Augmentation of working memory training by transcranial direct current stimulation (tDCS)

Transcranial direct current stimulation (tDCS) to the dorsolateral prefrontal cortex (dlPFC) can modulate working memory (WM) performance. However, evidence regarding the enhancement of WM training, its sustainability and transferability is ambiguous. Since WM functioning appears to be lateralized in respect to stimulus characteristics, this study examined the difference between task-congruent (spatial-right, verbal-left), task-incongruent (spatial-left, verbal-right) and sham tDCS in regards to the efficacy of WM training. In a randomized, sham-controlled experiment, 71 healthy adults trained on a spatial or verbal adaptive n-back task. After a baseline session, anodal or sham tDCS (1 mA) to the right or left dlPFC was applied during the next three training sessions. Sustainability of training gains and near-transfer (verbal or spatial 3-back task) were tested in a fourth training and a follow-up session. Compared to sham stimulation, we found a steeper learning curve when WM training was combined with task-congruent tDCS. This advantage was also present compared to task-incongruent tDCS. Moreover, these effects lasted for up to nine months and transferred to the respective untrained task. These long-lasting, transferable, task-specific effects demonstrate a behaviorally relevant and sustainable facilitation of neuroplastic processes by tDCS that could be harnessed for the treatment of disorders associated with deficient WM.

Correlation between baseline performance and sample characteristics. The linear regression revealed a negative relationship between age and baseline performance of the adaptive n-back task (β age = −0.07,  Reported adverse effects. Adverse effects reported by the participants are displayed in Table 2. For each adverse effect, a Kruskal-Wallis test was calculated to check for group differences. Analysis revealed no significant differences between groups regardless of type of adverse effect, indicating no noxious effects of stimulation and a successful sham arrangement.

Discussion
The present study examined the effects of anodal tDCS to the left and right dlPFC during spatial and verbal WM training on the learning effect across practice sessions and the transfer of improvements to untrained WM tasks.
The key results are first that enhancement of dlPFC activity by anodal tDCS can improve WM learning curves. Second that the beneficial effects of tDCS-enhanced training can transfer to an untrained domain. Third that the tDCS-dependent learning gains are sustained for up to nine months. Fourth, that lower pre-training performance predicts higher benefits from stimulation. And fifth, that the effects on WM training particularly emerge when the stimulus specific laterality of WM functioning is accounted for. At large, these data provide new evidence in support of the notion that tDCS can enhance the efficacy of WM training 18,20 . Nevertheless, the necessary pre-specification of stimulation and training parameters (e.g. intensity, Figure 3. At baseline, T4, and T5, performance (d′) on the 3-back near-transfer task was measured without concurrent tDCS to test the transfer of tDCS-enhanced adaptive n-back training gains. Error-bars represent the standard error (SEM). *Indicates significant t-tests (p < 0.05).  location and polarity of stimulation, number of training sessions and inter-training intervals) limit the generalization of the results 30,31 . It is quite unlikely that the parameters used here are the best possible but optimization of the stimulation parameters was beyond the scope of this study. However, the task-and laterality-specific effects that were predicted by the notion of a hemispheric organization of WM 39 support the reliability of the findings. This specification of the stimulation targets was based on a multitude of functional neuroimaging studies that have identified the dlPFC as a central hub of the neuronal network underlying WM functions 41 . Additionally, a range of other cortical areas are involved, including bilateral superior and inferior frontal gyri, (pre-) supplementary motor area as well as parietal areas 42 . However, non-invasive brain stimulation studies using repetitive transcranial magnetic stimulation (rTMS) and tDCS have focused on the dlPFC to support healthy and disturbed WM 18 . As tDCS appeared to be beneficial for WM performance, the question arises if the learning progress as such can be enhanced by tDCS. In this regard, several studies indicated that the performance during WM trainings can be facilitated by tDCS 26,27,29,[43][44][45] . But unambiguous evidence for improved learning progress across multiple sessions and sustainability of training gains is still scarce 28 . In this respect, showing differences in learning curves between tDCS and sham stimulation parallel to WM practice, our findings provide relevant additional proof for a sustainable improvement of WM training effects by tDCS. However, it has to be considered that the follow-up measures were obtained 3 and 9 months after the training of spatial and verbal WM, respectively. Therefore, conclusions on the temporal stability of training effects are preliminary.

