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

Sebastian Musslick, Jonathan D. Cohen, Amitai Shenhav

Research output: Chapter in Book/Report/Conference proceedingConference contribution

13 Scopus citations

Abstract

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.

Original languageEnglish (US)
Title of host publicationProceedings of the 41st Annual Meeting of the Cognitive Science Society
Subtitle of host publicationCreativity + Cognition + Computation, CogSci 2019
PublisherThe Cognitive Science Society
Pages2427-2433
Number of pages7
ISBN (Electronic)0991196775, 9780991196777
StatePublished - 2019
Event41st Annual Meeting of the Cognitive Science Society: Creativity + Cognition + Computation, CogSci 2019 - Montreal, Canada
Duration: Jul 24 2019Jul 27 2019

Publication series

NameProceedings of the 41st Annual Meeting of the Cognitive Science Society: Creativity + Cognition + Computation, CogSci 2019

Conference

Conference41st Annual Meeting of the Cognitive Science Society: Creativity + Cognition + Computation, CogSci 2019
Country/TerritoryCanada
CityMontreal
Period7/24/197/27/19

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Science Applications
  • Human-Computer Interaction
  • Cognitive Neuroscience

Keywords

  • cognitive control
  • individual differences
  • motivation
  • self-control

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