The primary goal of the proposed research is to understand the relationship between implicit learning and white matter microstructure in younger and older adults. Examining the role of white matter integrity in the aging of implicit learning will extend the emerging literature on lifespan cognitive neuroscience. Implicit learning occurs without intent or awareness of what has been learned, and until recently it has been studied less that its explicit counterpart. This is unfortunate because sensitivity to regularities in the environment is essential throughout life. Recent cognitive and neuroscience research on implicit learning indicates that there are multiple forms of implicit learning that call on different neural substrates, but aging research usually treats implicit learning as though it is unitary. Here, we will focus on a dissociation between two types of implicit learning, sequence learning and spatial context learning, that are especially important for studying age changes in brain-behavior relationships because they call on different brain systems that are differentially affected by healthy aging. Imaging and patient studies suggest that implicit sequence learning relies on a frontal-striatal-cerebellar network, and implicit spatial context learning is mediated by the medial temporal lobes. The proposed experiment will be the first to examine this dissociation in the same group of participants using diffusion tensor imaging (DTI) to measure the integrity of white matter that connects neural networks (Specific Aim 2). DTI research has shown that white matter integrity declines with aging, especially in anterior brain regions, which may affect cognitive performance in healthy older adults. In this study, older adults are expected to be impaired at implicit sequence learning, but not implicit spatial context learning (Specific Aim 1), a finding consistent with the view that healthy aging affects the frontal-striatal system more than the medial temporal lobes. Multiple regression analyses will also examine if age-related brain changes affect the relationships between these two implicit learning tasks and white matter integrity from their corresponding neural networks, being the first to-assess age differences in brain-behavior relationships using implicit learning tasks in which behavioral performance is both impaired and spared with aging (Specific Aim 3). Results from this study are relevant to successful aging. Implicit learning promotes independent living by enabling people to adapt to change (i.e. new settings, people, and technologies), and can facilitate recovery from brain damage following accidents or strokes. Thus, identifying age-related stability between forms of implicit learning and their underlying white matter connectivity is important for training programs aimed at maximizing successful aging and recovery after brain damage. [unreadable] [unreadable] [unreadable]