ABSTRACT Stacy L. Andersen is an Assistant Professor in the Department of Medicine at Boston University School of Medicine. She seeks a mentored career development award (K01) to obtain critical knowledge skills in biostatistics, communication patterns, neuropsychological assessment, and neuroimaging, particularly as they relate to cognitive aging, and necessary research experience leading to an independent career as a neuroscientist in field of aging research, specifically in the field of healthy aging and cognitive resilience. The training proposal details a five-year plan of formal and informal instruction in the pathophysiologic basis of brain changes associated with aging and neurodegenerative disease as well as training in biostatistics and analysis methods. Dr. Andersen’s mentors, established experts in the fields of neuropsychology, neuroimaging, and gerontology have met with Dr. Andersen to formulate a plan of course work, guided study, seminars and academic meetings. Short-term career goals include to complete course work in linguistics, neuroimaging methods, and statistical analysis, disseminate high quality mentored research findings via presentations and published works, engage in career development activities and to apply for independent R grant funding early in the fifth year of the award period. Long-term career goals are to be an independent neuropsychiatric epidemiologist with content expertise in the neuropsychological assessment of long-lived individuals, novel applications of technology for evaluating cognitive function, and factors associated with cognitive resilience. The specific aims of the proposed research are to (1) with specialized software, extract cognitive performance metrics from digital voice recordings and digitally-captured motor performance, (2) test the hypothesis that digital metrics of speech and motor production are sensitive to variations in cognitive function and clinical dementia status, (3) test the hypothesis that digital metrics of speech and motor production are associated with neuroanatomical substrates as detected by structural and functional MRI, and (4) institute prospective data collection of longitudinal, digitally-acquired neuropsychological test data. This study has the potential to identify digital metrics as correlates of cognitive function and possibly early markers of cognitive change allowing for earlier diagnosis and intervention. Completion of the proposed aims will provide preliminary findings that will lay the groundwork for a grant application investigating the association of longitudinal changes in traditional and digital neuropsychological metrics with incidence of cognitive impairment and dementia as well as the factors associated with an absence of longitudinal cognitive change (i.e., cognitive resilience).