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- W2885525925 abstract "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." @default.
- W2885525925 created "2018-08-22" @default.
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- W2885525925 date "2018-07-31" @default.
- W2885525925 modified "2023-09-27" @default.
- W2885525925 title "Random field theory-based p-values: A review of the SPM implementation" @default.
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- W2885525925 doi "https://doi.org/10.17605/osf.io/3dx9w" @default.
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