A Neural Model of Visual Contour Integration

We introduce a neurobiologically plausible model of contour integration from visual inputs of individual oriented edges. The model is composed of interacting excitatory neurons and inhibitory interneurons, receives visual inputs via oriented receptive fields (RFs) like those in V1. The RF centers are distributed in space. At each location, a finite number of cells tuned to orientations spanning 180° compose a model hypercolumn. Cortical interactions modify neural activities produced by visual inputs, selectively amplifying activities for edge elements belonging to smooth input contours. Elements within one contour produce synchronized neural activities. We show analytically and empirically that contour enhancement and neural synchrony increase with contour length, smoothness and closure, as observed experimentally. This model gives testable predictions, and in addition, introduces a feedback mechanism allowing higher visual centers to enhance, suppress, and segment contours.