Wiki » History » Version 11
Version 10 (Vitor Chaud, 30 Apr 2014 14:57) → Version 11/45 (Padraig Gleeson, 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** | **Comments** |
|Tonic spiking | A |OK | OK || |
|Phasic spiking| B |OK | OK || |
|Tonic bursting| C |OK | OK || |
|Phasic bursting| D |OK | OK || |
|Mixed mode| E |OK | OK || |
|Spike freq. adapt.| F |OK | OK || |
|Class 1 excitable| G |not yet implemented| OK (although new ComponentType [generalizedIzhikevichCell](https://github.com/OpenSourceBrain/IzhikevichModel/blob/master/NeuroML2/GeneralizedIzhikevichCell.xml) required)| PROBLEM| Different model parameterization | parameterization|
|Class 2 excitable| H |not yet implemented| OK || |
|Spike latency | I |OK| OK| |
|Subthresh. osc.| J |OK| OK| |
|Resonator| K |not yet implemented| OK || |
|Integrator| L |not yet implemented| PROBLEM| Different model parameterization|
|Rebound spike| M |OK| OK || |
|Rebound burst| N |OK| OK || |
|Threshold variability| O |not yet implemented| OK || |
|Bistability| P |PROBLEM| PROBLEM |
|Depolarizing after-potential| Q |PROBLEM| PROBLEM| Response depending on the time step|
|Accomodation| R |not yet implemented| PROBLEM| Different from fig1|
|Inhibition-induced spiking| S |PROBLEM| PROBLEM| Response depending on the time step|
|Inhibition-induced bursting| T |PROBLEM | PROBLEM| Response diverging on PyNN and depending on the time step on NeuroML|
------------
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** | **Comments** |
|Tonic spiking | A |OK | OK || |
|Phasic spiking| B |OK | OK || |
|Tonic bursting| C |OK | OK || |
|Phasic bursting| D |OK | OK || |
|Mixed mode| E |OK | OK || |
|Spike freq. adapt.| F |OK | OK || |
|Class 1 excitable| G |not yet implemented| OK (although new ComponentType [generalizedIzhikevichCell](https://github.com/OpenSourceBrain/IzhikevichModel/blob/master/NeuroML2/GeneralizedIzhikevichCell.xml) required)| PROBLEM| Different model parameterization | parameterization|
|Class 2 excitable| H |not yet implemented| OK || |
|Spike latency | I |OK| OK| |
|Subthresh. osc.| J |OK| OK| |
|Resonator| K |not yet implemented| OK || |
|Integrator| L |not yet implemented| PROBLEM| Different model parameterization|
|Rebound spike| M |OK| OK || |
|Rebound burst| N |OK| OK || |
|Threshold variability| O |not yet implemented| OK || |
|Bistability| P |PROBLEM| PROBLEM |
|Depolarizing after-potential| Q |PROBLEM| PROBLEM| Response depending on the time step|
|Accomodation| R |not yet implemented| PROBLEM| Different from fig1|
|Inhibition-induced spiking| S |PROBLEM| PROBLEM| Response depending on the time step|
|Inhibition-induced bursting| T |PROBLEM | PROBLEM| Response diverging on PyNN and depending on the time step on NeuroML|