Neural Computation & Adaptive Perception
Hidden somewhere in the dense architecture of the human brain is the astounding power to convert the signals flowing along millions of sensory nerve fibres into a coherent model of the world.
Neural Computation & Adaptive Perception aims to unlock the mystery of how our brains convert sensory stimuli into information and to recreate human-style learning in computers. While this group focuses on visual systems, their research also points to broader explanations of how the brain processes other kinds of important information, including sounds, smells and tastes.
Not only has their research provided promising new explanations of how people learn, it has also bolstered efforts to create new artificial visual systems and synthetic neural networks that have brain-like learning capability.
One key to understanding how the brain processes visual information is to determine the algorithm, or computational principle, responsible for brain function. This algorithm can be used to create intelligent devices, such as artificial eyes wired directly into the nervous system, or security surveillance devices at airports that can pick out suspicious objects.
Beyond engineering applications, a deeper understanding of the brain could also provide new understanding of brain diseases such as Parkinson’s and Alzheimer’s. Researchers know that these diseases result when the brain’s algorithms break down, but they are not sure exactly how or why. A better understanding of the brain could help to figure out how to do maintenance on it and help to sustain a high mental quality of life.
Program members have backgrounds in computer science, psychology, electrical and computer engineering, neuroscience, and ophthalmology.