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Abstract #3088

Comparison of Power Spectrum in Resting Brain Networks of Human and Rat using Seed Regions and Independent Component Analysis

Yu-Han Hong 1 , Hui-Yu Wang 1 , You-Yin Chen 2 , Yeu-Sheng Tyan 1,3 , and Jun-Cheng Weng 1,3

1 School of Medical Imaging and Radiological Sciences, Chung Shan Medical University, Taichung, Taiwan, 2 Department of Biomedical Engineering, National Yang-Ming University, Taipei, Taiwan, 3 Department of Medical Imaging, Chung Shan Medical University Hospital, Taichung, Taiwan

At present, resting state functional MRI (rsfMRI) is increasingly used in human and rodent neuropathological research. Therefore, the purpose of this study was to find a stable and reliable analysis method of rsfMRI for human and rat, and to compare the region correlation and power spectrum in human and rat brain networks using seed regions and independent component analysis (ICA). By acquiring rsfMRI data with a comparable protocol (e.g. anesthesia for rat), scanning and analysis, in both humans and rats we were able to compare findings obtained in both species. The outcome of rsfMRI is different for humans and rats and depends strongly on the seed position in the seed regions functional connectivity analysis, and the applied number of components in the ICA. The most important difference was the power spectrum of several networks, such as visual, motor, default mode, amygdala, hippocampus and thalamus, in the rat shifted to lower frequency regime compared to human brain. Furthermore, a higher number of components was needed for the ICA analysis to separate different cortical regions in rats as compared to humans.

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