Connectionist and other computational models of vision frequently assume, for simplicity or for other reasons, that the flow of information through the visual cortex is unidirectional, and that its architecture is purely feedforward. Although this self-imposed constraint is understandable in the light of the PDP group's  original concentration on feedforward networks, it is unwarranted both from the computational and from the biological standpoint. Anatomical and physiological evidence suggests that lateral connections constitute an important part of the local cortical circuitry, and, moreover, that these connections possess a clearly nonrandom (albeit not yet perfectly understood) structure [1,26]. The present paper argues that this ubiquity of lateral connections is to be expected, given the computational advantages such connections confer onto a feedforward layered network architecture. This argument is supported by a number of successful models of various cortical functions, all of which involve lateral connections. The functions addressed by the models range from low-level (the formation of the receptive fields in the primary visual cortical area V1 (the Shaping the RFs section); combining receptive fields to enhance their utility for recognition (the Pairs of RFs section)) to high-level (recognition of 3D objects (the Emergence of ... section); shape representation (the Lateral Comparisons... section)). The Discussion section contains a brief discussion of the functional value of lateral connections, considered from the standpoint of philosophy of representation.