A network model of the vertebrate retina (Publio et al. 2009)

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Accession:124063
In this work, we use a minimal conductance-based model of the ON rod pathways in the vertebrate retina to study the effects of electrical synaptic coupling via gap junctions among rods and among AII amacrine cells on the dynamic range of the retina. The model is also used to study the effects of the maximum conductance of rod hyperpolarization activated current Ih on the dynamic range of the retina, allowing a study of the interrelations between this intrinsic membrane parameter with those two retina connectivity characteristics.
Reference:
1 . Publio R, Oliveira RF, Roque AC (2009) A computational study on the role of gap junctions and rod Ih conductance in the enhancement of the dynamic range of the retina. PLoS One 4:e6970 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Realistic Network;
Brain Region(s)/Organism:
Cell Type(s): Retina ganglion GLU cell; Retina photoreceptor cone GLU cell; Retina bipolar GLU cell;
Channel(s):
Gap Junctions: Gap junctions;
Receptor(s):
Gene(s):
Transmitter(s): Glutamate;
Simulation Environment: NEURON;
Model Concept(s): Sensory processing;
Implementer(s): Publio, Rodrigo [publio at oist.jp];
Search NeuronDB for information about:  Retina ganglion GLU cell; Retina photoreceptor cone GLU cell; Retina bipolar GLU cell; Glutamate;
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PublioEtAl2009
README.html
A2hh_k.mod
A2hh_na.mod
Bip_Ca.mod
Bip_Cad.mod
Bip_ih.mod
Bip_Ka.mod
Bip_Kv.mod
Cone_CPR.mod
Cone_ih.mod
Cone_Kv.mod
Ganglion_hh.mod *
gap.mod
IinjLT.mod
IinjLT_cone.mod
IinjLTDim.mod *
Rod_Ca.mod
Rod_Cad.mod
Rod_Clca.mod
Rod_ih.mod
Rod_Kca.mod
Rod_Kv.mod
Rod_Kx.mod
Rod_leak.mod
syn_bip_gan.mod
syn_rod_bip.mod
A2.tem
Bip.tem
Cone.tem
createcells.hoc
Ganglion.tem
gap.hoc *
init.hoc
mosinit.hoc *
netconnection.hoc
parameters.hoc
Rod.tem
screenshot1.jpg
screenshot2.jpg
session.ses
                            
TITLE L-type calcium channel for Tiger Salamander Bipolar cell
:
: Modified from Fohlmeister et al, 1990, Brain Res 510, 343-345
:

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

NEURON {
	SUFFIX tsbp
	USEION ca READ cai, eca, cao WRITE ica
      USEION k READ ek WRITE ik
	RANGE gcabar , gkcabar
	RANGE c_inf , m_inf
	RANGE tau_c , tau_m
	RANGE c_exp , m_exp

}


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

}

PARAMETER {
	gcabar	= 0.002	(mho/cm2)
	gkcabar     = 0.0014
	eca		(mV)
	ek          (mV)
	cao	= 1.8	(mM)
	cai     = 0.0001 (mM)
	dt              (ms)
	v               (mV)

}

STATE {
	c m 
}

INITIAL {
: The initial values were determined at a resting value of -66.3232 mV in a single-compartment
:	c = 0.0016
: at -60 mV
        c = 0.0038
	  m =0.0345
}

ASSIGNED {
	ica	(mA/cm2)
	ik    (mA/cm2)
	c_inf  m_inf
	tau_c  tau_m
	c_exp  m_exp

}

BREAKPOINT {
	SOLVE states
	ica = gcabar * c*c*c * (v - eca)
	ik = gkcabar * m*m*((cai)/(cai+0.2)) * (v - ek)

	

}

PROCEDURE states() {	: exact when v held constant
	evaluate_fct(v)
	c = c + c_exp * (c_inf - c)
	m = m + m_exp * (m_inf - m)

	VERBATIM
	return 0;
	ENDVERBATIM

}

UNITSOFF

PROCEDURE evaluate_fct(v(mV)) { LOCAL a,b,am,bm
	
:CA channel

 a = (-0.3 * (v+70)) / ((exp(-0.1*(v+70))) - 1)
 b = 10 * (exp((-1*(v + 38))/9))


	tau_c = 1 / (a + b)
	c_inf = a * tau_c

: State vars to inifinity
	c_exp = 1 - exp(-dt/tau_c)

:IKCA channel

 am = (100* (230-v)) / ((exp((230-v)/52)) - 1)
 bm = 120 * (exp((-v/95)))


	tau_m = 1 / (am + bm)
	m_inf = a * tau_m

: State vars to inifinity
	m_exp = 1 - exp(-dt/tau_m)


}

UNITSON

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