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Activity Number: 70 - Utilizing High-Dimensional and Complex Data in Personalized Medicine
Type: Contributed
Date/Time: Sunday, July 30, 2017 : 4:00 PM to 5:50 PM
Sponsor: Mental Health Statistics Section
Abstract #322842 View Presentation
Title: Evaluation of Brain Activation Changes in Functional Magnetic Resonance Imaging Data Using Cluster Analysis
Author(s): Arunava Samaddar*
Companies: University of Georgia
Keywords: fMRI ; clustering ; wavelet ; dissimilarity
Abstract:

We aim to evaluate brain activation using Functional Magnetic Resonance Imaging (fMRI) data and activation changes across time associated with practice related cognitive control during tasks. FMR images are acquired from participants engaged in six designed runs(one block design and 5 event related designs) at two time points: 1) pre-test before any exposure to the task, and 2) post-test, after four days of daily practice on antisaccades (generating a glance away from a cue) or prosaccades (glancing toward a target). We cluster voxel time series in each group through the following steps: detrending, data aggregation, wavelet transform, and thresholding, the adaptive pivotal thresholding test, principal component analysis and K-medoids clustering. We also compare the clustered maps using a dissimilarity measure.


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

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