Neural Codes for Shape Perception

Shape perception is at the core of a range of cognitive skills from recognizing objects, to interpreting complex scenes, and guiding our actions. Psychophysical and computational work proposes that the perception of coherent and meaningful structures in natural images relies on neural processes that convert information about local edges to complex features. Here, we present evidence for an efficient and adaptive neural code that is optimized through training and experience to support shape perception.