Meta-analysis of neuroimaging data.
Meta-analysis of neuroimaging data.
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DOI：
10.1002/wcs.41
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发表时间：
2010-03
影响因子：
3.9
通讯作者：
Wager, Tor D.
中科院分区：
文献类型：
--
作者：
Kober, Hedy;Wager, Tor D.
随着研究心理现象的神经影像学研究数量的增加，整合研究中积累的知识变得越来越困难。荟萃分析的目的是服务于这一目的，因为它们不仅允许跨研究，而且还允许跨实验室和任务变量的结果的合成。元分析特别适合回答有关大脑区域或网络是否始终与特定心理领域相关的问题，包括工作记忆等广泛类别或更具体的类别，如条件恐惧。元分析还可以解决特异性问题，即区域或网络的激活是否是特定心理领域所独有的，或者是多种类型任务的特征。这篇综述讨论了几种技术，已被用来测试的一致性和特异性，在已发表的神经影像学数据，包括核密度分析（KDA），激活似然估计（ALE），和最近开发的多级核密度分析（MKDA）。我们讨论这些技术在该领域的当前和未来的方向。
As the number of neuroimaging studies that investigate psychological phenomena grows, it becomes increasingly difficult to integrate the knowledge that has accrued across studies. Meta-analyses are designed to serve this purpose, as they allow the synthesis of findings not only across studies but also across laboratories and task variants. Meta-analyses are uniquely suited to answer questions about whether brain regions or networks are consistently associated with particular psychological domains, including broad categories such as working memory or more specific categories such as conditioned fear. Meta-analysis can also address questions of specificity, which pertains to whether activation of regions or networks is unique to a particular psychological domain, or is a feature of multiple types of tasks. This review discusses several techniques that have been used to test consistency and specificity in published neuroimaging data, including the kernel density analysis (KDA), activation likelihood estimate (ALE), and the recently developed multilevel kernel density analysis (MKDA). We discuss these techniques in light of current and future directions in the field.
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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：
Turkeltaub, PE;Eden, GF;Zeffiro, TA
通讯作者：
Zeffiro, TA
影响因子：
5.7
作者：
Genovese, CR;Lazar, NA;Nichols, T
通讯作者：
Nichols, T
DOI：
10.1016/0197-2456(86)90046-2
发表时间：
1986-09-01
期刊：
CONTROLLED CLINICAL TRIALS
影响因子：
--
作者：
DERSIMONIAN, R;LAIRD, N
通讯作者：
LAIRD, N
影响因子：
2.9
作者：
Nee, Derek Evan;Wager, Tor D.;Jonides, John
通讯作者：
Jonides, John