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Activity Number: 63
Type: Contributed
Date/Time: Sunday, August 6, 2006 : 4:00 PM to 5:50 PM
Sponsor: Biometrics Section
Abstract - #306781
Title: Interpreting Experience-Based Cognition from fMRI
Author(s): Rajan Patel*+ and F. DuBois Bowman and Ying Guo and Gordana Derado and Lance Waller and Amita K. Manatunga
Companies: Rice University and Emory University and Emory University and Emory University and Emory University and Emory University
Address: 17 Via Colinas, Westlake Village, CA, 91362,
Keywords: fMRI ; prediction ; support vector machines ; boosting ; principle components
Abstract:

Recent advances in statistics and functional neuroimaging allow the use of distributed patterns of brain activity to predict subjective human experience. The Pittsburgh Brain Activity Competition set forth to challenge groups from multiple disciplines to use various statistical and data mining techniques to infer subjective experience from fMRI. Individuals were scanned watching three segments of videos after which each provided behavioral time vector ratings of experience coding categories ( i.e. human faces, tools, emotion). Groups were provided with functional scans from each video but time vector ratings of only the first two, with the goal to predict vector ratings for the third video. In this talk, we describe and compare several approaches, from iterative boosting and supervised principal components to support vector machines.

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