Carnegie Mellon study identifies where thoughts of familiar objects occur inside the human brain

Experts trained algorithm to extract patterns from participants' brain activation scans
A team of Carnegie Mellon University computer scientists and cognitive neuroscientists, combining methods of machine learning and brain imaging, have found a way to identify where people’s thoughts and perceptions of familiar objects originate in the brain by identifying the patterns of brain activity associated with the objects. An article in the Jan. 2 issue of PLoS One discusses this new method, which was developed over two years under the leadership of neuroscientist Professor Marcel Just and Computer Science Professor Tom M. Mitchell.