Functional Activity Features in Successful Cognitive Aging





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Cognitive aging research has traditionally studied the inevitable cognitive decline in older adults as a group. Recently, more research has recognized the importance of understanding the individual variability in cognitive aging trajectories. Some individuals show superior performance and better preservation of cognition relative to others at their age, termed “prime” agers in the present dissertation. By contrast, some individuals may exhibit substantial cognitive deficits and greater decline representing a suboptimal cognitive aging profile, termed “nonprime” individuals. Many neuroimaging research efforts have been made to explore the neural mechanisms associated with these individual differences. Two possible patterns of functional activity, youth-like activation and compensatory recruitment, have been proposed to be particularly related to individual variability in cognitive changes. However, there is still a lack of consensus on what brain activity patterns may represent optimal aging in prime individuals. The present dissertation investigated this question in two studies. Because one major source of difficulty in this topic is the challenge in identifying prime agers, Study 1 implemented an exploratory data-driven approach to classify participants based on their cognitive performance and longitudinal cognitive change across multiple cognitive domains. Using two waves of longitudinal cognitive data (with a four-year interval) in episodic memory, inductive reasoning, working memory, processing speed from the Dallas Lifespan Brain Study, Study 1 in Chapter 2 examined the cognitive aging profiles in middle-aged, young-old and very old participants, and successfully identified two distinct cognitive aging profiles among participants, representing prime and nonprime individuals. Study 2 in Chapter 3 then utilized this classification of subgroups and compared their patterns of functional activity using a subsequent memory fMRI task collected at the second wave of DLBS. The analyses revealed several functional activity pattern differences between prime and nonprime individuals. First, prime individuals showed greater subsequent memory effect than nonprime individuals across core task-related regions associated with successful encoding. In addition, the higher subsequent memory effect in prime individuals, compared to nonprime individuals, was most evident in the young-old group, because prime agers exhibited better preservation of higher effect comparable to in younger adults, until very old age. In contrast, nonprime agers showed reduced subsequent memory effect starting in young-old age. Finally, prime young-old adults also recruited additional frontal regions, including left superior frontal and right orbitofrontal cortex, compared to young adults. This additional recruitment showed a trend of relationship to better memory performance, possibly suggesting a compensatory nature of this activation. In conclusion, the present dissertation demonstrated the use of a data-driven, multivariate approach and successfully identified prime and nonprime agers with distinct cognitive aging profiles. Comparison of their patterns of functional brain activity revealed that prime agers show a preservation of higher activation until very late in the lifespan and additional frontal recruitment in young-old age.



Brain--Aging, Cognition--Age factors, Cognition in old age, Latent variables, Magnetic resonance imaging


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