An estimated 6.5 million Americans over the age of 65 live with Alzheimer’s disease, a progressive neurodegenerative disorder with no effective cure and the leading cause of dementia worldwide. Dementia is typically preceded by a prodromal phase of Mild Cognitive Impairment (MCI), in which the earliest observed cognitive changes are in memory. Research shows that up to 40% of dementia risk is due to modifiable risk factors including sleep and cardiovascular risk factors that exacerbate Cerebral Small Vessel Disease (CSVD). CSVD is found in approximately 80% of patients with concomitant Alzheimer’s disease pathology and represents early, subtle changes to the cerebrovascular system. Taken together, the interplay of sleep and CSVD is understudied, particularly in the context of Alzheimer’s disease-related cognitive changes in older adults. The overall goal of this proposal is to examine the mechanisms linking CSVD to sleep-dependent memory deficits seen in Alzheimer’s disease and to underscore the most relevant features of sleep that most robustly predict CSVD. The Specific Aims address the role of CSVD in sleep-dependent memory deficits by investigating fronto-temporal gray matter structure and local sleep expression as possible mechanistic links. The present study design allows for a detailed characterization of participants across clinical and cognitive domains. Participants undergo (1) magnetic resonance imaging (MRI), (2) two weeks of wrist-worn actigraphy, (3) an overnight in-lab polysomnography study with high-density electroencephalography (hdEEG) and (4) a memory task delivered in a sleep-dependent manner. This innovative, multi-modal study design has not been widely implemented in older adults and lends to the applicant’s training goals of using advanced computational and statistical methods to analyze high-dimensional datasets. This project will spearhead the applicant’s career goals of becoming an independent investigator, utilizing computational methods to study biomarkers of neurodegenerative disease. This project targets NIH’s goals for sleep research, including investigation of sleep mechanisms underlying disease and risk reduction. UCI is an ideal institution to enact these study aims, as it is a world-class research institution with modern neuroimaging facilities and a culture of collaboration. The applicant has support from two experts in the fields of sleep research, Alzheimer’s disease, basic memory science, and neuroimaging techniques. Collaborators listed on this proposal will provide additional support for assessment of clinical factors, hdEEG, and statistical modeling. Insights from this proposal will fill in two major gaps in our knowledge: (1) what features of sleep most strongly predict CSVD burden, and (2) what mechanisms link CSVD to sleep-dependent memory in older adults. This project may reveal new therapeutic targets for behavior-modifying interventions in sleep, inform precise screening in patients with disordered ...