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

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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
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 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 cell; GabaA; AMPA; NMDA;
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network
data
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 Golgi Cell Model

COMMENT
        Na resurgent channel
	  
	Author: T.Nieus
	Last revised: 30.6.2003 
	Critical value gNa
	Inserted a control in bet_s to avoid huge values of x1
			
ENDCOMMENT
 
NEURON { 
	SUFFIX Golgi_NaR
	USEION na READ ena WRITE ina 
	RANGE gnabar, ina, g
	RANGE Aalpha_s,Abeta_s,V0alpha_s,V0beta_s,Kalpha_s,Kbeta_s 
        RANGE Shiftalpha_s,Shiftbeta_s,tau_s,s_inf
	RANGE Aalpha_f,Abeta_f,V0alpha_f,V0beta_f,Kalpha_f, Kbeta_f
	RANGE f, tau_f,f_inf,s , tau_s,s_inf, tcorr
} 
 
UNITS {    
	(mA) = (milliamp) 
	(mV) = (millivolt) 
} 
 
PARAMETER { 
	
	: s-ALFA
	Aalpha_s = -0.00493 (/ms)
	V0alpha_s = -4.48754 (mV)
	Kalpha_s = -6.81881 (mV)
	Shiftalpha_s = 0.00008 (/ms)

	: s-BETA
	Abeta_s = 0.01558 (/ms)
	V0beta_s = 43.97494 (mV)
	Kbeta_s =  0.10818 (mV)
	Shiftbeta_s = 0.04752 (/ms)

	: f-ALFA
	Aalpha_f = 0.31836 (/ms)
	V0alpha_f = -80 (mV)
	Kalpha_f = -62.52621 (mV)

	: f-BETA
	Abeta_f = 0.01014 (/ms)
	V0beta_f = -83.3332 (mV)
	Kbeta_f = 16.05379 (mV)

	v (mV) 
	gnabar= 0.0017 (mho/cm2)
	ena  (mV) 
	celsius (degC) 
	Q10 = 3	(1)
} 

STATE { 
	s 
	f
} 

ASSIGNED { 
	ina (mA/cm2) 
	g (mho/cm2) 

	alpha_s (/ms)
	beta_s (/ms)
	s_inf
	tau_s (ms)
	
	alpha_f (/ms)
	beta_f (/ms)
	f_inf
	tau_f (ms)
	tcorr (1)
} 
 
INITIAL { 
	rate(v) 
	s = s_inf
	f = f_inf
} 
 
BREAKPOINT { 
	SOLVE states METHOD derivimplicit 
	g = gnabar*s*f
	ina = g*(v - ena)

	alpha_s = alp_s(v)
	beta_s = bet_s(v) 

	alpha_f = alp_f(v)
	beta_f = bet_f(v) 
} 
 
DERIVATIVE states { 
	rate(v) 
	s' = ( s_inf - s ) / tau_s 
	f' = ( f_inf - f ) / tau_f 
} 
 
PROCEDURE rate(v (mV)) { LOCAL a_s,b_s,a_f,b_f
	TABLE s_inf,tau_s,f_inf,tau_f DEPEND celsius FROM -100 TO 30 WITH 13000	

	a_s = alp_s(v)  
	b_s = bet_s(v) 
	s_inf = a_s / ( a_s + b_s ) 
	tau_s = 1 / ( a_s + b_s ) 

	a_f = alp_f(v)  
	b_f = bet_f(v) 
	f_inf = a_f / ( a_f + b_f ) 
	tau_f = 1 / ( a_f + b_f ) 
} 



FUNCTION alp_s(v (mV)) (/ms){
	tcorr = Q10^( ( celsius - 20 (degC) ) / 10 (degC) )
	alp_s = tcorr*(Shiftalpha_s+Aalpha_s*((v+V0alpha_s)/ 1 (mV) )/(exp((v+V0alpha_s)/Kalpha_s)-1))
}

FUNCTION bet_s(v (mV)) (/ms){ LOCAL x1
	tcorr = Q10^((celsius-20(degC))/10(degC))	

	x1=(v+V0beta_s)/Kbeta_s
	if (x1>200) {x1=200}
	bet_s =tcorr*(Shiftbeta_s+Abeta_s*((v+V0beta_s)/1 (mV) )/(exp(x1)-1))

}

FUNCTION alp_f(v (mV)) (/ms){
	tcorr = Q10^( ( celsius - 20 (degC) ) / 10 (degC) )
	alp_f =	tcorr * Aalpha_f * exp( ( v - V0alpha_f ) / Kalpha_f)
}

FUNCTION bet_f(v (mV)) (/ms){
	tcorr = Q10^( ( celsius - 20 (degC) ) / 10 (degC) )
	bet_f =	tcorr * Abeta_f * exp( ( v - V0beta_f ) / Kbeta_f )	
}


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