The invention discloses a brain function network modeling method for resting state synchronization EEG-fMRI, and relates to the research field of neural signal processing. The brain function network modeling method includes the steps that firstly, EEG signal preprocessing is conducted, a tape limit energy signal is extracted and a regression item is established; secondly, fMRI signal preprocessing is conducted, and a BOLD signal of each brain region is extracted; thirdly, the BOLD signal, extracted through fMRI, of each brain region and the regression item obtained from EEG are subjected to principal component analysis; fourthly, canonical correlation analysis is conducted on principal components of the two signals obtained from the last step; fifthly, modeling is conducted on a brain function network of resting state synchronization EEG-fMRI. By means of the brain function network modeling method, a plurality of the brain function networks can be obtained; the brain function networks and existing research results have high coherence so that the effectiveness of the modeling method can be proved, and thus a new thought and a scheme are provided for the resting state brain function research.