SPM5 uses priors with a Bayes rule to combine the likelihood for belonging to a tissue class and the prior probability derived from prior probability maps. However, the use of priors might cause problems for brains deviating from a healthy, adult control population. The ICBM priors in SPM5 are based on brains of subjects with an mean age of 25 years. Thus, brains of children or or elderly subjects will deviate from the tissue probabilities of the ICBM priors and will bias the segmentation. This options avoids the dependency on tissue priors and usually increases classification accuracy. Segmented images show clearer delineation particularly in the basal ganglia and in the sulci and this is the prefered option for most images. If no priors are used the segmented images are indicated by an “p” instead of “c”.
Keep in mind that even if you are using this option tissue priors are always used to register your images to MNI space. Only the bayesian rule to combine priors with tissue type probabilities will be omitted. Thus, for some cases the use of customized templates might utilize the spatial registration (e.g. infants).
However, there are some cases (e.g. large atrophy), where this option fails and gray matter distribution might be underestimated. You will notice these cases by a very thin gray matter ribbon and overestimated CSF. If this happens the default SPM5 tissue priors (or own priors) should be used.
Example of an infant brain
Comparison with default segmentation