The neural processing involved in visually recognizing even the simplest object in a natural environment is profound—and profoundly difficult to mimic. Neuroscientists have made broad advances in understanding the visual system, but much of the inner workings of biologically-based systems remain a mystery.
Using Graphics Processing Units (GPUs), the same technology video game designers use to render life-like graphics, researchers are now making progress faster than ever before. A new study, co-led by David Cox, Principal Investigator of the Visual Neuroscience Group at the Rowland Institute at Harvard, and Nicolas Pinto, a Ph.D. Candidate in James DiCarlo’s laboratory at the McGovern Institute for Brain Research and the Department of Brain and Cognitive Sciences at MIT, was published in the November 26th issue of PLoS Computational Biology.
“Reverse engineering a biological visual system—a system with hundreds of millions of processing units—and building an artificial system that works the same way is a daunting task,” says Cox. “It is not enough to simply assemble together a huge amount of computing power. We have to figure out how to put all the parts together so that they can do what our brains can do.”