
			onode = (i+1)/3
			dend1_2 nmda[i] = new NMDAt(onode)  synlist.append(nmda[i]) 
	}
	
	for i = 0, 1  {
			onode = (i+1)/3
			dend2_1 nmda[i] = new NMDAt(onode)  synlist.append(nmda[i]) 
	}
	
	for i = 0, 1  {
			onode = (i+1)/3
			dend2_2 nmda[i] = new NMDAt(onode)  synlist.append(nmda[i]) 
	}
	
	for i = 0, 1  {
			onode = (i+1)/3
			dend3_1 nmda[i] = new NMDAt(onode)  synlist.append(nmda[i]) 
	}
	
	for i = 0, 1  {
			onode = (i+1)/3
			dend3_2 nmda[i] = new NMDAt(onode)  synlist.append(nmda[i]) 
	}
	
	for i = 0, 1  {
			onode = (i+1)/3
			dend4_1 nmda[i] = new NMDAt(onode)  synlist.append(nmda[i]) 
	}
	
	for i = 0, 1  {
			onode = (i+1)/3
			dend4_2 nmda[i] = new NMDAt(onode)  synlist.append(nmda[i]) 
	}
	
	for i = 0, 1  {
			onode = (i+1)/3
			dend5_1 nmda[i] = new NMDAt(onode)  synlist.append(nmda[i]) 
	}
	
	for i = 0, 1  {
			onode = (i+1)/3
			dend5_2 nmda[i] = new NMDAt(onode)  synlist.append(nmda[i]) 
	}
	
	for i = 0, 1  {
			onode = (i+1)/3
			dend6_1 nmda[i] = new NMDAt(onode)  synlist.append(nmda[i]) 
	}
	
	for i = 0, 1  {
			onode = (i+1)/3
			dend6_2 nmda[i] = new NMDAt(onode)  synlist.append(nmda[i]) 
	}
	
	//Outer_level Dends
	
	for i = 0, 3  {		// 4 in each dist dend
			onode = (i+1)/5		// 0.2, 0.4, 0.6, 0.8
			dend1_1[1] nmda[i] = new NMDAt(onode)   synlist.append(nmda[i]) 
	}
	
	for i = 0, 3  {
			onode = (i+1)/5		// 0.2, 0.4, 0.6, 0.8
			dend1_1[2] nmda[i] = new NMDAt(onode)   synlist.append(nmda[i]) 
	}
	synloops_1() // continue in next proc to avoid to large a proc error
}  //end synloops



proc synloops_1() {
	for i = 0, 3  {
			onode = (i+1)/5		// 0.2, 0.4, 0.6, 0.8
			dend1_2[1] nmda[i] = new NMDAt(onode)   synlist.append(nmda[i]) 
	}
	
	for i = 0, 3  {
			onode = (i+1)/5		// 0.2, 0.4, 0.6, 0.8
			dend1_2[2] nmda[i] = new NMDAt(onode)   synlist.append(nmda[i]) 
	}
	
	for i = 0, 3  {
			onode = (i+1)/5		// 0.2, 0.4, 0.6, 0.8
			dend2_1[1] nmda[i] = new NMDAt(onode)   synlist.append(nmda[i]) 
	}
	
	for i = 0, 3  {
			onode = (i+1)/5		// 0.2, 0.4, 0.6, 0.8
			dend2_1[2] nmda[i] = new NMDAt(onode)   synlist.append(nmda[i]) 
	}
	
	for i = 0, 3  {
			onode = (i+1)/5		// 0.2, 0.4, 0.6, 0.8
			dend2_2[1] nmda[i] = new NMDAt(onode)   synlist.append(nmda[i]) 
	}
	
	for i = 0, 3  {
			onode = (i+1)/5		// 0.2, 0.4, 0.6, 0.8
			dend2_2[2] nmda[i] = new NMDAt(onode)   synlist.append(nmda[i]) 
	}
	
	for i = 0, 3  {
			onode = (i+1)/5		// 0.2, 0.4, 0.6, 0.8
			dend3_1[1] nmda[i] = new NMDAt(onode)   synlist.append(nmda[i]) 
	}
	
	for i = 0, 3  {
			onode = (i+1)/5		// 0.2, 0.4, 0.6, 0.8
			dend3_1[2] nmda[i] = new NMDAt(onode)   synlist.append(nmda[i]) 
	}
	
	for i = 0, 3  {
			onode = (i+1)/5		// 0.2, 0.4, 0.6, 0.8
			dend3_2[1] nmda[i] = new NMDAt(onode)   synlist.append(nmda[i])
	}
	
	for i = 0, 3  {
			onode = (i+1)/5		// 0.2, 0.4, 0.6, 0.8
			dend3_2[2] nmda[i] = new NMDAt(onode)  synlist.append(nmda[i])
	}
	 
