Cerebellar purkinje cell (De Schutter and Bower 1994)

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Accession:7176
Tutorial simulation of a cerebellar Purkinje cell. This tutorial is based upon a GENESIS simulation of a cerebellar Purkinje cell, modeled and fine-tuned by Erik de Schutter. The tutorial assumes that you have a basic knowledge of the Purkinje cell and its synaptic inputs. It gives visual insight in how different properties as concentrations and channel conductances vary and interact within a real Purkinje cell.
Reference:
1 . De Schutter E, Bower JM (1994) An active membrane model of the cerebellar Purkinje cell. I. Simulation of current clamps in slice. J Neurophysiol 71:375-400 [PubMed]
2 . De Schutter E, Bower JM (1994) An active membrane model of the cerebellar Purkinje cell II. Simulation of synaptic responses. J Neurophysiol 71:401-19 [PubMed]
3 . Staub C, De Schutter E, Knöpfel T (1994) Voltage-imaging and simulation of effects of voltage- and agonist-activated conductances on soma-dendritic voltage coupling in cerebellar Purkinje cells. J Comput Neurosci 1:301-11 [PubMed]
4 . De Schutter E, Bower JM (1994) Simulated responses of cerebellar Purkinje cells are independent of the dendritic location of granule cell synaptic inputs. Proc Natl Acad Sci U S A 91:4736-40 [PubMed]
5 . De Schutter E (1998) Dendritic voltage and calcium-gated channels amplify the variability of postsynaptic responses in a Purkinje cell model. J Neurophysiol 80:504-19 [PubMed]
6 . Jaeger D, De Schutter E, Bower JM (1997) The role of synaptic and voltage-gated currents in the control of Purkinje cell spiking: a modeling study. J Neurosci 17:91-106 [PubMed]
7 . de Schutter E (1994) Modelling the cerebellar Purkinje cell: experiments in computo. Prog Brain Res 102:427-41 [PubMed]
8 . De Schutter E (1997) A new functional role for cerebellar long-term depression. Prog Brain Res 114:529-42 [PubMed]
9 . Steuber V, Mittmann W, Hoebeek FE, Silver RA, De Zeeuw CI, Häusser M, De Schutter E (2007) Cerebellar LTD and pattern recognition by Purkinje cells. Neuron 54:121-36 [PubMed]
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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:
Cell Type(s): Cerebellum Purkinje GABA cell;
Channel(s): I Na,p; I Na,t; I T low threshold; I p,q; I A; I K; I M; I K,Ca; I Sodium; I Calcium; I Potassium;
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment: GENESIS;
Model Concept(s): Activity Patterns; Dendritic Action Potentials; Active Dendrites; Detailed Neuronal Models; Tutorial/Teaching; Synaptic Integration;
Implementer(s): Cornelis, Hugo [hugo at bbf.uia.ac.be]; Airong, Dong [tard at fimmu.com];
Search NeuronDB for information about:  Cerebellum Purkinje GABA cell; I Na,p; I Na,t; I T low threshold; I p,q; I A; I K; I M; I K,Ca; I Sodium; I Calcium; I Potassium; 
//genesis  - Purkinje cell M9 genesis2.1 script
/* Copyright E. De Schutter (Caltech and BBF-UIA) */

/* This file defines important simulation parameters, including gmax
** and Ek for all channels.  Everything uses SI units. */

int include_purk_const

if ( {include_purk_const} == 0 )

	include_purk_const = 1


echo Using Purkinje 2M9 preferences. Crank Nicholson method.
/* variables controlling hsolve integration */
float dt = 2.0e-5
int tab_xdivs = 149; int tab_xfills = 2999
/* The model is quite sensitive to these values in NO_INTERP (caclmode=0) */
float tab_xmin = -0.10; float tab_xmax = 0.05; float Ca_tab_max = 0.300
// only used for proto channels
float GNa = 1, GCa = 1, GK = 1, Gh = 1
/* cable parameters */
float CM = 0.0164 		// *9 relative to passive
float RMs = 1.000 		// /3.7 relative to passive comp
float RMd = 3.0
float RA = 2.50
/* preset constants */
float ELEAK = -0.0800 		// Ek value used for the leak conductance
float EREST_ACT = -0.0680 	// Vm value used for the RESET
/* concentrations */
float CCaO = 2.4000 		//external Ca as in normal slice Ringer
float CCaI = 0.000040		//internal Ca in mM
//diameter of Ca_shells
float Shell_thick = 0.20e-6
float CaTau = 0.00010	 	// Ca_concen tau
/* Currents: Reversal potentials in V and max conductances S/m^2 */
/* Codes: s=soma, m=main dendrite, t=thick dendrite, d=spiny dendrite */
float ENa = 0.045
float GNaFs = 75000.0
float GNaPs = 10.0
float ECa = 0.0125*{log {CCaO/CCaI}} // 0.135 V
float GCaTs = 5.00
float GCaTm = 5.00
float GCaTt = 5.00
float GCaTd = 5.00
float GCaPm = 45.0
float GCaPt = 45.0
float GCaPd = 45.0
float EK = -0.085
float GKAs = 150.0
float GKAm = 20.0
float GKdrs = 6000.0
float GKdrm = 600.0
float GKMs = 0.400
float GKMm = 0.100
float GKMt = 0.130
float GKMd = 0.130
float GKCm = 800.0
float GKCt = 800.0
float GKCd = 800.0
float GK2m = 3.90
float GK2t = 3.90
float GK2d = 3.90
float Eh = -0.030
float Ghs = 3.00
/* synapses: */
float E_GABA = -0.080
//float G_GABA = 70.0/dt
float G_GABA = 70.0
//float GB_GABA = 20.0/dt
float GB_GABA = 20.0
float E_non_NMDA = 0.000
//float G_par_syn = 750.0/dt
float G_par_syn = 750.0
//float G_cli_syn = 150.0/dt
float G_cli_syn = 150.0


end