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The retina is an ideal model for understanding the fundamental rules for how neural networks are constructed. The compact neural networks of the retina perform all of the initial processing of visual information before transmission to higher visual centers in the brain. The field of retinal connectomics uses high-resolution electron microscopy datasets to map the intricate organization of these networks and further our understanding of how these computations are performed by revealing the fundamental topologies and allowable networks behind retinal computations. In this article, we review some of the notable advances that retinal connectomics has provided in our understanding of the specific cells and the organization of their connectivities within the retina, as well as how these are shaped in development and break down in disease. Using these anatomical maps to inform modeling has been, and will continue to be, instrumental in understanding how the retina processes visual signals.