基于随机场理论的p值：SPM实现综述
摘要：P-values and null-hypothesis significance testing are popular data-analytical tools in functional neuroimaging. Sparked by the analysis of resting-state fMRI data, there has been a resurgence of interest in the validity of some of the p-values evaluated with the widely used software SPM in recent years. The default parametric p-values reported in SPM are based on the application of results from random field theory to statistical parametric maps, a framework commonly referred to as RFT. While RFT was established two decades ago and has since been applied in a plethora of fMRI studies, there does not exist a unified documentation of the mathematical and computational underpinnings of RFT as implemented in current versions of SPM. Here, we provide such a documentation with the aim of contributing to contemporary efforts towards higher levels of computational transparency in functional neuroimaging.
作者：Dirk Ostwald, Sebastian Schneider, Rasmus Bruckner, Lilla Horvath
论文ID：1808.04075
分类：Quantitative Methods
分类简称：q-bio.QM
提交时间：2021-08-10