Cerebellar Golgi cell (Solinas et al. 2007a, 2007b)

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Accession:112685
"... Our results suggest that a complex complement of ionic mechanisms is needed to fine-tune separate aspects of the neuronal response dynamics. Simulations also suggest that the Golgi cell may exploit these mechanisms to obtain a fine regulation of timing of incoming mossy fiber responses and granular layer circuit oscillation and bursting."
References:
1 . Solinas S, Forti L, Cesana E, Mapelli J, De Schutter E, D'Angelo E (2007) Computational reconstruction of pacemaking and intrinsic electroresponsiveness in cerebellar golgi cells. Front. Cell. Neurosci. 1:2:1-12 [PubMed]
2 . Solinas S, Forti L, Cesana E, Mapelli J, De Schutter E, D'Angelo E (2007) Fast-reset of pacemaking and theta-frequency resonance patterns in cerebellar golgi cells: Simulations of their impact in vivo. Front. Cell. Neurosci. 1:4:1-9 [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 Na,p; I Na,t; I T low threshold; I A; I K; I M; I K,Ca; I Sodium; I Calcium; I Potassium; I h;
Gap Junctions:
Receptor(s):
Gene(s): HCN1;
Transmitter(s):
Simulation Environment: NEURON; neuroConstruct (web link to model);
Model Concept(s): Activity Patterns; Oscillations;
Implementer(s): D'Angelo, Egidio [dangelo at unipv.it]; De Schutter, Erik [erik at oist.jp];
Search NeuronDB for information about:  I Na,p; I Na,t; I T low threshold; I A; I K; I M; I h; I K,Ca; I Sodium; I Calcium; I Potassium;
Files displayed below are from the implementation
/
Golgi_cell
sessions
readme.html
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 *
Pregen.mod *
Synapse.mod *
Channel_dynamics.hoc *
Golgi_ComPanel.hoc *
Golgi_count.txt
Golgi_template.hoc
mosinit.hoc
Save_data.hoc *
screenshot.jpg
Start_golgi.hoc
Synapses.hoc *
utils.hoc *
                            
TITLE SK2 multi-state model Cerebellum Golgi Cell Model

COMMENT

Author:Sergio Solinas, Lia Forti, Egidio DAngelo
Based on data from: Hirschberg, Maylie, Adelman, Marrion J Gen Physiol 1998
Last revised: May 2007

Published in:
             Sergio M. Solinas, Lia Forti, Elisabetta Cesana, 
             Jonathan Mapelli, Erik De Schutter and Egidio D`Angelo (2008)
             Computational reconstruction of pacemaking and intrinsic 
             electroresponsiveness in cerebellar golgi cells
             Frontiers in Cellular Neuroscience 2:2
ENDCOMMENT

NEURON{
	SUFFIX Golgi_SK2
	USEION ca READ cai
	USEION k READ ek WRITE ik 
	RANGE gkbar, g, ik, tcorr
}

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

PARAMETER {
	celsius  (degC)
	cai (mM)
	gkbar = 0.038 (mho/cm2)
	Q10 = 3
	diff = 3 (1) : diffusion factor

: rates ca-indipendent
	invc1 = 80e-3  ( /ms)
	invc2 = 80e-3  ( /ms)
	invc3 = 200e-3 ( /ms)

	invo1 = 1      ( /ms)
	invo2 = 100e-3 ( /ms)
	diro1 = 160e-3 ( /ms)
	diro2 = 1.2    ( /ms)

: rates ca-dipendent
	dirc2 = 200 ( /ms-mM )
	dirc3 = 160 ( /ms-mM )
	dirc4 = 80  ( /ms-mM )
}

ASSIGNED{ 
	v	(mV) 
	ek	(mV) 
	g	(mho/cm2) 
	ik	(mA/cm2) 
	invc1_t  ( /ms)
	invc2_t  ( /ms)
	invc3_t  ( /ms)
	invo1_t  ( /ms)
	invo2_t  ( /ms)
	diro1_t  ( /ms)
	diro2_t  ( /ms)
	dirc2_t  ( /ms)
	dirc3_t  ( /ms)
	dirc4_t  ( /ms)
	tcorr	 (1)

	dirc2_t_ca  ( /ms-mM)
	dirc3_t_ca  ( /ms-mM)
	dirc4_t_ca  ( /ms-mM)
} 

STATE {
	c1
	c2
	c3
	c4
	o1
	o2
}

BREAKPOINT{ 
	SOLVE kin METHOD sparse 
	g = gkbar*(o1+o2)	:(mho/cm2)
	ik = g*(v-ek)		:(mA/cm2)
} 

INITIAL{
	rate(celsius)
	SOLVE kin STEADYSTATE sparse
} 

KINETIC kin{ 
	rates(cai/diff) 
	~c1<->c2 (dirc2_t_ca, invc1_t) 
	~c2<->c3 (dirc3_t_ca, invc2_t) 
	~c3<->c4 (dirc4_t_ca, invc3_t) 
	~c3<->o1 (diro1_t, invo1_t) 
	~c4<->o2 (diro2_t, invo2_t) 
	CONSERVE c1+c2+c3+c4+o2+o1=1 
} 

FUNCTION temper (Q10, celsius (degC)) {
	temper = Q10^((celsius -23(degC)) / 10(degC)) 
}

PROCEDURE rates(cai(mM)){
	dirc2_t_ca = dirc2_t*cai
	dirc3_t_ca = dirc3_t*cai
	dirc4_t_ca = dirc4_t*cai 
} 

PROCEDURE rate (celsius(degC)) {
	tcorr = temper (Q10,celsius)
	invc1_t = invc1*tcorr  
	invc2_t = invc2*tcorr
	invc3_t = invc3*tcorr 
	invo1_t = invo1*tcorr 
	invo2_t = invo2*tcorr 
	diro1_t = diro1*tcorr 
	diro2_t = diro2*tcorr 
	dirc2_t = dirc2*tcorr
	dirc3_t = dirc3*tcorr
	dirc4_t = dirc4*tcorr
}

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