Mathematical principles of SPM and its applications to the functional neuroimages

Huanwen Tang, Lili Pan, Yiyuan Tang

Research output: Contribution to journalArticlepeer-review

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.

Original languageEnglish
Pages (from-to)223-231
Number of pages9
JournalYingyong Jichu yu Gongcheng Kexue Xuebao/Journal of Basic Science and Engineering
Volume13
Issue number3
StatePublished - Sep 2005

Keywords

  • Functional magnetic resonance imaging (fMRI)
  • General linear models
  • Regression analysis
  • SPM

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