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;
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## $Id: bounds.txt 1.3.2.1.1.2 Thu, 04 Apr 2002 12:35:02 +0200 hugo $
##
##
##############################################################################
##
## Purkinje tutorial
##
## (C) 1998-2002 BBF-UIA
##
## see our site at http://www.bbf.uia.ac.be/ for more information regarding
## the Purkinje cell and genesis simulation software.
##
##
## functional ideas ... Erik De Schutter, erik@bbf.uia.ac.be
## genesis coding ..... Hugo Cornelis, hugo@bbf.uia.ac.be
##
## general feedback ... Reinoud Maex, Erik De Schutter
##
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#
# this file describes the default color boundaries for the xcell
# and the default axes' ranges for the graph
# comments can start with a '#'
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# format-descr. :
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# 9 fields on each line, seperated by tabs :
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# 1. {enabled output button}_{displayed field}
# 2. XCell minimum, absolute mode
# 3. XCell maximum, absolute mode
# 4. XGraph minimum, absolute mode
# 5. XGraph maximum, absolute mode
# 6-9. Same as 2-5, normalized mode
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# 1		2	3	4	5	6	7	8	9
#
_Vm		-0.08	0.02	-0.1	0.05	-0.08	0.02	-0.1	0.05
Ca_pool_Ca	0.0	0.005	0.0	0.010	0.0	0.005	0.0	0.010
CaP_Ik		0.0	1e-10	0.0	6e-10	0.0	0.05	0.0	0.08
CaT_Ik		0.0	1e-12	0.0	6e-11	0.0	0.003	0	0.004
K2_Ik		-1e-11	0.0	-2e-11	0.0	-0.02	0.0	-0.04	0.0
KA_Ik		-5e-12	0.0	-5e-10	0.0	-0.001	0.0	-0.004	0.0
KC_Ik		-1e-11	0.0	-4e-10	0.0	-0.003	0.0	-0.005	0.0
KM_Ik		-2e-13	0.0	-4e-13	0.0	-0.02	0.0	-0.03	0.0
Kdr_Ik		-2e-11	0.0	-2e-8	0.0	-0.0005	0.0	-0.001	0.0
NaF_Ik		0.0	1.6e-9	0.0	3e-7	0.0	0.0001	0.0	0.001
NaP_Ik		0.0	2e-10	0.0	2e-9	0.0	0.02	0.0	0.07
h1_Ik		0.0	2e-12	0.0	2e-11	-0.001	0.002	-0.004	0.004
h2_Ik		0.0	1e-12	0.0	1e-11	-0.001	0.001	-0.002	0.002
excitatory_Ik	0.0	2e-11	0.0	4e-11	0.0	3e-10	0.0	1e-9
inhibitory_Ik	-6e-10	0.0	-1e-09	0.0	-3e-10	0.0	-5e-10	0.0
CaP_Gk		0.0	2e-9	0.0	6e-9	0.0	0.5	0.0	1.0
CaT_Gk		0.0	1e-10	0.0	4e-10	0.0	0.02	0.0	0.03
K2_Gk		0.0	2e-10	0.0	1e-9	0.0	0.5	0.0	0.8
KA_Gk		0.0	5e-11	0.0	7e-9	0.0	0.01	0.0	0.03
KC_Gk		0.0	5e-10	0.0	5e-9	0.0	0.05	0.0	0.05
KM_Gk		0.0	1e-11	0.0	5e-10	0.0	0.3	0.0	0.5
Kdr_Gk		0.0	1e-9	0.0	3e-7	0.0	0.01	0.0	0.05
NaF_Gk		0.0	1e-7	0.0	6e-6	0.0	0.01	0.0	0.03
NaP_Gk		0.0	1e-8	0.0	3e-8	0.0	0.1	0.0	1.0
h1_Gk		0.0	2e-10	0.0	1e-9	0.0	0.02	0.0	0.1
h2_Gk		0.0	1e-10	0.0	5e10	0.0	0.005	0.0	0.01
excitatory_Gk	0.0	5e-10	0.0	7e-10	0.0	5e-09	0.0	8e-09
inhibitory_Gk	0.0	1e-09	0.0	1e-08	0.0	1e-08	0.0	2e-08
CaP_Ek		0.10	0.14	0.07	0.14	0.10	0.14	0.07	0.14
CaT_Ek		0.10	0.14	0.07	0.14	0.10	0.14	0.07	0.14
K2_Ek		-0.09	1	-0.09	1	-0.09	1	-0.09	1
KA_Ek		-0.09	-0.08	-0.09	-0.08	-0.09	-0.08	-0.09	-0.08
KC_Ek		-0.09	-0.08	-0.09	-0.08	-0.09	-0.08	-0.09	-0.08
KM_Ek		-0.09	-0.08	-0.09	-0.08	-0.09	-0.08	-0.09	-0.08
Kdr_Ek		-0.09	-0.08	-0.09	-0.08	-0.09	-0.08	-0.09	-0.08
NaF_Ek		0.04	0.05	0.04	0.05	0.04	0.05	0.04	0.05
NaP_Ek		0.04	0.05	0.04	0.05	0.04	0.05	0.04	0.05
h1_Ek		-0.04	-0.02	-0.04	-0.02	-0.04	-0.02	-0.04	-0.02
h2_Ek		-0.04	-0.02	-0.04	-0.02	-0.04	-0.02	-0.04	-0.02
excitatory_Ek	-0.01	0.01	-0.01	0.01	-0.01	0.01	-0.01	0.01
inhibitory_Ek	-0.09	-0.07	-0.09	-0.07	-0.09	-0.07	-0.09	-0.07