Event
Brains, Meaning and Corpus Statistics

Dr. Tom M. Mitchell

November 15, 2007 1:00 PM  to 
November 15, 2007 2:00 PM
Room 375

CISE Distinguished Lecture

Thursday, November 15th, 2007 at 1:00pm, Rm. 375*

Brains, Meaning and Corpus Statistics

Dr. Tom M. Mitchell

E. Fredkin Professor and Department Head Machine Learning Department Carnegie Mellon University

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Abstract:

How does the human brain represent meanings of words and pictures in terms of the neural activity observable through fMRI brain imaging? Recent brain imaging studies have proven that different spatial patterns of fMRI neural activation are associated with thinking about particular semantic categories of words and pictures (e.g., tools, buildings, animals). As a next step we seek a general theory capable of predicting the neural activity associated with arbitrary English words, including words for which we do not yet have brain image data.  This talk will present the first such predictive theory, in the form of a computational model trained using a combination of co-occurrence statistics from a trillion-word text corpus, and observed fMRI data associated with viewing several dozen concrete nouns. Once trained, the model predicts fMRI activation for any other concrete noun appearing in the tera-word text corpus, with highly significant accuracies over the 60 nouns for which we currently have fMRI data.

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Bio:

Tom M. Mitchell is the E. Fredkin Professor and head of the Machine Learning Department at Carnegie Mellon University.  Mitchell is a past President of the American Association of Artificial Intelligence (AAAI), Chair of the American Association for the Advancement of Science (AAAS) section on Information, Computing and Communication, member of the US National Research Council's Computer Science and Telecommunications Board, and member of NSF's Steering Group on Brain Science.  His general research interests lie in machine learning, artificial intelligence, and cognitive neuroscience, and his current research includes combining machine learning with brain imaging, to study meaning representations in the human brain.  Mitchell believes the field of machine learning will be the fastest growing component of computer science during the 21st century.

For additional information please visit Dr. Mitchell's web home page http://epublish.nsf.gov/epublish/www.cs.cmu.edu/~tom

* If you would like to arrange a meeting with Dr. Mitchell, please contact Dawn Patterson (ext. 7097).

This event is part of Distinguished Lecture Series.

Meeting Type
Lecture

Contacts
Dawn Patterson, 7032928910 x7097 dpatters@nsf.gov
       Preferred Contact Method: Email

NSF Related Organizations
NSF-Wide
Division of Computing and Communication Foundations