Effects of biased feedback on learning and deciding in a vernier discrimination task

Abstract

We investigate the influence of biased feedback on decision and learning processes in a vernier discrimination task. Subjects adjust their decision criteria and hence their responses according to biased external feedback. However, they do not use learning processes to encode incorrectly classified stimuli. As soon as correct feedback is restored observers regain their original performance indicating an involvement of internal criteria. If the external feedback is switched off instead of being corrected, the rebound is less vigorous. The findings contradict predictions of supervised neural network models.