Cognitive informatics is a very hot topic today, trying to provide solutions to problems in computation that are easily solved by the brain but are hard for a computer. The information processing properties of the brain are taken as the basis for such artificial systems. The first step of visual information processing, the extraction of orientation selective contours, is done in the primary visual cortex. A similar, orientation based filtering can be the first step in many vision systems of cognitive informatics. This paper presents the VFA concept in which cognitive vision models of the brain can be deployed. An information processing model of the primary visual cortex is also proposed here. The VFA model is able to extract visual features from images, using the same principles as the primary visual cortex. The components of the proposed model are data arrays connected by filtering, lateral and projective operations. The main focus of this paper is the discussion of lateral operations in the VFA model, with a special respect on their stability.