Knox implementation of Destexhe 1998 spike and wave oscillation model (Knox et al 2018)

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Accession:234233
" ...The aim of this study was to use an established thalamocortical computer model to determine how T-type calcium channels work in concert with cortical excitability to contribute to pathogenesis and treatment response in CAE. METHODS: The model is comprised of cortical pyramidal, cortical inhibitory, thalamocortical relay, and thalamic reticular single-compartment neurons, implemented with Hodgkin-Huxley model ion channels and connected by AMPA, GABAA , and GABAB synapses. Network behavior was simulated for different combinations of T-type calcium channel conductance, inactivation time, steady state activation/inactivation shift, and cortical GABAA conductance. RESULTS: Decreasing cortical GABAA conductance and increasing T-type calcium channel conductance converted spindle to spike and wave oscillations; smaller changes were required if both were changed in concert. In contrast, left shift of steady state voltage activation/inactivation did not lead to spike and wave oscillations, whereas right shift reduced network propensity for oscillations of any type...."
Reference:
1 . Knox AT, Glauser T, Tenney J, Lytton WW, Holland K (2018) Modeling pathogenesis and treatment response in childhood absence epilepsy. Epilepsia 59:135-145 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Realistic Network;
Brain Region(s)/Organism: Neocortex; Thalamus;
Cell Type(s): Thalamus reticular nucleus GABA cell; Thalamus geniculate nucleus/lateral principal GLU cell; Hodgkin-Huxley neuron; Neocortex layer 4 pyramidal cell; Neocortex fast spiking (FS) interneuron;
Channel(s): I h; I Na,t; I K,leak; I T low threshold; I M;
Gap Junctions:
Receptor(s): GabaA; GabaB; AMPA;
Gene(s):
Transmitter(s):
Simulation Environment: NEURON;
Model Concept(s): Spindles; Oscillations;
Implementer(s): Knox, Andrew [knox at neurology.wisc.edu]; Destexhe, Alain [Destexhe at iaf.cnrs-gif.fr];
Search NeuronDB for information about:  Thalamus geniculate nucleus/lateral principal GLU cell; Thalamus reticular nucleus GABA cell; GabaA; GabaB; AMPA; I Na,t; I T low threshold; I K,leak; I M; I h;
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KnoxEtAl2017
README.html
README_.txt
ampa.mod
cadecay.mod *
gabaa.mod
gabab.mod
HH2.mod *
Ih.mod *
IM.mod
IT.mod *
IT2.mod *
ITREcustom.mod
kleak.mod *
vecevent.mod
Fsinglecell.oc
Fspikewave.oc
membrane_potential_heat_plot.py
mosinit.hoc *
RE.tem
rundemo.hoc
screenshot1.png
screenshot2.png
screenshot3.png
sIN.tem
sPY.tem
TC.tem
                            
TITLE Cortical M current
:
:   M-current, responsible for the adaptation of firing rate and the 
:   afterhyperpolarization (AHP) of cortical pyramidal cells
:
:   First-order model described by hodgkin-Hyxley like equations.
:   K+ current, activated by depolarization, noninactivating.
:
:   Model taken from Yamada, W.M., Koch, C. and Adams, P.R.  Multiple 
:   channels and calcium dynamics.  In: Methods in Neuronal Modeling, 
:   edited by C. Koch and I. Segev, MIT press, 1989, p 97-134.
:
:   See also: McCormick, D.A., Wang, Z. and Huguenard, J. Neurotransmitter 
:   control of neocortical neuronal activity and excitability. 
:   Cerebral Cortex 3: 387-398, 1993.
:
:   Written by Alain Destexhe, Laval University, 1995
:

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

NEURON {
	SUFFIX im
	USEION k READ ek WRITE ik
        RANGE gkbar, m_inf, tau_m, ik
	GLOBAL taumax

}

UNITS {
	(mA) = (milliamp)
	(mV) = (millivolt)
}


PARAMETER {
	v		(mV)
	celsius = 36    (degC)
	ek		(mV)
	gkbar	= 1e-6	(mho/cm2)
	taumax	= 1000	(ms)		: peak value of tau
}



STATE {
	m
}

ASSIGNED {
	ik	(mA/cm2)
	m_inf
	tau_m	(ms)
	tau_peak	(ms)
	tadj
}

BREAKPOINT {
	SOLVE states METHOD cnexp
	ik = gkbar * m * (v - ek)
}

DERIVATIVE states { 
	evaluate_fct(v)

	m' = (m_inf - m) / tau_m
}

UNITSOFF
INITIAL {
	evaluate_fct(v)
	m = 0
:
:  The Q10 value is assumed to be 2.3
:
        tadj = 2.3 ^ ((celsius-36)/10)
	tau_peak = taumax / tadj
}

PROCEDURE evaluate_fct(v(mV)) {

	m_inf = 1 / ( 1 + exptable(-(v+35)/10) )
	tau_m = tau_peak / ( 3.3 * exptable((v+35)/20) + exptable(-(v+35)/20) )
}
UNITSON


FUNCTION exptable(x) { 
	TABLE  FROM -25 TO 25 WITH 10000

	if ((x > -25) && (x < 25)) {
		exptable = exp(x)
	} else {
		exptable = 0.
	}
}

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