Abstract: It has a positive effect on the research of brain function to introduce the concept of network into neuroscience. However, in the real application the brain network with complex characteristics makes it hard to understand. In this paper, based on the functional connectivity patterns estimated by the Directed Transfer Function (DTF) methods, flow gain is proposed to assess the role of the specific brain region involved in the information transmission process. Integrating input and output information simultaneously, flow gain simplifies the identification of complex networks, as well as improves the display scale of the results. Both the simulation and spontaneous, evoked ElectroEncephaloGram (EEG) data indicate that flow gain can describe the output intensity of specific region to the whole brain. The results prove that with the definition of flow gain, it is possible to further the understanding of brain cognitive mechanism.