S-Space College of Medicine/School of Medicine (의과대학/대학원) Psychiatry (정신과학전공) Journal Papers (저널논문_정신과학전공)
Surface-based functional magnetic resonance imaging analysis of partial brain echo planar imaging data at 1.5 T
- Jo, Hang Joon; Lee, Jong-Min; Kim, Jae-Hun; Choi, Chi-Hoon; Kwon, Jun Soo; Kim, Sun I.; Kang, Do-Hyung
- Issue Date
- ELSEVIER SCIENCE INC
- MAGNETIC RESONANCE IMAGING; Vol.27(5); 691-700
- Functional magnetic resonance imaging; Segmented echo planar imaging; Surface-based analysis
- Surface-based functional magnetic resonance imaging (fMRI) analysis is more sensitive and accurate than volume-based analysis for detecting neural activation. However, these advantages are less important in practical fMRI experiments with commonly used 1.5-T magnetic resonance devices because of the resolution gap between the echo planar imaging data and the cortical surface models. We expected high-resolution segmented partial brain echo planar imaging (EPI) data to overcome this problem, and the activation patterns of the high-resolution data could be different from the low-resolution data. For the practical applications of surface-based fMRI analysis using segmented EPI techniques, the effects of some important factors (e.g., activation patterns, registration and local distortions) should be intensively evaluated because the results of surface-based fMRI analyses could be influenced by them. In this Study, we demonstrated the difference between activations detected from low-resolution EPI data, which were covering whole brain, and high-resolution segmented EPI data covering partial brain by volume- and surface-based analysis methods. First, we compared the activation maps of low- and high-resolution EPI datasets; detected by volume- and surface-based analyses, with the spatial patterns of activation clusters, and analyzed the distributions of activations in occipital lobes. We also analyzed the high-resolution EPI data covering motor areas and fusiform gyri of human brain, and presented the differences of activations detected by volume- and surface-based methods.
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