The D-REX model is designed for exploring the computational mechanisms in the brain involved in statistical regularity extraction from dynamic sounds. Utilizing a Bayesian inference framework for performing sequential prediction in the presence of unknown changepoints, this model can be used to test alternative statistics collected by the brain while listening to ongoing sounds. Perceptual parameters can be used to fit the model to individual behavior.