An integrated utility-based model of conflict evaluation and resolution in the Stroop task

Area of Science:

• Cognitive Psychology
• Computational Neuroscience
• Human-Computer Interaction

Background:

• Cognitive control enables goal-directed behavior despite interference.
• The Stroop task is a key paradigm for studying cognitive control, presenting conflicting response tendencies.
• Existing computational models offer limited explanations for Stroop task dynamics.

Purpose of the Study:

• To propose a novel, integrated utility-based computational model for cognitive control within the Stroop task.
• To demonstrate the model's ability to replicate a wide range of experimental findings.
• To provide a unified framework for understanding Stroop task performance and adaptation.

Main Methods:

• Development of a utility-based model incorporating response utility reinforcement learning.
• Integration of utility-based conflict evaluation using the Festinger formula.
• Implementation of top-down adaptation of response utility for conflict resolution.

Main Results:

• The proposed model successfully replicated 18 experimental effects from the Stroop literature, the largest dataset explained by a single model to date.
• Simulations accurately reproduced basic congruency effects, including response latency distributions.
• The model also captured performance dynamics, adaptation, and effects of stimulation/response manipulations, aligning with EEG indices of conflict.

Conclusions:

• The integrated utility-based model offers a comprehensive framework for understanding cognitive control in the Stroop task.
• The model's success in replicating numerous effects highlights the importance of utility calculations and adaptive control mechanisms.
• This work advances computational approaches to cognitive control, providing a robust tool for future research.