Kruskal-Wallis p-value
Regarding the transfer of stimulation-enhanced training gains to untrained tasks, available studies provide inconsistent results. Transfer effects were reported comparing a tDCS-only (without training) group with a tDCS and training group 43 or comparing an active tDCS group with a no-contact control group 26 . Recently, transfer effects to another spatial task 28 and, in older subjects, far transfer gains after one month 29,45 were documented after tDCS to the right dlPFC parallel to spatial WM training.
Moreover, the optimal stimulation timing is largely unclear. Recent meta-analyses on differential effects of online and offline tDCS on WM performance come to conflicting results 18,20,30 . However, based on our own experience [46][47][48] and other previous studies 25 we used tDCS parallel to WM training and thus confirm the efficacy of the direct combination of tDCS and cognitive training. In order to improve the precision of our intervention, we followed up on considerations attributing the lack of tDCS-effects on spatial WM after stimulation to the left dlPFC 26 . Considering the domain-specific lateralization of WM functions with the left dlPFC particularly involved in verbal and the right dlPFC in spatial WM functioning 33,35,36 , we performed a crosswise comparison of task-congruent with task-incongruent and sham stimulation. The electrode placement over left (F3) or right (F4) dlPFC together with an extracephalic return electrode, enabled us to test the hypothesis that, for effective enhancement, anodal tDCS has to be targeted to domain-specific active dlPFC (left for verbal, right for spatial stimulus material). These results, in line with previous studies 49,50 , support the notion of an at least partially left-and right-lateralization of verbal and spatial WM. Of course, this dichotomy of verbal and spatial WM pinpoints only a small aspect of the much more complex functional organization of the networks subserving WM processes 51 . For instance, the very recent study of Au et al. 28 demonstrated training-enhancement by both tDCS of the left and right dlPFC. However, in this study only visuospatial WM was trained, comprising seven training sessions and applying 2 mA anodal tDCS. Therefore, it is quite possible that compared to our study, longer training and higher stimulation intensities might overcome the laterality effects. But, consistent with our findings, in the study of Au et al. transfer effects were only found after the task-congruent right sided stimulation. Therefore, regarding transfer effects, our results advocate the idea that tDCS should be targeted to the cortical area that is involved in the training task and not the task to which a transfer of performance is intended. This observation is again in line with the notion that tDCS should be linked with cortical activity 25 to yield appropriate effects. Hence, translation of tDCS-enhanced WM trainings into clinical and therapeutic settings should consider this left-right lateralization of working memory functioning. Performance improvements and transfer effects induced by tDCS may only be achievable when the location of electrodes match the specific stimuli of the training task. However, further studies are needed to investigate under which circumstances the transfer of tDCS-induced learning effects appear robustly.
Furthermore, our results indicate that effects of tDCS are dependent on the pre-training performance. Participants with relatively low WM ability benefit the most, while participants with higher WM performance profit less from task-congruent stimulation. This contrasts with our observation that the subjects with higher WM proficiency at baseline generally show better training effects. Presumably, these individuals are more likely to activate the required neuronal resources. Accordingly, in these subjects, adding activation by tDCS would be less effective. In this regard, it must be noted that in our study, participants in the sham group were slightly older (mean age: 27 in the sham group vs. 23 and 24 years in the active groups). This might be relevant since, at baseline, age correlates negatively with performance. However, performance at baseline did not differ between groups. Moreover, differential effects were also found on training between congruent and incongruent stimulation as well as comparing performance between sham and task-congruent tDCS at follow-up, discounting baseline performance. Nevertheless, in general, the interaction between baseline performance and the efficacy of tDCS is complex. For example, it has been demonstrated that in an older group of subjects, participants with higher levels of education benefited more from tDCS during a WM task than adults with lower education 52 indicating that strategy and motivation influence the effectiveness of tDCS 53 . Therefore, a direct link between our results -that lower baseline performance predicts better TDCS effects -and promising clinical use in subjects with lower baseline performance is premature and needs more specific empirical data.
Similarly, the idea that additional brain activation by anodal tDCS generally leads to enhanced behavioral performance has not always proved to be correct 54 . In healthy populations especially, a non-linear effect of stimulation intensity was reported 55 , i.e. a lower current intensity of 1 mA can, performance-wise, be superior to stimulation with 2 mA. These data, our own respective findings 46-48, 56, 57 , and the more reliable sham control, prompted us to use 1 mA stimulation intensity, despite previous and recent studies showing effects on WM with 2 mA stimulation 28,29,34,58,59 . However, patients with Parkinson's disease 60 and schizophrenia 61 seem to benefit more from increased current intensity in regards to cognitive performance.
Furthermore, high inter-individual variability and the possibility of non-responders in regards to the efficacy of tDCS, e.g. caused by COMT gene or other polymorphisms, have to be considered when effects of tDCS vary [62][63][64] . Thus, future studies should place special emphasis on the elucidation of possible moderator variables and their impact in regards to tDCS efficacy.
In summary, the current study endorses the notion that tDCS can augment WM training if applied in a taskand laterality-dependent manner, specifically to the right dlPFC in spatial and the left dlPFC in verbal WM training. Moreover, these beneficial effects of tDCS can transfer to an untrained task and are observable for up to nine months. This proof of concept could help to develop effective tDCS-enhanced training regimens for the application in therapeutic settings.

