Thursday, April 25, 2024
4/25/2024
Project Summary/Abstract The goal of our research is to understand the visual processing performed by the human retina. In the proposed work, we will explore the striking and novel visual properties of numerous new cell types we have recently discovered in the human retina – including more than 10 retinal ganglion cell (RGC) types that send visual information to the brain, and more than 10 polyaxonal amacrine cell (PAC) types that modulate RGC activity over large areas. We will develop new methods to understand their role in natural vision. We will leverage our large, unique database of recordings from macaque monkeys, the animal model closest to the human, to direct our experiments with precious human tissue. This work is made possible by several technical advances: novel large-scale high-density recordings from human donor retinas, novel machine-learning methods for mining of similar large-scale recordings from macaque monkey retinas performed over the last 15 years, and novel analytical methods to identify, model and compare new cell types and their function in the two species. Preliminary results in both species reveal a striking variety of new RGC and PAC types, some of which are likely homologs, and others that may be unique to humans. We will pursue two aims: (1) identify many novel RGC and PAC types in the macaque retina, probe their unusual light response properties, and develop models that allow us to further probe their role in natural vision, and (2) identify and characterize many RGC and PAC types in the human retina, and then use novel large-scale analysis methods to identify homologous types in the macaque retina. At the conclusion of this work, we will have identified and thoroughly characterized many of the most important visual pathways at the output of the human retina, developed and tested models of their function in natural vision, quantitatively compared to homologs in the most important animal model, and identified retinal cell types and visual signals that are likely unique to humans.
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