A Multi-modal Imaging Model to Predict Mobility in Older Adults

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Project Summary Although functional and structural MRI have been used to characterize aging, disease, and cognition, the central nervous system mechanisms underlying mobility impairments in older age remain under-explored. The current proposal investigates brain contributions to the clinically valuable measure of walking speed, a known predictor of falls, disability, and mortality in older age. Several studies to date have found evidence that neurocognitive dysfunction and neurodegeneration result in slower walking. The observed relationships, however, are not consistent across studies. Structural investigations may or may not report relationships with impaired mobility; age-related declines of structure are variable, spatially diffuse, and cannot be fully captured in a single imaging modality. The applicant’s previous work has shown that brain function may be a better predictor of gait, although these measures are typically underutilized and not easily integrated with structural measures. This proposal aims to address the need to accurately identify the most important neural mechanisms of walking for older adults by combining imaging data across multiple MR modalities in the presence of other clinical factors and predictors. The overall objectives of this proposal are to identify the relative contributions of brain structure, function, and their interactions to walking speed, and to test their generalizability to other older adult populations. Specifically, the applicant will 1) develop an integrative model utilizing functional and structural MR biomarkers from the MOBILIZE Boston Study (MBS) of older community- dwelling adults to predict walking speed, and 2) validate the model in a separate cohort from the Rush University Alzheimer’s Disease Center Memory and Aging Project (MAP). For this project, the applicant’s central hypothesis is that the intact functional dynamics of executive and attention neural networks are essential for maintained/improved mobility in older adults. For this three-year Career Development Award, the applicant proposes to pursue these research aims and train in advanced statistical modeling and data science, project management, and rehabilitative interventions for mobility under the guidance of a multi-disciplinary multi-institutional team. The specific research and statistical modeling methods gained from this project supports the applicant’s long-term goal to inform successful aging for older adults by (1) investigating the neural mechanisms that contribute to functional impairments commonly encountered in older age, (2) identifying early biomarkers of these declines, and (3) developing neuroscience-informed interventions for improved outcomes.