Diffusion Models for Two-Choice Decisions

Roger Ratcliff


I will discuss the diffusion model for perceptual and cognitive two-choice decisions beginning with presentation of data from two choice tasks and showing relationships between the different dependent measures (accuracy, and correct and error RT distributions) that need to be explained. I will explain how the model accounts for difficulty, speed-accuracy tradeoffs, error response times (RTs), and RT distributions. One of the major contributions of the model is that it solves a long-standing problem for decision-making models, specifically, the relationship between correct and error RTs. It solves this problem with the assumption that the parameters of the model vary in their values from trial to trial. I will also describe recent studies in which we have used the model to examine differences in processing between college-age students and older adults. We have found that in several paradigms, the rate of accumulation of evidence in the decision process is not significantly different for the two groups. Longer RTs for the older adults come from more conservative decision criteria and from a small increase in the nondecision components of processing. In addition to differences between groups, the model extracts meaningful individual differences such that their parameters correlate across tasks. If there is time, I will discuss an application of the diffusion model to EEG data for memory and show how EEG measures (single trial regressors) map into diffusion model parameters. This provides direct evidence for trial to trial variability in drift rate.