Thalamocortical augmenting response (Bazhenov et al 1998)

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Accession:37819
In the cortical model, augmenting responses were more powerful in the "input" layer compared with those in the "output" layer. Cortical stimulation of the network model produced augmenting responses in cortical neurons in distant cortical areas through corticothalamocortical loops and low-threshold intrathalamic augmentation. ... The predictions of the model were compared with in vivo recordings from neurons in cortical area 4 and thalamic ventrolateral nucleus of anesthetized cats. The known intrinsic properties of thalamic cells and thalamocortical interconnections can account for the basic properties of cortical augmenting responses. See reference for details. NEURON implementation note: cortical SU cells are getting slightly too little stimulation - reason unknown.
Reference:
1 . Bazhenov M, Timofeev I, Steriade M, Sejnowski TJ (1998) Computational models of thalamocortical augmenting responses. J Neurosci 18:6444-65 [PubMed]
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Model Information (Click on a link to find other models with that property)
Model Type: Realistic Network;
Brain Region(s)/Organism: Thalamus;
Cell Type(s): Thalamus geniculate nucleus/lateral principal GLU cell; Thalamus reticular nucleus GABA cell; Neocortex L5/6 pyramidal GLU cell;
Channel(s): I Na,t; I T low threshold; I A; I K,Ca;
Gap Junctions:
Receptor(s): GabaA; GabaB; AMPA;
Gene(s):
Transmitter(s): Gaba; Glutamate;
Simulation Environment: NEURON;
Model Concept(s): Synchronization; Synaptic Integration;
Implementer(s): Lytton, William [bill.lytton at downstate.edu];
Search NeuronDB for information about:  Thalamus geniculate nucleus/lateral principal GLU cell; Thalamus reticular nucleus GABA cell; Neocortex L5/6 pyramidal GLU cell; GabaA; GabaB; AMPA; I Na,t; I T low threshold; I A; I K,Ca; Gaba; Glutamate;
: $Id: Iahp.mod,v 1.8 2000/01/05 19:55:19 billl Exp $
TITLE Slow Ca-dependent potassium current
:
:   Ca++ dependent K+ current IC responsible for slow AHP
:   Differential equations
:
:   Model of Destexhe, 1992.  Based on a first order kinetic scheme
:      <closed> + n cai <-> <open>	(alpha,beta)
:   Following this model, the activation fct will be half-activated at 
:   a concentration of Cai = (beta/alpha)^(1/n) = cac (parameter)
:   The mod file is here written for the case n=2 (2 binding sites)
:   ---------------------------------------------
:
:   This current models the "slow" IK[Ca] (IAHP): 
:      - potassium current
:      - activated by intracellular calcium
:      - NOT voltage dependent
:
:   A minimal value for the time constant has been added
:
:   Written by Alain Destexhe, Salk Institute, Nov 3, 1992
:

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

NEURON {
	SUFFIX iahp
	USEION k2 WRITE ik2 VALENCE 1
	USEION Ca READ Cai VALENCE 2
	USEION ca READ cai
        RANGE gkbar, i, g, ratc, ratC, minf, taum
	GLOBAL beta, cac, m_inf, tau_m, x
}


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


PARAMETER {
	v		(mV)
	celsius	= 36	(degC)
	erev = -95		(mV)
	Cai 	= 5e-5	(mM)		: initial [Ca]i = 50 nM
	cai 	= 5e-5	(mM)		: initial [Ca]i = 50 nM
	gkbar	= .001	(mho/cm2)
	beta	= 2.5	(1/ms)		: backward rate constant
	cac	= 1e-4	(mM)		: middle point of activation fct
	taumin	= 1	(ms)		: minimal value of the time cst
        ratc    = 0
        ratC    = 0
        x       = 2
}


STATE {
	m
}
ASSIGNED {
	ik2 	(mA/cm2)
	i	(mA/cm2)
	g       (mho/cm2)
	m_inf
	tau_m	(ms)
	minf
        taum
	tadj
}

BREAKPOINT { 
	SOLVE states METHOD cnexp
        minf=m_inf
        taum=tau_m
	g = gkbar * m*m
	i = g * (v - erev)
	ik2  = i
}

DERIVATIVE states { 
	evaluate_fct(v,Cai,cai)

	m' = (m_inf - m) / tau_m
}

UNITSOFF
INITIAL {
:
:  activation kinetics are assumed to be at 22 deg. C
:  Q10 is assumed to be 3
:
	VERBATIM
	cai = _ion_cai;
	Cai = _ion_Cai;
	ENDVERBATIM

	tadj = 3 ^ ((celsius-22.0)/10)

	evaluate_fct(v,Cai,cai)
	m = m_inf
        minf=m_inf
        taum=tau_m
}

PROCEDURE evaluate_fct(v(mV),Cai(mM), cai(mM)) {  LOCAL car, tcar

        tcar = ratC*Cai + ratc*cai
	car = (tcar/cac)^x

	m_inf = car / ( 1 + car )
	tau_m = 1 / beta / (1 + car) / tadj

        if(tau_m < taumin) { tau_m = taumin } 	: min value of time cst
}
UNITSON