This collection includes both ASU Theses and Dissertations, submitted by graduate students, and the Barrett, Honors College theses submitted by undergraduate students. 

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Description
A converging operations approach using response time distribution modeling was adopted to better characterize the cognitive control dynamics underlying ongoing task cost and cue detection in event based prospective memory (PM). In Experiment 1, individual differences analyses revealed that working memory capacity uniquely predicted nonfocal cue detection, while proactive control

A converging operations approach using response time distribution modeling was adopted to better characterize the cognitive control dynamics underlying ongoing task cost and cue detection in event based prospective memory (PM). In Experiment 1, individual differences analyses revealed that working memory capacity uniquely predicted nonfocal cue detection, while proactive control and inhibition predicted variation in ongoing task cost of the ex-Gaussian parameter associated with continuous monitoring strategies (mu). In Experiments 2A and 2B, quasi-experimental techniques aimed at identifying the role of proactive control abilities in PM monitoring and cue detection suggested that low ability participants may have PM deficits during demanding tasks due to inefficient monitoring strategies, but that emphasizing importance of the intention can increase reliance on more efficacious monitoring strategies that boosts performance (Experiment 2A). Furthermore, high proactive control ability participants are able to efficiently regulate their monitoring strategies under scenarios that do not require costly monitoring for successful cue detection (Experiment 2B). In Experiments 3A and 3B, it was found that proactive control benefited cue detection in interference-rich environments, but the neural correlates of cue detection or intention execution did not differ when engaged in proactive versus reactive control. The results from the current set of studies highlight the importance of response time distribution modeling in understanding PM cost. Additionally, these results have important implications for extant theories of PM and have considerable applied ramifications concerning the cognitive control processes that should be targeted to improve PM abilities.
ContributorsBall, Brett Hunter (Author) / Brewer, Gene A. (Thesis advisor) / Goldinger, Stephen (Committee member) / Glenberg, Arthur (Committee member) / Amazeen, Eric (Committee member) / Arizona State University (Publisher)
Created2015
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Description
Recent findings in human interactions with complex objects, objects with unpredictable interaction dynamics, revealed predictability as an important factor when determining effective control strategies. The current study extended these findings by examining the role of predictability in the selection of control strategies in two scenarios: during initial interactions with a

Recent findings in human interactions with complex objects, objects with unpredictable interaction dynamics, revealed predictability as an important factor when determining effective control strategies. The current study extended these findings by examining the role of predictability in the selection of control strategies in two scenarios: during initial interactions with a novel, complex object, and when intentional constraints are imposed. In Experiment 1, methods with which people can identify and improve their control strategy during initial interactions with a complex object were examined. Participants actively restricted their movements at first to simplify the object’s complex behavior, then gradually adjusted movements to improve the system’s predictability. In Experiment 2, predictability of participants’ control strategies was monitored when the intention to act was changed to prioritize speed over stability. Even when incentivized to seek alternative strategies, people still prioritized predictability, and would compensate for the loss of predictability. These experiments furthered understanding of the motor control processes as a whole and may reveal important implications when generalized to other domains that also interact with complex systems.
ContributorsNguyen, Tri Duc (Author) / Amazeen, Eric (Thesis advisor) / Glenberg, Arthur (Committee member) / Amazeen, Polemnia G (Committee member) / Brewer, Gene (Committee member) / Arizona State University (Publisher)
Created2022