We are getting closer to understanding how the human brain works.
Two hundred years ago, archaeologists used the Rosetta Stone to understand the ancient Egyptian scrolls. Now, a team of Carnegie Mellon University scientists has discovered the beginnings of a neural Rosetta Stone. By combining brain imaging and machine learning techniques, neuroscientists Marcel Just and Vladimir Cherkassky and computer scientists Tom Mitchell and Sandesh Aryal determined how the brain arranges noun representations. Understanding how the brain codes nouns is important for treating psychiatric and neurological illnesses.
"In effect, we discovered how the brain's dictionary is organized," said Just, the D.O. Hebb Professor of Psychology and director of the Center for Cognitive Brain Imaging. "It isn't alphabetical or ordered by the sizes of objects or their colors. It's through the three basic features that the brain uses to define common nouns like apartment, hammer and carrot."
The three factors, each coded in three to five different locations in the brain, were found by a computer algorithm that searched for commonalities among brain areas in how participants responded to 60 different nouns describing physical objects. For example, the word apartment evoked high activation in the five areas that code shelter-related words.
The research also showed that the noun meanings were coded similarly in all of the participants' brains. "This result demonstrates that when two people think about the word 'hammer' or 'house,' their brain activation patterns are very similar. But beyond that, our results show that these three discovered brain codes capture key building blocks also shared across people," said Mitchell, head of the Machine Learning Department in the School of Computer Science.
Identifying Thoughts Through Brain Codes Leads to Deciphering the Brain's Dictionary 
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