New research from the University of Pittsburgh will develop a neuromorphic vision system that takes a new approach to capturing visual information that is based on the human brain, benefiting everything from self-driving vehicles to neural prosthetics.

The project will receive $500,000 from the National Science Foundation. Ryad Benosman, professor of ophthalmology at the University of Pittsburgh School of Medicine who holds appointments in electrical engineering and bioengineering, and Feng Xiong, assistant professor of electrical and computer engineering at the Swanson School of Engineering, are leading the effort.

The team will use a “spiking neural network” with realistic dynamic synapses that will enhance computational abilities, develop brain-inspired machine learning to understand the input, and connect it to a neuromorphic event-based silicon retina for real-time operating vision.