UC Berkeley

In order to study the limits of spatial vision in normal human subjects, it is important to look at and near the fovea. The fovea is the specialized part of the retina, the light-sensitive multi-layered neural tissue that lines the inner surface of the human eye, where the cone photoreceptors are smallest (approximately 2.5 microns or 0.5 arcmin) and cone density reaches a peak. In addition, there is a 1:1 mapping from the photoreceptors to the brain in this central region of the retina. As a result, the best spatial sampling is achieved in the fovea and it is the retinal location used for acuity and spatial vision tasks. However, vision is typically limited by the blur induced by the normal optics of the eye and clinical tests of foveal vision and foveal imaging are both limited due to the blur. As a result, it is unclear what the perceptual benefit of extremely high cone density is. Cutting-edge imaging technology, specifically Adaptive Optics Scanning Laser Ophthalmoscopy (AOSLO), can be utilized to remove this blur, zoom in, and as a result visualize individual cone photoreceptors throughout the central fovea. This imaging combined with simultaneous image stabilization and targeted stimulus delivery expands our understanding of both the anatomical structure of the fovea on a microscopic scale and the placement of stimuli within this retinal area during visual tasks. The final step is to investigate the role of temporal variables in spatial vision tasks since the eye is in constant motion even during steady fixation. In order to learn more about the fovea, it becomes important to study the effect of this motion on spatial vision tasks. This dissertation steps through many of these considerations, starting with a model of the foveal cone mosaic imaged with AOSLO. We then use this high resolution imaging to compare anatomical and functional markers of the center of the normal human fovea. Finally, we investigate the role of natural and manipulated fixational eye movements in foveal vision, specifically looking at a motion detection task, contrast sensitivity, and image fading.