4.7 Article

Comparing connectomes across subjects and populations at different scales

期刊

NEUROIMAGE
卷 80, 期 -, 页码 416-425

出版社

ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.neuroimage.2013.04.084

关键词

Brain connectivity; Magnetic resonance imaging (MRI); Diffusion imaging; Multiple testing; Multiple comparisons; Bonferroni; Family-wise error rate (FWER); False discovery rate FDR; Graph theory

资金

  1. FNS [200020_14467, 320030_130090]
  2. Leenaards Foundation
  3. Swiss National Science Foundation (SNF) [320030_130090] Funding Source: Swiss National Science Foundation (SNF)

向作者/读者索取更多资源

Brain connectivity can be represented by a network that enables the comparison of the different patterns of structural and functional connectivity among individuals. In the literature, two levels of statistical analysis have been considered in comparing brain connectivity across groups and subjects: 1) the global comparison where a single measure that summarizes the information of each brain is used in a statistical test; 2) the local analysis where a single test is performed either for each node/connection which implies a multiplicity correction, or for each group of nodes/connections where each subset is summarized by one single test in order to reduce the number of tests to avoid a penalizing multiplicity correction. We comment on the different levels of analysis and present some methods that have been proposed at each scale. We highlight as well the possible factors that could influence the statistical results and the questions that have to be addressed in such an analysis. (C) 2013 Elsevier Inc. All rights reserved.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.7
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据