There is compelling evidence that glaucomatous damage to the macula occurs even in early stages of the disease. The macula comprises about 30% of all retinal ganglion cells and its information corresponds to over 50% of the visual cortex. However, glaucomatous damage to the macula is often missed in clinical practice. Some of the reasons are: 1) traditional glaucoma knowledge supports that glaucoma is fundamentally a peripheral disease; 2) inherent limitations of conventional clinical tests to detect damage to the macula; and 3) the paucity of large, prospective studies that describe the nature of glaucomatous damage to the macula. Our group has published numerous papers in the past two years showing that macular damage is prevalent among patients with early glaucoma if one employs the appropriate tools to assess it, namely 10-2 visual fields and high-resolution optical coherence tomography (OCT). This information comes from a unique prospective cross- sectional database and techniques we developed to produce objective metrics of structure and function. Now that we understand the cross-sectional nature of macular damage, this proposal aims to: 1) develop a longitudinal database including patients with early glaucoma and healthy controls, 2) to test models that explain progression of macular damage, and 3) to apply new statistical methods combining structural and functional tests which could improve the accuracy to detect progression and shorten the length of clinical trials. Our main hypothesis is that incorporating 10-2 visual field testing and high-resolution OCT scans of the macula to the conventional repertoire of technologies used in clinical practice, in addition to translating recently described statistical methods into softwares that can be used in daily practice, enhances the performance and confidence to detect glaucoma progression. In Aim 1 we plan to follow healthy subjects and glaucoma patients at regular intervals with 10-2, 24-2 visual fields, and swept source (ss) OCT tests and define metrics of short- and long-term test variability that are needed to differentiate true progression from 'noise'. To date, there is no such database combining these technologies. In Aim 2 we plan to combine metrics of structure and function from this longitudinal database using two methods: a spatial approach, which will ultimately produce a joint structure-function index using 10-2 and ssOCT data; and a temporal approach, which will employ Bayesian statistics to measure rates of progression using trend analysis. By the end of the study, our contributions to the field should be: 1) to make available a unique and pristine longitudinal database that could be used for other hypotheses testing, 2) to translate techniques recently described in the literature into objective tools to be readily useful in clinicl practice, and 3) to mitigate the burdens of progressive loss of central vision in glaucoma.