However, it should be noted that repetitive practice of adaptatio

However, it should be noted that repetitive practice of adaptation tasks could lead to performance improvements over time in the form of “savings,” expressed as faster readaptation to external perturbations relative to the initial rate of adaptation (e.g., Landi et al., 2011). Moreover, skill learning tasks, in which lasting improvements are seen over time, for instance whole-body SAHA HDAC balancing (Taubert et al., 2010), may involve an adaptation component. Motor skills are typically learned slowly over multiple training sessions until performance reaches nearly asymptotic levels. Across different experimental paradigms, skill acquisition develops (Figure 1A) initially relatively fast (i.e., rapid

improvements measured over the course of a single training session) and later more slowly, when further gains develop incrementally over multiple sessions of practice (Doyon and Benali, 2005 and Doyon and Ungerleider, 2002). Of note, the relative duration of what can be defined as fast and slow learning is highly task specific. For example, the fast stage of

learning a simple four-component key-press sequence could last minutes (e.g., Karni et al., 1995), whereas the fast stage of learning to play a complex musical piece may last months (Figure 1B). Similarly, nearly asymptotic levels in end-point measures of skill can be acquired very rapidly when learning a key-press sequence but much more slowly when learning to play a complex musical piece.

Skill changes can occur during training (online) but also Alisertib after training ended (offline; Figure 1C). Offline processes, including skill stabilization and improvement (Fischer et al., 2005, Korman et al., 2003 and Walker et al., 2002), reflect motor memory consolidation (Doyon and Benali, 2005, Muellbacher et al., 2002 and Robertson et al., 2004a), an intermediate stage between fast and slow learning (Doyon and Benali, 2005 and Doyon et al., 2009a). Online and offline skill gains check can be maintained over time, resulting in long-term retention (Romano et al., 2010). Identifying optimal measurements of skill learning is not trivial. Previous studies have typically defined skill acquisition in terms of reduction in the speed of movement execution or reaction times, increase in accuracy, or decrease in movement variability. Yet these measurements are often interdependent, in that faster movements can be performed at the cost of reduced accuracy and vice versa, a phenomenon which has been often referred to as speed-accuracy trade-off (Fitts, 1954). One solution to this issue is through assessment of changes in speed-accuracy trade-off functions (Figure 2; Reis et al., 2009 and Krakauer and Mazzoni, 2011). The fast stage of motor skill learning has been studied in human and nonhuman primates (e.g., Karni et al., 1995, Lehéricy et al., 2005 and Miyachi et al., 2002) and in rodents (Costa et al., 2004 and Yin et al., 2009).

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