This study addresses the fundamental issue of specificity and generality of training in the context of Perceptual Learning (PL). PL broadly encompasses the set of mechanisms through which experience with the environment gives rise to changes in perceptual processing. Careful research in this domain can greatly enhance our basic understanding of the perceptual systems and the plasticity of these systems. Furthermore, translational approaches underpinned by the basic science of PL are becoming increasingly prominent. This includes a host of emerging translational approaches for the rehabilitation of both perceptual deficits and for cognitive training, which are believed to share cortical plasticity mechanisms. However, while existing research provides evidence that PL approaches can improve perceptual skills, our ability to develop effective interventions is limited by a lack of understanding of the behavioral outcomes associated with different PL approaches. One major obstacle to successful translation of PL is that the field to-date has been strongly driven by "novel" and "provocative" findings demonstrated via small N studies with very few projects digging deep to achieve robust and reliable results. In turn, not surprisingly, the field of PL, like many others in psychology, has suffered from numerous replication challenges. Here we address these limitations by comparing a large number of different training tasks using common outcome measures and in a large subject population. Each training tasks involves a different "critical feature" for learning proposed by one or more research groups. However, these training tasks have never been directly compared or contrasted. Robust and reliable results will be achieved by training a large sample of participants on PL tasks and assess the outcomes via a common set of measures. The investigators will also collect a broad assessment of individual differences, which will provide a unique dataset that can resolve controversies in the literature and lead to new understandings. Our proposed analytical approach tests several key hypotheses in the field, explores the extent to which different training approaches lead to systematically different profiles of learning, and examines how these can differ based upon the individuals being trained.