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Population models of temporal differentiation

Description: 
This package contains the simulation software for Tripp & Eliasmith, Population models of temporal differentiation, Neural Computation. This software is not self-contained -- it runs within the Nengo simulation environment (www.nengo.ca). The enclosed code consists of Java classes, which contain the models, and Python scripts, which automate loading and simulation of the models.
Requirements: 
Peer Reviewed: 
Yes
Publication: 
Tripp, B., Eliasmith, C. (2010). Population models of temporal differentiation. Neural Computation. 22(3), 621-59
Instructions: 

Overview
--------

This package contains the simulation software for Tripp & Eliasmith, Population models of temporal differentiation, Neural Computation.
This software is not self-contained -- it runs within the Nengo simulation environment (www.nengo.ca). The enclosed code consists of
Java classes, which contain the models, and Python scripts, which automate loading and simulation of the models.

Browsing The Code
-----------------

If you just want to see precisely how we did something, you may want to read the Java code. This code is based on the Nengo API, which is
documented at http://nengo.ca/javadoc/index.html A good place to start is the class com.bptripp.diff.DifferentiatorNetwork, which is the
parent class for all of the models.

Running the Code
----------------

1) Download and install Nengo from www.nengo.ca
2) Add the enclosed diff.jar (which contains compiled versions of the Java classes) to the "plugins" directory under the Nengo install.
3) Start Nengo.
4) Open the Python script console within Nengo, and type "run [path]loadNetworks.py" where [path] is the path to your copy of the
Python scripts.

You may then run other scripts of interest, e.g. simulations.py.

Help
----

If you run into difficulties, please do not hesitate to contact Bryan Tripp (bptripp at gmail.com).