Date of Degree


Document Type


Degree Name





Joel Sneed

Committee Members

Laura Rabin

Justin Storbeck

Desiree Byrd

Carolyn Pytte

Subject Categories

Biological Psychology | Cognitive Psychology | Geriatrics | Other Psychology


neuroimaging, aging, mild cognitive impairment, depression, cognition


Mild cognitive impairment (MCI) is a neurocognitive disorder defined by cognitive decline in older adults. Although MCI has been studied for decades, there remain important areas to be explored in order to adequately characterize aspects of this disorder that provide information valuable for possible interventions and disease progression to dementia, including a better understanding of the neuroanatomical variables relevant to this disorder. Such neuroanatomical variables include cortical thickness, hippocampal volume, and white matter hyperintensities (WMHs). This dissertation consists of three separate studies aimed at addressing gaps in the literature on MCI in relation to brain morphometrics and under-studied characteristics involved in MCI, such as functional skills, treatment expectancy, and comorbid depression. The first study evaluated the relationship between neuroanatomical variables and a performance-based functional skills measure that is increasingly used to evaluate functional status in MCI. Furthermore, this first study explored the relationship between the functional skills measure and cognitive measures known to be affected in MCI. The second study evaluated the relationship between neuroanatomical variables and expectancy beliefs in individuals with MCI partaking in a computerized cognitive training (CCT) trial. Due to a dearth of research on this topic, additional demographic and clinical characteristics known to be affected in MCI were also investigated in relation to expectancy beliefs, to build a foundation for future research. The third study evaluated neuroanatomical and cognitive differences between MCI and comorbid depression and MCI (Dep-MCI), a comorbidity that may be an indicator of progression from MCI to dementia. The results from the three studies together support the importance of measuring multiple aspects of structural brain changes in individuals with MCI, as the different characteristics in MCI were related to differing structural abnormalities. Best brain morphometric evidence for functional skills, participant treatment expectancy, and comorbid Dep-MCI varied between cortical thickness, hippocampal volume, and white matter lesion burden metrics. In general, cortical thickness was the best metric for evaluating functional skills in MCI, hippocampal volume was the best metric for evaluating participant treatment expectancy, and cortical thickness and WMHs were the best metrics for comparing MCI and Dep-MCI. Taken together, unique structural brain abnormalities are present in these less-studied aspects of MCI, with evidence of variable relationships to other facets of MCI such as cognition and demographic characteristics. Results provide information that can be further studied longitudinally to examine potential interventions for MCI, contribute to diagnosis of disease severity, and evaluate progression to dementia. By establishing the structural neuroanatomical correlates of various aspects of MCI, information important for evaluating disease-modifying effects of interventions will be determined.