Abstract
Perceptual Learning (PL), a training induced improvement in sensory perception, is known to be sensitive to the stimuli, task, and training parameters that can dramatically affect learning outcomes. However, to date there is little standardization of lab methodologies, which makes comparisons across studies difficult. This limits both our basic understanding of the plasticity of the perceptual systems and the possibility of developing effective translational approaches for rehabilitation of perceptual and cognitive deficits. Here, we introduce a cross-platform application built using the UNITY engine that enables and supports data collection on several platforms including computers, tablets and even smart phones. This platform supports a variety of PL training and assessment procedures, with a current emphasis on understanding PL of contrast sensitivity, as well as a number of outcome measures ranging from measures of basic vision, to cognitive measures, and even psychoacoustic measures. We here present an overview of the PLFest platform and preliminary data showing that it produces reliable data on Apple iPad tablet computers. This platform is intended to support data collection for large scale multi-site studies and will be made public as a tool to support open science, data sharing and reproducible science.