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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