In previous work[1] it was shown that a mechanism competing for a presynaptic factor enables the self-organizing formation of local receptive fields with orientation selectivity, even though the synapses between the input and output layers are all nonlocal, i.e., fully connected. The previous model, however, assumed a priori competitive systems, called hypercolumns, that may not appropriately represent the inherent structure of the input, which is a hierarchy of low- to high-level features. In this paper we propose to use a self-organizing competitive system, rather than an a priori determined system. Self-organization is implemented by including Földiák's anti-Hebbian learning rule in out system. Computer simulations show that this model allows for the formation of local receptive fields with orientation selectivity, and that selforganization successfully structures the competitive system.