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]
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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

kca.mod

Calcium-dependent potassium channel
Based on
Pennefather (1990) -- sympathetic ganglion cells
taken from
Reuveni et al (1993) -- neocortical cells

Author: Zach Mainen, Salk Institute, 1995, zach@salk.edu
	
ENDCOMMENT

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

NEURON {
	SUFFIX kca
	USEION k READ ek WRITE ik
	USEION ca READ cai
	RANGE n, gk, gbar
	RANGE ninf, ntau
	GLOBAL Ra, Rb, caix
	GLOBAL q10, temp, tadj, vmin, vmax
}

UNITS {
        (molar) = (1/liter)
        (mM) = (millimolar)
	(mA) = (milliamp)
	(mV) = (millivolt)
	(pS) = (picosiemens)
	(um) = (micron)
} 

PARAMETER {
	gbar = 10   	(pS/um2)	: 0.03 mho/cm2
	v 		(mV)
	cai  		(mM)
	caix = 1	
									
	Ra   = 0.01	(/mM/ms)	: max act rate  
	Rb   = 0.02	(/ms)		: max deact rate 

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

	vmin = -120	(mV)
	vmax = 100	(mV)
} 


ASSIGNED {
	a		(/ms)
	b		(/ms)
	ik 		(mA/cm2)
	gk		(pS/um2)
	ek		(mV)
	ninf
	ntau 		(ms)	
	tadj
}
 

STATE { n }

INITIAL { 
	rates(cai)
	n = ninf
}

BREAKPOINT {
        SOLVE states
	gk = tadj*gbar*n
	ik = (1e-4) * gk * (v - ek)
} 

LOCAL nexp

PROCEDURE states() {   :Computes state variable n 
        rates(cai)      :             at the current v and dt.
        n = n + nexp*(ninf-n)

        VERBATIM
        return 0;
        ENDVERBATIM
}

PROCEDURE rates(cai(mM)) {  

        LOCAL tinc

        a = Ra * (1(mM))*(cai*(1(/mM)))^caix : tedious units manipulations so modlunit doesn't complain
        b = Rb
        ntau = 1/(a+b)
	ninf = a*ntau

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

        tinc = -dt * tadj
        nexp = 1 - exp(tinc/ntau)
}