Materials and Methods
Ethical Statement. The study was performed in accordance to the Declaration of Helsinki and approved by the ethics committee of the Medical Faculty of the Eberhard Karls University Tübingen. Prior to the conduction of the study, all participants gave their written informed consent. Participants received a small monetary compensation for their participation in the study.

Subjects.
Overall, 81 participants were recruited for both training schedules. They were randomly allocated to one of three groups by means of a computer-generated table: anodal stimulation to the left dlPFC, anodal stimulation to the right dlPFC, and sham stimulation. Nine participants dropped out before finishing all sessions. Data of one participant was excluded because n-back values were more than three interquartile-ranges above the upper quartile. In total, 71 participants (M = 24.45 years, SD = 5.16, 57 female, 14 male) completed all training and measurements sessions and were included in the statistical analysis. The first 36 individuals (M = 23.5 years, SD = 3.39, 30 female) were subjected to a spatial and the latter 35 (M = 25.4 years, SD = 6.40, 27 female) to a verbal WM training. Participants were checked for the following exclusion criteria: left-handedness (assessed by the Edinburgh Handedness Inventory 65 with a cut-off score of 50), current psychopharmacological medication or psychotherapeutic treatment, mental or neurological disorders, brain implants, or history of seizures. All participants had corrected to normal or normal vision. A detailed description of the study sample is given in Table 3.
Procedure. The training schedules were performed in a sham-controlled, single-blinded training design with a baseline session, three tDCS-supported training sessions (T1-T3), a post-tDCS training session (T4) and a follow-up session (Fig. 4). The training started 2-3 days after baseline and was carried out during one week with    1 day (T1-T3) and 2-3 days (T4) inter-session intervals. The follow-up session took place nine and three months after spatial and verbal training, respectively. The baseline session was comprised of the questionnaires and the baseline assessment of the adaptive n-back and the near-transfer 3-back task. During T1-T3 participants trained the adaptive n-back task parallel to tDCS according to their group allocation (left dlPFC, right dlPFC, sham). The subjects were trained either on an adaptive spatial or verbal n-back task and performed a spatial or verbal 3-back as a near-transfer task, respectively. At T1-T3, before and after the training, the current affective state of the participants was assessed by the PANAS 66 to evaluate possible stimulation dependent changes of affect. At T4 and follow-up, participants performed the adaptive n-back training without tDCS and 3-back near-transfer task.
To ensure blinding of tDCS, the participants were asked to guess if they received active or sham stimulation. They also rated the adverse effects of stimulation on a 1 to 5 Likert-scale 67 including questions on the most frequent adverse effects of tDCS: itching, tingling (near electrode and overall head area), headache, nausea, and fatigue.