	for i = 0, 3  {
			onode = (i+1)/5		// 0.2, 0.4, 0.6, 0.8
			dend4_1[1] nmda[i] = new NMDAt(onode)   synlist.append(nmda[i])
	}
	
	for i = 0, 3  {
			onode = (i+1)/5		// 0.2, 0.4, 0.6, 0.8
			dend4_1[2] nmda[i] = new NMDAt(onode)   synlist.append(nmda[i])
	}
	
	for i = 0, 3  {
			onode = (i+1)/5		// 0.2, 0.4, 0.6, 0.8
			dend4_2[1] nmda[i] = new NMDAt(onode)   synlist.append(nmda[i])
	}
	
	for i = 0, 3  {
			onode = (i+1)/5		// 0.2, 0.4, 0.6, 0.8
			dend4_2[2] nmda[i] = new NMDAt(onode)   synlist.append(nmda[i])
	}
	for i = 0, 3  {
			onode = (i+1)/5		// 0.2, 0.4, 0.6, 0.8
			dend5_1[1] nmda[i] = new NMDAt(onode)   synlist.append(nmda[i])
	}
	
	for i = 0, 3  {
			onode = (i+1)/5		// 0.2, 0.4, 0.6, 0.8
			dend5_1[2] nmda[i] = new NMDAt(onode)   synlist.append(nmda[i])
	}
	
	for i = 0, 3  {
			onode = (i+1)/5		// 0.2, 0.4, 0.6, 0.8
			dend5_2[1] nmda[i] = new NMDAt(onode)   synlist.append(nmda[i])
	}
	
	for i = 0, 3  {
			onode = (i+1)/5		// 0.2, 0.4, 0.6, 0.8
			dend5_2[2] nmda[i] = new NMDAt(onode)   synlist.append(nmda[i])
	}
	for i = 0, 3  {
			onode = (i+1)/5		// 0.2, 0.4, 0.6, 0.8
			dend6_1[1] nmda[i] = new NMDAt(onode)   synlist.append(nmda[i])
	}
	
	for i = 0, 3  {
			onode = (i+1)/5		// 0.2, 0.4, 0.6, 0.8
			dend6_1[2] nmda[i] = new NMDAt(onode)   synlist.append(nmda[i])
	}
	
	for i = 0, 3  {
			onode = (i+1)/5		// 0.2, 0.4, 0.6, 0.8
			dend6_2[1] nmda[i] = new NMDAt(onode)   synlist.append(nmda[i])
	}
	
	for i = 0, 3  {
			onode = (i+1)/5		// 0.2, 0.4, 0.6, 0.8
			dend6_2[2] nmda[i] = new NMDAt(onode)   synlist.append(nmda[i])
	}
	//***************************
	
	
	
	
	
	//***************************
	//Build GABA synapses
	// soma GABA
	for i = 0, 15 {		// 16 in soma
			soma gaba[i] = new GABAt(0.5) 	synlist.append(gaba[i])
	}
	
	// Inner dends GABA
	for i = 0, 2  {	// 3 each
			dend1 gaba[i] = new GABAt(0.5)    synlist.append(gaba[i]) 
	}
	
	for i = 0, 2  {
			dend2 gaba[i] = new GABAt(0.5)  synlist.append(gaba[i]) 
	
	}
	
	for i = 0, 2 {
			dend3 gaba[i] = new GABAt(0.5)  synlist.append(gaba[i]) 
	
	}
	
	for i = 0, 2  {
			dend4 gaba[i] = new GABAt(0.5)  synlist.append(gaba[i]) 
	
	}
	
	for i = 0, 2 {
			dend5 gaba[i] = new GABAt(0.5)  synlist.append(gaba[i]) 
	
	}
	
	for i = 0, 2  {
			dend6 gaba[i] = new GABAt(0.5)  synlist.append(gaba[i]) 
	
	}
	
	//Second level dends
	for i = 0, 2  {	// 3 each
			dend1_1 gaba[i] = new GABAt(0.5)  synlist.append(gaba[i]) 
	
	}
	
	for i = 0, 2  {
			dend1_2 gaba[i] = new GABAt(0.5)  synlist.append(gaba[i]) 
	
	}
	
	for i = 0, 2  {
			dend2_1 gaba[i] = new GABAt(0.5)  synlist.append(gaba[i]) 
	
	}
	
	for i = 0, 2  {
			dend2_2 gaba[i] = new GABAt(0.5)  synlist.append(gaba[i]) 
	
	}
	
	for i = 0, 2  {
			dend3_1 gaba[i] = new GABAt(0.5)  synlist.append(gaba[i]) 
	
	}
	
	for i = 0, 2  {
			dend3_2 gaba[i] = new GABAt(0.5)  synlist.append(gaba[i]) 
	
	}
	
	for i = 0, 2  {
			dend4_1 gaba[i] = new GABAt(0.5)  synlist.append(gaba[i]) 
	
	}
	
	for i = 0, 2  {
			dend4_2 gaba[i] = new GABAt(0.5)  synlist.append(gaba[i]) 
	
