Neurophysiological studies have reported that mentally simulated movements and anodal tDCS increased the motor evoked potential (Kasai et al ., 1997 ; Rossini et al ., 1999 ; Nitsche & Paulus, 2000 , 2001 ) and decreased the motor threshold of the M1 (Facchini et al ., 2002 ; Nitsche et al ., 2005 ). These physiological similarities between the effect of excitatory tDCS and MP could be ascribed, at least in part, to shared common substrates for learning of motor skill, including the strengthening of synapses, reflecting long‐term potentiation (Rioult‐Pedotti et al ., 2000 ). Long‐term potentiation‐like processes have been identified as the likely physiological basis of learning (Rioult‐Pedotti et al ., 2000 ; Ziemann et al ., 2004 ; Stefan et al ., 2006 ) and a likely candidate mechanism for anodal tDCS/mental training effects (Nitsche et al ., 2003a ; Stagg et al ., 2009 ). Thus, excitatory tDCS may be an excellent tool for identifying which cortical areas are significantly associated with neuroplastic effects of mental imagery on motor learning. Here, we investigated (i) whether the application of anodal tDCS could increase the neuroplastic effects of MP on motor learning, and (ii) whether these effects are site‐dependent.

Non‐invasive brain stimulations such as transcranial direct current stimulation (tDCS) have been used to investigate the role of cortical areas in different brain functions (Nitsche et al ., 2003b ; Pope & Miall, 2012 ). tDCS is a non‐invasive brain stimulation technique that applies a weak direct electrical current via the scalp to modulate cortical excitability in the human brain in a painless and reversible way (Nitsche & Paulus, 2000 ). When applied for several minutes, tDCS is able to hyperpolarise (cathodal stimulation) or depolarise (anodal stimulation) neuronal membranes at a subthreshold level for up to 1 hour after the end of stimulation (Nitsche & Paulus, 2001 ; Nitsche et al ., 2003a ).

Although it is clear that MP enhances physical performance, the neural mechanisms underlying this effect are unknown. It has been proposed that imagined movement shares similar neural substrates with those that are involved in executed motor actions (Decety, 1996a , b ; Guillot et al ., 2008 ). Indeed, as shown by neuroimaging studies, imagined actions are associated with functional and structural changes in a wide range of neural structures including the premotor and supplementary motor area (SMA) (Ingvar & Philipson, 1977 ; Roland et al ., 1980 ; Decety et al ., 1990 , 1994 ), primary motor cortex (M1) (Porro et al ., 1996 ; Ehrsson et al ., 2003 ; Kuhtz‐Buschbeck et al ., 2003 ; Solodkin et al ., 2004 ), cerebellum and basal ganglia (Decety et al ., 1994 ; Lafleur et al ., 2002 ; Naito et al ., 2002 ; Guillot et al ., 2008 ). The dorsolateral prefrontal cortex of the left hemisphere seems also to be involved in imagined movement (Decety et al ., 1994 ). Despite evidence of engagement of these cerebral substrates during motor imagery, the specific role of each area in the MP effects on motor learning have not been clarified. A better understanding of the action mechanisms is essential for MP to be used effectively as a therapeutic tool.

Mental practice (MP) is a training method in which a specific action is cognitively repeated without inducing any actual movement for the intention of acquiring motor skill and enhancing motor performance (Grouios, 1992 ). Several studies have shown that MP improves motor skill performance in healthy people and in different patient populations (for a review, see Dickstein & Deutsch, 2007 ). For instance, in individuals who are healthy, these improvements of performance include gains in muscular force (Ranganathan et al ., 2004 ) and upper limb kinematics (Gentili et al ., 2006 ). In the field of neurological rehabilitation, for example, promising findings have been reported for enhancing sit‐to‐stand performance and activities of daily living in people after stroke (Liu et al ., 2004 ; Malouin et al ., 2004 ; Page et al ., 2005 ).

The data were analysed, blind to experimental condition. The postintervention means were normalised to intra‐individually and are given as ratios of the baseline. Statistical analyses were performed with a repeated‐measures anova with stimulation type (M1, PMA, SMA, cerebellum, left dorsolateral prefrontal cortex and sham) and time (prestimulation and poststimulation) as the between factor for each dependent variable (writing time, letter legibility, word legibility, word size and word length). Posthoc Least Significant Difference tests were performed as appropriate to determine where differences occurred. Additionally, to test whether the baseline absolute value of each handwriting variable differed significantly from the postintervention values, a paired‐simples Student's t ‐test was applied. We did not correct the posthoc tests for multiple comparisons. A P value of < 0.05 was considered significant for all statistical analyses. The Mauchly test of sphericity was checked and the Greenhouse–Geisser correction was performed, when appropriate.

