【作者】 唐焕文； 潘丽丽； 唐一源；

【Author】 TANG Huan-wen , PAN Li-li, TANG Yi-yuan ( Department of Applied Mathematics, Dalian University, Dalian 116023,China; institute of Neuroinformatics, Dalian University of Technology, Liaoning, Dalian 116023, China; Laboratory of Visual Information Processing, the Chinese Academy of Sciences, Beijing 100101, China)

【机构】 大连理工大学应用数学系； 大连理工大学神经信息学研究所；

【摘要】 SPM(Statistical Parametric Mapping)方法是一种为检验人脑中特定的脑区效应而构建空间延展的统计过程的方法;SPM是利用SPM方法分析脑成像数据的软件包,主要用于大脑反应的功能定位,是刻画脑病变和功能解剖的最常用的工具。本文探讨SPM的数学基础,给出了,SPM中利用一般线性模型(General Linear Model,GLM)构建统计参数图的方法;为了适应处理功能磁共振成像(functional Magnetic Resonance Imaging,fMRI)数据的需要,对一般线性模型做了扩展,推导出扩展的GLM的检验统计量和自由度。最后将扩展的一股线性模型应用于一个具体的fMRI实验,说明了方法的有效性。更多还原

【Abstract】 SPM (Statistical Parametric Mapping) method refers to the construction and assessment of spatially extended statistical process used to test hypotheses about specific cerebral area effects. SPM, which is the software for analysis of neruoimage data, is generally used to identify functional specialized brain responses and is the most prevalent approach to characterizing functional anatomy and disease-related changes. In this essay, the mathematical principles of SPM are discussed and the method that constructed statistical parametric maps using general linear model is given. To accommodate fMRI (functional Magnetic Resonance Imaging) data analysis, we extend GLM and induce the test statistics and degree of freedom. At last, the extended GLM is applied to a real fMRI experiment, which shows that the method is effective.更多还原