Activation likelihood estimation meta-analysis revisited.
Activation likelihood estimation meta-analysis revisited.
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DOI：
10.1016/j.neuroimage.2011.09.017
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发表时间：
2012-02-01
期刊：
影响因子：
5.7
通讯作者：
Fox, Peter T.
中科院分区：
文献类型：
--
作者：
Eickhoff, Simon B.;Bzdok, Danilo;Laird, Angela R.;Kurth, Florian;Fox, Peter T.
神经影像学数据的基于坐标的元分析的一个广泛使用的技术是激活似然估计（ALE），它确定从不同的实验报告的焦点的收敛。ALE分析涉及将这些病灶建模为概率分布，其宽度基于对由于神经成像数据的受试者间和模板间变异性而引起的空间不确定性的经验估计。ALE结果是根据实验之间随机空间关联的零分布进行评估的，从而导致随机效应推断。在本修订本算法中，我们解决了两个遗留的缺点，以前的算法。首先，实验之间的空间关联的评估是基于一个非常耗时的排列检验，但这带来了低估零分布的右尾的危险。在本报告中，我们概述了如何用更快，更精确的分析方法取代以前的方法。第二，以前应用的校正程序，即控制错误发现率（FDR），补充了新的方法，用于校正的家庭明智的错误率和集群级别的意义。不同的替代品绘制推理的元分析结果进行评估的一个示例性的数据集上的人脸感知，以及讨论他们的方法的局限性和优势。总之，我们因此用零分布的更快和更严格的解析解取代了先前的置换算法，并全面解决了多重比较校正的问题。ALE算法的拟议修订应提供一种改进的工具，用于对功能成像数据进行基于坐标的荟萃分析。
A widely used technique for coordinate-based meta-analysis of neuroimaging data is activation likelihood estimation (ALE), which determines the convergence of foci reported from different experiments. ALE analysis involves modelling these foci as probability distributions whose width is based on empirical estimates of the spatial uncertainty due to the between-subject and between-template variability of neuroimaging data. ALE results are assessed against a null-distribution of random spatial association between experiments, resulting in random-effects inference. In the present revision of this algorithm, we address two remaining drawbacks of the previous algorithm. First, the assessment of spatial association between experiments was based on a highly time-consuming permutation test, which nevertheless entailed the danger of underestimating the right tail of the null-distribution. In this report, we outline how this previous approach may be replaced by a faster and more precise analytical method. Second, the previously applied correction procedure, i.e. controlling the false discovery rate (FDR), is supplemented by new approaches for correcting the family-wise error rate and the cluster-level significance. The different alternatives for drawing inference on meta-analytic results are evaluated on an exemplary dataset on face perception as well as discussed with respect to their methodological limitations and advantages. In summary, we thus replaced the previous permutation algorithm with a faster and more rigorous analytical solution for the null-distribution and comprehensively address the issue of multiple-comparison corrections. The proposed revision of the ALE-algorithm should provide an improved tool for conducting coordinate-based meta-analyses on functional imaging data.
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影响因子：
4.8
作者：
Eickhoff, Simon B.;Laird, Angela R.;Grefkes, Christian;Wang, Ling E.;Zilles, Karl;Fox, Peter T.
通讯作者：
Fox, Peter T.
影响因子：
5.7
作者：
Genovese, CR;Lazar, NA;Nichols, T
通讯作者：
Nichols, T
DOI：
10.1523/jneurosci.4004-09.2009
发表时间：
2009-11-18
期刊：
The Journal of neuroscience : the official journal of the Society for Neuroscience
影响因子：
--
作者：
Laird AR;Eickhoff SB;Li K;Robin DA;Glahn DC;Fox PT
通讯作者：
Fox PT
DOI：
10.1111/j.2517-6161.1995.tb02031.x
发表时间：
1995-01-01
影响因子：
5.8
作者：
BENJAMINI, Y;HOCHBERG, Y
通讯作者：
HOCHBERG, Y
影响因子：
5.7
作者：
Britton, Jennifer C.;Taylor, Stephan F.;Liberzon, Israel
通讯作者：
Liberzon, Israel