JSM 2011 Online Program

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Abstract Details

Activity Number: 518
Type: Contributed
Date/Time: Wednesday, August 3, 2011 : 10:30 AM to 12:20 PM
Sponsor: ENAR
Abstract - #302999
Title: Generalized Estimating Equation and Bootstrapping Approaches to Evaluate Functional Connectivity
Author(s): Gina M. D'Angelo*+ and Nicole Lazar and Guofu Zhou
Companies: Washington University and University of Georgia and Washington University
Address: 660 South Euclid Avenue, Box 8067, St. Louis, MO, 63110-1093, USA
Keywords: fMRI ; GEE ; transition model ; bootstrap ; Functional connectivity
Abstract:

In the neurodegenerative disease area it is often of interest to evaluate relationships between regional brain measures. Specifically, in resting-state functional magnetic resonance imaging (fMRI) studies an objective is to assess inter-regional correlations at resting-state with no task or stimulus. Resting-state fMRI studies produce cross-sectional time-series data across many regions of the brain. We propose using a generalized estimating equation (GEE) transition model to account for the lag and model the within-subject correlation for each region. In addition, the residuals from this GEE transition model will be extracted to correlate brain regions and assess between group differences. The GEE approach and standard pooling approach of group averages of the fisher-z transformation will be compared with simulation studies to determine statistical properties. Various bootstrapping approaches, including the block bootstrap and circular bootstrap, will be applied to estimate the standard error and confidence intervals. Both methods will be demonstrated with an Alzheimer's disease connectivity study in a population of Alzheimer's disease subjects and healthy control subjects.


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