Neural mapping and space-variant image processing

Network equations for the cortical area network (CAN) are presented. The nodes are formed by cortical areas with their intrinsic connectivity and the according computational capabilities. Intrinsic processing is modeled by convolutions. The edges are formed by the mappings between the various cortex areas. With respect to the spatial organization, one can distinguish topographic maps (coordinate transforms), patchy maps that occur when multiple input converges to a common target area, and parametric maps (2-D histograms that encode stimulus into a spatial position). Applications include space-variant image processing and visual receptive field organization