This project significantly extends the power of MRI and diffusion tensor imaging (DTI) at ultra-high magnetic field strengths (7T) to resolve previously unseen features of brain structure and fiber properties, providing unique power to investigate disease. We will exploit the extreme spatial resolution and signal contrast at 7T, to compute sensitive biomarkers of aging, mild cognitive impairment (MCI), and Alzheimer's disease (AD). Combining data from 80 human subjects scanned at both 7T and 3T, we will compute the profile of cortical gray matter thickness (Aim 1), a measure sensitive to subtle changes in aging, development and a key target of drug trials in dementia and neuropsychiatric research. Extending DTI to 7T, we will assess white matter microstructure and fiber integrity with unprecedented power (Aim 2), and how it changes with aging and dementia. We will quantify how much 7T (versus 3T) boosts the detection sensitivity, signal to noise, stability and effect size of these key biomarkers of brain disease. Uniting the UCLA/University of Minnesota imaging centers, we will develop novel signal processing computations and mathematics to extract maximal information from the 7T images, advancing their current resolution and detection limits. New denoising, registration, and statistical techniques will detect individual and group differences in cortical thickness and fiber integrity. Advances in the mathematics of partial differential equations (PDEs), harmonic maps, and Riemannian manifolds, will provide unique power to denoise tensor- and vector-valued imaging signals (DTI). New statistics will detect disease-sensitive changes in the brain's fiber pathways. We will quantify how much effect sizes increase at 7T versus 3T, and what benefits our novel algorithms yield. In the first high- field study of AD and MCI, we will exploit the higher contrast and resolution at 7T to map key brain changes, undetected at 3T. We will unravel the geometry of cortical surfaces in the brain, and map how cortical thickness changes in aging (Aim 3), AD and MCI (Aim 4). We will map individuals and populations, encoding group patterns of cortical thinning and fiber architecture to detect local or diffuse brain changes. These gains will immediately advance clinical trials of anti-dementia and anti-psychotic drugs that depend on MRI for their power. Validated on unique data, our tools will help monitor disease progression, and map how brain diseases begin and spread in human populations. We will share all images, protocols, and algorithms with our network of 100+ collaborating laboratories.