How does the human brain adapt to changes in the environment and store information to form memories? Decades of research has explored how information input from the environment triggers plastic changes in the brain, leading to new memory traces that have the potential to become long-term memories. My thesis asks what the optimal brain states (i.e., level of engagement with the external environment and the internal neural dynamics) are for these memory consolidation processes to occur. Sleep promotes memory consolidation (Rasch & Born, 2013), with the majority of prior studies focusing on the role of non-rapid eye movement (NREM) sleep for reducing forgetting in explicit memory contexts. Less is known about the role of rapid eye movement (REM) sleep, however, studies have shown REM may be critical for implicit or procedural learning (Cai, Mednick, Harrison, Kanady, & Mednick, 2009; Mednick, Nakayama, & Stickgold, 2003; Plihal & Born, 1997). The current thesis examines the effect of different brain states on memory consolidation, with a specific focus on visual perceptual learning. In the first two studies, I manipulated levels of sensory input from the external environment by using different wake conditions (active and quiet wake) compared with sleep, and manipulated internal neural dynamics by using different sleep conditions (naps with NREM sleep alone or NREM plus REM sleep). I tested perceptual learning of both motion direction (Study 1) and texture (Study 2) discrimination. My results show that REM sleep promotes training-induced improvements in performance (i.e., plasticity) on visual skills tasks. I hypothesize that REM sleep is the optimal brain state for this consolidation due to its unique combination of low external input coupled with neural dynamics that promote plasticity. As a secondary aim of this thesis, I explored the utility of napping beyond its use as an experimental tool by examining individual differences in nap-dependent learning. In other words, should everyone nap to boost daytime performance? I found that learning profiles after a nap are different in men and women (Study 1), and that people who regularly nap show greater magnitude of nap-dependent learning compared to people who nap infrequently (Study 3). These findings should be taken into consideration when recommending napping in operational settings.