An application of the general linear model appears in the analysis of multiple [[brain scan]]s in scientific experiments where '''{{var|Y'''}} contains data from brain scanners, '''{{var|X'''}} contains experimental design variables and confounds. It is usually tested in a univariate way (usually referred to a ''mass-univariate'' in this setting) and is often referred to as [[statistical parametric mapping]].<ref>{{Cite journal| doi = 10.1002/hbm.460020402|author1=K.J. Friston |author2=A.P. Holmes |author3=K.J. Worsley |author4=J.-B. Poline |author5=C.D. Frith |author6=R.S.J. Frackowiak | year = 1995| title = Statistical Parametric Maps in functional imaging: A general linear approach| journal = Human Brain Mapping| volume = 2| pages = 189–210| issue = 4}}</ref>
