July 29, 2025

Exploring the synthesis of mouse cursor tracking and drift diffusion modeling in a perceptual decision-making task.

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Research demonstrates improved prediction of DDM parameters using mouse cursor tracking in decision-making, highlighting key cursor measures.

MAIN FINDING: Combining mouse cursor tracking with the drift diffusion model enhances predictions in decision-making tasks.
KEY EVIDENCE: Four cursor measures accounted for significant predictions of drift rate, threshold separation, and non-decision time.
APPROACH: The study involved 103 participants completing 90 trials using a random dot kinematogram and analyzed cursor measures.
SIGNIFICANCE: Findings simplify the use of mouse cursor tracking in research, aiding novice researchers with decision-making analysis.

Grenke et al. (2025) studied this question.

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Research demonstrates improved prediction of DDM parameters using mouse cursor tracking in decision-making, highlighting key cursor measures.