Cerebellar Golgi cells, dendritic processing, and synaptic plasticity (Masoli et al 2021)

 Download zip file 
Help downloading and running models
Accession:266806
The Golgi cells are the main inhibitory interneurons of the cerebellar granular layer. To study the mechanisms through which these neurons integrate complex input patterns, a new set of models were developed using the latest experimental information and a genetic algorithm approach to fit the maximum ionic channel conductances. The models faithfully reproduced a rich pattern of electrophysiological and pharmacological properties and predicted the operating mechanisms of these neurons.
Reference:
1 . Masoli S, Ottaviani A, Casali S, D'Angelo E (2020) Cerebellar Golgi cell models predict dendritic processing and mechanisms of synaptic plasticity. PLoS Comput Biol 16:e1007937 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Neuron or other electrically excitable cell;
Brain Region(s)/Organism: Cerebellum;
Cell Type(s): Cerebellum golgi cell;
Channel(s): I Sodium;
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment: NEURON;
Model Concept(s): Action Potential Initiation; Neurotransmitter dynamics; Calcium dynamics;
Implementer(s): Masoli, Stefano [stefano.masoli at unipv.it];
Search NeuronDB for information about:  I Sodium;
/
Golgi_cell_2020
Morphology_1
mod_files
Cav12.mod *
Cav13.mod *
Cav2_3.mod *
Cav3_1.mod *
cdp5StCmod.mod *
GOLGI_Ampa_mossy_det_vi.mod *
GOLGI_Ampa_pf_aa_det_vi.mod *
GRC_CA.mod *
GRC_KM.mod *
Hcn1.mod *
Hcn2.mod *
Kca11.mod *
Kca22.mod *
Kca31.mod *
Kv11.mod *
Kv34.mod *
Kv43.mod *
Leak.mod *
Nav16.mod *
PC_NMDA_NR2B.mod *
                            
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))
} 

Loading data, please wait...