For decades, neuroscientists have been trying to design computer networks that can mimic visual skills such as recognizing objects, which the human brain does very accurately and quickly. Until now, no computer model has been able to match the primate brain at visual object recognition during a brief glance. However, a new study from MIT neuroscientists has found that one of the latest generation of these so-called ‘deep neural networks’ matches the primate brain.
Because these networks are based on neuroscientists' current understanding of how the brain performs object recognition, the success of the latest networks suggests that neuroscientists have a fairly accurate grasp of how object recognition works. The fact that the models predict the neural responses and the distances of objects in neural population space shows that these models encapsulate our current best understanding as to what is going on in this previously mysterious portion of the brain.