Sift - Statistical Parametric Mapping

Statistical Parametric Mapping (SPM) is a method to create "Maps" of arbitrary statistical tests, which can be applied across the entirety of a continuous curve. These maps exist in the same n-dimensional space as their underlying data, which allows for the results to be more interpret-able, as well as removing bias relating to selecting summary statistics like maximums, minimums or averages. Using random-field-theory, the inherent dependence between the parameters on these maps can be accounted for when determining how statistically relevant the results of a map are.