Matthew Webber

Neural Field Theory, which is a way of performing a mean-field continuum approximation for neural networks. The advantage of this approach is that macroscopic properties of large networks that would not otherwise be obvious can be found by analysis of the underlying equations. This is in contrast to a traditional neural network where usually numerical simulation has to be relied upon to discover the system's properties.

In particular, I use this approach to model binocular rivalry, which is the phenomenon in which observers (e.g. Humans) can experiance perceptual oscillations when presented with differing stimuli in each eye.