Before revision:  We found that the temporal statistics of UP and DOWN states is robustly different in natural slow-wave sleep compared to the slow-waves of anesthesia. Computational models predict that an interplay between noise and spike-frequency adaptation can yield a transition from sleep-like to anesthesia-like slow-wave dynamics.
After revision:  We found that the temporal statistics of UP and DOWN states is robustly different in natural slow-wave events. The first type of slow waves is seen during sleep, while the second type prevails in anesthetized states. Network models of spiking neurons predict that the two slow wave types emerge due to a different gain on inhibitory vs excitatory cells and that different levels of spike-frequency adaptation can yield a transition from sleep-like to anesthesia-like slow-wave dynamics.