Mass Meta-Analysis in Talairach Space

Abstract

We provide a method for mass meta-analysis in a neuroinformatics database containing stereotaxic Talairach coordinates from neu- roimaging experiments. Database labels are used to group the in- dividual experiments, e.g., according to cognitive function, and the consistent pattern of the experiments within the groups are de- termined. The method voxelizes each group of experiments via a kernel density estimation, forming probability density volumes. The values in the probability density volumes are compared to null-hypothesis distributions generated by resamplings from the entire unlabeled set of experiments, and the distances to the null- hypotheses are used to sort the voxels across groups of experi- ments. This allows for mass meta-analysis, with the construction of a list with the most prominent associations between brain ar- eas and group labels. Furthermore, the method can be used for functional labeling of voxels.