A Model Circuit of Thalamocortical Convergence (Behuret et al. 2013)

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Accession:150240
“… Using dynamic-clamp techniques in thalamic slices in vitro, we combined theoretical and experimental approaches to implement a realistic hybrid retino-thalamo-cortical pathway mixing biological cells and simulated circuits. … The study of the impact of the simulated cortical input on the global retinocortical signal transfer efficiency revealed a novel control mechanism resulting from the collective resonance of all thalamic relay neurons. We show here that the transfer efficiency of sensory input transmission depends on three key features: i) the number of thalamocortical cells involved in the many-to-one convergence from thalamus to cortex, ii) the statistics of the corticothalamic synaptic bombardment and iii) the level of correlation imposed between converging thalamic relay cells. In particular, our results demonstrate counterintuitively that the retinocortical signal transfer efficiency increases when the level of correlation across thalamic cells decreases. …”
Reference:
1 . Behuret S, Deleuze C, Gomez L, Fregnac Y and Bal T (2013) Cortically-controlled population stochastic facilitation as a plausible substrate for guiding sensory transfer across the thalamic gateway PLoS Computational Biology 9(12):e1003401
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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: Neocortex; Thalamus; Retina;
Cell Type(s): Thalamus geniculate nucleus/lateral principal neuron; Thalamus reticular nucleus cell; Neocortex U1 L5B pyramidal pyramidal tract cell; Retina ganglion cell; Thalamus lateral geniculate nucleus interneuron;
Channel(s): I Na,t; I T low threshold; I K; I M;
Gap Junctions:
Receptor(s): GabaA; AMPA;
Gene(s):
Transmitter(s):
Simulation Environment: NEURON;
Model Concept(s): Synaptic Convergence;
Implementer(s): Behuret, Sebastien [behuret at unic.cnrs-gif.fr];
Search NeuronDB for information about:  Thalamus geniculate nucleus/lateral principal neuron; Thalamus reticular nucleus cell; Retina ganglion cell; Neocortex U1 L5B pyramidal pyramidal tract cell; GabaA; AMPA; I Na,t; I T low threshold; I K; I M;
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TCconvergenceModel
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cadecay.mod *
ConductancePattern.mod
ConstantCurrent.mod
hh2.mod *
IM.mod
IT.mod
ITGHK.mod
RandomGenerator.mod
RetinalInput.mod
SineWaveCurrent.mod
SynapticNoise.mod
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Geometry.hoc
GUI.hoc
mosinit.hoc
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Templates.hoc
                            
TITLE Low threshold calcium current
:
:   Ca++ current responsible for low threshold spikes (LTS)
:   THALAMOCORTICAL CELLS
:   Differential equations
:
:   Model based on the data of Huguenard & McCormick, J Neurophysiol
:   68: 1373-1383, 1992 and Huguenard & Prince, J Neurosci.
:   12: 3804-3817, 1992.
:
:   Features:
:
:	- kinetics described by Nernst equations using a m2h format
:	- activation considered at steady-state
:	- inactivation fit to Huguenard's data using a bi-exp function
:	- shift for screening charge, q10 of inactivation of 3
:
:
:   Written by Alain Destexhe, Salk Institute, 1993; modified 1995
:

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

NEURON {
	SUFFIX it
	USEION ca READ cai,cao WRITE ica
	GLOBAL q10
	RANGE gcabar, m_inf, tau_m, h_inf, tau_h, shift
}

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

	FARADAY = (faraday) (coulomb)
	R = (k-mole) (joule/degC)
}

PARAMETER {
	v		(mV)
	celsius	= 36	(degC)
	gcabar	= 0.002	(mho/cm2)
	q10	= 3			: Q10 of inactivation
	shift	= 2 	(mV)		: corresponds to 2mM ext Ca++
	cai	= 2.4e-4 (mM)		: adjusted for eca=120 mV
	cao	= 2	(mM)
}

STATE {
	h
}

ASSIGNED {
	ica	(mA/cm2)
	carev	(mV)
	m_inf
	tau_m	(ms)			: dummy variable for compatibility
	h_inf
	tau_h	(ms)
	phi_h
}

BREAKPOINT {
	SOLVE castate METHOD euler
	carev = (1e3) * (R*(celsius+273.15))/(2*FARADAY) * log (cao/cai)
	ica = gcabar * m_inf * m_inf * h * (v-carev)
}

DERIVATIVE castate {
	evaluate_fct(v)

	h' = (h_inf - h) / tau_h
}


UNITSOFF
INITIAL {
	h = 0

:
:   Transformation to 36 deg assuming Q10 of 3 for h
:   (as in Coulter et al., J Physiol 414: 587, 1989)
:
	phi_h = q10 ^ ((celsius-24 (degC) )/10 (degC) )
}

PROCEDURE evaluate_fct(v(mV)) { LOCAL Vm

	Vm = v + shift

	m_inf = 1.0 / ( 1 + exp(-(Vm+57)/6.2) )
	h_inf = 1.0 / ( 1 + exp((Vm+81)/4.0) )

:	if(Vm < -80) {
:		tau_h = exp((Vm+467)/66.6) / phi_h
:	} else {
:		tau_h = ( 28 + exp(-(Vm+22)/10.5) ) / phi_h
:	}

	tau_h = 30.8 + (211.4 + exp((Vm+113.2)/5)) / (1 + exp((Vm+84)/3.2))

	tau_h = tau_h / phi_h

}

UNITSON