Training-based improvements in visual performance are one possible non-invasive approach for remediation for a range of visual impairments. The last several decades of research in perceptual learning has demonstrated a remarkable ability of training or practice to enhance perception in the adult human, and has greatly improved our understanding of the associated plasticity in the human brain. Now is the time to use our understanding of the mechanisms and specificity of perceptual learning to develop predictive theories and new training paradigms that improve the efficiency or magnitude of perceptual improvement and its generalization. In this proposal, we develop a research program to systematically investigate how to improve the efficiency and magnitude of learning in a given task, how to improve the immediate generalization of those improvements to related tasks and stimuli, and how to improve the ability of the individual to learn new tasks. Improvements in perceptual task performance through perceptual learning or training, and the extent of transfer to related conditions, both depend critically upon the training protocol and the mixture of stimuli and tasks being trained. The current research uses computational models of visual perceptual learning, new and extended training and testing protocols, efficient estimation methods, and empirical tests to improve our understanding of the principles of learning that can be used to design protocols that enhance efficient learning and generalization. The goal of this research program is to develop the theories and practical implementation of perceptual learning in normal populations that could contribute to translational applications to developmental learning and to ameliorative training in populations with perceptual deficits. These aims are consistent with the goals of the National Eye Institute.