Effects of spinal cord stimulation on WDR dorsal horn network (Zhang et al 2014)

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Accession:168414
" ... To study the mechanisms underlying SCS (Spinal cord stimulation), we constructed a biophysically-based network model of the dorsal horn circuit consisting of interconnected dorsal horn interneurons and a wide dynamic range (WDR) projection neuron and representations of both local and surround receptive field inhibition. We validated the network model by reproducing cellular and network responses relevant to pain processing including wind-up, A-fiber mediated inhibition, and surround receptive field inhibition. ..." See paper for more.
Reference:
1 . Zhang TC, Janik JJ, Grill WM (2014) Modeling effects of spinal cord stimulation on wide-dynamic range dorsal horn neurons: influence of stimulation frequency and GABAergic inhibition. J Neurophysiol 112:552-67 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Realistic Network;
Brain Region(s)/Organism:
Cell Type(s): Wide dynamic range neuron;
Channel(s):
Gap Junctions:
Receptor(s): GabaA; AMPA; NMDA; Glutamate; Glycine;
Gene(s):
Transmitter(s):
Simulation Environment: NEURON;
Model Concept(s):
Implementer(s): Zhang, Tianhe [tz5@duke.edu];
Search NeuronDB for information about:  GabaA; AMPA; NMDA; Glutamate; Glycine;
/
ZhangEtAl2014
Foreman SCS
CellTemplates.hoc *
CellTempList.dat *
CellTypeVector.txt *
CellVector.txt *
Connectivities_Surround_ERev_70.xls
Coordinates_Trial.xlsx *
DelayVector.txt *
ERevVector.txt
EX_Cell_filenames.dat *
EX_Cell_filenamesH.dat *
EX_Cell_filenamesM.dat *
EX_Cell_SynapseID.dat *
EX_Cell_Synapses_OneEX_Zone2_SCS.txt *
FromVector.txt *
MakeNetwork.hoc *
MATLAB_Afferent_Spikes_Foreman.mat
MATLAB_Afferent_Spikes_Foreman_Grouped.mat
nrnmech.dll *
RunSim_Foreman.hoc
S_NetStim_SynapseID.dat *
SG_Cell_filenames.dat *
SG_Cell_filenamesH.dat *
SG_Cell_filenamesM.dat *
SG_Cell_Pair_1_Vm.png *
SG_Cell_SynapseID.dat *
SG_Cell_Synapses_OneEX_Multiconn_Glycine.dat *
SG_Cell_Synapses_OneEX_Zone2_SCS.txt *
SGSCS_Cell_filenames.dat *
SGSCS_Cell_filenamesH.dat *
SGSCS_Cell_filenamesM.dat *
SGSCS_Cell_SynapseID.dat *
SGSCS_Cell_Synapses_OneEX_Zone2_SCS.txt *
SGZ2_Cell_Synapses_OneEX_Zone2_SCS.txt *
Shell.hoc
SpikeStatsVector.txt
SpikeTimesVector.txt
SynapseVector.txt *
T_Cell_filenames.dat *
T_Cell_filenamesH.dat *
T_Cell_filenamesM.dat *
T_Cell_SpikeCount.png *
T_Cell_SynapseID.dat *
T_Cell_Synapses_OneEX_Zone2_SCS.txt *
ThresholdVector.txt *
ToVector.txt *
WeightVector.txt
XVector.txt *
YVector.txt *
ZVector.txt *
                            
//Template file for all cell types used in the network described in Zhang TC et al., J. Neurophysiology, 2014.  Relevant geometric and cellular parameters are listed within each "template."  Units for all values used listed at bottom (scroll down) of .hoc file.

load_file("nrngui.hoc")

begintemplate MelnickSG //This is "SG Cell" and "SGSCS Cell"

//From Melnick et al. J. Physiol (2004) Modified by Tianhe C. Zhang (tz5@duke.edu).

ndend=1

public soma, hillock, axon, dend
public synlist, x, y, z, position, connect2target
objref synlist, syn_
create soma, hillock, axon, dend


proc init(){
access soma
{diam=10 L=10 nseg=10} // area 100 um2 means mA/cm2 identical to nA 
insert B_Na
insert B_A
insert B_DR
insert KDR
insert KDRI
insert pas
{gnabar_B_Na = 0.008 ena = 60 g_pas = 1.1e-05 e_pas = -70 gkbar_KDRI = 0.0043 ek = -84}

access hillock
{L=30 nseg=30 dsoma=1 daxon=0.5 diam(0:1)=dsoma:daxon} 
insert B_Na
insert B_A
insert B_DR
insert KDR
insert KDRI
insert pas
{gnabar_B_Na = 3.45 ena = 60 g_pas = 1.1e-05 e_pas = -70 gkbar_KDRI = 0.076 ek = -84} // Tonic firing with maintained I-F characteristics.

