Combining brains: A survey of methods for statistical pooling of information
Combining brains: A survey of methods for statistical pooling of information
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DOI：
10.1006/nimg.2002.1107
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发表时间：
2002-06-01
期刊：
影响因子：
5.7
通讯作者：
Eddy, WF
中科院分区：
文献类型：
--
作者：
Lazar, NA;Luna, B;Eddy, WF
在典型的功能性脑成像实验中，扫描不止一个受试者。科学家如何最好地利用获得的数据来绘制在执行不同任务时变得活跃的大脑特定区域？很明显，我们可以通过汇集来自多个受试者的图像来获得科学和统计能力;此外，为了比较受试者组（临床患者与健康对照组，不同年龄的儿童，左撇子与右撇子，仅举几个例子），必须有一个“组图”来代表每个人群并形成统计检验的基础。虽然人们已经认识到了将图像组合在一起的重要性，但神经科学家们还没有有组织地尝试去理解解决这个问题的不同统计方法，这些方法有各种各样的优点和缺点。在本文中，我们回顾了一些流行的方法，结合信息，并展示了调查的技术样本数据集。鉴于大脑图像的组合，研究人员需要解释结果并决定激活的区域;阈值化的问题在这里是至关重要的，也是探索的。(C)2002 Eleevier Science（美国）。
More than one subject is scanned in a typical functional brain imaging experiment. How can the scientist make best use of the acquired data to map the specific areas of the brain that become active during the performance of different tasks? It is clear that we can gain both scientific and statistical power by pooling the images from multiple subjects; furthermore, for the comparison of groups of subjects (clinical patients vs healthy controls, children of different ages, left-handed people vs right-handed people, as just some examples), it is essential to have a "group map" to represent each population and to form the basis of a statistical test. While the importance of combining images for these purposes has been recognized, there has not been an organized attempt on the part of neuroscientists to understand the different statistical approaches to this problem, which have various strengths and weaknesses. In this paper we review some popular methods for combining information, and demonstrate the surveyed techniques on a sample data set. Given a combination of brain images, the researcher needs to interpret the result and decide on areas of activation; the question of thresholding is critical here and is also explored. (C) 2002 Eleevier Science (USA).