Experimental design. Prior to experimental sessions (S0), the mental capacity of subjects to learn the imagery techniques was tested by the Kinesthetic and Visual Imagery Questionnaire and a chronometric test. Subjects who successfully performed these tests participated in experimental sessions (S1‐S6). In each experimental session, the subjects performed two motor performance assessments, before and after MP combined with sham or active tDCS. Anodal tDCS at 2 mA was administered during the whole course of the MP. Five different electrode montages were tested to find the optimal position for DC stimulation in increasing the neuroplastic effects of mental imagery on motor performance: (i) right M1, (ii) right premotor cortex (PMA), (iii) right supplementary area (SMA), (iv) right cerebellar hemisphere (C) and (v) left dorsolateral prefrontal cortex (LDLPFC). The order of the different stimulation conditions was counterbalanced among participants.

The experiment was conducted in a double‐blinded sham‐controlled complete crossover design. Each subject participated in six experimental sessions separated by at least 48 h to avoid cumulative stimulation effect. In each experimental session, the subjects performed two handwriting tests (before and after MP), one MP session and received anodal/sham tDCS on only one electrode position condition. The experimental procedures are summarised in Fig. 1 . tDCS was administered by a researcher who neither instructed the handwriting test nor took part in the data analysis. Subjects were blind to condition tDCS (real or sham).

Individual means in each category were calculated for each time (baseline and after MP), separately for each experimental session. Because of imprecise measurements or subjectivity with the judgment of letter and word legibility, two examiners, both blind to stimulation type, independently scored each sample. If the reviewers disagreed regarding the legibility of a word/letter, it was given a score of “0” (illegible). Some authors consider a word/letter to be illegible if it cannot be read by two people (Glisson et al ., 2011 ). The legibility represents the handwriting quality, so a score nearer to the maximum score (36) represented a higher level of writing performance.

In each experimental session, motor performance was assessed by the handwriting test. This test measured legibility and writing time, important elements in handwriting performance (Bonney, 1992 ). Handwriting is a complex perceptual–motor skill that includes fine motor control (hand manipulation, bilateral integration, and motor planning) (Feder & Majnemer, 2007 ). For the test, the subjects were instructed to copy a six‐word set with the non‐dominant hand on a blank sheet of paper positioned on a table to the left of the subject. The word list was presented approximately three inches away from the paper. The handwriting task was performed with spontaneous production, free from the influence of the writing instructions.

The anodal tDCS was administered for 13 min during the whole course of the MP. Continuous direct currents were transferred by saline‐soaked surface sponge electrodes (surface 20 cm 2 ) and delivered by a clinical microcurrent stimulator (Soterix, USA) with a maximum output of 2 mA. Five different electrode montages were tested to find the optimal position for DC stimulation in increasing the neuroplastic effects of mental imagery on motor performance. The excitatory tDCS was applied over the: (i) right M1, (ii) right premotor area (PMA), (iii) right SMA, (iv) right cerebellar hemisphere, and (v) left dorsolateral prefrontal cortex. For M1 tDCS, the anode electrode was positioned above C3 (international 10‐20 system) (Nitsche et al ., 2003b ). For stimulation of the premotor cortex, it was moved 2 cm forward and 2 cm to the midline relative to the M1 position (Nitsche et al ., 2003b ). The SMA tDCS was performed with the anode electrode placed 2 cm anterior to the vertex (position Cz), in the sagittal midline (Cunnington et al ., 1996 ). For DC stimulation of the dorsolateral prefrontal cortex, the anode electrode was positioned 5 cm forward relative to C3 (Nitsche et al ., 2003b ). In all cases, the reference electrode was placed above the contralateral orbit. For cerebellar tDCS, electrodes were placed with one (anode electrode) over the right cerebellar hemisphere, 3 cm lateral to the inion (Ugawa et al ., 1995 ), and the other over the deltoid muscle (Ferrucci et al ., 2008 ). These methods of electrode montage have been used in previous studies and been shown to be effective in the modulation of cerebral activity. The order of stimulation condition was counterbalanced across subjects. The anodal tDCS was administered with a current strength of 2 mA. In the sham session, tDCS was applied over the M1 for 30 s, a method shown to achieve a good level of blinding (Gandiga et al ., 2006 ).