access axon //Stump to measure AP propagation.  No other purpose.
{diam=0.001 L=0.001 nseg=50}
insert B_Na
insert B_A
insert B_DR
insert KDR
insert KDRI
insert pas
{gnar_B_Na = 0 ena = 60 g_pas = 0 e_pas = -70 gkbar_KDRI = 0 ek = -84}

access dend
{nseg=50 diam=1.4 L = 1371}
insert SS
insert B_DR
insert KDR
insert KDRI	
insert pas
{gnabar_SS = 0 ena = 60 g_pas = 1.1e-05 e_pas = -70 gkbar_KDRI = 0.034 ek = -84}

soma connect hillock(0),1
hillock connect axon(0),1
soma connect dend(0),0

forall Ra = 80 

synlist = new List()

synapses()

x = y = z = 0

}

objref SynapseID, SynapseFile, NumVec
strdef SynapseIDFile

proc synapses(){
//Uploads list of files that contains the number of each type of synapse (see below) corresponding to each neuron of this type in the system.

SynapseFile = new File()
SynapseID = new File()
SynapseID.ropen("SG_Cell_SynapseID.dat")
SynapseID.scanstr(SynapseIDFile)
SynapseID.close()
NumVec = new Vector()

SynapseFile.ropen(SynapseIDFile)
NumVec.scantil(SynapseFile, -1e15)
SynapseFile.close()

//Assigns synapses based on synapse counts obtained from "SynapseFile".  Unfortunately, synapse composition can't be dynamically defined using HOC, so one must redo the list below if synapse counts need to be changed.

for num = 0, NumVec.x[0]-1{
dend syn_ = new AMPA_DynSyn(0.5) syn_.tau_rise = 0.1 syn_.tau_decay = 5 synlist.append(syn_)
}
for num = 0, NumVec.x[1]-1{
dend syn_ = new AMPA_DynSyn(0.5) syn_.tau_rise = 0.1 syn_.tau_decay = 5 synlist.append(syn_)
}
}

proc position() { local i  // Optional feature.  This allows coupling of neuron to extracellular space e.g. for simulations of extracellular stimulation.
  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
}

obfunc connect2target() { localobj nc //$o1 target point process, optional $o2 returned NetCon.  "Black box."
  soma nc = new NetCon(&v(1), $o1)
  nc.threshold = -30
  if (numarg() == 2) { $o2 = nc } // for backward compatibility
  return nc
}

endtemplate MelnickSG


//*NEW TEMPLATE*//
//*NEW TEMPLATE*//
//*NEW TEMPLATE*//


begintemplate AguiarIN// This is "EX Cell".

//Created by Paulo Aguiar [pauloaguiar@fc.up.pt].  Modified by Tianhe C. Zhang (tz5@duke.edu)

public soma, dend, hillock, axon, synlist, x, y, z, position, connect2target
create soma, dend, hillock, axon
objref synlist, syn_

proc init() {
x = y = z = 0
create soma // Soma
 
     soma {    
	nseg = 3  
	L = 20.0
	diam = 20.0
	
	//HH channels: iK
	insert HH2 {
	    gnabar_HH2 = 0.00  // Na not in soma.
	    gkbar_HH2 = 0.0043*1/4 // Scaled to safronov et al. (1997) and Wolff et al.(1998) ratios.
	    vtraub_HH2 = -55.0
	}
	
	//intracellular Ca dynamics
	insert CaIntraCellDyn {
	    depth_CaIntraCellDyn = 0.1
	    cai_tau_CaIntraCellDyn = 1.0
	    cai_inf_CaIntraCellDyn = 50.0e-6
	}
	
	//potassium current dependent on intracellular calcium concentration 
	insert iKCa {
	    gbar_iKCa = 0.002 //0.002
	}
	
	insert pas // Passive parameters.
	g_pas = 4.2e-5
	e_pas = -65.0
	ek = -70.0
	Ra = 150.0
    }
    
create dend // Single dendrite. 
 
    dend {    
	nseg = 5    
	L = 400.0  
	diam = 3.0

	//HH channels: iNat and iK
	insert HH2{
	    gnabar_HH2 = 0.000
	    gkbar_HH2 = 0.036 // *5/6
	}
	
	//intracellular Ca dynamics
	insert CaIntraCellDyn {
	    depth_CaIntraCellDyn = 0.1
	    cai_tau_CaIntraCellDyn = 2.0
	    cai_inf_CaIntraCellDyn = 50.0e-6
	}

