The visual system can effortlessly recognize hundreds of thousands of objects in spite of tremendous variation in their appearance, resulting, for instance, from changes in objects’ position and pose, variable lighting conditions, and presence of background objects in the visual field. To achieve such an invariant representation of the visual world is an extremely difficult computational problem that even the most advanced artificial vision systems are not fully able to solve.

Our lab investigates the neuronal processing of visual object information, using a combination of psychophysics and multi-unit neuronal recordings in rodents, as well as simulations of computational models. Our hope is that this work will lead to a greater understanding of the neuronal substrates of visual perception and will assist in the development of machine vision systems and neuronal prostheses.