Comparing drift-diffusion modeling and finger tracking as a window into decision-making in handball penalty situations

Deciding between multiple options in a split second is a crucial aspect in various domains, including traffic, aviation, policing, and sports. Both drift-diffusion modeling (DDM), a computational model that approaches decision-making as noisy evidence accumulation, and finger tracking have been suggested to capture the evolution of a decision over time. In this study, we comparatively applied DDM and finger tracking to examine the processes underlying split-second decision-making within an anticipatory handball penalty task. Participants were shown temporally occluded videos of handball penalties and predicted shot direction by either pointing or continuously swiping toward one of two target areas. We extended previous research by using an optical motion capture system to track trajectories of both pointing and swiping and also calculated drift-diffusion models grouped by response modality. Results indicate that the DDM robustly mirrors the decision-making process. The model reflects the movement differences between pointing and swiping accurately in the non-decision time and shows consistent correlations between response modalities. In contrast, the finger tracking parameters (i.e., area under the curve, velocity, x-flips, and entropy) did not show consistent correlations between pointing and swiping trials and were strongly dependent on response modality. Furthermore, the effect of the response modality manipulation could not be clearly identified by finger tracking parameters. We conclude that DDM when compared to finger tracking seems to provide more modality-invariant insights into the processes underlying decision-making across different response tasks (i.e., modalities).