Emotion network dysfunction and anxiety in early Alzheimer's disease - PROJECT SUMMARY / ABSTRACT Alzheimer's Disease (AD) is the most common neurodegenerative disorder and a major cause of dementia among the elderly. Affective symptoms, especially anxiety, manifest during the early stages and may reflect cortico- limbic circuit changes in AD. Notably, healthy aging is associated with a “positivity” effect in affect, including reduction in anxiety, despite age-related cognitive decline. Thus, it is critical to understand how people with AD risks deviate from healthy aging and manifest higher levels of anxiety and whether these neural phenotypes may predict cognitive decline in those at risk. We propose to address these questions by investigating the roles of the cortico- limbic circuit dysfunction in manifesting anxiety in people with mild cognitive impairment (MCI) and subjective cognitive decline (SCD). We will use resting-state functional magnetic resonance imaging (fMRI) data of healthy participants of the HCP-A and both healthy participants and people with MCI of the ADNI (K99 studies) and collect task-based fMRI data on negative emotion processing in people SCD and healthy participants along with follow-up assessments (R00 study) to address three specific aims. Our two K99 aims are to (Aim 1) characterize the functional connectivities of emotion regulation circuit during healthy aging and (Aim 2) characterize the functional connectivities of emotion regulation circuit in MCI and employ machine learning to identify the connectivity markers that distinguish AD and HC. The R00 aim is to (Aim 3) investigate corticolimbic circuit dysfunction in emotion perception, regulation, and memory in SCD vs. HC using task-based fMRI and employ connectome predictive modeling to identify the predictors of cognitive changes during follow-up. Our overall goal is to understand emotion circuit dysfunction and the neural markers of anxiety and how these processes contribute to changes in cognitive function in early AD. The K99/R00 study will prepare the candidate for an independent career in aging and AD neuroscience research. The proposed study will support this goal by providing additional training in systems and clinical neuroscience, machine learning, and statistical modeling for the candidate. The candidate has identified her training needs, assembled a team of expert mentors and formulated a training plan that includes structured mentoring, supervised research, formal coursework, presentations at scientific meetings, and professional development. The study will also allow the candidate to collect critical pilot data for an R01 proposal in career development. Together, the K99/R00 study will allow the candidate to receive ample guidance, broaden her knowledge, learn novel techniques, and gain independence, while pursuing a research program of critical importance to public health.
