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Activity Number: 32 - Longitudinal/Correlated Data I
Type: Contributed
Date/Time: Sunday, July 29, 2018 : 2:00 PM to 3:50 PM
Sponsor: Biometrics Section
Abstract #330599
Title: Efficient Analysis for fMRI Studies
Author(s): Lan Liu*
Companies: University of Minnesota at Twin Cities
Keywords: Efficiency; Multivariate analysis; fMRI
Abstract:

Functional magnetic resonance imaging (fMRI) is a popular technology that measures brain activity by detecting changes associated with blood flow. Such data could be used to provide information on behavior, brain development trajectories, and metabolic diseases. As the technology advances, we can obtain brain images with higher resolution these days. While traditional methods of analysis may have produced acceptable results when the imaging data was in low resolution, the high dimensional images demand better statistical methods for more precise and efficient estimations for task fMRI studies. We develop novel statistical methodologies for conducting efficient multivariate inferences for fMRI studies.


Authors who are presenting talks have a * after their name.

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