Our research focuses on how structured visual information is acquired and converted into sophisticated internal representations for controlling cognition and behavior. We use an integrated approach with three main components: human psychophysical and learning experiments, computational modeling of perception and learning, and multi-electrode recording from behaving animals. The recurrent theme of our work is the pursuit of a statistically based and biologically sound framework to link low-level visual processes and mechanisms (e.g., orientation coding and adaptation) with the development and learning of higher level complex features and constancies for efficient representations of objects and scenes of the visual environment.