Afferent Integration in the NAcb MSP Cell (Wolf et al. 2005)

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Accession:112834
"We describe a computational model of the principal cell in the nucleus accumbens (NAcb), the medium spiny projection (MSP) neuron. The model neuron, constructed in NEURON, includes all of the known ionic currents in these cells and receives synaptic input from simulated spike trains via NMDA, AMPA, and GABAA receptors. ... results suggest that afferent information integration by the NAcb MSP cell may be compromised by pathology in which the NMDA current is altered or modulated, as has been proposed in both schizophrenia and addiction."
Reference:
1 . Wolf JA, Moyer JT, Lazarewicz MT, Contreras D, Benoit-Marand M, O'Donnell P, Finkel LH (2005) NMDA/AMPA ratio impacts state transitions and entrainment to oscillations in a computational model of the nucleus accumbens medium spiny projection neuron. J Neurosci 25:9080-95 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Neuron or other electrically excitable cell;
Brain Region(s)/Organism:
Cell Type(s): Nucleus accumbens spiny projection neuron;
Channel(s): I Na,p; I Na,t; I L high threshold; I N; I T low threshold; I A; I h; I K,Ca; I Krp; I R; I Q;
Gap Junctions:
Receptor(s): GabaA; AMPA; NMDA;
Gene(s):
Transmitter(s):
Simulation Environment: NEURON;
Model Concept(s): Oscillations; Schizophrenia; Addiction;
Implementer(s): Wolf, John A. [johnwolf at warpmail.net]; Moyer, Jason [jtmoyer at seas.upenn.edu];
Search NeuronDB for information about:  GabaA; AMPA; NMDA; I Na,p; I Na,t; I L high threshold; I N; I T low threshold; I A; I h; I K,Ca; I Krp; I R; I Q;
/
nacb_msp
tau_tables
readme.html
AMPA.mod
bkkca.mod *
cadyn.mod *
caL.mod *
caL13.mod *
caldyn.mod
can.mod *
caq.mod *
car.mod *
cat.mod *
GABA.mod *
kaf.mod *
kas.mod *
kir.mod *
krp.mod *
naf.mod *
nap.mod *
NMDA.mod
skkca.mod *
stim.mod *
_run_me.hoc
all_tau_vecs.hoc *
baseline_values.txt *
basic_procs.hoc
create_mspcells.hoc *
current_clamp.ses *
make_netstims.hoc
mosinit.hoc *
msp_template.hoc
nacb_main.hoc
netstims_template.hoc *
screenshot.jpg
screenshot2.jpg
stimxout_jns_sqwave.dat
synapse_templates.hoc
                            
//**************************************************************************
// 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 all, Prox_Dend, Mid_Dend, Dist_Dend
public leaf
public gaba, ampa, nmda

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]

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

proc init() { 
	topol()
	subsets()
	geom()
	biophys()
	
	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 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)
  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)}
}

objref all, Prox_Dend, Mid_Dend, Dist_Dend

proc subsets() { local i
  objref all, Prox_Dend, Mid_Dend, Dist_Dend
  all = new SectionList()
    soma all.append()
    dend1 all.append()
    dend2 all.append()
    dend3 all.append()
    dend4 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()

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

  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()

}

// 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() {
  forsec Prox_Dend { L = 20     diam = 2.25 }	
  forsec Mid_Dend  {L = 24.23	diam = 1.10}	// { L = 20		diam = 1 * (1+0.3) }	
  forsec Dist_Dend {L = 395.2	diam = 0.72}	// { L = 190	diam = 0.5 * (1+2) } 
  soma {  L = 16  diam = 16  }
}




//**********
// 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 = 0.15

	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 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 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 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 krp
	insert bkkca
	insert skkca
	
	insert caldyn
	insert caL
	insert caL13

	insert cadyn
	insert can
	insert caq
	insert car	
	insert cat
 
 }
}

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]) 
	}
	
	//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]) 
	}
	
	//Outer_level Dends
	
	for i = 0, 3  {				// 4 in each distal 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
			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]) 
	}
	
	//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]) 
	}
	
	//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])
	}
	//***************************
	
	
	
	
	
	//***************************
	//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]) 
	
	}
	
	//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]) 
	
	}
	
	//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])
	}
	//**************************
}	// end synloops()

endtemplate MSP_Cell

//**************************************************************************


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