Schedule of Events | Symposia

Leveraging Continuous Psychophysics to Study Cognitive Control Allocation in Dynamic Environments

Poster Session A - Saturday, March 29, 2025, 3:00 – 5:00 pm EDT, Back Bay Ballroom/Republic Ballroom

Yihuan Dong¹ (yihuand1025@gmail.com), Ivan Grahek², Dominik Straub³, Atsushi Kikumoto⁴, Amitai Shenhav²; ¹Harvard Medical School, ²University of California, Berkeley, ³Technische Universität Darmstadt, ⁴Brown University

Cognitive control processes allow for adjustments in how we process information and select actions. In everyday life cognitive control operates on dynamically changing inputs (e.g., a friend talking in a crowded cafe) and allows us to continuously select goal-directed actions (e.g., what we say in response). However, cognitive control is commonly measured using discrete stimuli and responses (e.g., Stroop or Flanker tasks). Here, we leverage a continuous psychophysics approach to investigate cognitive control allocation in a continuous tracking task. Participants used their cursor to track a randomly moving target (Gaussian blob) using their mouse over a 20s period. We test whether task performance is affected by two manipulations known to modulate cognitive control: incentives and distractors. In Study 1 (N=38), we show that tracking performance improves when participants are expecting to earn high compared to low performance-based incentives. In Study 2 (N=38), we show that distractors moving in a direction opposite to the target impair performance relative to static or direction-congruent distractors. To characterize the mechanisms that drive reward and distractor-induced changes in performance, we fit participant data to the Linear Quadratic Gaussian model, a bounded optimal control model which assumes that people track targets based on the noisy perception of their position while minimizing their motor effort. This analysis revealed that perceptual noise decreased with higher incentives, while increasing in the presence of incongruent distractors. These findings pave the way for using continuous tracking paradigms in conjunction with optimal control models for studying cognitive control allocation in continuous domains.

Topic Area: EXECUTIVE PROCESSES: Monitoring & inhibitory control