Comparing actual and imagined movement times, the chronometric test determined the motor imagery ability of participants. For the test, sitting on a chair with a back rest with both feet resting on the floor, the subject was asked (i) to physically write one six‐letter word, and (ii) to imagine the same movement for each upper limb (dominant and non‐dominant hand). Two trials were performed. The test always began with the dominant hand. A motor imagery index was calculated (imagery time/executed time) for each subject as an indicator of the temporal congruence of the imaged and physically executed task. If the duration of imagined action had a much larger variance (> 0.4) than the real movement duration, the subject was excluded.

Prior to experimental sessions, the mental capacity of subjects to learn the imagery techniques was tested by the Kinesthetic and Visual Imagery Questionnaire and a chronometric test. The Kinesthetic and Visual Imagery Questionnaire is an imagery assessment tool comprised of 10 items, each scored on a five‐point ordinal scale, including the image clarity (visual dimension) and the sensations intensity (kinesthetic dimension) of body movements. Each item describes an action: (i) neck flexion/extension, (ii) shoulder shrugging, (iii) forward trunk flexion, (iv) forward shoulder flexion, (v) elbow flexion, (vi) thumb to finger tips, (vii) knee extension, (viii) hip abduction, (ix) foot external rotation, and (x) foot tapping. Subjects physically execute each movement and immediately afterwards imagine performing the same movement. A score of 5 corresponds to the highest clarity/intensity, and a score of 1 corresponds to the lowest clarity/ intensity (for a review, see Malouin et al ., 2007 ). The Kinesthetic and Visual Imagery Questionnaire scores allowed the researcher to assess each participant's abilities and decide whether the subject was a suitable candidate for MP.

Eighteen healthy volunteers participated in the experiment (16 women, aged 23.2 ± 2.23 years). All subjects were native Portuguese speakers and right‐handed according to the Edinburgh Inventory of Manual Preference (Oldfield, 1971 ). None were taking any acute or regular medication at the time of the study, or had a history of neurological, psychiatric, or medical disease, family history of epilepsy, pregnancy, cardiac pacemaker or previous surgery involving metallic implants. Subjects with six or more symptoms of inattention and/or hyperactivity–impulsivity measured by the Adult Self‐Report Scale (a highly valid and reliable instrument to diagnose attention‐deficit/hyperactivity disorder) were excluded (Kessler et al ., 2005 ). Subjects were recruited from the campus of the Federal University of Pernambuco, Brazil. Experiments were conducted under a protocol approved by the Research Ethics Committee of the Center for Health Sciences, Federal University of Pernambuco and were performed in accordance with the Declaration of Helsinki. All participants gave their written informed consent prior to the experiment.

Effect of stimulation type on four categories of handwriting legibility. Average of word size (A), letter legibility (B), word legibility (C) and word length (D) plotted against the baseline condition before and after mental training combined with sham or active anodal tDCS of the M1, SMA, PMA, cerebellum (C) or left dorsolateral prefrontal cortex (DLPFC). Vertical bars depict SEM. Filled symbols indicate significant deviations of the handwriting legibility category from baseline values (Student's t ‐test, two‐tailed, paired samples, P < 0.05). *Significant deviations of active tDCS with different electrode montage vs. sham tDCS conditions within the respective time (Least Significant Difference, P < 0.05).

Figure 3 shows the mean values for the word size (Fig. 3 A), letter legibility (Fig. 3 B), word legibility (Fig. 3 C) and word length (Fig. 3 D) after each experimental session plotted against the baseline condition. The average minus the reference value of 1 indicated a decrease for the parameter measured compared with the baseline condition, whereas a value > 1 indicated an increase for that parameter. With regard to categories of legibility, the anova revealed a significant main effect of “time” on the categories word size and word legibility, and the interaction “stimulation type” × “time” on the category word size. The other main effects and interactions of other categories were not significant (Table 2 ). Additionally, paired t ‐testing between pre‐experimental and postexperimental sessions for each stimulation type also revealed no significant difference on categories of letter legibility and word length (Fig. 3 B and D). In comparison to the baseline and sham condition, the word size increased after mental training combined with excitatory tDCS on the cerebellum (Fig. 3 A), which suggested that motor performance deteriorated after stimulation.

Discussion

This is the first report demonstrating that anodal tDCS significantly enhances MP‐induced improvement in motor performance as compared with sham tDCS and that there was a specific effect depending on the site of stimulation. In the present study, the motor learning was studied by observing and measuring handwriting performance components. Considering the hypothesis that handwriting movements become faster with motor learning (Overvelde & Hulstijn, 2011), our results suggest that the M1 and left dorsolateral prefrontal cortex are the brain structures mainly associated with MP effects on motor skill performance.

