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提高脑行为相关性分析的标准。

Improving standards in brain-behavior correlation analyses.

作者信息

Rousselet Guillaume A, Pernet Cyril R

机构信息

Centre for Cognitive Neuroimaging (CCNi), Institute of Neuroscience and Psychology, College of Medical, Veterinary and Life Sciences, University of Glasgow Glasgow, UK.

出版信息

Front Hum Neurosci. 2012 May 3;6:119. doi: 10.3389/fnhum.2012.00119. eCollection 2012.

DOI:10.3389/fnhum.2012.00119
PMID:22563313
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3342588/
Abstract

Associations between two variables, for instance between brain and behavioral measurements, are often studied using correlations, and in particular Pearson correlation. However, Pearson correlation is not robust: outliers can introduce false correlations or mask existing ones. These problems are exacerbated in brain imaging by a widespread lack of control for multiple comparisons, and several issues with data interpretations. We illustrate these important problems associated with brain-behavior correlations, drawing examples from published articles. We make several propositions to alleviate these problems.

摘要

两个变量之间的关联，例如大脑测量与行为测量之间的关联，通常使用相关性进行研究，尤其是皮尔逊相关性。然而，皮尔逊相关性并不稳健：异常值可能会引入虚假相关性或掩盖现有的相关性。在脑成像中，由于普遍缺乏对多重比较的控制以及数据解释方面的几个问题，这些问题会更加严重。我们从已发表的文章中举例说明与脑-行为相关性相关的这些重要问题。我们提出了几个建议来缓解这些问题。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f707/3342588/3cf1ab921392/fnhum-06-00119-a0005.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f707/3342588/e3354b0ac18d/fnhum-06-00119-a0002.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f707/3342588/3cf1ab921392/fnhum-06-00119-a0005.jpg

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