	}
	
	for i = 0, 2  {
			dend5_1 gaba[i] = new GABAt(0.5)  synlist.append(gaba[i]) 
	
	}
	
	for i = 0, 2  {
			dend5_2 gaba[i] = new GABAt(0.5)  synlist.append(gaba[i]) 
	
	}
	
	for i = 0, 2  {
			dend6_1 gaba[i] = new GABAt(0.5)  synlist.append(gaba[i]) 
	
	}
	
	for i = 0, 2  {
			dend6_2 gaba[i] = new GABAt(0.5)  synlist.append(gaba[i]) 
	
	}
	
	//Outer_level Dends
	for i = 0, 1  {			// 2 each
			onode = (i+1)/3		// 0.33, 0.66
			dend1_1[1] gaba[i] = new GABAt(onode)   synlist.append(gaba[i]) 
	}
	
	for i = 0, 1  {
			onode = (i+1)/3
			dend1_1[2] gaba[i] = new GABAt(onode)   synlist.append(gaba[i]) 
	}
	
	for i = 0, 1  {
			onode = (i+1)/3
			dend1_2[1] gaba[i] = new GABAt(onode)   synlist.append(gaba[i]) 
	}
	
	for i = 0, 1  {
			onode = (i+1)/3
			dend1_2[2] gaba[i] = new GABAt(onode)   synlist.append(gaba[i]) 
	}
	
	for i = 0, 1  {
			onode = (i+1)/3
			dend2_1[1] gaba[i] = new GABAt(onode)   synlist.append(gaba[i]) 
	}
	
	for i = 0, 1  {
			onode = (i+1)/3
			dend2_1[2] gaba[i] = new GABAt(onode)   synlist.append(gaba[i]) 
	}
	
	for i = 0, 1  {
			onode = (i+1)/3
			dend2_2[1] gaba[i] = new GABAt(onode)   synlist.append(gaba[i]) 
	}
	
	for i = 0, 1  {
			onode = (i+1)/3
			dend2_2[2] gaba[i] = new GABAt(onode)   synlist.append(gaba[i]) 
	}
	
	for i = 0, 1  {
			onode = (i+1)/3
			dend3_1[1] gaba[i] = new GABAt(onode)   synlist.append(gaba[i]) 
	}
	
	for i = 0, 1  {
			onode = (i+1)/3
			dend3_1[2] gaba[i] = new GABAt(onode)   synlist.append(gaba[i]) 
	}
	
	for i = 0, 1  {
			onode = (i+1)/3
			dend3_2[1] gaba[i] = new GABAt(onode)   synlist.append(gaba[i])
	}
	
	for i = 0, 1  {
			onode = (i+1)/3
			dend3_2[2] gaba[i] = new GABAt(onode)  synlist.append(gaba[i])
	}
	 
	for i = 0, 1  {
			onode = (i+1)/3
			dend4_1[1] gaba[i] = new GABAt(onode)   synlist.append(gaba[i])
	}
	
	for i = 0, 1  {
			onode = (i+1)/3
			dend4_1[2] gaba[i] = new GABAt(onode)   synlist.append(gaba[i])
	}
	
	for i = 0, 1  {
			onode = (i+1)/3
			dend4_2[1] gaba[i] = new GABAt(onode)   synlist.append(gaba[i])
	}
	
	for i = 0, 1  {
			onode = (i+1)/3
			dend4_2[2] gaba[i] = new GABAt(onode)   synlist.append(gaba[i])
	} 
	for i = 0, 1  {
			onode = (i+1)/3
			dend5_1[1] gaba[i] = new GABAt(onode)   synlist.append(gaba[i])
	}
	
	for i = 0, 1  {
			onode = (i+1)/3
			dend5_1[2] gaba[i] = new GABAt(onode)   synlist.append(gaba[i])
	}
	
	for i = 0, 1  {
			onode = (i+1)/3
			dend5_2[1] gaba[i] = new GABAt(onode)   synlist.append(gaba[i])
	}
	
	for i = 0, 1  {
			onode = (i+1)/3
			dend5_2[2] gaba[i] = new GABAt(onode)   synlist.append(gaba[i])
	} 
	for i = 0, 1  {
			onode = (i+1)/3
			dend6_1[1] gaba[i] = new GABAt(onode)   synlist.append(gaba[i])
	}
	
	for i = 0, 1  {
			onode = (i+1)/3
			dend6_1[2] gaba[i] = new GABAt(onode)   synlist.append(gaba[i])
	}
	
	for i = 0, 1  {
			onode = (i+1)/3
			dend6_2[1] gaba[i] = new GABAt(onode)   synlist.append(gaba[i])
	}
	
	for i = 0, 1  {
			onode = (i+1)/3
			dend6_2[2] gaba[i] = new GABAt(onode)   synlist.append(gaba[i])
	}
	//**************************
}	
//end synloops()


endtemplate MSP_Cell

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