In contrast to previous studies, where motor imagery alone sufficed to induce motor improvement (Blair et al., 1993; Roure et al., 1999; Gentili et al., 2006, 2010), in our study, although there was a slight trend for a reduction of writing time after MP (sham tDCS group), the motor imagery alone did not significantly alter motor learning. One reason for this discrepancy might be that one session of MP would not be able to induce motor skill improvement. Indeed, most studies with no evidence of the effectiveness of mental imagery on motor improvement conducted evaluation of MP outcomes on the same day, usually after only one session (Epstein, 1980; Wilkes & Summers, 1984; Woolfolk et al., 1985). For optimal results, Warner & McNeill (1988) recommend a minimum of five mental training sessions on separate days. Another alternative explanation for the MP used in our study not being effective enough to improve the motor skill might be due to the fact that, in the present study, we used audiotape with directed instruction of MP (externally guided task). An active mental process in contrast to passiveness seems to be more effective in producing neural modulation after motor imagery (Jones, 1965). In the passive mental process, using directed instructions during the mental activity, subjects may tend to follow the mechanically taped instruction rather than create their own mental image similar to when MP is self‐directed (Warner & McNeill, 1988).

The observed trend of reduced time of the handwriting task with the non‐dominant hand after MP was confirmed when it was associated with anodal tDCS on the M1. In line with this result, as mental and physical motor practice share common neural substrates (Ehrsson et al., 2003; Bakker et al., 2007), improvements in motor function as measured by clinical scores have been described for combined tDCS with motor practice in both healthy (Dockery et al., 2009) and stroke (Fregni et al., 2005a; Hummel & Cohen, 2005; Hesse et al., 2007; Celnik et al., 2008) patients. The mechanisms of action underlying motor practice (mental or physical)‐induced and/or tDCS‐induced performance enhancement are not well understood. However, as the learning facilitation seems to be a process dependent on increasing the cortical excitability (Nitsche et al., 2003b), we speculate that the increased neural firing rates induced by mental training and an additional anodal tDCS‐induced synaptic activation may have been crucial for motor improvement of the writing task after only one experimental session. However, further investigation is needed to understand how brain stimulation can consolidate motor improvement after mental training.

It is highly unlikely that the observed effect of the present study is due to an effect of anodal tDCS alone on the M1. Studies point out that a single tDCS session might not be sufficient to modify sensorimotor learning of a highly skilled task (Boggio et al., 2006; Buttkus et al., 2011). Thus, it is probable that the association between MP and tDCS was, in fact, responsible for reducing the writing time with the non‐dominant hand.

At first sight, compared with baseline, anodal tDCS on the SMA and PMA also seems to decrease the time of the handwriting task after MP. However, these results were not statistically significant. This negative finding was not expected, as SMA and PMA activation during MP is well documented (Stephan et al., 1995; Lotze et al., 1999). It is possible that the MP type (externally guided motor imagery) used in our study was not effective enough to activate the SMA. Electrophysiological studies in monkeys point out that the SMA exhibits preferential activity during internally‐guided movements and PMA neurons are more active during externally guided tasks (Mushiake et al., 1991; Tanji & Shima, 1994). In line with our result, another study, which used an externally guided task, also failed to show after‐effects of repetitive transcranial magnetic stimulation over the SMA on the performance of a tapping task (Del Olmo et al., 2007). However, excitability elevation of the PMA induced by anodal tDCS did not also improve the non‐dominant handwriting skill. We cannot exclude the possibility that, because medial and lateral area 6 is located further from the surface of the scalp than the M1, our tDCS protocol was unable to activate neurons in the SMA and PMA. In a former study, anodal tDCS on the premotor cortex, in contrast to on the M1, also resulted in no effect on motor learning (Nitsche et al., 2003b), which suggests that the pattern of tDCS‐induced plasticity changes might be slightly different in distinct cortical areas.

Anodal tDCS on the left DLPFC applied during mental training clearly decreased the writing time not only relative to baseline, but also compared with the sham condition. Knowledge about the cognitive processes (such as working memory) responsible for generating the motor actions needed for producing written words (Purcell et al., 2011) can help to understand these results. Motor plans for producing the writing, such as letter forms, the size and ordering of the strokes, and subsequently, effector‐specific motor programming compiles instructions for the specific limb to be used in carrying out the motor actions, held in memory working (Ellis & Young, 1988). A substantial literature points to an involvement of the left DLPFC in working memory (Fregni et al., 2005b). It has been proposed that the activity enhancement of working memory induced by tDCS over the left DLPFC could be responsible for motor improvement (Fregni et al., 2005a). Therefore, we suggest that activation of this area by mental training (Thobois et al., 2000) added to the anodal tDCS‐induced excitability increase (Zaehle et al., 2011) in our study might allow an increase in the capacity of the system responsible for maintaining order information active. With enhancement of working memory efficiency, the motor plans may be stored and/or precompiled not only for individual letters but also for larger graphemic chunks, allowing for faster production of letter sequences. This explanation of the results is necessarily somewhat hypothetical at present, as further investigations are needed to prove or disprove this proposed mechanism.

