Higher brain function relies upon the ability to flexibly integrate information across specialized communities of brain regions; however, it is unclear how this mechanism manifests over time. In this study, we used time-resolved network analysis of fMRI data to demonstrate that the human brain traverses between functional states that maximize either segregation into tight-knit communities or integration across otherwise disparate neural regions. Integrated states enable faster and more accurate performance on a cognitive task, and are associated with dilations in pupil diameter, suggesting that ascending neuromodulatory systems may govern the transition between these alternative modes of brain function. Together, our results confirm a direct link between cognitive performance and the dynamic reorganization of the network structure of the brain. •The human brain network traverses segregated and integrated states over time•Integrated states enable fast, effective performance on an N-back task•Integrated states track with fluctuations in pupil diameter•Cognitive performance relates to the dynamic reorganization of brain architecture Shine et al. use dynamic analyses of fMRI data to demonstrate that the network architecture of the human brain fluctuates between states of high and low global integration that track with effective task performance and may relate to fluctuations in arousal.