Scientists at Carnegie Mellon University have developed a computational model that can predict the unique human brain activation patterns associated with names for things that can be seen, heard, felt, tasted or smelt.

Previously researchers used functional magnetic resonance imaging (fMRI) to detect which areas of the brain are activated when a person thinks about a specific word. A Carnegie Mellon team has taken the next step by predicting these activation patterns for concrete nouns - things that are experienced through the senses - for which fMRI data does not yet exist.

The work could eventually lead to the use of brain scans to identify thoughts and could have applications in the study of autism, disorders of thought such as paranoid schizophrenia, and semantic dementias such as Pick’s disease.

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