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Reinforcement learning (RL) in humans is subserved by a network of striatal and frontal brain areas. The electrophysiological signatures of feedback evaluation are increasingly well understood, but how those signatures relate to the use of feedback to guide subsequent behavioral adjustment remains unclear. One mechanism for post-feedback behavioral optimization is the modulation of sensory processing. We used source-reconstructed MEG to test whether feedback affects the interactions between sources of oscillatory activity in the learning network and task-relevant stimulus-processing areas. Participants performed a probabilistic RL task in which they learned associations between colored faces and response buttons using trial-and-error feedback. Delta-band (2–4 Hz) and theta-band (4–8 Hz) power in multiple frontal regions were sensitive to feedback valence. Low and high beta-band power (12–20 and …