In our study, two dimensions were used to evaluate handwriting performance: writing time and legibility. With regards to legibility, compared with the sham condition, any stimulation type used in our study combined with mental training was unable to alter the quality of legibility in the categories word length, word and letter legibility. However, only the cerebellar stimulation worsened one category of legibility (word size). The letter/word size outcome can be used to measure the development of the motor control of distal movements (Chartrel & Vinter, 2008). It has been proposed that, at the beginning of the handwriting learning process, essentially it uses proximal articulations resulting in impulsive and large‐sized movements. Motor maturity enables the distalisation of the movement, which gives subjects better control of their movements and therefore improves the quality of the production, revealed by a decrease of word/letter size (Meulenbroek & Van Galen, 1988; Chartrel & Vinter, 2008). The lack of specific effects on handwriting legibility might be mainly due to limitations of the assessment approach. As a complex motor skill, it is likely that handwriting quality is not sufficiently sensitive to precisely show the effects of only one session of tDCS combined with MP. In this scenario, perhaps quantitative kinematic analysis of writing quality (such as length, duration, mean and peak velocity of components and strokes) could be too sensitive to detect changes of performance on complex handwriting tasks after mental training.

Size, specifically the vertical stroke size, was found to be the most invariant property of handwriting (Teulings & Schomaker, 1993). However, in our study, the cerebellar tDCS increases word size after mental training. It is known that the cerebellum is a brain structure where mismatches between intended and perceived outcomes of motor processes are monitored and corrected (Oscarsson, 1980; Schmahmann et al., 1999). Damage to the cerebellum produces errors in the planning and execution of movements (Kleim et al., 1998; Oberdick & Sillitoe, 2011). It has been strongly suggested that physical and/or MP of a movement sequence improves performance and induces plasticity in the cerebellum (Jenkins et al., 1994; Toni et al., 1998; Lacourse et al., 2004). Strangely, anodal tDCS over the right cerebellar hemisphere impaired the motor performance. Similarly, a former study using anodal tDCS over the cerebellum showed that anodal tDCS impaired the practice‐dependent proficiency increase in working memory (Ferrucci et al., 2008). Galea et al. (2009) found that anodal tDCS over the right cerebellar cortex can increase the inhibitory tone that the cerebellum exerts over the M1. The inhibition of the M1 after cerebellar tDCS could be one explanation for the impairment of handwriting legibility observed in our study.

Potential limiting aspects of the study should be mentioned. (i) In principle, motor practice alone of the handwriting task with the non‐dominant hand over six experimental sessions could have had an impact on motor performance and it might have somewhat compromised the interpretation of the results. However, this is improbable in our opinion as the experimental session order was counterbalanced among subjects and baseline writing performance on the experimental first day did not differ from that on the last day, (ii) It cannot be ruled out that additional cortical areas may have been influenced by tDCS due to the relatively poor spatial resolution of the technique (Nitsche et al., 2008; Datta et al., 2009). Although we cannot completely rule out this possibility, it should be noted that other studies using tDCS successfully modulated close cortical areas in different ways (Nitsche & Paulus, 2000; Nitsche et al., 2003b; Vollmann et al., 2012). (iii) Some studies have reported gender differences in responses to tDCS (Knops et al., 2006; Boggio et al., 2008; Chaieb et al., 2008). In the present study, as the most of subjects were women, it is possible that sex hormones somewhat influenced the results of our study. It is necessary to replicate the study using male participants in future research to investigate a potential gender influence on the results.

In conclusion, our results suggest that MP‐induced effects in improving motor performance can be successfully consolidated by excitatory non‐invasive brain stimulation on the M1 and left DLPFC. Although this finding is novel, further investigation is needed to understand how motor performance improvement is consolidated after mental training and whether it can be extended to other populations such as patients with neurological pathologies. If so, tDCS could be effectively used as a complementary method to increase the mental training effects. Moreover, our findings may help to improve to understanding about the specific role of each area involved in the MP effects on motor learning. However, a better understanding of the action mechanisms is essential for MP to be used effectively as a therapeutic tool. It might be important in future studies to increase knowledge on the specific brain areas involved in motor imagery to investigate the effects on MP‐induced learning when the cortical areas are downregulated by cathodal tDCS.