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;
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ZhangEtAl2014
Critical Mod Files
AMPA_DynSyn.mod
B_A.mod
B_DR.mod
B_NA.mod
CaIntraCellDyn.mod *
GABAa_DynSyn.mod *
GABAb_DynSyn.mod *
Glycine_DynSyn.mod
HH2.mod *
HH2new.mod *
iCaAN.mod *
iCaL.mod
iKCa.mod *
iNaP.mod *
KDR.mod
KDRI.mod
NK1_DynSyn.mod *
NMDA_DynSyn.mod *
SS.mod
vsource.mod *
                            
TITLE GABA_A receptor with pre-synaptic short-term plasticity 


COMMENT
GABA_A receptor conductance using a dual-exponential profile
Pre-synaptic short-term plasticity based on Fuhrmann et al, 2002

Written by Paulo Aguiar and Mafalda Sousa, IBMC, May 2008
pauloaguiar@fc.up.pt ; mafsousa@ibmc.up.pt
ENDCOMMENT



NEURON {
	POINT_PROCESS GABAa_DynSyn	
	RANGE tau_rise, tau_decay
	RANGE U1, tau_rec, tau_fac
	RANGE i, g, e
	NONSPECIFIC_CURRENT i
}

PARAMETER {
	tau_rise  = 1.0   (ms)  : dual-exponential conductance profile
	tau_decay = 20.0  (ms)  : IMPORTANT: tau_rise < tau_decay
	U1        = 1.0   (1)   : The parameter U1, tau_rec and tau_fac define _
	tau_rec   = 0.1   (ms)  : the pre-synaptic short-term plasticity _
	tau_fac   = 0.1   (ms)  : mechanism (see Fuhrmann et al, 2002)
	e         = -80.0 (mV)  : GABAa synapse reversal potential
}
     

ASSIGNED {
	v (mV)
	i (nA)
	g (umho)
	factor
}

STATE {
	A	: state variable to construct the dual-exponential profile
	B	: 
}

INITIAL{
	LOCAL tp
	A = 0
	B = 0
	tp = (tau_rise*tau_decay)/(tau_decay-tau_rise)*log(tau_decay/tau_rise)
	factor = -exp(-tp/tau_rise)+exp(-tp/tau_decay)
	factor = 1/factor
}

BREAKPOINT {
	SOLVE state METHOD cnexp
	g = B-A
	i = g*(v-e)
}

DERIVATIVE state{
	A' = -A/tau_rise
	B' = -B/tau_decay
}

NET_RECEIVE (weight, Pv, P, Use, t0 (ms)){
	INITIAL{
		P=1
		Use=0
		t0=t
	    }	
	Use = Use * exp(-(t-t0)/tau_fac)
	Use = Use + U1*(1-Use) 
	P   = 1-(1- P) * exp(-(t-t0)/tau_rec)
	Pv  = Use * P
	P   = P - Use * P
	
	t0 = t
	
	A = A + weight*factor*Pv
	B = B + weight*factor*Pv	
}

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