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Updated: Feb 8, 2026

Network Analysis of the Default Mode Network Using Functional Connectivity MRI in Temporal Lobe Epilepsy
Published on: August 5, 2014
Evaluation of the default-mode network by quantitative 15O-PET: comparative study between cerebral blood flow and
Jo Aoe1, Tadashi Watabe2, Eku Shimosegawa1,3
1Department of Nuclear Medicine and Tracer Kinetics, Osaka University Graduate School of Medicine, 2-2 Yamadaoka, Suita, Osaka, 565-0871, Japan.
Objective:
Resting-state functional MRI (rs-fMRI) has revealed the existence of a default-mode network (DMN) based on spontaneous oscillations of the blood oxygenation level-dependent (BOLD) signal. The BOLD signal reflects the deoxyhemoglobin concentration, which depends on the relationship between the regional cerebral blood flow (CBF) and the cerebral metabolic rate of oxygen (CMRO2). However, these two factors cannot be separated in BOLD rs-fMRI. In this study, we attempted to estimate the functional correlations in the DMN by means of quantitative 15O-labeled gases and water PET, and to compare the contribution of the CBF and CMRO2 to the DMN.
Methods:
Nine healthy volunteers (5 men and 4 women; mean age, 47.0 ± 1.2 years) were studied by means of 15O-O2, 15O-CO gases and 15O-water PET. Quantitative CBF and CMRO2 images were generated by an autoradiographic method and transformed into MNI standardized brain template. Regions of interest were placed on normalized PET images according to the previous rs-fMRI study. For the functional correlation analysis, the intersubject Pearson's correlation coefficients (r) were calculated for all pairs in the brain regions and correlation matrices were obtained for CBF and CMRO2, respectively. We defined r > 0.7 as a significant positive correlation and compared the correlation matrices of CBF and CMRO2.
Results:
Significant positive correlations (r > 0.7) were observed in 24 pairs of brain regions for the CBF and 22 pairs of brain regions for the CMRO2. Among them, 12 overlapping networks were observed between CBF and CMRO2. Correlation analysis of CBF led to the detection of more brain networks as compared to that of CMRO2, indicating that the CBF can capture the state of the spontaneous activity with a higher sensitivity.
Conclusions:
We estimated the functional correlations in the DMN by means of quantitative PET using 15O-labeled gases and water. The correlation matrix derived from the CBF revealed a larger number of brain networks as compared to that derived from the CMRO2, indicating that contribution to the functional correlation in the DMN is higher in the blood flow more than the oxygen consumption.
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