Chris Eliasmith, University of Waterloo, Canada

Chris Eliasmith, University of Waterloo, Canada


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, which we call the Semantic Pointer Architecture (SPA).  I demonstrate the approach with applications to the well-known Tower of Hanoi task (which demands planning, memory, and decision making), and the Raven's Progressive Matrices (a general intelligence test) if time permits. I argue that the SPA provides a principled way of bridging the gap between biological constraints and psychological constraints on cognition. 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.


Neural representations of compositional structures

Neural cognitive Modelling