Aming Li

This paper introduces compressive learning, a framework that uses higher-order network structure to improve human knowledge acquisition by embedding node-degree inhomogeneity into pre-learning trajectories.

The paper investigates memory effects in ecological systems, showing they enhance stability and short-term recovery but delay full restoration.

The paper shows that 10-Hz repetitive visual stimulation enhances wakeful consolidation of visual learning, while 1-Hz RVS impairs it, suggesting a role for alpha entrainment and LTP-like plasticity.