Skill learning is the improvement in perceptual, cognitive, or motor performance following practice. Expert performance levels can be achieved with well-organized knowledge, using sophisticated and specific mental representations and cognitive processing, applying automatic sequences quickly and efficiently, being able to deal with large amounts of information, and many other challenging task demands and situations that otherwise paralyze the performance of novices. The neural reorganizations that occur with expertise reflect the optimization of the neurocognitive resources to deal with the complex computational load needed to achieve peak performance. As such, capitalizing on neuronal plasticity, brain modifications take place over time-practice and during the consolidation process. One major challenge is to investigate the neural substrates and cognitive mechanisms engaged in expertise, and to define "expertise" from its neural and cognitive underpinnings. Recent insights showed that many brain structures are recruited during task performance, but only activity in regions related to domain-specific knowledge distinguishes experts from novices. The present review focuses on three expertise domains placed across a motor to mental gradient of skill learning: sequential motor skill, mental simulation of the movement (motor imagery), and meditation as a paradigmatic example of "pure" mental training. We first describe results on each specific domain from the initial skill acquisition to expert performance, including recent results on the corresponding underlying neural mechanisms. We then discuss differences and similarities between these domains with the aim to identify the highlights of the neurocognitive processes underpinning expertise, and conclude with suggestions for future research.

BackgroundDuring non-rapid eye movement (NREM) sleep synchronous neural oscillations between neural silence (down state) and neural activity (up state) occur. Sleep Slow Oscillations (SSOs) events are their EEG correlates. Each event has an origin site and propagates sweeping the scalp. While recent findings suggest a SSO key role in memory consolidation processes, the structure and the propagation of individual SSO events, as well as their modulation by sleep stages and cortical areas have not been well characterized so far.Methodology/Principal FindingsWe detected SSO events in EEG recordings and we defined and measured a set of features corresponding to both wave shapes and event propagations. We found that a typical SSO shape has a transition to down state, which is steeper than the following transition from down to up state. We show that during SWS SSOs are larger and more locally synchronized, but less likely to propagate across the cortex, compared to NREM stage 2. Also, the detection number of SSOs as well as their amplitudes and slopes, are greatest in the frontal regions. Although derived from a small sample, this characterization provides a preliminary reference about SSO activity in healthy subjects for 32-channel sleep recordings.Conclusions/SignificanceThis work gives a quantitative picture of spontaneous SSO activity during NREM sleep: we unveil how SSO features are modulated by sleep stage, site of origin and detection location of the waves. Our measures on SSOs shape indicate that, as in animal models, onsets of silent states are more synchronized than those of neural firing. The differences between sleep stages could be related to the reduction of arousal system activity and to the breakdown of functional connectivity. The frontal SSO prevalence could be related to a greater homeostatic need of the heteromodal association cortices.

Sleep is known to contribute to motor memory consolidation. Recent studies have provided evidence that a night of sleep plays a similar functional role following motor imagery (MI), while the simple passage of time does not result in performance gains. Here, we examined the benefits of a daytime nap on motor memory consolidation after MI practice. Participants were trained by MI on an explicitly known sequence of finger movements at 11:00. Half of the participants were then subjected (at 14:00) to either a short nap (10 min of stage 2 sleep) or a long nap (60-90 min, including slow wave sleep and rapid eye movement sleep). We also collected data from both quiet and active rest control groups. All participants remained in the lab until being retested at 16:00. The data revealed that a daytime nap after imagery practice improved motor performance and, therefore, facilitated motor memory consolidation, as compared with spending a similar time interval in the wake state. Interestingly, the results revealed that both short and long naps resulted in similar delayed performance gains. The data might also suggest that the presence of slow wave and rapid eye movement sleep does not provide additional benefits for the sleep-dependent motor skill consolidation following MI practice.