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Ly, Maria (2020) BRAIN AGE AS A MEASURE OF BRAIN RESERVE IN NEUROPSYCHIATRIC DISORDERS. Doctoral Dissertation, University of Pittsburgh. (Unpublished)

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Aging represents a highly heterogeneous process with highly variable clinical outcomes. Differential expression of risk and resilience factors may provide explanations for this variability. Gaining a better understanding of resilience in aging is critical as it will allow for improved individualized outcome prediction, as well as providing insight for targeted interventions that may improve the process of aging. Currently, the prevailing models of neurocognitive resilience are cognitive reserve and brain reserve. The theory of cognitive reserve suggests that those with greater cognitive reserve may better cope with loss of brain integrity through presence of more adaptable and efficient neural systems. Most studies utilize education level to assess cognitive reserve; however, many proxy measures are subjective and susceptible to hindsight bias. The concept of brain reserve overlaps with that of cognitive reserve but focuses instead on the biological characteristics that allow the brain to be resilient to the effects of aging and pathological insults. It is generally thought that with sufficient brain substrate (e.g., larger grey matter volumes, greater synaptic density, more elaborate network complexity), the brain is more capable of preserving normal functioning and maintaining homeostasis despite the presence of factors of neurodegeneration or trauma. Overall, the main goals of this dissertation are to demonstrate the impact of cognitive and brain reserve on neuropsychological outcomes and brain activation patterns (Aim 1, Chapters 2 and 3), to utilize machine learning brain age prediction as a novel proxy of brain reserve (Aim 2, Chapter 4), and to utilize brain age prediction in several
neuropsychiatric disorders to predict outcome or gain a better understanding on the disease process (Aim 3, Chapters 5, 6, 7).


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Item Type: University of Pittsburgh ETD
Status: Unpublished
CreatorsEmailPitt UsernameORCID
Ly, Mariamjl138@pitt.edumjl138
ETD Committee:
TitleMemberEmail AddressPitt UsernameORCID
Thesis AdvisorAizenstein,
Committee ChairDeFranco,
Committee MemberRaji,
Committee MemberRosano,
Committee MemberStetten,
Date: 19 May 2020
Date Type: Publication
Defense Date: 24 February 2020
Approval Date: 19 May 2020
Submission Date: 14 April 2020
Access Restriction: 1 year -- Restrict access to University of Pittsburgh for a period of 1 year.
Number of Pages: 134
Institution: University of Pittsburgh
Schools and Programs: School of Medicine > Neurobiology
Degree: PhD - Doctor of Philosophy
Thesis Type: Doctoral Dissertation
Refereed: Yes
Uncontrolled Keywords: brain age, aging, resilience
Date Deposited: 20 May 2020 01:51
Last Modified: 19 May 2021 05:15

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