This study used signal detection theory to examine how neuroscientists identify the default mode network compared to other prominent resting-state networks. Twenty participants were asked to distinguish the default mode network from three other networks in a rapid forced-choice task, where the networks were presented at different signal thresholds. Results showed that participants more accurately identified the default mode network when it was presented at the most stringent threshold, and made the most conservative decisions when networks were not thresholded. These findings suggest that thresholding fMRI data improves accuracy in identifying brain networks.