3dttest++ now can analyze a single dataset and compare it to a collection of reference datasets. The result is a t-statistic in each voxel that measures the difference between the singleton dataset and the mean of the reference datasets, normalized by the standard deviation of the reference datasets and by a scale factor that makes the null-hypothesis distribution be the Student t. In addition, covariates can be used.

The practical details (including some math) are given in the "-help" output. The usage is to replace the "-setA" option with the new option "-singletonA datasetname". The reference datasets are from the "-setB" option.

The purpose of this feature is to allow you to explore one subject (a "patient") vs. a collection of other subjects ("normals"), and see where the "patient" is markedly different from the "normals".

Please note that the singleton dataset is assumed to be statistically independent of the reference datasets -- if you put the singleton dataset into the reference collection, then you are violating this assumption -- a different statistic would have to be computed.