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  <title type="html">Zero Brane</title>
  <subtitle type="html">By seeking, you will discover...</subtitle>
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  <updated>2005-12-03T07:13:26Z</updated>
  <author><name>Paul Kulchenko</name></author>
  <id>http://notebook.kulchenko.com/modeling/neural-modeling-neuron</id>
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  <entry>
    <title>Neural Modeling: Neuron</title>
    <category term='modeling' />
    <content type="html">&lt;p&gt;It seems logical to &lt;a href="modeling/neural-modeling"&gt;start building a neural network framework or a simulator&lt;/a&gt; with a neuronal model. Neuronal models and their implementations range from simple (like the &lt;a href="http://www.btinternet.com/~cfinnie/model.html"&gt;model that is implemented in Neural Viewer&lt;/a&gt;) to very complex (like the Hodgkin-Huxley model). While there are many models to use (&lt;a href="references/papers/which-model-to-use"&gt;Which model to use for cortical spiking neurons?&lt;/a&gt; article provides a good coverage of the existing models) I like the model proposed by Eugene Izhikevich in &lt;a href="references/papers/simple-model-of-spiking-neurons"&gt;Simple model of Spiking Neurons&lt;/a&gt; as it is computationally efficient and still biologically plausible.&lt;/p&gt;

&lt;p&gt;Eugene's website provides &lt;a href="http://www.nsi.edu/users/izhikevich/publications/figure1.m"&gt;&lt;span class="caps"&gt;MATLAB &lt;/span&gt;scripts&lt;/a&gt; to play with the models, but since I didn't have access to a &lt;span class="caps"&gt;MATLAB &lt;/span&gt;instance I decided to reproduce the same set of diagrams using Perl. After a couple of weeks of experiments and several emails to the author I was able to model various types of neurons according to the parameters described in &lt;a href="references/books/dynamical-systems-in-neuroscience"&gt;Dynamical Systems in Neuroscience: The Geometry of Excitability and Bursting&lt;/a&gt;. Here is how the results look for the &lt;strong&gt;regular spiking (RS)&lt;/strong&gt; neuron:&lt;/p&gt;

&lt;p&gt;&lt;img src="/images/neuron-izh-rs.gif" alt="" /&gt;&lt;/p&gt;

&lt;p&gt;And here are the results for the &lt;strong&gt;chattering (CH)&lt;/strong&gt; neuron:&lt;/p&gt;

&lt;p&gt;&lt;img src="/images/neuron-izh-ch.gif" alt="" /&gt;&lt;/p&gt;</content>
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    <published>2005-12-03T07:13:26Z</published>
    <updated>2005-12-03T07:13:26Z</updated>
    
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