Doctoral Dissertation Research in DRMS: Choice Overload in the Digital Age: A Cognitive Neuroscience Approach

University Of South Carolina At Columbia, Columbia SC

Investigators

Abstract

Technological progress has expanded the diversity of choice options in many critical sectors, including healthcare, finance, and consumer markets. As a result, people are increasingly subjected to states of choice overload, which occur when an excess of options reduces choice satisfaction, increases choice deferment, and leads to potentially poorer decisions. This research seeks to provide a neural account of brain processing of decisions among choice sets of varying sizes and complexity. That is, to reveal areas of the brain that are recruited in response to decision demands that exceed available cognitive resources, as well as the neural correlates of high and low satisfaction and engagement. This research should shed light on how brain processing adapts to facilitate optimal outcomes in complex environments and demonstrate how individual differences in brain activity relate to differential decision strategies. This study should provide insights on how to reduce decision anxiety, design more engaging decision environments, and explain individual differences in choice outcomes. The project utilizes a cognitive neuroscience approach to investigate the biological underpinnings of choice overload by examining how different numbers of options, presented in decision environments of varying complexity, map onto brain activity and decision outcomes. Employing functional magnetic resonance imaging, a cutting-edge neuroimaging technology, the study focuses on the activation patterns in brain areas such as the anterior cingulate cortex and dorsolateral prefrontal cortex, which are crucial for cognitive control and satisfaction in decision-making. This research empirically tests whether there exists a neural representation for an optimal range of choices that maximizes cognitive engagement and satisfaction. By utilizing statistical and computational modeling, the project seeks to establish a scientifically validated framework that can be applied across various decision-making environments. The results aim to contribute robust insights into the strategic presentation of choices, potentially transforming practices in industries and decision-making that hinge on effective decision strategies. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.