A single column thalamocortical network model (Traub et al 2005)

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Accession:45539
To better understand population phenomena in thalamocortical neuronal ensembles, we have constructed a preliminary network model with 3,560 multicompartment neurons (containing soma, branching dendrites, and a portion of axon). Types of neurons included superficial pyramids (with regular spiking [RS] and fast rhythmic bursting [FRB] firing behaviors); RS spiny stellates; fast spiking (FS) interneurons, with basket-type and axoaxonic types of connectivity, and located in superficial and deep cortical layers; low threshold spiking (LTS) interneurons, that contacted principal cell dendrites; deep pyramids, that could have RS or intrinsic bursting (IB) firing behaviors, and endowed either with non-tufted apical dendrites or with long tufted apical dendrites; thalamocortical relay (TCR) cells; and nucleus reticularis (nRT) cells. To the extent possible, both electrophysiology and synaptic connectivity were based on published data, although many arbitrary choices were necessary.
Reference:
1 . Traub RD, Contreras D, Cunningham MO, Murray H, LeBeau FE, Roopun A, Bibbig A, Wilent WB, Higley MJ, Whittington MA (2005) Single-column thalamocortical network model exhibiting gamma oscillations, sleep spindles, and epileptogenic bursts. J Neurophysiol 93:2194-232 [PubMed]
2 . Traub RD, Contreras D, Whittington MA (2005) Combined experimental/simulation studies of cellular and network mechanisms of epileptogenesis in vitro and in vivo. J Clin Neurophysiol 22:330-42 [PubMed]
Citations  Citation Browser
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 geniculate nucleus/lateral principal GLU cell; Thalamus reticular nucleus GABA cell; Neocortex U1 L6 pyramidal corticalthalamic GLU cell; Neocortex U1 L2/6 pyramidal intratelencephalic GLU cell; Neocortex fast spiking (FS) interneuron; Neocortex spiking regular (RS) neuron; Neocortex spiking low threshold (LTS) neuron;
Channel(s): I Na,p; I Na,t; I L high threshold; I T low threshold; I A; I K; I M; I h; I K,Ca; I Calcium; I A, slow;
Gap Junctions: Gap junctions;
Receptor(s): GabaA; AMPA; NMDA;
Gene(s):
Transmitter(s):
Simulation Environment: NEURON; FORTRAN;
Model Concept(s): Activity Patterns; Bursting; Temporal Pattern Generation; Oscillations; Simplified Models; Epilepsy; Sleep; Spindles;
Implementer(s): Traub, Roger D ;
Search NeuronDB for information about:  Thalamus geniculate nucleus/lateral principal GLU cell; Thalamus reticular nucleus GABA cell; Neocortex U1 L2/6 pyramidal intratelencephalic GLU cell; Neocortex U1 L6 pyramidal corticalthalamic GLU cell; GabaA; AMPA; NMDA; I Na,p; I Na,t; I L high threshold; I T low threshold; I A; I K; I M; I h; I K,Ca; I Calcium; I A, slow;
Files displayed below are from the implementation
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nrntraub
mod
alphasyndiffeq.mod *
alphasynkin.mod *
alphasynkint.mod *
ampa.mod *
ar.mod *
cad.mod *
cal.mod *
cat.mod *
cat_a.mod *
gabaa.mod *
iclamp_const.mod *
k2.mod *
ka.mod *
ka_ib.mod *
kahp.mod *
kahp_deeppyr.mod *
kahp_slower.mod *
kc.mod *
kc_fast.mod *
kdr.mod *
kdr_fs.mod *
km.mod *
naf.mod *
naf_tcr.mod *
naf2.mod *
nap.mod *
napf.mod *
napf_spinstell.mod *
napf_tcr.mod *
par_ggap.mod *
pulsesyn.mod *
rampsyn.mod *
rand.mod *
ri.mod *
traub_nmda.mod *
                            
TITLE Calcium low threshold T type current for RD Traub, J Neurophysiol 89:909-921, 2003

COMMENT

	Implemented by Maciej Lazarewicz 2003 (mlazarew@seas.upenn.edu)

ENDCOMMENT

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

UNITS { 
	(mV) = (millivolt) 
	(mA) = (milliamp) 
}
 
NEURON { 
	SUFFIX cat
	NONSPECIFIC_CURRENT i   : not causing [Ca2+] influx
	RANGE gbar, i, m, h, alphah, betah 	: m,h, alphah, betah for comparison with FORTRAN
}

PARAMETER { 
	gbar = 0.0 	(mho/cm2)
	v 		(mV)  
}
 
ASSIGNED { 
	i 		(mA/cm2) 
	minf hinf 	(1)
	mtau  (ms) htau 	(ms) 
	alphah (/ms) betah	(/ms)
}
 
STATE {
	m h
}

BREAKPOINT { 
	SOLVE states METHOD cnexp 
	i = gbar * m * m * h * ( v - 125 ) 
	alphah = hinf/htau
	betah = 1/htau - alphah
}
 
INITIAL { 
	settables(v) 
:	m  = minf
	h  = hinf
	m  = 0
} 

DERIVATIVE states { 
	settables(v) 
	m' = ( minf - m ) / mtau 
	h' = ( hinf - h ) / htau
}

UNITSOFF 

PROCEDURE settables(v(mV)) { 
	TABLE minf, mtau,hinf, htau FROM -120 TO 40 WITH 641
	minf  = 1 / ( 1 + exp( ( -v - 56 ) / 6.2 ) )
	mtau  = 0.204 + 0.333 / ( exp( ( v + 15.8 ) / 18.2 ) + exp( ( - v - 131 ) / 16.7 ) )
	hinf  = 1 / ( 1 + exp( ( v + 80 ) / 4 ) )
	if( v < -81 ) {
		htau  = 0.333 * exp( ( v + 466 ) / 66.6 )
	}else{
		htau  = 9.32 + 0.333 * exp( ( -v - 21 ) / 10.5 )
	}
}

UNITSON