David Daniel Cox

Systems and Approaches
electrophysiology, microelectrode recording, computational neuroscience, behavior, high performance computing

Interests
visual object recognition, sensory neuroscience, machine vision

Summary
Humans recognize visual objects with such ease that it is easy to overlook what an impressive computational feat this represents. Any given object in the world can cast an effectively infinite number of different images onto the retina, depending on its position relative to the viewer, the configuration of light sources, and the presence of other objects in the visual field. In spite of this extreme variation, biological visual systems are able to effortlessly recognize at least hundreds of thousands of distinct object classes—a feat that no current artificial system can come close to achieving. Our laboratory seeks to understand the neuronal mechanisms that enable this ability by reverse engineering simple biological visual systems. It is our hope that this work leads to a greater understanding of how our own brain works and to the construction of improved artificial visual systems.