Nengo and Large-Scale Neural Modelling

Members: Aleksandrs Ecins, Chris Eliasmith, Garrick Orchard, Kwabena Boahen, Mounya Elhilali, Michael Pfeiffer, Shih-Chii Liu, Tomas Figliolia, Timmer Horiuchi, Troy Lau, Andre van Schaik

This tutorial is meant to give a hands-on introduction to Nengo, a neural modelling toolkit. The main difference between Nengo and other neural modelling approaches is that we can directly specify a particular computation to be performed by the synaptic connections from one neural group to another. For example, if one neural group of 100 neurons represents velocity (a 2-dimensional vector) and we want to have another neural group of 100 neurons represent position (the integral of velocity), Nengo can solve for the feed-forward and recurrent 100x100 connection weight matrices that will compute that function.

Nengo is written primarily in Java, with a Python scripting interface. The latest version is available at  http://ctn.uwaterloo.ca/~cnrglab/f/nengo-1.3b.zip and it runs on Linux, OS X, and Windows. To install, unzip the file and run nengo (under Linux and and OS X) or nengo.bat (under Windows).

Tutorial Material