A computer that can 'read' your mind
For centuries, the concept of mind readers was strictly the domain of folklore and science fiction. But according to new research published today in the journal Science, scientists are closer to knowing how specific thoughts activate our brains. The findings demonstrate the power of computational modeling to improve our understanding of how the brain processes information and thoughts. The research was conducted by a computer scientist, Tom Mitchell, and a cognitive neuroscientist, Marcel Just, both of Carnegie Mellon University. Their previous research, supported by the National Science Foundation (NSF) and the W.M. Keck Foundation, had shown that functional magnetic resonance imaging (fMRI) can detect and locate brain activity when a person thinks about a specific word. Using this data, the researchers developed a computational model that enabled a computer to correctly determine what word a research subject was thinking about by analyzing brain scan data.
In their most recent work, Just and Mitchell used fMRI data to develop a more sophisticated computational model that can predict the brain activation patterns associated with concrete nouns, or things that we experience through our senses, even if the computer did not already have the fMRI data for that specific noun.
The researchers first built a model that took the fMRI activation patterns for 60 concrete nouns broken down into 12 categories including animals, body parts, buildings, clothing, insects, vehicles and vegetables. The model also analyzed a text corpus, or a set of texts that contained more than a trillion words, noting how each noun was used in relation to a set of 25 verbs associated with sensory or motor functions. Combining the brain scan information with the analysis of the text corpus, the computer then predicted the brain activity pattern of thousands of other concrete nouns.