Self control as a value based decision: neural, behavioral, and computational mechanisms
OA Version
Citation
Abstract
Self-control enables individuals to pursue goals even when faced with transient motivational shifts. While self-control has traditionally been understood to involve resisting temptation through willpower, it can alternatively be understood as a value-based decision. This project examined the interplay of valuation and control processes across three dimensions: human neuroscience with functional neuroimaging, participant behavior, and computational modeling. This was accomplished through (1) analyzing valuation and reward signals in the brain, (2) investigating behavioral decisions to engage in the self-control strategy of precommitment, and (3) computationally formalizing the elements driving these decisions. Distinguishing brain systems connected to valuation and executive function is challenging due to overlapping cortical topography and individual variability. In Study 1, I tested the reliability of individual brain maps of value and reward. In a multi-task test-retest neuroimaging protocol (n=18), I hypothesized that valuation and executive-function-related systems could be delineated and differentiated in individual participants. Results indicated that both value and executive function had pronounced group-level effects. While effects of executive function were evident at the individual level, value signals were more elusive. This implies that value signals might have a higher degree of within-person variation. Precommitment, where individuals limit their own future options to avoid anticipated self-control lapses, is a proactive self-control strategy. In Study 2, I hypothesized that the decision to engage in precommitment is a value-based decision influenced by perceptions of environmental stability. Two behavioral experiments (n=64, n=192) showed that participants modified their precommitment decisions in response to a manipulation of volatility in the decision environment, emphasizing the role of context-sensitive valuation in self-control-related decision-making. In Study 3, I developed computational models for value-based self-control decisions. These models simulated decisions in two paradigms: choices to precommit (as in Study 2) and choices to persist toward delayed rewards. I hypothesized that the models could utilize internal representations of the environment in a belief-based structure to estimate subjective value and mimic human decisions. Results indicated that the models performed effectively in their ability to make decisions. Participant-level estimates of the internal parameters of these models provide a new potential approach to operationalizing individual differences.
Description
2024
License
Attribution 4.0 International