Deep Neural Networks Are Helping Decipher How Brains Work

In the winter of 2011, Daniel Yamins, a postdoctoral researcher in computational neuroscience at the Massachusetts Institute of Technology, would at times toil past midnight on his machine vision project. He was painstakingly designing a system that could recognize objects in pictures, regardless of variations in size, position, and other properties--something that humans do with ease. The system was a deep neural network, a type of computational device inspired by the neurological wiring of living brains. Original story reprinted with permission from Quanta Magazine, an editorially independent publication of the Simons Foundation whose mission is to enhance public understanding of science by covering research develop ments and trends in mathe matics and the physical and life sciences. "I remember very distinctly the time when we found a neural network that actually solved the task," he said.