Sleep renormalizes learning-perturbed cortical population dynamics to stabilize memory

Sleep is thought to stabilize newly formed memories, yet the neural reorganization through which sleep converts learning-induced plasticity burden into stable memory remains unclear. Current state-specific oscillatory markers provide limited insight into how learning reshapes population dynamics across sleep-wake states. Using spectral parameterization of high-density EEG, we show that declarative learning redistributes frontocentral waking aperiodic regimes toward flatter slopes relative to a non-learning control. These deviations are renormalized during subsequent NREM sleep toward steeper slopes with accompanying oscillatory power shifts. Spatial deviations in waking slopes reveal a region-specific coupling with NREM, dissociable from canonical oscillatory signatures. A latent neural-memory mode showed that the wake-sleep aperiodic contrast best predicted overnight accuracy changes, whereas local oscillations and aperiodic shifts defined the spatial pattern of neural variation supporting memory stabilization. Together, these findings identify sleep-dependent recalibration of learning-perturbed population dynamics as a systems-level mechanism linking homeostatic plasticity to memory consolidation.