All ETDs from UAB

Advisory Committee Chair

Kristina Visscher

Advisory Committee Members

Gene E Alexander

Karlene K Ball

Lloyd J Edwards

David C Knight

Document Type


Date of Award


Degree Name by School

Doctor of Philosophy (PhD) College of Arts and Sciences


There is an increasing number of people aged 65 and older, particularly in the oldest old cohort (aged 85 and older). Aging is characterized by significant changes in the brain including disruptions to white matter and functional connectivity. While cognition is impacted in many age related diseases, like Alzheimer’s Disease or Parkinson’s Disease, an understanding of the healthy aging brain is important for informing research on successful aging. My dissertation consists of three aims: (1) For the first aim, my overall objective was to determine the validity of the NIH toolbox in the oldest old cohort. I used other standard measures of cognition and compared performance on the NIH toolbox measures of cognition in order to determine validity of the toolbox. (2) For the second aim, I created a brain parcellation based on an oldest-old sample so that I could use age appropriate network node locations when studying network dynamic measures in Aim 3. (3) For the third aim, my overall objective was to identify the degree to which brain networks are segregated in healthy oldest-old adults and whether network properties explain variance in cognitive performance. To address these aims, I used The McKnight Brain Aging Registry (MBAR), which is a multisite study across the McKnight Brain Research Foundation institutes. The dataset consists of cognition and MRI data from 200 individuals who were screened for neurological disorders and cognitive impairment. iv I have expanded the field’s current knowledge of cognition of successful agers by investigating the relationship between brain functional network dynamics and cognitive performance in the healthy oldest old as well as the validity of new measures of cognition in this cohort. I add to the literature on age-related dedifferentiation, showing that even in a very old and cognitively healthy sample, cognitive dedifferentiation may impact executive functioning abilities and functional network dedifferentiation is related to cognitive abilities.



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