Our lab studies how sensory systems interpret the surrounding environment. Our goal is to reveal the strategies and algorithms used by our visual system to parse the complex, dynamic inputs received during natural vision, and to elucidate how populations of visual-cortical neurons represent and transmit visual information to support perceptual experience. We integrate theories of probabilistic neural coding, machine learning and natural image statistics, visual psychophysics, and neurophysiology through collaborations. Currently active projects include: perceptual grouping and segmentation, processing of natural images in the visual cortex, development of statistical tools to study interactions between neurons, and testing theories of visual processing in ASD. There will be opportunities for substantial interactions with and travel to the collaborating labs.