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From Harmony to Melody: A Cross-Disciplinary Exploration of the Brain's Dynamical Repertoire. The proposed project aims at developing a methodology to identify significant transient brain states around a metastable ground state. How the brain seamlessly transitions, or "flows", from one state of network activity to another remains an open question in neuroscience. Neuroimaging studies have focused on mapping "static" representations of brain functional networks by averaging dynamical interactions between brain areas over long recording intervals, hence disregarding the importance of time. Drawing from the musical world, these static network representations are analogous to a harmony: a set of notes simultaneously played together, such as a piano chord, that produce a characteristic sound in unison. However it is not clear how the vast repertoire of the brain's possible notes and chords follow each other in a particular temporal sequence to yield the complex melody that underlies mental processes. To explore this important fundamental question, we will leverage on the recent evolution of whole-brain computational models capable of producing long time-series of simulated neural activity. We will then extend upon recent developments in graph signal processing, a technique mixing networks and dynamics, to ultimately characterize transient brain states from the simulated brain data.