Explaining Fast Errors in Perceptual Decision Making: Starting Point Variability or Jumping to Conclusion?

The diffusion model has become a standard model for perceptual decision making over the last decades. A challenge for cognitive models for this type of task is to model differences in mean reaction times for correct responses and error responses. In particular, for simple tasks with short response times, incorrect responses typically have lower mean response times than correct responses. In the diffusion model framework, this asymmetry is typically explained by variability in the starting point of the evidence accumulation process. Recently, the Levy-Flight model was introduced as an alternative explanation for fast errors based on jumps in evidence accumulation. In this talk, the goodness-of-fit of the Diffusion Model and the Levy-Flight Model is compared for different tasks.