Spatio-temporal dynamics during perceptual processing in an oscillatory neural network

We examine the dynamics of object recognition in a multi-layer network of oscillatory elements. The derivation of network dynamics is based on principles of sparse representation, and results in system behavior that achieves binding through phase synchronization. We examine the behavior of the network during recognition of objects with missing contours. We observe that certain network units respond to missing contours with reduced amplitude and temporal delay, similar to neuroscientific findings. Furthermore, these units maintain synchronization with a high-level object representation only in the presence of feedback. Our results suggest that the illusory contour phenomena are formal consequences of a system that dynamically solves the binding problem, and highlight the functional relevance of feedback connections.