NEUROIMAGING CORE SUMMARY Much has yet to be understood about the brains of "superagers" and what and how resilience factors impact the typical brain-aging trajectory, and identify which aspects of brain reserve are most associated with preserved cognition functioning in centenarian cognitive superagers. The Neuroimaging Core oversees the acquisition, storage, and analysis of imaging data at three participating imaging centers: MGH (Boston), Columbia University (NYC), and UCLA (Los Angeles). These sites have identical scanners, the Siemens Prisma 3T MRI, that are also the most advanced pulse sequencers available. The Core will optimize acquisition and analysis approaches to ensure that the data across centers are highly standardized and achieve equivalent contrast to noise ratios (CNRs) to ensure that data integration is successful. The Core's broad goal is to answer specific questions about resilience by identifying a set of high-resolution pulse sequences that examine brain structure and function, in a time interval tolerable for centenarians, using state of the art data analysis techniques. The NIC's general hypothesis is that preserved structural and functional connectivity are essential to long-term preserved cognition. This hypothesis will be tested by generating optimal MRI data combined with analysis tools designed to examine network dynamics and longitudinal trajectories, focusing on brain networks and regions most critical to cognition and memory. The three specific aims are: Aim 1:Test and employ across three sites, state of the art pulse sequences on the Prisma platform that are essential for understanding the resilient brain structure including Multi-echo/Multiband, navigator high-resolution T1/T2, resting-state functional connectivity MR, Diffuser Tensor Imaging, Pseudo-Continuous Arterial Spin Labeling, and Quantitative Susceptibility Mapping. Aim 2:Perform ongoing with-and between-site QA, pre-processing for image standardization and bias corrections, and centralize data across sites into an imaging data repository. Aim 3: Conduct image analysis that combines data across sites/within modality; create output metrics for each data-type, and in conjunction with the projects, assist in integrating imaging measures into project hypotheses. The imaging centers are joined and further integrated by a state-of-the-art data analysis center at the University of Utah. Experts in imaging statistics interface with the other RADCO cores and projects to integrate data types for hypothesis testing.