Psychology Theses and Dissertations

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https://hdl.handle.net/1794/995

This collection contains some of the theses and dissertations produced by students in the University of Oregon Psychology Graduate Program. Paper copies of these and other dissertations and theses are available through the UO Libraries.

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Browsing Psychology Theses and Dissertations by Subject "Aging"

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    The Dynamics of Global States in Executive Control
    (University of Oregon, 2017-09-06) Hubbard, Jason; Mayr, Ulrich
    In the present work, we examine how the cognitive system responds to complex environments. It has been proposed that executive control, which is responsible for orchestrating high-level behavior in such environments, operates according to different broad processing modes, one geared towards stability and focus (“maintenance”), and the other that’s open to environmental influence (“updating”). Aging work has proposed that this latter mode is over-represented in older age, leading to deficits in many, but not all cognitive domains. Across three studies, we sought to identify the dynamics of the updating state in particular, and how those dynamics are shifted in older age. In Chapter 2, we used a paradigm designed specifically to enforce maintenance and updating states with an age-comparative sample, and found that older adults show increased behavioral costs (reaction times) and distractibility (distractor fixations) consistent with being “chronic updaters”. In Chapter 3 we probed the updating state by examining spontaneous fixations towards irrelevant cues, allowing us to identify how it occurs both in response to the task context, and independently from it. We found that older adults were more sensitive to global changes in the task context (single versus mixed-task blocks), but also showed a stronger tendency to update independently from the task. Younger adults, by contrast, were more prone to update in response to transient task events. In Chapter 4, we lay the groundwork to address these questions with neuroimaging, using machine learning to extract information regarding the task context (task set, targets, distractors, response-selection) in a task-switching paradigm on a trial-by-trial and moment-by-moment level. This opens the door for more directly measuring neural signatures of updating and gives a more high-fidelity measure to examine the dynamics of how and when it occurs. Together, this work provides some insight into the dynamics and age-differences involved in global processing states, which heretofore have been under-investigated in the literature. Additionally, we provide important analytic and methodological advancements for extending this work in the future.