The temporal dynamics of self-control.

Abstract

Self-control-the ability to pursue long-term goals over short-term temptations-is a critical faculty of human cognition, but the cognitive processes enabling self-control are not well understood. Traditional models have focused on impulse inhibition: effortfully inhibiting prepotent motor responses toward a temptation, yielding a stage-based evolution of choice. Other models emphasize dynamic competition between goal and temptation, yielding a more integrative evolution of choice. Although these models represent fundamentally different conceptions of self-control, current methods are inadequate for investigating real-time dynamics, leaving the question of which model best describes self-control unresolved. We investigate these models using mouse-tracking: a dynamic, real-time measure of decision-making in which we measure participants' computer mouse movements as they navigate tradeoffs between immediate and delayed gratification (e.g., $5 today vs. $20 in 3 mo). We develop a quantitative approach that integrates the rich spatial and temporal information contained in mouse trajectories, and find evidence for <i>both</i> impulse inhibition and dynamic competition. Notably, impulse inhibition is less frequent, occurring in only one-quarter of choices favoring larger later rewards over smaller sooner ones. We further find substantial individual variability on who relies on impulse inhibition, with more present-biased individuals more likely to use impulse inhibition to choose larger-later options. Finally, our approach reveals the diverse variability within impulse inhibition and dynamic competition, and accounting for this variability greatly strengthened models predicting out-of-sample choices. Our findings clarify the mechanisms underlying self-control and introduce a robust tool for quantifying real-time decision-making dynamics.