Measuring in vivo dynamics can yield valuable information for studying the functioning of the cardiovascular or the musculoskeletal system and for the diagnosis of related diseases. MRI is a powerful medical imaging modality, but it shows severe limitations when dealing with motion at high spatial and temporal resolutions. In this work, a method called spectro-dynamic MRI is proposed, which can identify dynamical information directly from k-space data. It combines a measurement model, relating the measured data in k-space to the displacement fields, and a dynamical model, introducing prior knowledge about the dynamics of a system. The data sampling process is tailored to compute spatial and temporal derivatives in the spectral domain at a high temporal resolution. Preliminary results from four simple pendulum setups for which the dynamics are explicitly known show that spectro-dynamic MRI can estimate motion fields from heavily undersampled data on a millisecond timescale. Furthermore, the length of the pendula and the stiffness of the spring can be identified as the dynamical system’s parameters, giving additional information about the systems under investigation.