Stimulus prior and reward probability differentially affect response bias in perceptual decision making

Abstract

Signal detection theory posits that subjects in two-stimulus, two-choice discrimination tasks decide by comparing random samples of an evidence variable to a static decision criterion. While the core assumptions of the theory have received ample experimental support, it has become evident that the decision criterion is not static but subject to trial-by-trial fluctuations and can be influenced by experimental manipulations. The mechanisms governing the trial-by-trial criterion changes are however not well understood. Here, we report results from five experiments in which we subjected rats to a two-stimulus, two-choice auditory discrimination task. In the first three experiments, we investigated the effects of stimulus presentation ratios and reward ratios and provide clear evidence that the effects of changing reward ratios are more pronounced than those of stimulus presentation ratios. A model-based analysis revealed that this effect was due to more than tenfold higher learning rates when reward ratios were manipulated. In two separate experiments, we investigated the effect of reward density (i.e., global reward rate) on criterion learning but failed to find consistent effects. A systematic comparison of three different trial-by-trial criterion learning models based on detection theory, the matching law, and reinforcement learning showed that no model was able to capture the differential effects of stimulus presentation and reward ratios. We conclude that subjects explicitly represent either prior stimulus probabilities or entire stimulus distributions, and accordingly future models need to represent these factors as well.