SC5 Neural Engineering with Nengo
Course content: This course explores how to build behaving brains. That is, we will use the neural modelling software Nengo to define complex biologically realistic neural networks that are capable of performing tasks. These models can combine sensory systems, motor systems, memory, decision making, adaptation, reinforcement learning, and so on, into an integrated whole. We will look at how these techniques can be used to model simple animal behaviour tasks, and up to complex cognitive tasks.
Session 1: Representing and Computing with Spiking Neurons
Session 2: Temporal Dynamics and Integrated Behaviour
Session 3: Decision Making and Cognitive Control
Session 4: Learning and Adaptation
Participants will be able to run Nengo for themselves, constructing small models demonstrating basic principles. They will also work with and modify existing, more complex models of behaviour such as foraging, seeking, reward learning, and sequential decision making. Ideally, participants can define possible projects related to their own research that can be worked on either at IK or afterwards (as has happened in previous years).
- Eliasmith. How to build a brain: A neural architecture for biological cognition. Oxford University Press, New York, NY, 2013. http://nengo.ca/build-a-brain
- Bekolay, Bergstra, Hunsberger, DeWolf, Stewart, Rasmussen, Choo, Voelker, and Eliasmith. Nengo: a Python tool for building large-scale functional brain models. Frontiers in Neuroinformatics, 2014. http://compneuro.uwaterloo.ca/publications/bekolay2014.html
- Sharma, Aubin, and Eliasmith. Large-scale cognitive model design using the Nengo neural simulator. Biologically Inspired Cognitive Architectures, 2016. http://compneuro.uwaterloo.ca/publications/sharma2016.html
- Eliasmith, Stewart, Choo, Bekolay, DeWolf, Tang, and Rasmussen. A large-scale model of the functioning brain. Science, 338:1202-1205, 2012. http://compneuro.uwaterloo.ca/publications/eliasmith2012.html
Lecture Room 3Course requirements