Author Summary This study demonstrates that sensorimotor behavior can be accurately predicted from single-trial EEG oscillations that exhibit coordinated fluctuations across various brain regions, frequency bands, and movement time epochs. We introduce high-dimensional oscillatory portraits to capture the relationships among basic oscillatory elements, quantifying oscillations at specific frequencies and times during individual trials. Our findings indicate that the overall structure of these interdependence networks, or effective connectivity, remains stable across different task conditions, showcasing an intrinsic coordination architecture that adapts to task constraints through subtle topological changes. Additionally, fluctuations in single-trial oscillatory portraits can predict variations in movement kinematics, with movement accuracy reflecting the oscillatory architecture’s ability to adapt in response to movement errors.