A method for removal of global effects from fMRI time series
A method for removal of global effects from fMRI time series
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DOI：
10.1016/j.neuroimage.2003.12.042
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发表时间：
2004-05-01
期刊：
影响因子：
5.7
通讯作者：
Harper, RM
中科院分区：
文献类型：
--
作者：
Macey, PM;Macey, KE;Harper, RM
我们提出了一种从功能磁共振成像（fMRI）图像中去除全局效应的技术，使用全局信号（LMGS）的体素级线性模型。该程序不假设低频的整体效应，而是基于整体信号（每体积平均强度的时间过程）在整个大脑中以相同的模式复制的假设，尽管不一定是相同的量级。第二个假设是，所有与全局信号匹配的效应都无关紧要，可以删除。该方法包括将每个体素的时间过程建模为全局信号，并从体素的时间过程中去除任何这样的全局分量。在144秒24扫描fMRI过程中，对14名受试者进行了激发性高碳酸血症（5% CO2/95% O-2）的挑战，引发了全球血氧水平依赖性（BOLD）信号的巨大变化；还收集了基线系列。将该方法应用于这些数据，并与强度归一化和低频样条去趋势进行了比较。对于高碳酸血症的挑战，出现了一个大的全球BOLD信号增加。由于区域差异，强度归一化无法去除全局分量。LMGS和样条去趋势都能有效地去除低频分量，但与样条去趋势不同（样条去趋势的设计目的是去除低频趋势），LMGS在整个挑战和基线系列中去除了高频的全球波动。LMGS消除了与全局信号相关的所有影响，对于包含大全局影响的fMRI数据和生成用于后续兴趣体积（VOI）分析的去趋势图像尤其有用。(C) 2004爱思唯尔公司版权所有。
We present a technique for removing global effects from functional magnetic resonance imaging (fMRI) images, using a voxel-level linear model of the global signal (LMGS). The procedure does not assume low-frequency global effects and is based on the assumption that the global signal (the time course of the average intensity per volume) is replicated in the same pattern throughout the brain, although not necessarily at the same magnitude. A second assumption is that all effects that match the global signal are of no interest and can be removed. The method involves modeling the time course of each voxel to the global signal and removing any such global component from the voxel's time course. A challenge that elicits a large change in the global blood oxygenation level-dependent (BOLD) signal, inspired hypercapnia (5% CO2/95% O-2), was administered to 14 subjects during a 144-s, 24-scan fMRI procedure; baseline series were also collected. The method was applied to these data and compared to intensity normalization and low-frequency spline detrending. A large global BOLD signal increase emerged to the hypercapnic challenge. Intensity normalization failed to remove global components due to regional variability. Both LMGS and spline detrending effectively removed low-frequency components, but unlike spline detrending (which is designed to remove only low frequency trends), the LMGS removed higher-frequency global fluctuations throughout the challenge and baseline series. LMGS removes all effects correlated with the global signal, and may be especially useful for fMRI data that include large global effects and for generating detrended images to use with subsequent volume-of-interest (VOI) analyses. (C) 2004 Elsevier Inc. All rights reserved.