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Vitor Chaud, 30 Apr 2014 14:57

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Introduction
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This project will contain examples of the Izhikevich spiking neuron model.





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### Installation





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To get local clone of this project…





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### Versions of the project





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The original model in [MATLAB format](http://izhikevich.org/publications/figure1.m) has been converted to a number of other formats.





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#### PyNN





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…





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Tested with simulators: NEURON…





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#### NeuroML 2





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…





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The XML for an Izhikevich model in NeuroML v2.0 is below:





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    <code class="xml">





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    <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>





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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)





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Tested with simulators: …





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### Comparison to original model behaviour





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table{border:1px solid black}.





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{background:\#ddd}. |**Model**|**Label** |**PyNN** |**NeuroML** | **Comments** |





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|Tonic spiking | &nbsp;&nbsp;&nbsp;A&nbsp; &nbsp; &nbsp; |OK | &nbsp;&nbsp;&nbsp;OK |





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|Phasic spiking| &nbsp;&nbsp;&nbsp;B |OK | &nbsp;&nbsp;&nbsp;OK |





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|Tonic bursting| &nbsp;&nbsp;&nbsp;C |OK | &nbsp;&nbsp;&nbsp;OK |





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|Phasic bursting| &nbsp;&nbsp;&nbsp;D |OK | &nbsp;&nbsp;&nbsp;OK |





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|Mixed mode| &nbsp;&nbsp;&nbsp;E |OK | &nbsp;&nbsp;&nbsp;OK |





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|Spike freq. adapt.| &nbsp;&nbsp;&nbsp;F |OK | &nbsp;&nbsp;&nbsp;OK |





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|Class 1 excitable| &nbsp;&nbsp;&nbsp;G |not yet implemented| &nbsp;&nbsp;&nbsp;PROBLEM| &nbsp;&nbsp;&nbsp;Different model parameterization|





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|Class 2 excitable| &nbsp;&nbsp;&nbsp;H |not yet implemented| &nbsp;&nbsp;&nbsp;OK |





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|Spike latency | &nbsp;&nbsp;&nbsp;I |OK| &nbsp;&nbsp;&nbsp;OK|





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|Subthresh. osc.| &nbsp;&nbsp;&nbsp;J |OK| &nbsp;&nbsp;&nbsp;OK|





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|Resonator| &nbsp;&nbsp;&nbsp;K |not yet implemented| &nbsp;&nbsp;&nbsp;OK |





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|Integrator| &nbsp;&nbsp;&nbsp;L |not yet implemented| &nbsp;&nbsp;&nbsp;PROBLEM| &nbsp;&nbsp;&nbsp;Different model parameterization|





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|Rebound spike| &nbsp;&nbsp;&nbsp;M |OK| &nbsp;&nbsp;&nbsp;OK |





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|Rebound burst| &nbsp;&nbsp;&nbsp;N |OK| &nbsp;&nbsp;&nbsp;OK |





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|Threshold variability| &nbsp;&nbsp;&nbsp;O |not yet implemented| &nbsp;&nbsp;&nbsp;OK |





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|Bistability| &nbsp;&nbsp;&nbsp;P |PROBLEM| &nbsp;&nbsp;&nbsp;PROBLEM |





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|Depolarizing after-potential| &nbsp;&nbsp;&nbsp;Q |PROBLEM| &nbsp;&nbsp;&nbsp;PROBLEM| &nbsp;&nbsp;&nbsp;Response depending on the time step|





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|Accomodation| &nbsp;&nbsp;&nbsp;R |not yet implemented| &nbsp;&nbsp;&nbsp;PROBLEM| &nbsp;&nbsp;&nbsp;Different from fig1|





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|Inhibition-induced spiking| &nbsp;&nbsp;&nbsp;S |PROBLEM| &nbsp;&nbsp;&nbsp;PROBLEM| &nbsp;&nbsp;&nbsp;Response depending on the time step|





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|Inhibition-induced bursting| &nbsp;&nbsp;&nbsp;T |PROBLEM | &nbsp;&nbsp;&nbsp;PROBLEM| &nbsp;&nbsp;&nbsp;Response diverging on PyNN and depending on the time step on NeuroML|