Cerebellar cortex oscil. robustness from Golgi cell gap jncs (Simoes de Souza and De Schutter 2011)

 Download zip file   Auto-launch 
Help downloading and running models
Accession:139656
" ... Previous one-dimensional network modeling of the cerebellar granular layer has been successfully linked with a range of cerebellar cortex oscillations observed in vivo. However, the recent discovery of gap junctions between Golgi cells (GoCs), which may cause oscillations by themselves, has raised the question of how gap-junction coupling affects GoC and granular-layer oscillations. To investigate this question, we developed a novel two-dimensional computational model of the GoC-granule cell (GC) circuit with and without gap junctions between GoCs. ..."
Reference:
1 . Simões de Souza F, De Schutter E (2011) Robustness effect of gap junctions between Golgi cells on cerebellar cortex oscillations Neural Systems & Circuits 1:7:1-19
Citations  Citation Browser
Model Information (Click on a link to find other models with that property)
Model Type: Realistic Network;
Brain Region(s)/Organism: Cerebellum;
Cell Type(s): Cerebellum interneuron granule GLU cell; Cerebellum golgi cell;
Channel(s):
Gap Junctions: Gap junctions;
Receptor(s): GabaA; AMPA; NMDA;
Gene(s): HCN1; HCN2;
Transmitter(s):
Simulation Environment: NEURON;
Model Concept(s): Oscillations; Synchronization; Action Potentials;
Implementer(s): Simoes-de-Souza, Fabio [fabio.souza at ufabc.edu.br];
Search NeuronDB for information about:  Cerebellum interneuron granule GLU cell; GabaA; AMPA; NMDA;
/
network
README.txt
gap.mod
Golgi_BK.mod *
Golgi_Ca_HVA.mod *
Golgi_Ca_LVA.mod *
Golgi_CALC.mod *
Golgi_CALC_ca2.mod *
Golgi_hcn1.mod *
Golgi_hcn2.mod *
Golgi_KA.mod *
Golgi_KM.mod *
Golgi_KV.mod *
Golgi_lkg.mod *
Golgi_Na.mod *
Golgi_NaP.mod *
Golgi_NaR.mod *
Golgi_SK2.mod *
GRC_CA.mod *
GRC_CALC.mod *
GRC_KA.mod *
GRC_KCA.mod *
GRC_KIR.mod *
GRC_KM.mod *
GRC_KV.mod *
GRC_LKG1.mod *
GRC_LKG2.mod *
GRC_NA.mod *
K_conc.mod *
Na_conc.mod *
Golgi_ComPanel.hoc *
Golgi_template.hoc
granule_template.hoc
MF_template.hoc
mosinit.hoc
network.hoc
utils.hoc *
                            
TITLE Cerebellum Granule Cell Model

COMMENT
Based on Raman 13 state model. Adapted from Magistretti et al, 2006.
ENDCOMMENT

NEURON {
	SUFFIX GRC_NA
	USEION na READ ena WRITE ina
	RANGE gnabar, ina, g
	RANGE gamma, delta, epsilon, Con, Coff, Oon, Ooff
	RANGE Aalfa, Valfa, Abeta, Vbeta, Ateta, Vteta, Agamma, Adelta, Aepsilon, ACon, ACoff, AOon, AOoff
	RANGE n1,n2,n3,n4
}

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

PARAMETER {
	v (mV)
	celsius = 20  	(degC)
	ena = 87.39		(mV)
	gnabar = 0.013	(mho/cm2)
	Aalfa = 353.91 ( /ms)
	Valfa = 13.99 ( /mV) 
	Abeta = 1.272  ( /ms)
	Vbeta = 13.99 ( /mV)
	Agamma = 150 ( /ms)
	Adelta = 40  ( /ms)
	Aepsilon = 1.75 ( /ms)
	Ateta = 0.0201 ( /ms)
	Vteta = 25
	ACon = 0.005    ( /ms)
	ACoff = 0.5     ( /ms)
	AOon = 0.75     ( /ms)
	AOoff = 0.005   ( /ms)
	n1 = 5.422
	n2 = 3.279
	n3 = 1.83
	n4 = 0.738
}

ASSIGNED {
	ina  (mA/cm2)
	g   (mho/cm2)
	
	gamma
	delta
	epsilon
	Con
	Coff
	Oon
	Ooff
	a
	b
	Q10
	
}

STATE {
	C1
	C2
	C3
	C4
	C5
	O
	OB
	I1
	I2
	I3
	I4
	I5
	I6
}


INITIAL {
	C1=1
	C2=0
	C3=0
	C4=0
	C5=0
	O=0
	OB=0
	I1=0
	I2=0
	I3=0
	I4=0
	I5=0
	I6=0
	Q10 =3^((celsius-20(degC))/10 (degC))
	gamma = Q10 * Agamma
	delta = Q10 * Adelta
	epsilon = Q10 * Aepsilon
	Con = Q10 * ACon
	Coff = Q10 * ACoff
	Oon = Q10 * AOon
	Ooff = Q10 * AOoff
	a = (Oon/Con)^0.25
	b = (Ooff/Coff)^0.25

}

BREAKPOINT {
	SOLVE kstates METHOD sparse
	g = gnabar * O	      	: (mho/cm2)
	ina = g * (v - ena)  	: (mA/cm2)
}


FUNCTION alfa(v(mV))(/ms){ 
	alfa = Q10*Aalfa*exp(v/Valfa) 
}

FUNCTION beta(v(mV))(/ms){ 
	beta = Q10*Abeta*exp(-v/Vbeta) 
}

FUNCTION teta(v(mV))(/ms){ 
	teta = Q10*Ateta*exp(-v/Vteta) 
}
 

KINETIC kstates {
	: 1 riga
	~ C1 <-> C2 (n1*alfa(v),n4*beta(v))
	~ C2 <-> C3 (n2*alfa(v),n3*beta(v))
	~ C3 <-> C4 (n3*alfa(v),n2*beta(v))
	~ C4 <-> C5 (n4*alfa(v),n1*beta(v))
	~ C5 <-> O  (gamma,delta)
	~  O <-> OB (epsilon,teta(v))
	
	: 2 riga
	~ I1 <-> I2	(n1*alfa(v)*a,n4*beta(v)*b)
	~ I2 <-> I3	(n2*alfa(v)*a,n3*beta(v)*b)
	~ I3 <-> I4	(n3*alfa(v)*a,n2*beta(v)*b)
	~ I4 <-> I5 (n4*alfa(v)*a,n1*beta(v)*b)
	~ I5 <-> I6 (gamma,delta)
	
	: connette 1 riga con 2 riga
	~ C1 <-> I1 (Con,Coff)
	~ C2 <-> I2 (Con*a,Coff*b)
	~ C3 <-> I3 (Con*a^2,Coff*b^2)
	~ C4 <-> I4 (Con*a^3,Coff*b^3)
	~ C5 <-> I5 (Con*a^4,Coff*b^4)
	~  O <-> I6 (Oon,Ooff)
	
	CONSERVE C1+C2+C3+C4+C5+O+OB+I1+I2+I3+I4+I5+I6=1
}