Perceptual Learning

Abstract

Abstract Experience significantly influences how sensory stimuli are processed and the quality of sensory-based decisions and human performance. This is true for all sensory modalities. Perceptual learning research, especially but not restricted to the visual domain, has focused on not just learning but its specificity as well. This chapter provides a sketch of some of the principles of perceptual learning based on an analysis of behavioral experiments, physiology and brain imaging studies, and computational models. It highlights several theoretical contrasts, including the trade-off between plasticity and stability; the significance of signal and noise; the role of retuning and reweighting (improved readout) in learning; and the importance of top-down influences such as task or goal, attention and reward, as well as bottom-up factors in learning. Each of these reveals some principles of learning and memory in the perceptual domain. The training applications inspired by laboratory research, some of which are beginning to yield potential translations, highlight the motivation for considering not just perceptual learning but also generalizability.