Decomposing Individual Differences in Cognitive Control: A Model-Based Approach

Researchers have long been interested in using laboratory measures of cognitive control to predict a person's cognitive control/self control success outside the lab. We used a computational approach to identify which lab-based performance measures provide the most valid individual difference measures of one's ability and/or motivation to exert cognitive control. We simulated performance across an array of cognitive control tasks, and estimated the degree to which different performance metrics (e.g., congruency effects, conflict adaptation, and demand avoidance) could theoretically provide valid estimates of processes underlying control allocation. By performing dimension reduction on these performance metrics, we further revealed latent dimensions that can index separate mechanisms of control-demanding behavior. Our results suggest that individual differences in measures of cognitive control can originate from multiple factors, several of which are unrelated to capacity for cognitive control. We conclude by discussing implications of these analyses for assessing individual differences in cognitive control phenomena.