Phase response curves firing rate dependency of rat purkinje neurons in vitro (Couto et al 2015)

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Accession:155735
NEURON implementation of stochastic gating in the Khaliq-Raman Purkinje cell model. NEURON implementation of the De Schutter and Bower model of a Purkinje Cell. Matlab scripts to compute the Phase Response Curve (PRC). LCG configuration files to experimentally determine the PRC. Integrate and Fire models (leaky and non-leaky) implemented in BRIAN to see the influence of the PRC in a network of unconnected neurons receiving sparse common input.
Reference:
1 . Couto J, Linaro D, De Schutter E, Giugliano M (2015) On the firing rate dependency of the phase response curve of rat Purkinje neurons in vitro. PLoS Comput Biol 11:e1004112 [PubMed]
2 . Linaro D, Couto J, Giugliano M (2014) Command-line cellular electrophysiology for conventional and real-time closed-loop experiments. J Neurosci Methods 230:5-19 [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;
Brain Region(s)/Organism:
Cell Type(s): Cerebellum Purkinje GABA cell;
Channel(s):
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment: NEURON; MATLAB; Brian; LCG; Python;
Model Concept(s): Phase Response Curves;
Implementer(s): Couto, Joao [jpcouto at gmail.com];
Search NeuronDB for information about:  Cerebellum Purkinje GABA cell; 
TITLE Purkinje Leak Current

: A passive purkinje cell leak current
NEURON {
	SUFFIX lkpkj
	NONSPECIFIC_CURRENT i
	RANGE i, e, g
}
PARAMETER {
	g = 5e-5	(siemens/cm2)  < 0, 1e9 >
	e = -60	(millivolt)
}
ASSIGNED {
	i  (milliamp/cm2)
	v  (millivolt)
}
BREAKPOINT { i = g*(v - e) }