Cortical feedback alters visual response properties of dLGN relay cells (Martínez-Cañada et al 2018)

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Accession:239878
Network model that includes biophysically detailed, single-compartment and multicompartment neuron models of relay-cells and interneurons in the dLGN and a population of orientation-selective layer 6 simple cells, consisting of pyramidal cells (PY). We have considered two different arrangements of synaptic feedback from the ON and OFF zones in the visual cortex to the dLGN: phase-reversed (‘push-pull’) and phase-matched (‘push-push’), as well as different spatial extents of the corticothalamic projection pattern. This project is the result of a research work and its associated publication is: (Martínez-Cañada et al 2018). Installation instructions as well as the latest version can be found in the Github repository: https://github.com/CINPLA/biophysical_thalamocortical_system
Reference:
1 . Martínez-Cañada P, Mobarhan MH, Halnes G, Fyhn M, Morillas C, Pelayo F, Einevoll GT (2018) Biophysical network modeling of the dLGN circuit: Effects of cortical feedback on spatial response properties of relay cells. PLoS Comput Biol 14:e1005930 [PubMed]
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):
Channel(s):
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment: LFPy; NEURON; NEST; Python;
Model Concept(s): Vision;
Implementer(s): Martínez-Cañada, Pablo [pablomc at ugr.es];
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Biophysical_thalamocortical_system
cortex_neurons
.README.swp
README *
cadecay.mod *
hh2.mod
IM.mod *
IT.mod *
demo_IN_FS.oc *
demo_PY_LTS.oc *
demo_PY_RS.oc *
mosinit.hoc *
rundemo.hoc *
sIN_template
soma.hoc *
sPY_template
sPYr_template
                            
TITLE Fast mechanism for submembranal Ca++ concentration (cai)
:
: Takes into account:
:
:	- increase of cai due to calcium currents
:	- extrusion of calcium with a simple first order equation
:
: This mechanism is compatible with the calcium pump "cad" and has the 
: same name and parameters; however the parameters specific to the pump
: are dummy here.
:
: Parameters:
:
:	- depth: depth of the shell just beneath the membran (in um)
:	- cainf: equilibrium concentration of calcium (2e-4 mM)
:	- taur: time constant of calcium extrusion (must be fast)
:	- kt,kd: dummy parameters
:
: Written by Alain Destexhe, Salk Institute, 1995
:

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

NEURON {
	SUFFIX cad
	USEION ca READ ica, cai WRITE cai
	RANGE depth,kt,kd,cainf,taur
}

UNITS {
	(molar) = (1/liter)			: moles do not appear in units
	(mM)	= (millimolar)
	(um)	= (micron)
	(mA)	= (milliamp)
	(msM)	= (ms mM)
}

CONSTANT {
	FARADAY = 96489		(coul)		: moles do not appear in units
:	FARADAY = 96.489	(k-coul)	: moles do not appear in units
}

PARAMETER {
	depth	= .1	(um)		: depth of shell
	taur	= 5	(ms)		: rate of calcium removal
	cainf	= 2e-4	(mM)
	kt	= 0	(mM/ms)		: dummy
	kd	= 0	(mM)		: dummy
}

STATE {
	cai		(mM) 
}

INITIAL {
	cai = cainf
}

ASSIGNED {
	ica		(mA/cm2)
	drive_channel	(mM/ms)
}
	
BREAKPOINT {
	SOLVE state METHOD derivimplicit
}

DERIVATIVE state { 

	drive_channel =  - (10000) * ica / (2 * FARADAY * depth)

	if (drive_channel <= 0.) { drive_channel = 0. }	: cannot pump inward

	cai' = drive_channel + (cainf-cai)/taur
}


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