JSM 2004 - Toronto

Abstract #301253

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Activity Number: 78
Type: Topic Contributed
Date/Time: Monday, August 9, 2004 : 8:30 AM to 10:20 AM
Sponsor: Biometrics Section
Abstract - #301253
Title: Recursive Partitioning for Changing Kriging Models in Brain Regions
Author(s): William R. Schucany*+ and Patrick S. Carmack and Richard F. Gunst and Wayne A. Woodward and Jeff Spence
Companies: Southern Methodist University and Southern Methodist University and Southern Methodist University and Southern Methodist University and Southern Methodist University
Address: Department of Statistical Science, Dallas, TX, 75275-0332,
Keywords: changepoint ; regression trees ; spatial correlation ; PET ; fMRI ; voxels
Abstract:

A brain image analysis package like SPM yields a comprehensive analysis of the entire brain, but it does so at the cost of a special global approximation for spatial correlations. On the other hand, spatial kriging models have been fit in manually selected spatially homogenous regions. While these models take advantage of the regional correlation structure, they fail to yield a comprehensive analysis of the entire brain. Recursive partitioning promises to automate the placement of localized spatial kriging models. These models exploit the correlation present in imaging data and potentially yield a spatial analysis of the entire brain. Demonstrations by examples and simulations will be presented.

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Revised March 2004