, 2011). The cellular mechanisms underlying learning-dependent changes in white matter microstructure remain to be established, Everolimus supplier and so do the links between these changes and measures of functional plasticity. It has been proposed that changes in white matter properties, indexed by FA, could affect the velocity and synchronicity of impulse conduction between distant cortical regions and thus contribute to the optimization of information flow required for skill acquisition (see Fields, 2008 and Fields, 2011), a hypothesis that requires specific testing. Altogether, demonstrations of learning-induced gray and white matter plasticity in humans represent an exciting development in systems neuroscience. Yet the

contribution of this line of research to our understanding of motor skill learning is still limited. The biological mechanisms that underlie these forms of plasticity remain to be elucidated, and its time scales need to be more clearly established.

Additionally, strict comparative evaluation of structural and functional plasticity associated with motor skill learning Selleck Docetaxel is difficult at this point, given the different experimental paradigms used in the literature. This issue should be overcome in future investigations by evaluating both forms of plasticity in longitudinal studies in the same subjects (Thomas et al., 2009). Progression from fast to slow motor skill learning is thought to rely on appropriate consolidation

(Doyon and Benali, 2005, Muellbacher et al., 2002 and Robertson et al., 2004a), defined as the progressive stabilization of a recently acquired memory (Dudai, 2004). Through consolidation, new memories are transformed from their initial fragile states into more robust and stabile forms (Robertson et al., 2004a). In relation to motor skill learning, the term consolidation has been used in the literature to describe two different, but not mutually exclusive, phenomena: the offline behavioral skill improvements that occur after the end of a practice session (Robertson et al., 2004a) and the reduction in fragility of a motor memory trace that follows about encoding (Robertson, 2009 and Robertson et al., 2004a). In humans, offline skill improvements may be affected by sleep (e.g., Diekelmann and Born, 2010, Fischer et al., 2002 and Korman et al., 2003). Sleep-dependent motor memory consolidation, which correlates with the amount of stage II nonrapid eye movement sleep (Walker et al., 2002), has been mostly demonstrated for explicit motor sequence learning (Fischer et al., 2005, Korman et al., 2003 and Walker et al., 2002; but see Brawn et al., 2010 and Rickard et al., 2008). Other forms of procedural motor learning are not necessarily sleep dependent (Debas et al., 2010, Doyon et al., 2009b and Song et al., 2007). Notably, sleep does not benefit implicit forms of sequence learning (Robertson et al., 2004b and Song et al., 2007).