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Artificial neuron model (Izhikevich 2003, 2004, 2007)
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Accession:
39948
A set of models is presented based on 2 related parameterizations to reproduce spiking and bursting behavior of multiple types of cortical neurons and thalamic neurons. These models combine the biologically plausibility of Hodgkin Huxley-type dynamics and the computational efficiency of integrate-and-fire neurons. Using these model, one can simulate tens of thousands of spiking cortical neurons in real time (1 ms resolution) using a desktop PC.
References:
1 .
Izhikevich EM (2007)
Dynamical Systems in Neuroscience: The Geometry of Excitability and Bursting
2 .
Izhikevich EM (2004) Which model to use for cortical spiking neurons?
IEEE Trans Neural Netw
15
:1063-70
[
PubMed
]
3 .
Izhikevich EM (2003) Simple model of spiking neurons.
IEEE Trans Neural Netw
14
:1569-72
[
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:
Cell Type(s):
Abstract Izhikevich neuron;
Channel(s):
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment:
NEURON;
MATLAB;
Model Concept(s):
Action Potential Initiation;
Activity Patterns;
Parameter Fitting;
Simplified Models;
Tutorial/Teaching;
Action Potentials;
Implementer(s):
Lytton, William [billl at neurosim.downstate.edu];
Dura-Bernal, Salvador [salvadordura at gmail.com];
Download the displayed file
/
izhikevich_simple_nrn
README
izhi2003a.mod
izhi2003b.mod
izhi2007a.mod
izhi2007b.mod
izhi2007bS.mod
izh2003.gif
*
Other models using izh2003.gif:
Artificial neuron model (Izhikevich 2003, 2004, 2007)
izhi2003.m
izhi2003.png
izhi2004.gif
*
Other models using izhi2004.gif:
Artificial neuron model (Izhikevich 2003, 2004, 2007)
izhi2004a.hoc
izhi2007.m
izhi2007Comparison.pdf
izhi2007Figs.py
izhi2007Wrapper.py
izhiGUI.py
mosinit.py
simple.py
execfile('izhiGUI.py')
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