In short, the statistic is a basic t-stat. The process to produce it is quite involved - we're using a newer method called "lesion network mapping". Starting with a set of lesion masks and a functional connectome with resting state data, each of the lesion masks are entered as the ROI in each of the functional images, producing that many stat maps with correlation coefficients. These are aggregated with a t-test for each subject in the lesion dataset. Then we use a software called PALM (https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/PALM) to do the rest - fitting a general linear model at each voxel with the t-stat as the independent variable used to predict the subject's score on some test, which produces a regression coefficient map. Then it performs permutation analysis to test each of those values for significance, which is what gives us the ultimate t-statistic as the final output. I should note here that it also gives us p-values, both corrected and uncorrected, as separate files.
Hope this answers your question,
--john
