Modeling trial by trial and block feedback in perceptual learning

•We model the varied effects of different kinds of feedback on perceptual learning.•We extend an Hebbian reweighting model to consider different kinds of feedback.•The model fits seven conditions of feedback in the data of Herzog and Fahle (1997).•Block feedback is modeled through adaptive criterion setting.•The study provides an integrated account of a full range of feedback phenomena.

Feedback has been shown to play a complex role in visual perceptual learning. It is necessary for performance improvement in some conditions while not others. Different forms of feedback, such as trial-by-trial feedback or block feedback, may both facilitate learning, but with different mechanisms. False feedback can abolish learning. We account for all these results with the Augmented Hebbian Reweight Model (AHRM). Specifically, three major factors in the model advance performance improvement: the external trial-by-trial feedback when available, the self-generated output as an internal feedback when no external feedback is available, and the adaptive criterion control based on the block feedback. Through simulating a comprehensive feedback study (Herzog & Fahle, 1997), we show that the model predictions account for the pattern of learning in seven major feedback conditions. The AHRM can fully explain the complex empirical results on the role of feedback in visual perceptual learning.