Pyramidal neuron conductances state and STDP (Delgado et al. 2010)

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Neocortical neurons in vivo process each of their individual inputs in the context of ongoing synaptic background activity, produced by the thousands of presynaptic partners a typical neuron has. That background activity affects multiple aspects of neuronal and network function. However, its effect on the induction of spike-timing dependent plasticity (STDP) is not clear. Using the present biophysically-detailed computational model, it is not only able to replicate the conductance-dependent shunting of dendritic potentials (Delgado et al,2010), but show that synaptic background can truncate calcium dynamics within dendritic spines, in a way that affects potentiation more strongly than depression. This program uses a simplified layer 2/3 pyramidal neuron constructed in NEURON. It was similar to the model of Traub et al., J Neurophysiol. (2003), and consisted of a soma, an apical shaft, distal dendrites, five basal dendrites, an axon, and a single spine. The spine’s location was variable along the apical shaft (initial 50 μm) and apical. The axon contained an axon hillock region, an initial segment, segments with myelin, and nodes of Ranvier, in order to have realistic action potential generation. For more information about the model see supplemental material, Delgado et al 2010.
1 . Delgado JY, Gómez-González JF, Desai NS (2010) Pyramidal neuron conductance state gates spike-timing-dependent plasticity. J Neurosci 30:15713-25 [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: Auditory cortex;
Cell Type(s): Neocortex L2/3 pyramidal GLU cell;
Channel(s): I Na,p; I Sodium; I Calcium; I Potassium; I_AHP;
Gap Junctions:
Receptor(s): AMPA; NMDA;
Simulation Environment: NEURON;
Model Concept(s): Action Potentials; STDP; Calcium dynamics; Conductance distributions; Audition;
Implementer(s): Gomez-Gonzalez, JF [jfcgomez at]; Delgado JY, [jyamir at];
Search NeuronDB for information about:  Neocortex L2/3 pyramidal GLU cell; AMPA; NMDA; I Na,p; I Sodium; I Calcium; I Potassium; I_AHP;


Sodium channel, Hodgkin-Huxley style kinetics.  

Kinetics were fit to data from Huguenard et al. (1988) and Hamill et
al. (1991)

qi is not well constrained by the data, since there are no points
between -80 and -55.  So this was fixed at 5 while the thi1,thi2,Rg,Rd
were optimized using a simplex least square proc

voltage dependencies are shifted approximately from the best
fit to give higher threshold

Author: Zach Mainen, Salk Institute, 1994,



	RANGE m, h, gna, gbar
	GLOBAL tha, thi1, thi2, qa, qi, qinf, thinf
	RANGE minf, hinf, mtau, htau
	GLOBAL Ra, Rb, Rd, Rg
	GLOBAL q10, temp, tadj, vmin, vmax, vshift

	gbar  	(pS/um2)	: 0.12 mho/cm2     (1000)
	vshift = -3.5 	(mV)		: voltage shift (affects all), changed to obtain AP in spines (-10)
	tha  = -50	(mV)		: v 1/2 for act		(-42)
	qa   = 9	(mV)		: act slope		
	Ra   = 0.182	(/mV/ms)	: open (v)		
	Rb   = 0.124	(/mV/ms)	: close (v)		

	thi1  = -42	(mV)		: v 1/2 for inact        (-50)	
	thi2  = -75	(mV)		: v 1/2 for inact 	 (-75)
	qi   = 5	(mV)	        : inact tau slope
	thinf  = -65	(mV)		: inact inf slope	
	qinf  = 6.2	(mV)		: inact inf slope
	Rg   = 0.0091	(/mV/ms)	: inact (v)	
	Rd   = 0.024	(/mV/ms)	: inact recov (v) 

	temp = 23	(degC)		: original temp 
	q10  = 2.3			: temperature sensitivity

	v 		(mV)
	dt		(ms)
	celsius		(degC)
	vmin = -120	(mV)
	vmax = 100	(mV)

	(mA) = (milliamp)
	(mV) = (millivolt)
	(pS) = (picosiemens)
	(um) = (micron)

	ina 		(mA/cm2)
	gna		(pS/um2)
	ena		(mV)
	minf 		hinf
	mtau (ms)	htau (ms)

STATE { m h }

	m = minf
	h = hinf

        SOLVE states
        gna = tadj*gbar*m*m*m*h
	ina = (1e-4) * gna * (v - ena)

LOCAL mexp, hexp 

PROCEDURE states() {   :Computes state variables m, h, and n 
        trates(v+vshift)      :             at the current v and dt.
        m = m + mexp*(minf-m)
        h = h + hexp*(hinf-h)
        return 0;

PROCEDURE trates(v (mV)) {  
        LOCAL tinc
        TABLE minf, mexp, hinf, hexp
	DEPEND dt, celsius, temp, Ra, Rb, Rd, Rg, tha, thi1, thi2, qa, qi, qinf
	FROM vmin TO vmax WITH 199

	rates(v): not consistently executed from here if usetable == 1

        tadj = q10^((celsius - temp)/10(degC))
        tinc = -dt * tadj

        mexp = 1 - exp(tinc/mtau)
        hexp = 1 - exp(tinc/htau)

PROCEDURE rates(vm (mV)) {  
        LOCAL  a, b

	a = trap0(vm,tha,Ra,qa)
	b = trap0(-vm,-tha,Rb,qa)
	mtau = 1/(a+b)
	minf = a*mtau

		:"h" inactivation 

	a = trap0(vm,thi1,Rd,qi)
	b = trap0(-vm,-thi2,Rg,qi)
	htau = 1/(a+b)
	hinf = 1/(1+exp((vm-thinf)/qinf))

FUNCTION trap0(v (mV), th (mV), a (/mV/ms), q (mV)) (/ms) {
	if (fabs(v/th) > 1e-6) {
	        trap0 = a * (v - th) / (1 - exp(-(v - th)/q))
	} else {
	        trap0 = a * q

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