	//potassium current dependent on intracellular calcium concentration 
	insert iKCa {
	    gbar_iKCa = 0.002 //0.002
	}	
	
	insert pas
	g_pas = 4.2e-5
	e_pas = -65.0
	ek = -70.0
	Ra = 150.0
    }
    
    
create hillock

    hillock {   
	nseg = 3  
	L = 9.0
	diam(0:1) = 2.0:1.0
	
	//HH channels: iNa,t and iK
	insert HH2 {
	    gnabar_HH2 = 3.45
	    gkbar_HH2 = 0.076
	    vtraub_HH2 = -55.0
	}
	
	insert pas
	g_pas = 4.2e-5
	e_pas = -65.0
	Ra = 150.0
    }
    
    create axon
    axon {    
	nseg = 5
	L = 1000.0
	diam = 1.0
	
	//HH channels: iNa,t and iK
	insert HH2 {
	    gnabar_HH2 = 0.0
	    gkbar_HH2 = 0.00	//0.06
	    vtraub_HH2 = -55
	}
	
	insert pas
	g_pas = 4.2e-5
	e_pas = -65.0
	Ra = 150.0
    }
    
    //CONNECTIONS between cell elements.
    soma connect hillock(0),1
    hillock connect axon(0),1
    soma connect dend(0),0 

    synlist = new List()
    synapses()
}

proc position() { local i // Optional feature.  This allows coupling of neuron to extracellular space e.g. for simulations of extracellular stimulation.
  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
}

obfunc connect2target() { localobj nc //$o1 target point process, optional $o2 returned NetCon
  soma nc = new NetCon(&v(1), $o1)
  nc.threshold = -30
  if (numarg() == 2) { $o2 = nc } // for backward compatibility
  return nc
}


objref SynapseID, SynapseFile, NumVec
strdef SynapseIDFile

proc synapses(){
//Uploads list of files that contains the number of each type of synapse (see below) corresponding to each neuron of this type in the system.

SynapseFile = new File()
SynapseID = new File()
SynapseID.ropen("EX_Cell_SynapseID.dat")
SynapseID.scanstr(SynapseIDFile)
SynapseID.close()
NumVec = new Vector()

SynapseFile.ropen(SynapseIDFile)
NumVec.scantil(SynapseFile, -1e15)
SynapseFile.close()

//Assigns synapses based on synapse counts obtained from "SynapseFile".  Unfortunately, synapse composition can't be dynamically defined using HOC, so one must redo the list below if synapse counts need to be changed.

for num = 0, 29{
dend syn_ = new AMPA_DynSyn(0.5) syn_.tau_rise = 0.1 syn_.tau_decay = 5 synlist.append(syn_)
}
for num = 0, 29{
dend syn_ = new NMDA_DynSyn(0.5) syn_.tau_rise = 2 syn_.tau_decay = 100 synlist.append(syn_)
}
for num = 0, 29{
dend syn_ = new NK1_DynSyn(0.5) syn_.tau_rise = 100 syn_.tau_decay = 3000 synlist.append(syn_)
}
for num = 0, 1{
dend syn_ = new GABAa_DynSyn(0.5) syn_.tau_rise = 0.1 syn_.tau_decay = 20 syn_.e = -70 synlist.append(syn_)
}
for num = 0, 1{
dend syn_ = new GABAa_DynSyn(0.5) syn_.tau_rise = 0.1 syn_.tau_decay = 20 syn_.e = -70 synlist.append(syn_)
}

}

endtemplate AguiarIN


//*NEW TEMPLATE*//
//*NEW TEMPLATE*//
//*NEW TEMPLATE*//

//Created by Paulo Aguiar [pauloaguiar@fc.up.pt].  Modified by Tianhe C. Zhang (tz5@duke.edu)

// CREATE WDR NEURON

begintemplate AguiarWDR // This is "T_Cell"

public soma, dend, hillock, axon, x, y, z, position, connect2target
public synlist
objref syn_, synlist
create soma, dend, hillock, axon

proc init() {
 
x = y = z = 0
cascale = 1 // Scale calcium currents responsible for wind-up.  Set to 0 to eliminate calcium currents without having to change template codes below.  Do not set to a negative value unless a very good reason is found to do so.

create soma    

    soma {    
	nseg = 3  
	L = 20.0
	diam = 20.0
	
	//HH channels: iNat and iK
	insert HH2 { //No AP Initiation in the soma?
		gnabar_HH2 = 0.000 //"Default" 0.08.  Melnick 0.008.
		gkbar_HH2 = 0.0043*6/24  //0.3e-3 in P&D. "/4" is there in parallel with Safronov.
		vtraub_HH2 = -55.0
	}
	
