Mean RT was calculated for 50-trial blocks of practiced and rando

Mean RT was calculated for 50-trial blocks of practiced and random sequences for baseline, EoA and retention. For the practice session performance, mean RT was calculated for 100-trial practice blocks. Implicit sequence-specific performance was measured

as the difference in the mean response time between the sequence and random trials. Sequence specific performance was assessed at baseline, at the EoA and at retention. Offline learning was quantified as the change in implicit sequence-specific performance from the EoA to retention testing on Day 2. Offline learning encompasses multiple post-practice processes (e.g. consolidation) that contribute to stabilization and enhancement of motor memory. A repeated-measures anova (anovaRM) with independent factor Stimulation Condition (M1-AtDCS, PMd-AtDCS, and Sham) BIBW2992 datasheet and dependent factor Time (baseline, EoA and retention) was employed to assess selleck compound implicit motor

sequence-specific learning over time. Additionally, a similar anovaRM with repeated measures on practice blocks was used to evaluate the stimulation condition-dependent changes in sequence performance during practice. A Bonferroni correction was used for post-hoc tests to determine the locus of significant stimulation condition by time interactions. Changes in motor sequence performance online and offline were compared for the three stimulation conditions using an anovaRM with repeated measures on time. Statistical significance was pre-set at P = 0.05. Figure 2 illustrates the performance Tryptophan synthase on the sequence trial blocks and random trial blocks at baseline, during practice, at EoA and at retention. At baseline, anovaRM did not reveal a significant difference in the implicit sequence performance

between the three stimulation conditions (P = 0.773). During practice, there was a significant effect of practice, which indicated participants improved performance with practice (P < 0.001) irrespective of the stimulation condition. A main effect of AtDCS on implicit sequence performance during practice was revealed (F2,33 = 3.879, P = 0.031). Post-hoc analysis revealed that AtDCS M1 significantly improved practice performance compared with sham tDCS (P = 0.032). Although AtDCS applied over PMd also improved practice performance, the effect did not reach statistical significance (P = 0.064). At the end of the acquisition phase, although there was no statistically significant difference in performance between the three stimulation conditions (P = 0.08), there was a tendency for M1 and PMd to reveal better performance compared with sham stimulation. At retention, there was a statistically significant effect of the stimulation condition (P = 0.002; Fig. 2; retention block). Post-hoc analysis using Bonferroni correction revealed that AtDCS over M1 significantly improved retention performance of the implicit sequence compared with AtDCS applied over PMd (P = 0.003) or sham stimulation (P = 0.008).

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