ROIs Analysis: Comparison of the Activation Pattern Differences Between Two Occasions by Using Feature Extraction

• Activity Number: 375
• Type: Contributed
• Date/Time: Tuesday, August 11, 2015 : 10:30 AM to 12:20 PM
• Sponsor: Section on Statistics in Imaging
• Author(s): Jinae Lee* and Cheolwoo Park and Kara A. Dyckman and Nicole A. Lazar and Benjamin P. Austin and Qingyang Li and Jennifer E. McDowell and Hyungwook Park
• Companies: Yonsei University and University of Georgia and University of Georgia and University of Georgia and University of Wisconsin and Child Mind Institute and University of Georgia and Ulsan National Institute of Science and Technology
• Keywords: fMRI ; ROI ; Wavelet ; Feature extraction

Abstract

Functional Magnetic Resonance Imaging (fMRI) studies can be divided into two streams depending on the goal: a whole-brain voxelwise analysis and a regions of interest (ROIs) analysis.The method based on a whole-brain voxelwise analysis is a common approach for exploring the brain areas related to specific cognitive processes, but it does not permit us to examine specific statistical hypotheses about the subregions of the brain. If brain regions involved in specific cognitive processes are detected in the primary research, then it is usual to investigate the detected brain regions (i.e., ROIs) to determine how specific neural regions within whole brain may have been differentially affected. In this work, we conduct an analysis using 11 bilateral neural ROIs previously identified using saccade task; our analysis is built in the wavelet domain to take temporal correlation into account. First, we analyze the fMRI data acquired on two occasions while the participants are engaged in eye movement tasks. We attempt to compare the activation pattern differences between the two occasions by using the bootstrap resampling-based test and by using the feature extraction approach.