	//intracellular Ca dynamics
	insert CaIntraCellDyn {
	    depth_CaIntraCellDyn = 0.1
	    cai_tau_CaIntraCellDyn = 1.0
	    cai_inf_CaIntraCellDyn = 50.0e-6
	}

	//high-voltage activated long-lasting calcium current, L-type
	insert iCaL {
	    pcabar_iCaL = 0.0001 * cascale//0.0001- IMPORTANT: this current drives the (activity control) somatic iKCa current
	}      
 
	//non-specific current dependent on intracellular calcium concentration 
	insert iCaAN {
	    gbar_iCaAN = 0.0000 //0.00000
	}    

	//potassium current dependent on intracellular calcium concentration 
	insert iKCa {
	    gbar_iKCa = 0.0001 * cascale //0.0001
	}

	//sodium persistent current
	insert iNaP {
	    gnabar_iNaP = 0.0001 * cascale//0.0001
	}    

	insert pas
	g_pas = 4.2e-5
	e_pas = -65.0
	ek = -70.0
	Ra = 150.0
    }
    
create dend

    dend {    
	nseg = 5    
	L = 350.0     
	diam = 2.5
	
	//intracellular Ca dynamics
	insert CaIntraCellDyn {
	    depth_CaIntraCellDyn = 0.1
	    cai_tau_CaIntraCellDyn = 2.0
	    cai_inf_CaIntraCellDyn = 50.0e-6
	}

	//high-voltage activated long-lasting calcium current, L-type
	insert iCaL {
	    pcabar_iCaL = 3e-5 * cascale //3.0e-5 IMPORTANT: this current is important for activity control (drives the iKCa current).  cascale currently set to 1.
	}             
    
	//non-specific current dependent on intracellular calcium concentration 
	insert iCaAN {
	    gbar_iCaAN = 0.00007 * cascale * 1.3 //0.00007; This is a sensible parameter
	    //higher values of gbar_iCaAN produce graphs similar to Silviloti et al 93.  Need 1.3 scalar to match up to Herrero (2000).
	}        

	//potassium current dependent on intracellular calcium concentration 
	insert iKCa {
	    gbar_iKCa = 0.001 * cascale//0.001; higher values place "holes" in the scatter plot, resulting from the cai bump after synaptic activation);
		//naturally, lower values will lead to increased firing
	}
	
	insert HH2{
	    gnabar_HH2 = 0.000
	    gkbar_HH2 = 0.036 // *5/6
	}

	insert pas
	g_pas = 4.2e-5
	e_pas = -65.0
	ek = -70.0
	Ra = 150.0
    }
    
create hillock

hillock {   
	nseg = 3  
	L = 9 //Note that default is 3.
	diam(0:1) = 2.0:1.0
	
	//HH channels: iNa,t and iK
	insert HH2 {
	    gnabar_HH2 = 3.45 //Remember Melnick is 3.45.  "/4" is for surface area compensation.
	    gkbar_HH2 = 0.076 // Default 0.04.  POss. need to scale by 0.25.  Check I-F with normal K.
	    vtraub_HH2 = -55.0
	}

	insert B_A{
	   gkbar_B_A = 0.0 // A-current for delayed firing.
	}

	insert pas
	g_pas = 4.2e-5
	e_pas = -65.0
	Ra = 150.0
    }
    
create axon

    axon {    // Axon is a single node "stump" used only to check action potential propagation.
	nseg = 5
	L = 1000
	diam = 1.0
	
	//HH channels: iNa,t and iK
	insert HH2 {
	    gnabar_HH2 = 0 //0.1
	    gkbar_HH2 = 0	//0.04
	    vtraub_HH2 = -55
	}

	insert pas // Axon is a single node "stump."
	g_pas = 0
	e_pas = -65.0	
	Ra = 150.0
    }
    
//CONNECTIONS between neural elements.
soma connect hillock(0),1
hillock connect axon(0),1
soma connect dend(0),0 

synlist = new List()
synapses()

}

objref SynapseID, SynapseFile, NumVec
strdef SynapseIDFile

proc synapses(){

//Uploads list of files that contains the number of each type of synapse (see below) corresponding to each neuron of this type in the system.

SynapseFile = new File()
SynapseID = new File()
SynapseID.ropen("T_Cell_SynapseID.dat")
SynapseID.scanstr(SynapseIDFile)
SynapseID.close()
NumVec = new Vector()

//Assigns synapses based on synapse counts obtained from "SynapseFile".  Unfortunately, synapse composition can't be dynamically defined using HOC, so one must redo the list below if synapse counts need to be changed.

