Perceptual Learning

Perceptual learning refers to a long-term change in the ability to extract perceptual information from the environment that arises via experience or practice. In this chapter, we first explore many examples of perceptual learning in relatively simple as well as in more complex tasks. Furthermore, we do so across sensory modalities (vision, audition, touch, taste, smell) with the goal of highlighting the commonalities seen in perceptual learning across systems that are typically considered separately. We then consider the most substantial issues in the domain, including the question of learning specificity (i.e., when do improvements on one task transfer to new unpracticed tasks?), the conditions under which learning occurs, the neural basis of perceptual learning, computational models of perceptual learning, and potential real-world applications of perceptual learning. We conclude with future directions; although the field has clearly made tremendous progress over the past century or more, there remain critical gaps in our knowledge that preclude our ability to fully harness perceptual learning to make a real-world impact.