Statistical Properties of Single and Competing Non-Linear Fast-Slow Oscillators in Noise

Statistical properties offast-slow Ellias-Grossberg oscillators are studied in response to deterministic and noisy inputs. Oscillatory responses remain stable in noise due to the slow inhibitory variable, which establishes an adaptation level that centers the oscillatory responses of the fast excitatory variable to deterministic and noisy inputs. Competitive interactions between oscillators improve the stability in noise. Although individual oscillation amplitudes decrease with input amplitude, the average to'tal activity increases with input amplitude, thereby suggesting that oscillator output is evaluated by a slow process at downstream network sites.

A Recurrent Cooperative/Competitive Field for Segmentation of Magnetic Resonance Brain Imagery

The Grey-White Decision Network is introduced as an application of an on-center, off-surround recurrent cooperative/competitive network for segmentation of magnetic resonance imaging (MRI) brain images. The three layer dynamical system relaxes into a solution where each pixel is labeled as either grey matter, white matter, or "other" matter by considering raw input intensity, edge information, and neighbor interactions. This network is presented as an example of applying a recurrent cooperative/competitive field (RCCF) to a problem with multiple conflicting constraints. Simulations of the network and its phase plane analysis are presented.