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 Granule Cell Model

COMMENT
        KM channel
   
	Author: A. Fontana
	CoAuthor: T.Nieus Last revised: 20.11.99
	
ENDCOMMENT
 
NEURON { 
	SUFFIX GRC_KM 
	USEION k READ ek WRITE ik 
	RANGE gkbar, ik, g, alpha_n, beta_n 
	RANGE Aalpha_n, Kalpha_n, V0alpha_n
	RANGE Abeta_n, Kbeta_n, V0beta_n
	RANGE V0_ninf, B_ninf
	RANGE n_inf, tau_n 
} 
 
UNITS { 
	(mA) = (milliamp) 
	(mV) = (millivolt) 
} 
 
PARAMETER { 
	Aalpha_n = 0.0033 (/ms)
	Kalpha_n = 40 (mV)

	V0alpha_n = -30 (mV)
	Abeta_n = 0.0033 (/ms)
	Kbeta_n = -20 (mV)

	V0beta_n = -30 (mV)
	V0_ninf = -35 (mV)	:-30
	B_ninf = 6 (mV)		:6:4 rimesso a 6 dopo calibrazione febbraio 2003	
	v (mV) 
	gkbar= 0.00025 (mho/cm2) :0.0001
	ek = -84.69 (mV) 
	celsius = 30 (degC) 
} 

STATE { 
	n 
} 

ASSIGNED { 
	ik (mA/cm2) 
	n_inf 
	tau_n (ms) 
	g (mho/cm2) 
	alpha_n (/ms) 
	beta_n (/ms) 
} 
 
INITIAL { 
	rate(v) 
	n = n_inf 
} 
 
BREAKPOINT { 
	SOLVE states METHOD derivimplicit 
	g = gkbar*n 
	ik = g*(v - ek) 
	alpha_n = alp_n(v) 
	beta_n = bet_n(v) 
} 
 
DERIVATIVE states { 
	rate(v) 
	n' =(n_inf - n)/tau_n 
} 
 
FUNCTION alp_n(v(mV))(/ms) { LOCAL Q10
	Q10 = 3^((celsius-22(degC))/10(degC)) 
	alp_n = Q10*Aalpha_n*exp((v-V0alpha_n)/Kalpha_n) 
} 
 
FUNCTION bet_n(v(mV))(/ms) { LOCAL Q10
	Q10 = 3^((celsius-22(degC))/10(degC)) 
	bet_n = Q10*Abeta_n*exp((v-V0beta_n)/Kbeta_n) 
} 
 
PROCEDURE rate(v (mV)) {LOCAL a_n, b_n 
	TABLE n_inf, tau_n 
	DEPEND Aalpha_n, Kalpha_n, V0alpha_n, 
	       Abeta_n, Kbeta_n, V0beta_n, V0_ninf, B_ninf, celsius FROM -100 TO 30 WITH 13000 
	a_n = alp_n(v)  
	b_n = bet_n(v) 
	tau_n = 1/(a_n + b_n) 
:	n_inf = a_n/(a_n + b_n) 
	n_inf = 1/(1+exp(-(v-V0_ninf)/B_ninf))
} 

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