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SUMMARY:Predicting Human Brain Activity Associated with the Meanings of No
 uns - Colin Kelly (University of Cambridge)
DTSTART:20091123T123000Z
DTEND:20091123T133000Z
UID:TALK21628@talks.cam.ac.uk
CONTACT:Diarmuid Ó Séaghdha
DESCRIPTION:At this session of the NLIP Reading Group we’ll be discussin
 g the following paper:\n\nTom M. Mitchell\, Svetlana V. Shinkareva\, Andre
 w Carlson\, Kai-Min Chang\, Vicente L. Malave\, Robert A. Mason and Marcel
  Adam Just. 2008. "Predicting Human Brain Activity Associated with the Mea
 nings of Nouns":http://www.cs.cmu.edu/~tom/pubs/science2008.pdf. Science 3
 20: 1191-1195.\n(supplemental material is available "here":http://www.cs.c
 mu.edu/~tom/pubs/science2008_SOM.pdf)\n\n*Abstract:* \nThe question of how
  the human brain represents conceptual knowledge has been debated in many 
 scientific fields. Brain imaging studies have shown that different spatial
  patterns of neural activation are associated with thinking about differen
 t semantic categories of pictures and words (for example\, tools\, buildin
 gs\, and animals). We present a computational model that predicts the func
 tional magnetic resonance imaging (fMRI) neural activation associated with
  words for which fMRI data are not yet available. This model is trained vi
 a a combination of data from a trillion-word text corpus\, and observed fM
 RI data associated with viewing several dozen concrete nouns. Once trained
 \, the model predicts fMRI activation for thousands of other concrete noun
 s in the text corpus\, with highly significant accuracies over the 60 noun
 s for which we currently have fMRI data.
LOCATION:GS15\, Computer Laboratory
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