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Abstract
The Primary goal of this research is an application of feature extraction and a mixed model to functional Magnetic Resonance Imaging (fMRI) data. The goal of study is a comparison of multiple groups of subjects when they conduct a cognitive task. Since fMRI data of interest are the information of stimulus-response reactions from human brain activity over time, they show repeated patterns in the signals. Therefore, we use the feature extraction method that collects the characteristics or patterns of data. Then, we apply a mixed model that includes both fixed and random effects to find any group difference. Through a simulation study we find a mixed model with feature extraction approach effective for detecting a difference between groups. Finally, we have applied the approach on the11 regions of interest in human brain from the cognitive task fMRI data, and found that the region called Striatum shows significant difference.