%0 Journal Article %A Jukka-Pekka Kauppi %A Juha Pajula %A Jari Niemi %A Riitta Hari %A Jussi Tohka %T Functional brain segmentation using inter-subject correlation in fMRI %D 2016 %R 10.1101/057620 %J bioRxiv %P 057620 %X For a long time, neuroscientists have studied the human brain functionsunder an assumption that brain mechanisms are similar across a group of subjects under study. In real life, however, individuals process informationmore or less differently. To facilitate understanding of complex, natural processing of the brain, we present an exploratory data analysis approach called functional segmentation inter-subject correlation analysis (FuSeISC). The method provides a new type of functional segmentation of the brain characterizing not only brain areas with similar processing across subjects but also areas in which processing across subjects is different. We tested FuSeISC using functional magnetic resonance imaging (fMRI) data sets collected during traditional block-design stimuli (37 subjects) as well as naturalistic auditory narrative stimuli (19 subjects). The method identified spatially coherent clusters in various cortical areas with neuroscientifically plausible interpretations. Our results suggest FuSeISC as an interesting approach for exploratory analysis of human brain fMRI. %U https://www.biorxiv.org/content/biorxiv/early/2016/06/07/057620.full.pdf