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Imaging individual neurons in the retinal ganglion cell layer of the living eye

Significance Retinal ganglion cells are the primary output neurons of the retina that process visual information and transmit it to the brain. We developed a method to reveal these cells in the living eye that does not require the fluorescent labels or high light levels that characterize more invasive methods. The death of these cells causes vision loss in glaucoma, the second leading cause of blindness worldwide. The ability to image these cells in the living eye could accelerate our understanding of their role in normal vision and provide a diagnostic tool for evaluating new therapies for retinal disease. Although imaging of the living retina with adaptive optics scanning light ophthalmoscopy (AOSLO) provides microscopic access to individual cells, such as photoreceptors, retinal pigment epithelial cells, and blood cells in the retinal vasculature, other important cell classes, such as retinal ganglion cells, have proven much more challenging to image. The near transparency of inner retinal cells is advantageous for vision, as light must pass through them to reach the photoreceptors, but it has prevented them from being directly imaged in vivo. Here we show that the individual somas of neurons within the retinal ganglion cell (RGC) layer can be imaged with a modification of confocal AOSLO, in both monkeys and humans. Human images of RGC layer neurons did not match the quality of monkey images for several reasons, including safety concerns that limited the light levels permissible for human imaging. We also show that the same technique applied to the photoreceptor layer can resolve ambiguity about cone survival in age-related macular degeneration. The capability to noninvasively image RGC layer neurons in the living eye may one day allow for a better understanding of diseases, such as glaucoma, and accelerate the development of therapeutic strategies that aim to protect these cells. This method may also prove useful for imaging other structures, such as neurons in the brain.