The extraction of “fingerprints'' from human brain connectivity data has become a new frontier in neuroscience. However, the time scales of human brain identifiability are still largely unexplored. In other words, what temporal features make our brains more “identifiable”? We here explore the dynamics of brain fingerprints along two complementary axes: 1) what is the optimal time scale at which brain fingerprints integrate sufficient information, 2) when best identification happens. Using dynamic identifiability, we show that the best identification emerges at longer time scales (~200s); however, short transient “bursts of identifiability'' persist even when looking at shorter functional interactions. We find that these bursts of identifiability might be strongly associated with neuronal activity. Furthermore, we report evidence that different parts of connectome fingerprints relate to different time scales: i.e., more visual-somatomotor at short temporal windows, more frontoparietal-DMN driven by increasing temporal windows. Finally, different cognitive functions appear to be meta- analytically implicated in dynamic fingerprints across different time scales. At faster time scales, human brain fingerprints are linked to multisensory stimulation, eye movements, affective processing, and visuospatial attention. At slower time scales instead, we find higher-cognitive functions, such as language and verbal semantics, awareness, declarative and working memory, social cognition. We hope that this investigation of the temporality of the human brain fingerprint will pave the way towards a better understanding of what and when makes our brains unique.