LAUSR

At the Conference on Cognitive Computational Neuroscience this month, researchers presented new tools for comparing data collected from living brains with readouts from computational models known as deep neural networks. Such comparisons might offer up new hypotheses about how humans interpret sights and sounds, understand language, or navigate the world. Until recently, artificial intelligence couldn9t come anywhere close to human performance on tasks like recognizing sounds or classifying images. But deep neural networks, loosely inspired by the brain, have logged increasingly impressive performances, especially on visual tasks. That has led some neuroscientists to wonder whether these models could yield insight into how our own brains process information.