This article argues that the distributed semantic processing system in the human brain can be explored through individual
typological differences, based on the dataset of the 2008 Science article by Mitchell et al. on computational
neurolinguistics. The crucial finding is that both modality specific and supramodal semantic areas, which have raised
critical issues in neuro cognitive semantics and its metaanalysis,
could be extracted from a subgroup of subjects exhibiting mediocre precision by using different feature selection methods (ANOVA and Stability). This result might
create new possibilities for human neuroscience by
interlocking a single-subject analysis with methods for evaluation of individual variability and fMRI meta-analysis with collective data sources associated with various types of external knowledge system.