ORCID iD: 0000-0002-0486-213X

My research dovetails between three interrelated fields using MRI as the foundational technology for modeling human disease (hearing loss, environmental enrichment and Alzheimer’s Disease). In hearing loss, we explore rodent models to develop structural probabilistic maps using machine learning and genetics. Here we establish neuroimaging templates which can be used for assessing the impact to the brain throughout the lifespan. In humans, we construct endophenotypic templates of hearing loss ascertained by MRI images in a population wide cross-sectional longitudinal survey to determine confounding variables and predictors. The aim here is to ascertain covariates which may reduce the severity of hearing loss across the lifespan. Some of the aforementioned variables are linked to environmental enrichment; therefore, in rodent models we construct different environments which impact the brain to determine how they affect rodent models with hearing loss. Lastly, Alzheimer’s Disease (AD) is known to be confounded by hearing loss; therefore, my research attempts to use rodent models of AD to discern the influence of hearing loss progression contributing to the neuropathology in dementia. My work concentrates on MRI imaging defined phenotypes to reveal features in humans and in rodent models that can ameliorate disease.