A detailed Purkinje cell model (Masoli et al 2015)

 Download zip file   Auto-launch 
Help downloading and running models
Accession:229585
The Purkinje cell is one of the most complex type of neuron in the central nervous system and is well known for its massive dendritic tree. The initiation of the action potential was theorized to be due to the high calcium channels presence in the dendritic tree but, in the last years, this idea was revised. In fact, the Axon Initial Segment, the first section of the axon was seen to be critical for the spontaneous generation of action potentials. The model reproduces the behaviours linked to the presence of this fundamental sections and the interplay with the other parts of the neuron.
Reference:
1 . Masoli S, Solinas S, D'Angelo E (2015) Action potential processing in a detailed Purkinje cell model reveals a critical role for axonal compartmentalization. Front Cell Neurosci 9:47 [PubMed]
Citations  Citation Browser
Model Information (Click on a link to find other models with that property)
Model Type: Neuron or other electrically excitable cell; Axon;
Brain Region(s)/Organism: Cerebellum;
Cell Type(s): Cerebellum Purkinje GABA cell;
Channel(s): I Sodium; I Calcium; I Na,t; I K;
Gap Junctions:
Receptor(s):
Gene(s): Cav2.1 CACNA1A; Cav3.1 CACNA1G; Cav3.2 CACNA1H; Cav3.3 CACNA1I; Nav1.6 SCN8A; Kv1.1 KCNA1; Kv1.5 KCNA5; Kv3.3 KCNC3; Kv3.4 KCNC4; Kv4.3 KCND3; KCa1.1 KCNMA1; KCa2.2 KCNN2; KCa3.1 KCNN4; Kir2.1 KCNJ2; HCN1;
Transmitter(s):
Simulation Environment: NEURON; Python;
Model Concept(s): Bursting; Detailed Neuronal Models; Action Potentials; Action Potential Initiation; Axonal Action Potentials;
Implementer(s): Masoli, Stefano [stefano.masoli at unipv.it]; Solinas, Sergio [solinas at unipv.it];
Search NeuronDB for information about:  Cerebellum Purkinje GABA cell; I Na,t; I K; I Sodium; I Calcium;
pc_param = dict()

#Conductances for all the channels with the same order as in the template

#SOMA
pc_param['eleak'] = -63
pc_param['LeakSoma'] = 1.1E-3
pc_param['Cav3.1Soma'] = 7e-6
pc_param['Cav2.1Soma'] = 2.2e-4 
pc_param['HCNSoma'] = 0.0004
pc_param['Nav1.6Soma'] = 0.214
pc_param['Kv3.4Soma'] = 0.05
pc_param['Kv1.1Soma'] = 0.002 
pc_param['Cav3.2Soma'] = 0.0008 
pc_param['Kca3.1Soma'] = 0.01 
pc_param['Cav3.3Soma'] = 0.0001 
pc_param['PC_KirSoma'] = 0.00003 
pc_param['Kca1.1Soma'] = 0.01 
pc_param['Kca2.2Soma'] = 1e-3 


#DEND
pc_param['Cav2.1Dend'] = 1e-3 
pc_param['Kca1.1Dend'] = 3.5e-2
pc_param['Kv4.3Dend'] = 0.001
pc_param['Kv1.1Dend'] = 0.0012 
pc_param['Kv1.5Dend'] = 0.13195e-3
pc_param['Kv3.3Dend'] = 0.01 
pc_param['Cav3.3Dend'] = 0.0001 
pc_param['Cav3.2Dend'] = 0.0012 
pc_param['Kca3.1Dend'] = 0.002
pc_param['Cav3.1Dend'] = 5e-6 
pc_param['Kca2.2Dend'] = 1e-3
pc_param['PC_KirDend'] = 0.00001
pc_param['Nav1.6Dend'] = 0.016
pc_param['HCNDend'] = 0.000004 

#AIS
pc_param['Cav3.1Ais'] = 8.2e-6
pc_param['Nav1.6AIS'] = 0.50 
pc_param['Cav2.1AIS'] = 2.2e-4 
pc_param['Kv3.4AIS'] = 0.01 

#AISK
pc_param['Kv1.1AisK'] = 0.01 

#First node Of Ranvier
pc_param['Nav1.6Nor'] = 0.03 
pc_param['Kv3.4Nor'] = 0.02  
pc_param['Cav3.1Nor'] = 1e-5 
pc_param['Cav2.1Nor'] = 2.2e-4 

#Second node Of Ranvier
pc_param['Nav1.6Nor2'] = 0.03 
pc_param['Kv3.4Nor2'] = 0.02  
pc_param['Cav3.1Nor2'] = 1e-5 
pc_param['Cav2.1Nor2'] = 2.2e-4  

#Third node Of Ranvier
pc_param['Nav1.6Nor3'] = 0.03
pc_param['Kv3.4Nor3'] = 0.02  
pc_param['Cav3.1Nor3'] = 1e-5 
pc_param['Cav2.1Nor3'] = 2.2e-4 

#Axon collateral
pc_param['Nav1.6Axoncoll'] = 0.03 
pc_param['Kv3.4Axoncoll'] = 0.02
pc_param['Cav3.1Axoncoll'] = 1e-5 
pc_param['Cav2.1Axoncoll'] = 2.2e-4