A puzzling problem is how neural ensembles provide a uniform, high-resolution visual representation in spite of irregularities in the RFs of individual cells. This problem was approached by simultaneously mapping the RFs of hundreds of primate retinal ganglion cells. As observed in previous studies, RFs exhibited irregular shapes that deviated from standard Gaussian models. Surprisingly, these irregularities were coordinated at a fine spatial scale: RFs interlocked with their neighbors, filling in gaps and avoiding large variations in overlap.
Consider random germs in a pattern engine. Each germ will grow fast initially, until lateral inhibition ( veto ) will stop the growth. A slight variation may either increase or decrease the veto. The veto may vanish, too. In this case the germ will grow a little further. We will end up with areas of constancy whose borders are interlocked in complex patterns. I believe that the so-called feature detectors in early vision arise in this way. Their erratic complexity has puzzled researchers for a long time.