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 language | English |
|---|---|
| Pages (from-to) | 223-231 |
| Number of pages | 9 |
| Journal | Yingyong Jichu yu Gongcheng Kexue Xuebao/Journal of Basic Science and Engineering |
| Volume | 13 |
| Issue number | 3 |
| State | Published - Sep 2005 |
Keywords
- Functional magnetic resonance imaging (fMRI)
- General linear models
- Regression analysis
- SPM