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Abstract Details
Activity Number:
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405
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Type:
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Contributed
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Date/Time:
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Tuesday, August 2, 2011 : 2:00 PM to 3:50 PM
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Sponsor:
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Biometrics Section
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Abstract - #303100 |
Title:
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Testing Variance Components in a Functional Mixed-Effects Model for fMRI Data
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Author(s):
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Ragnheidur Helga Haraldsdottir*+ and Wesley Thompson and Tor D. Wager and Martin A. Lindquist
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Companies:
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Columbia University and University of California at San Diego and University of Colorado and Columbia University
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Address:
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1255 Amsterdam Ave Rm 1005, New York, NY, 10027,
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Keywords:
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fMRI ;
Brain ;
FDA ;
Mixed-effects model
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Abstract:
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Currently most analysis of multi-subject fMRI data involves fitting a GLM model for each subject, and using the resulting activation parameter estimates in a "second level" group analysis. In this work we introduce a functional mixed-effects model which allows us to not only directly estimate the activation parameters, but also the variance components of the model. Further, we discuss an approach for performing inference on the variance components that allows us to test for significant individual differences between subjects; something not currently performed in fMRI data analysis. We apply the method to the FBIRN data, where a group of subjects perform the same task at 4 different sites.
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