StatBrainz contains Matlab code to perform statistical inference and visualization of brain imaging data. This includes functions to perform resampling and multiple testing. In particular methods for clustersize inference (including associated TDP bounds), and both single and simultaneous CoPE (coverage of probability sets) are provided. The package also provides code for reading and visualizing volumetric and surface brain imaging data. Detailed tutorials exploring these features are provided.


This package contains python code to perform inference in multivariable linear and generalized linear models using permutation and the bootstrap. In particular it provides post-hoc inference for multiple testing methods when considering multiple contrasts.


The RFTtoolbox contains Matlab code to perform voxelwise RFT analysis, LKC estimation, generation of convolution fields, perform Gaussizianization to improve Gaussianity, provide confidence regions for the location of peaks of random fields and many other features. These can be used to perform multiple testing and general study of multi-dimensional imaging data. Tutorials exploring these features are provided.

SIbootstrap: Correcting for circular inference

A toolbox to correct for circular inference aka voodoo correlations in neuroimaging data using resampling techniques.