Modeling Response Times for Two-Choice Decisions

TLDR

Rapid two‑choice decisions generate multiple empirical measures, including response times for correct and error trials, accuracy probabilities, and interactions between accuracy and response time that vary with instructions and task difficulty. The authors apply a diffusion model to four psychophysical tasks, modeling decision variability to explain error generation and predict when errors are faster or slower than correct responses. The diffusion model accounts for all observed data, including error response times, and explains how stimulus information is processed over time to produce correct and incorrect decisions, with variability predicting when errors are faster or slower than correct responses.

Abstract

The diffusion model for two-choice real-time decisions is applied to four psychophysical tasks. The model reveals how stimulus information guides decisions and shows how the information is processed through time to yield sometimes correct and sometimes incorrect decisions. Rapid two-choice decisions yield multiple empirical measures: response times for correct and error responses, the probabilities of correct and error responses, and a variety of interactions between accuracy and response time that depend on instructions and task difficulty. The diffusion model can explain all these aspects of the data for the four experiments we present. The model correctly accounts for error response times, something previous models have failed to do. Variability within the decision process explains how errors are made, and variability across trials correctly predicts when errors are faster than correct responses and when they are slower.