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Toward reliable characterization of functional homogeneity in the human brain: Preprocessing, scan duration, imaging resolution and computational space
Zuo, Xi-Nian; Xu, Ting; Jiang, Lili; Yang, Zhi; Cao, Xiao-Yan; He, Yong; Zang, Yu-Feng; Castellanos, F. Xavier; Milham, Michael P.; Zuo, XN (reprint author), 4A Datun Rd, Beijing 100101, Peoples R China.
2013
发表期刊NEUROIMAGE
ISSN1053-8119
文章类型期刊论文
卷号65页码:374-386
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摘要While researchers have extensively characterized functional connectivity between brain regions, the characterization of functional homogeneity within a region of the brain connectome is in early stages of development. Several functional homogeneity measures were proposed previously, among which regional homogeneity (ReHo) was most widely used as a measure to characterize functional homogeneity of resting state fMRI (R-fMRI) signals within a small region (Zang et al., 2004). Despite a burgeoning literature on ReHo in the field of neuroimaging brain disorders, its test-retest (TRT) reliability remains unestablished. Using two sets of public R-fMRI TRT data, we systematically evaluated the ReHo's TRT reliability and further investigated the various factors influencing its reliability and found: 1) nuisance (head motion, white matter, and cerebrospinal fluid) correction of R-fMRI time series can significantly improve the TRT reliability of ReHo while additional removal of global brain signal reduces its reliability, 2) spatial smoothing of R-fMRI time series artificially enhances ReHo intensity and influences its reliability, 3) surface-based R-fMRI computation largely improves the TRT reliability of ReHo, 4) a scan duration of 5 min can achieve reliable estimates of ReHo, and 5) fast sampling rates of R-fMRI dramatically increase the reliability of ReHo. Inspired by these findings and seeking a highly reliable approach to exploratory analysis of the human functional connectome, we established an R-fMRI pipeline to conduct ReHo computations in both 3-dimensions (volume) and 2-dimensions (surface). (C) 2012 Elsevier Inc. All rights reserved.
关键词Connectome Test-retest Reliability Functional homogeneity Default network
学科领域Cognitive Neuroscience
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收录类别SCI
语种英语
项目资助者National Natural Science Foundation of China [81220108014, 81171409, 81030028] ; Open Research Fund of the Key Laboratory of Behavioral Science ; Startup Foundation for Distinguished Research Professor of the Institute of Psychology, Chinese Academy of Sciences [Y0CX492S03] ; NIMH [R01MH083246]
项目简介This work was partially supported by the National Natural Science Foundation of China (81220108014, 81171409, 81030028) the Open Research Fund of the Key Laboratory of Behavioral Science and the Startup Foundation for Distinguished Research Professor (Y0CX492S03) of the Institute of Psychology, Chinese Academy of Sciences as well as R01MH083246 from NIMH. We thank Caitlin Hinz and Ting-Ting Cheng for their contribution of language editing, and Qing-Yang Li for his coordination of the fast imaging data. We also thank Dr. Chao-Gan Yan for valuable discussions on headmotion and Dr. Thomas Yea for his insightful guidance on surface data processing and quality control.
WOS记录号WOS:000312283900034
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被引频次:193[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
条目标识符http://ir.psych.ac.cn/handle/311026/10675
专题中国科学院行为科学重点实验室
通讯作者Zuo, XN (reprint author), 4A Datun Rd, Beijing 100101, Peoples R China.
作者单位Zuo, XN (reprint author), 4A Datun Rd, Beijing 100101, Peoples R China.
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Zuo, Xi-Nian,Xu, Ting,Jiang, Lili,et al. Toward reliable characterization of functional homogeneity in the human brain: Preprocessing, scan duration, imaging resolution and computational space[J]. NEUROIMAGE,2013,65:374-386.
APA Zuo, Xi-Nian.,Xu, Ting.,Jiang, Lili.,Yang, Zhi.,Cao, Xiao-Yan.,...&Zuo, XN .(2013).Toward reliable characterization of functional homogeneity in the human brain: Preprocessing, scan duration, imaging resolution and computational space.NEUROIMAGE,65,374-386.
MLA Zuo, Xi-Nian,et al."Toward reliable characterization of functional homogeneity in the human brain: Preprocessing, scan duration, imaging resolution and computational space".NEUROIMAGE 65(2013):374-386.
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