Extraction of between-participants common patterns of brain activity is currently one of the most debated challenges in cognitive neuroscience. So far, by applying functional hyperalignment method [1] to functional magnetic resonance imaging (FMRI) data, relevant results have been obtained on datasets where different participants underwent the same stimulations. This challenge is however less explored when participants undergo resting state sessions: there, it is hard to characterize whether different participants experienced similar brain states. Here we propose to combine autonomic activity information with FMRI acquisitions of resting state to characterize between-participants synchrony levels and drive the extraction of functional hyperalignment transformations. We show that between participants common patterns are modulated by functionally aligning using time-segments characterized by different synchrony. We study this effect on different brain areas, showing that modulations are not homogeneous and suggesting that different brain areas carry different contributions to between-participants common patterns.