Paper Info
Title
Detecting resting-state brain activity using OEF-weighted imaging.
Abstract
Traditional resting-state functional magnetic resonance imaging (fMRI) is mainly based on the blood oxygenation level-dependent (BOLD) contrast. The oxygen extraction fraction (OEF) represents an important parameter of brain metabolism and is a key biomarker of tissue viability, detecting the ratio of oxygen utilization to oxygen delivery. Investigating spontaneous fluctuations in the OEF-weighted signal is crucial for understanding the underlying mechanism of brain activity because of the immense energy budget during the resting state. However, due to the poor temporal resolution of OEF mapping, no studies have reported using OEF contrast to assess resting-state brain activity. In this fMRI study, we recorded brain OEF-weighted fluctuations for 10 min in healthy volunteers across two scanning visits, using our recently developed pulse sequence that can acquire whole-brain voxel-wise OEF-weighted signals with a temporal resolution of 3 s. Using both group-independent component analysis and seed-based functional connectivity analysis, we robustly identified intrinsic brain networks, including the medial visual, lateral visual, auditory, default mode and bilateral executive control networks, using OEF contrast. Furthermore, we investigated the resting-state local characteristics of brain activity based on OEF-weighted signals using regional homogeneity (ReHo) and fractional amplitude of low-frequency fluctuations (fALFF). We demonstrated that the gray matter regions of the brain, especially those in the default mode network, showed higher ReHo and fALFF values with the OEF contrast. Moreover, voxel-wise test-retest reliability comparisons across the whole brain demonstrated that the reliability of resting-state brain activity based on the OEF contrast was moderate for the network indices and high for the local activity indices, especially for ReHo. Although the reliabilities of the OEF-based indices were generally lower than those based on BOLD, the reliability of OEF-ReHo was slightly higher than that of BOLD-ReHo, with a small effect size, which indicated that OEF-ReHo could be used as a reliable index for characterizing resting-state local brain activity as a complement to BOLD. In conclusion, OEF can be used as an effective contrast to study resting-state brain activity with a medium to high test-retest reliability.
Year
DOI
Venue
2019
10.1016/j.neuroimage.2019.06.038
NeuroImage
Keywords
Field
DocType
Resting state,OEF,Networks,ReHo,fALFF,Test-retest reliability
Neuroscience,Default mode network,Functional magnetic resonance imaging,Resting state fMRI,Psychology,Cognitive psychology,Brain activity and meditation,Oxygenation,Tissue viability,Temporal resolution,Apparent oxygen utilisation
Journal
Volume
ISSN
Citations 
200
1053-8119
0
PageRank 
References 
Authors
0.34
0
5
Name
Order
Citations
PageRank
Yang Yang100.34
Yayan Yin200.34
Jie Lu3516.19
Qihong Zou4455.35
Jia-Hong Gao5328.81