Chris Eliasmith

Center for Theoretical Neuroscience

University of Waterloo

How to Build a Brain: From Single Cells to Cognitive Systems

Our lab has developed a method for constructing biologically realistic single cell models called the Neural Engineering Framework (NEF). We have used the NEF to propose novel models that successfully capture single cell dynamics, tuning properties, and spike patterns. Most of these models have been for small-scale neural systems (e.g. rodent path integration, working memory, the translational VOR, zebrafish motor control, etc.). In this talk I describe how these same principles can be used to provide a useful approach to cognitive modelling. I demonstrate the approach with applications to the well-known Wason card task (which demands context-sensitive linguistic inference), and the Raven's Progressive Matrices (a general intelligence test). I suggest that the consistent architecture used for these models is general, and dub it the Semantic Pointer Architecture. In the course of presenting these models, I will demonstrate Nengo (, a neural modelling environment which can be used to simplify the construction and simulation of such models.



Eliasmith C, Anderson CH (2003). Neural Engineering: Computation, Representation and Dynamics in Neurobiological Systems. MIT Press, Cambridge MA


Litt A, Eliasmith C, Thagard P (2008) Neural affective decision theory: choices, brains, and emotions. Cog Syst Res 9:252-73