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

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Accession:144482
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.
Reference:
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;
Gene(s):
Transmitter(s):
Simulation Environment: NEURON;
Model Concept(s): Action Potentials; STDP; Calcium dynamics; Conductance distributions; Audition;
Implementer(s): Gomez-Gonzalez, JF [jfcgomez at ull.edu.es]; Delgado JY, [jyamir at ucla.edu];
Search NeuronDB for information about:  Neocortex L2/3 pyramidal GLU cell; AMPA; NMDA; I Na,p; I Sodium; I Calcium; I Potassium; I_AHP;
COMMENT
T-type Ca channel 
ca.mod to lead to thalamic ca current inspired by destexhe and huguenrd
Uses fixed eca instead of GHK eqn
changed from (AS Oct0899)
changed for use with Ri18  (B.Kampa 2005)
changed the suffix for ease of implementation in (Delgado J.Y. )
ENDCOMMENT

INDEPENDENT {t FROM 0 TO 1 WITH 1 (ms)}

NEURON {
	SUFFIX cat
	USEION ca READ eca WRITE ica
	RANGE m, h, gca, gbar
	RANGE minf, hinf, mtau, htau, inactF, actF
	GLOBAL  vshift,vmin,vmax, v12m, v12h, vwm, vwh, am, ah, vm1, vm2, vh1, vh2, wm1, wm2, wh1, wh2
}

PARAMETER {
	gbar = 0.0008 (mho/cm2)	: 0.12 mho/cm2
	vshift = 0	(mV)		: voltage shift (affects all)

	cao  = 2.5	(mM)	        : external ca concentration
	cai		(mM)
						 
	v 		(mV)
	dt		(ms)
	celsius		(degC)
	vmin = -120	(mV)
	vmax = 100	(mV)

	v12m=50         	(mV)
	v12h=78         	(mV)
	vwm =7.4         	(mV)
	vwh=5.0         	(mV)
	am=3         	(mV)
	ah=85         	(mV)
	vm1=25         	(mV)
	vm2=100         	(mV)
	vh1=46         	(mV)
	vh2=405         	(mV)
	wm1=20         	(mV)
	wm2=15         	(mV)
	wh1=4         	(mV)
	wh2=50         	(mV)


}


UNITS {
	(mA) = (milliamp)
	(mV) = (millivolt)
	(pS) = (picosiemens)
	(um) = (micron)
	FARADAY = (faraday) (coulomb)
	R = (k-mole) (joule/degC)
	PI	= (pi) (1)
} 

ASSIGNED {
	ica 		(mA/cm2)
	gca		(pS/um2)
	eca		(mV)
	minf 		hinf
	mtau (ms)	htau (ms)
	tadj
}
 

STATE { m h }

INITIAL { 
	trates(v+vshift)
	m = minf
	h = hinf
}

BREAKPOINT {
        SOLVE states
        gca = gbar*m*m*h
	ica = gca * (v - eca)
} 

LOCAL mexp, hexp

PROCEDURE states() {
        trates(v+vshift)      
        m = m + mexp*(minf-m)
        h = h + hexp*(hinf-h)
	VERBATIM
	return 0;
	ENDVERBATIM
}


PROCEDURE trates(v) {  
                      
        LOCAL tinc
        TABLE minf, mexp, hinf, hexp
	DEPEND dt	
	FROM vmin TO vmax WITH 199

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

        tinc = -dt 

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


PROCEDURE rates(v_) {  
        LOCAL  a, b

	minf = 1.0 / ( 1 + exp(-(v_+v12m)/vwm) )
	hinf = 1.0 / ( 1 + exp((v_+v12h)/vwh) )

	mtau = ( am + 1.0 / ( exp((v_+vm1)/wm1) + exp(-(v_+vm2)/wm2) ) ) 
	htau = ( ah + 1.0 / ( exp((v_+vh1)/wh1) + exp(-(v_+vh2)/wh2) ) ) 
}

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