Introduction. Recent studies have shown that, following brain injury, sleep-like cortical dynamics intrude into wakefulness, potentially contributing to brain network disruption and behavioral deficits. Aim. We employ TMS in combination with EEG to detect these dynamics and assess their impact on brain networks and clinical evolution in awake stroke patients. Methods. Twelve patients with subacute unilateral ischemic cortical stroke underwent a longitudinal study with two assessments (t0 and t1), including clinical evaluation using the National Institutes of Health Stroke Scale (NIHSS) and TMS-EEG recordings targeting perilesional and contralesional cortical sites. Parameters such as slow wave amplitude (SWa), high-frequency power (HFp) suppression, and the Perturbational Complexity Index-state transition (PCIst) were analyzed to quantify sleep-like cortical dynamics and their network-level consequences. Results. Results demonstrated a significant clinical improvement (NIHSS score: 7.16 +/- 0.73 at t0, 4.33 +/- 0.74 at t1; W=78, P<0.001). Perilesional SWa and HFp suppression decreased significantly at t1 compared to t0 (T(11)=3.05, P=0.01 and T(11)=-3.39, P<0.01, respectively), along with recovery of PCIst values (T(11)=-2.35, P=0.04). Importantly, both the dissipation of sleep-like perilesional cortical dynamics and the recovery of network-level interactions correlated with patients' clinical improvement (Spearman rho=0.62, P=0.03; rho=-0.68, P=0.01, respectively). Conclusion. These findings underscore the potential of TMS-EEG as an objective measure of neurological evolution and suggest targeting sleep-like cortical dynamics as a viable strategy for post-stroke neuromodulation and rehabilitation.