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Recent advances in non-linear computational and dynamical modelling have opened up the possibility to parametrize dynamic neural mechanisms that drive complex behavior. Importantly, building models of neuronal processes is of key importance to fully understand disorders of the brain as it may provide a quantitative platform that is capable of binding multiple neurophysiological processes to phenotype profiles. In this study, we apply a newly developed adaptive frequency-based model of whole-brain oscillations to resting-state fMRI data