SynapseFile.ropen(SynapseIDFile)
NumVec.scantil(SynapseFile, -1e15)
SynapseFile.close()

for num = 0, 14{
dend syn_ = new AMPA_DynSyn(0.5) syn_.tau_rise = 0.1 syn_.tau_decay = 5 synlist.append(syn_)
}
for num = 0, 14{
dend syn_ = new NMDA_DynSyn(0.5) syn_.tau_rise = 2 syn_.tau_decay = 100 synlist.append(syn_)
}
for num = 0, 14{
dend syn_ = new AMPA_DynSyn(0.5) syn_.tau_rise = 0.1 syn_.tau_decay = 5 synlist.append(syn_)
}
for num = 0, 14{
dend syn_ = new NMDA_DynSyn(0.5) syn_.tau_rise = 2 syn_.tau_decay = 100 synlist.append(syn_)
}
for num = 0, 29{
dend syn_ = new NK1_DynSyn(0.5) syn_.tau_rise = 200 syn_.tau_decay = 3000 synlist.append(syn_)
}
for num = 0, 29{
dend syn_ = new AMPA_DynSyn(0.5) syn_.tau_rise = 0.1 syn_.tau_decay = 5 synlist.append(syn_)
}
for num = 0, 29{
dend syn_ = new NMDA_DynSyn(0.5) syn_.tau_rise = 2 syn_.tau_decay = 100 synlist.append(syn_)
}
for num = 0, 0{
dend syn_ = new Glycine_DynSyn(0.5) syn_.tau_rise = 0.1 syn_.tau_decay = 10 synlist.append(syn_)
}
for num = 0, 0{
dend syn_ = new GABAa_DynSyn(0.5) syn_.tau_rise = 0.1 syn_.tau_decay = 20 syn_.e = -70 synlist.append(syn_)
}
for num = 0, 0{
dend syn_ = new GABAa_DynSyn(0.5) syn_.tau_rise = 0.1 syn_.tau_decay = 20 syn_.e = -70 synlist.append(syn_)
}
for num = 0, 0{
dend syn_ = new GABAa_DynSyn(0.5) syn_.tau_rise = 0.1 syn_.tau_decay = 20 syn_.e = -70 synlist.append(syn_)
}
}

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
}

obfunc connect2target() { localobj nc //$o1 target point process, optional $o2 returned NetCon
  soma nc = new NetCon(&v(1), $o1)
  nc.threshold = -30
  if (numarg() == 2) { $o2 = nc } // for backward compatibility
  return nc
}

endtemplate AguiarWDR

begintemplate S_NetStim 

//DUMMY NetStims; These are only included because Syn objects must be connected to NetCon object as noted in General Readme file.

public pp, connect2target, x, y, z, position, is_art
objref pp
proc init() {
  pp = new NetStim()
    pp.interval = 0
    pp.number = 0
    pp.start = 0
}

func is_art() { return 1 }
obfunc connect2target() { localobj nc
  nc = new NetCon(pp, $o1)
  if (numarg() == 2) { $o2 = nc }
  return nc
}

proc position(){x=$1  y=$2  z=$3}
endtemplate S_NetStim


//Network specification interface.  This is called in "MakeNetwork.hoc."  Black box.
objref cells, nclist, netcon
{cells = new List()  nclist = new List()}

func cell_append() {cells.append($o1)  $o1.position($2,$3,$4)
	return cells.count - 1
}

func nc_append() {//srcindex, tarcelindex, synindex
  if ($3 >= 0) {
    netcon = cells.object($1).connect2target(cells.object($2).synlist.object($3))
    netcon.weight = $4   netcon.delay = $5
  }else{
    netcon = cells.object($1).connect2target(cells.object($2).pp)
    netcon.weight = $4   netcon.delay = $5
  }
  nclist.append(netcon)
  return nclist.count - 1
}



//************************************************************************************
//UNITS	    
//Category          Variable        [Units]  (notes)

//Time                  t	    [ms]
//Voltage               v	    [mV]
//Current               i	    [mA/cm2] (distributed)	[nA] (point process)
//Concentration		ko, ki, etc.	[mM]
//Specific capacitance	cm          [uf/cm2]
//Length                diam, L     [um]
//Conductance		g	    [S/cm2]  (distributed)	[uS] (point process)
//Cytoplasmic resistivity  Ra	    [ohm cm]
//Resistance	        Ri	    [10E6 ohm]

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