Wiki » History » Version 19
Version 18 (Vitor Chaud, 30 Apr 2014 14:57) → Version 19/45 (Vitor Chaud, 30 Apr 2014 14:57)
Introduction
------------
This project will contain examples of the Izhikevich spiking neuron model.
### Installation
To get local clone of this project…
### Versions of the project
The original model in [MATLAB format](http://izhikevich.org/publications/figure1.m) has been converted to a number of other formats.
#### PyNN
…
Tested with simulators: NEURON…
#### NeuroML 2
…
The XML for an Izhikevich model in NeuroML v2.0 is below:
<code class="xml">
<izhikevichCell id="TonicSpiking" v0 = "-70mV" thresh = "30mV" a ="0.02" b = "0.2" c = "-65.0" d = "6" Iamp="0" Idel="0ms" Idur="2000ms"/></code>
For full examples of single cells see [TonicSpiking](/projects/izhikevichmodel/repository/entry/neuroConstruct/cellMechanisms/TonicSpiking/TonicSpiking.nml) or [PhasicBursting](/projects/izhikevichmodel/repository/entry/neuroConstruct/cellMechanisms/PhasicBursting/PhasicBursting.nml)
Tested with simulators: …
### Comparison to original model behaviour
table{border:1px solid black}.
{background:\#ddd}. |**Model**| **Label** | **PyNN** | **NeuroML** |
|Tonic spiking | A |(a) | (a) |
|Phasic spiking| B |(a) | (a) |
|Tonic bursting| C |(b) | (b) |
|Phasic bursting| D |(a) | (a) |
|Mixed mode| E |(a) | (a) |
|Spike freq. adapt.| F |(a) | (a) |
|Class 1 excitable| G |(d, e)| (a, e) |
|Class 2 excitable| H |(d)| © |
|Spike latency | I |(b)| (b) |
|Subthresh. osc.| J |(a)| (a) |
|Resonator| K |(a)| (a) |
|Integrator| L |(e)| (a, e) |
|Rebound spike| M |(a)| (a) |
|Rebound burst| N |(a)| (a) |
|Threshold variability| O |(a)| (a) |
|Bistability| P |(b)| (b) |
|Depolarizing after-potential| Q |(b)| (b) |
|Accomodation| R |(d)| (a, f)|
|Inhibition-induced spiking| S |(a)| ©|
|Inhibition-induced bursting| T |(b) | (b)|
(a) Same behaviour
(b) Similar behaviour when slightly modifying parameters
© Similar but not identical behaviour (different number of spikes in the stimulus time frame)
(d) Not yet implemented. Need ramp injected current. See https://github.com/NeuralEnsemble/PyNN/issues/257 See..
(e) Requires an alternative model implementation since the model parameterization is different in the original Matlab code. In NeuroML new ComponentType [generalizedIzhikevichCell](https://github.com/OpenSourceBrain/IzhikevichModel/blob/master/NeuroML2/GeneralizedIzhikevichCell.xml) was created.
(f) Requires an alternative model implementation since the model parameterization is different in the original Matlab code. In NeuroML new ComponentType [accomodationIzhikevichCell](https://github.com/OpenSourceBrain/IzhikevichModel/blob/master/NeuroML2/GeneralizedIzhikevichCell.xml) was created.
------------
This project will contain examples of the Izhikevich spiking neuron model.
### Installation
To get local clone of this project…
### Versions of the project
The original model in [MATLAB format](http://izhikevich.org/publications/figure1.m) has been converted to a number of other formats.
#### PyNN
…
Tested with simulators: NEURON…
#### NeuroML 2
…
The XML for an Izhikevich model in NeuroML v2.0 is below:
<code class="xml">
<izhikevichCell id="TonicSpiking" v0 = "-70mV" thresh = "30mV" a ="0.02" b = "0.2" c = "-65.0" d = "6" Iamp="0" Idel="0ms" Idur="2000ms"/></code>
For full examples of single cells see [TonicSpiking](/projects/izhikevichmodel/repository/entry/neuroConstruct/cellMechanisms/TonicSpiking/TonicSpiking.nml) or [PhasicBursting](/projects/izhikevichmodel/repository/entry/neuroConstruct/cellMechanisms/PhasicBursting/PhasicBursting.nml)
Tested with simulators: …
### Comparison to original model behaviour
table{border:1px solid black}.
{background:\#ddd}. |**Model**| **Label** | **PyNN** | **NeuroML** |
|Tonic spiking | A |(a) | (a) |
|Phasic spiking| B |(a) | (a) |
|Tonic bursting| C |(b) | (b) |
|Phasic bursting| D |(a) | (a) |
|Mixed mode| E |(a) | (a) |
|Spike freq. adapt.| F |(a) | (a) |
|Class 1 excitable| G |(d, e)| (a, e) |
|Class 2 excitable| H |(d)| © |
|Spike latency | I |(b)| (b) |
|Subthresh. osc.| J |(a)| (a) |
|Resonator| K |(a)| (a) |
|Integrator| L |(e)| (a, e) |
|Rebound spike| M |(a)| (a) |
|Rebound burst| N |(a)| (a) |
|Threshold variability| O |(a)| (a) |
|Bistability| P |(b)| (b) |
|Depolarizing after-potential| Q |(b)| (b) |
|Accomodation| R |(d)| (a, f)|
|Inhibition-induced spiking| S |(a)| ©|
|Inhibition-induced bursting| T |(b) | (b)|
(a) Same behaviour
(b) Similar behaviour when slightly modifying parameters
© Similar but not identical behaviour (different number of spikes in the stimulus time frame)
(d) Not yet implemented. Need ramp injected current. See https://github.com/NeuralEnsemble/PyNN/issues/257 See..
(e) Requires an alternative model implementation since the model parameterization is different in the original Matlab code. In NeuroML new ComponentType [generalizedIzhikevichCell](https://github.com/OpenSourceBrain/IzhikevichModel/blob/master/NeuroML2/GeneralizedIzhikevichCell.xml) was created.
(f) Requires an alternative model implementation since the model parameterization is different in the original Matlab code. In NeuroML new ComponentType [accomodationIzhikevichCell](https://github.com/OpenSourceBrain/IzhikevichModel/blob/master/NeuroML2/GeneralizedIzhikevichCell.xml) was created.