We describe the use of anatomically informed basis functions (AIBF) in the analysis of multisubject functional imaging studies. AIBF are used to specify an anatomically informed spatial model that embodies anatomical knowledge for the statistical analysis of neuroimaging data. In a previous communication, we showed how AIBF can be used to incorporate prior anatomical constraints in single subject functional magnetic resonance image (fMRI) analyses to augment their anatomical precision. In this paper, we extend AIBF such that it can be applied to multisubject studies using fMRI or PET. The key concept is that, after spatial normalization, a canonical cortical surface can be used to generate a forward model of signal sources for all subjects. By estimating the hemodynamic signal in this canonical AIBF-space and then projecting it back into the voxel-space, one effectively extracts functional activity that is smooth, within and only within, the cortical sheet while attenuating other components unrelated to the physiological process of interest. The ensuing procedure can be considered as a highly non-stationary, anisotropic anatomically informed [de]convolution or smoothing. It is shown that this procedure offers various advantages compared to existing conventional methods for the analysis of multisubject studies, in particular it is more sensitive to underlying activations.
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