Summary: How to build a brain: From function to implementation
Chris Eliasmith, University of Waterloo
Abstract: To have a fully integrated understanding of neurobiological systems, we
must address two fundamental questions: 1. What do brains do (what is their function)?
and 2. How do brains do whatever it is that they do (how is that function implemented)?
I begin by arguing that these questions are necessarily inter-related. Thus, addressing one
without consideration of an answer to the other, as is often done, is a mistake. I then
describe what I take to be the best available approach to addressing both questions.
Specifically, to address 2, I adopt the Neural Engineering Framework (NEF) of
Eliasmith & Anderson (2003) which identifies implementational principles for neural
models. To address 1, I suggest that adopting statistical modeling methods for perception
and action will be functionally sufficient for capturing biological behaviour. I show how
these two answers will be mutually constraining, since the process of model selection for
the statistical method in this approach can be informed by known anatomical and
physiological properties of the brain, captured by the NEF. Similarly, the application of
the NEF must be informed by functional hypotheses, captured by the statistical modeling
Theoretical approaches to cognitive science (which I take to include both psychology
and neuroscience) often attempt to construct models of human or animal behavior. These