Linking the diffusion model and general recognition theory: Circular diffusion with bivariate-normally distributed drift rates

Abstract

The circular diffusion model is a model of continuous outcome decisions, which are modeled as evidence accumulation by a two-dimensional Wiener diffusion process on the interior of a disk whose bounding circle represents the decision criterion. When there is across-trial variability in the evidence entering the decision process, represented by variability in drift rates, the model predicts that inaccurate responses will be slower than accurate responses, in agreement with, and generalizing, the slow-error property of the one-dimensional diffusion model of two-choice decisions. A natural generalization of the one-dimensional model's assumption of normally distributed drift rates is provided b..