JSM 2005 - Toronto

Abstract #303600

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Legend: = Applied Session, = Theme Session, = Presenter
Activity Number: 131
Type: Topic Contributed
Date/Time: Monday, August 8, 2005 : 10:30 AM to 12:20 PM
Sponsor: Biometrics Section
Abstract - #303600
Title: Model Selection for Functional Magnetic Resonance Imaging
Author(s): Nicole Lazar*+
Companies: University of Georgia
Address: Department of Statistics, Athens, GA, 30602,
Keywords:
Abstract:

Many models have been proposed for the analysis of functional magnetic resonance imaging (fMRI) data. These range from standard linear models, to wavelets, to nonparametric analysis. The question of model selection is, by contrast, largely unexplored. In this talk, I describe some of the difficulties in performing model selection for fMRI. A critical question relates to the model selection strategy: Should one look for the model that provides the best fit over the whole brain, or should the best model be found for each voxel individually? Both approaches pose challenges in terms of computation and interpretation of the results. I will present some first attempts at tackling this problem, using simple models for the fMRI time course as an example.

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Revised March 2005