Distinct neural oscillations predict covert switching between stable and unstable cognitive representations

Cognitive flexibility is the ability to keep or update contextual cognitive representations. The underlying neural mechanisms and how it is influenced by individual sensitivity to feedback are not known. We measured cognitive flexibility under uncertainty with the Wisconsin Card Sorting Task and brain activity with magnetoencephalography (MEG). Using a behavioral sequential learning model, we show that variability in cognitive flexibility is predicted by individual reward and punishment sensitivity to feedback and anticipation and exploration tendencies. Uncovering their brain oscillatory signatures showed that individual learning speed is predicted by suppressed alpha-beta (7–32 Hz) and increased broad-band gamma (52–96 Hz) amplitudes along with concurrent large-scale alpha (7–13 Hz) desynchronization. Importantly, these oscillatory sub-processes were explained by individual levels of distinct feedback sensitivities. These results provide a novel account on neural sub-computations underlying flexible contextual switching between stable and unstable cognitive representations that predict the individual speed of rule learning.