Approaching a connectome of the human foveal retina

The foveal retina is a unique primate specialization and a promising target for the first connectome of a human central nervous system structure. In the fovea, neural cells and circuits are miniaturized and compressed to sample the visual image at high spatial resolution, initiating form, color, and motion perception. Here, we report a working-draft human foveal connectome. We used deep learning to segment all cells and their synaptic connections in a piece of human fovea. We classified ~3,000 cells into 51 neuronal types and three glial types based on morphology and connectivity. Some cell types and synaptic motifs—including the midget and small bistratified ganglion cell circuits—are conserved between human and nonhuman primates. However, most other cell types and related synaptic connectivity remain unexplored. We find that in comparison to peripheral retina, the human foveal retina shows reduced cell type diversity with markedly unequal densities and distinct patterns of synaptic connectivity. For example, foveal H1 horizontal cells are present at high density relative to H2 cells and receive unexpected synaptic input from S cones, predicting fovea-specific chromatic properties of downstream receptive fields. Retinal ganglion cells could be divided into only 13 types—a contrast to the ~20 types in peripheral retina and the 40+ types recognized in mouse retina—but consistent with recent transcriptomic studies of human fovea. These findings support the hypothesis that the human fovea has traded a repertoire of feature detectors for high-precision, saccade-supported active vision centered around a small number of high-density visual pathways.