Resting-state fMRI confounds and cleanup.
Resting-state fMRI confounds and cleanup.
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DOI：
10.1016/j.neuroimage.2013.04.001
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发表时间：
2013-10-15
期刊：
影响因子：
5.7
通讯作者：
Bandettini, Peter A.
中科院分区：
文献类型：
--
作者：
Murphy, Kevin;Birn, Rasmus M.;Bandettini, Peter A.
关键词：
静息态功能性磁共振成像（FMRI）的目的是通过使用“静息”时大脑不同区域中血氧水平依赖（BOLD）信号之间的时间相似性作为同步神经活动的指标来研究大脑的功能连接。由于这种测量依赖于大脑不同部分之间的功能磁共振成像信号变化的时间相关性，任何影响信号的非神经活动相关过程都会影响功能连接的测量，从而产生虚假的结果。为了了解这些静息态FMRI混淆的来源，本文从MR物理学和脑生理学的角度描述了BOLD信号的起源。潜在的混淆所产生的运动，心脏和呼吸周期，动脉CO2浓度，血压/脑自动调节，血管运动进行了讨论。两类技术，以消除混乱的休息状态BOLD时间序列：1）那些利用外部记录的生理和2）基于数据的清理方法，只使用休息状态的功能磁共振成像数据本身。还讨论了在组水平上从功能连接性测量中去除噪声的进一步方法。为了成功地解释静息状态的功能磁共振成像的比较和结果，噪声清除是一个经常被忽视，但在分析管道中的重要步骤。
The goal of resting-state functional magnetic resonance imaging (FMRI) is to investigate the brain’s functional connections by using the temporal similarity between blood oxygenation level dependent (BOLD) signals in different regions of the brain “at rest” as an indicator of synchronous neural activity. Since this measure relies on the temporal correlation of FMRI signal changes between different parts of the brain, any non-neural activity-related process that affects the signals will influence the measure of functional connectivity, yielding spurious results. To understand the sources of these resting-state FMRI confounds, this article describes the origins of the BOLD signal in terms of MR physics and cerebral physiology. Potential confounds arising from motion, cardiac and respiratory cycles, arterial CO2 concentration, blood pressure/cerebral autoregulation, and vasomotion are discussed. Two classes of techniques to remove confounds from resting-state BOLD time series are reviewed: 1) those utilising external recordings of physiology and 2) data-based cleanup methods that only use the resting-state FMRI data itself. Further methods that remove noise from functional connectivity measures at a group level are also discussed. For successful interpretation of resting-state FMRI comparisons and results, noise cleanup is an often over-looked but essential step in the analysis pipeline.
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影响因子：
2.5
作者：
Bianciardi, Marta;Fukunaga, Masaki;van Gelderen, Peter;Horovitz, Silvina G.;de Zwart, Jacco A.;Shmueli, Karin;Duyn, Jeff H.
通讯作者：
Duyn, Jeff H.
影响因子：
3.3
作者：
BANDETTINI, PA;JESMANOWICZ, A;HYDE, JS
通讯作者：
HYDE, JS
DOI：
10.1098/rstb.2005.1634
发表时间：
2005-05-29
影响因子：
6.3
作者：
Beckmann, CF;DeLuca, M;Smith, SM
通讯作者：
Smith, SM
影响因子：
5.7
作者：
Beall, Erik B.;Lowe, Mark J.
通讯作者：
Lowe, Mark J.
影响因子：
56.9
作者：
AKSELROD, S;GORDON, D;COHEN, RJ
通讯作者：
COHEN, RJ