Transcranial Direct Current Stimulation. A CE-certified DC-Stimulator MC (NeuroConn GmbH,
Ilmenau, Germany) was used to administer anodal direct current on the three training sessions. The current was applied via a pair of rubber electrodes (5 × 7 cm, 35 cm 2 ) which where coated in adhesive conducting paste (10/20 conductive EEG paste, Kappamedical, USA). Electrode resistances were kept < 8 kΩ. In the active conditions, tDCS (1 mA) was administered for a total period of 20 min with the anode placed on F3 or F4 according to randomization (international 10-20 system 68 , longer side of the electrode positioned horizontally). The reference electrode was placed on the contralateral deltoid muscle (longer side of the electrode, positioned horizontally) to avoid unwanted stimulation effects on brain activity of other cortical regions 48,69 . Modeling data indicates that the distribution of current density with this electrode placement is focused on the dlPFC 48 74 . In the adaptive spatial n-back, blue squares were presented subsequently on a black 3 × 3 grid (except the center position). Participants had to respond with a key press (space bar) if the current position of the blue square matched the position n-presentations before (target). In case of a mismatch the key press had to be omitted. The position of the squares varied randomly. In the adaptive verbal n-back, stimuli were sets of letters containing 8 letters randomly selected out of the complete alphabet (A-Z). The letters were randomly presented in a succeeding order and the participants had to press a key (space bar) when the current letter matched the letter n-presentations before (target). A schematic representation of the tasks is depicted in Fig. 5. Participants were instructed to react as accurately and as fast as possible. As stimulus selection occurred randomly, on average every eighth presentation was a target. The tasks consisted of 20 trials with each trial comprised of 20 + n presentations. As the task was adaptive, the task difficulty n varied per trial. Every participant started the task on every session with n = 1. After each trial they received feedback concerning their performance, with which the difficulty n for the upcoming trial was adapted: (1) with a score of < = 50%, task difficulty n was decreased (n − 1); (2) in case of a score between 50% and 70%, n remained unchanged; (3) scoring > 70%, n was increased (n + 1). The score for each trial was calculated as follows: score = hit/(hit + miss + false alarm). The outcome measure for the training task was mean n, averaged over the last 15 out of 20 trials 75 .

Near-transfer Task.
To measure transfer to untrained tasks in a similar context (near transfer) and to test the transferability between WM domains, a verbal 3-back task was used if the adaptive training task was spatial and vice-versa 4,14,76 . The transfer tasks were programmed using PsychoPy2 v1.80.04 74 . Stimuli were the same as in the adaptive n-back tasks. The stimuli were randomly presented in a succeeding order and the participants had to press a key (space bar) when the current stimulus matched the stimulus three presentations before (target). In case of a mismatch the key press had to be omitted. The task itself consisted of five trials with 40 stimulus presentations per trial (Fig. 5) and a practice trial to get familiar with the task. In each trial, a different set of stimuli, i.e. positions of squares or letters, was used. Participants were instructed to react as accurately and as fast as possible. Due to its favorable psychometric properties 77 d'-prime was defined as the outcome measure. It is calculated by subtraction of the standardized (z-transformed) hit-rate and false-alarms: d' = z(HIT)−z(FA) 78,79 .
Statistical Analysis. Statistical analysis was conducted using the software R Version 3.3.1 80 including the packages lme4 81 and multcomp 82 . To examine the effects of tDCS on across-session learning (T1-T4) of the adaptive n-back tasks, linear mixed-effect models were fitted. For each model the dependent variable was the performance outcome (mean n) and the following fixed effects were entered: session (metric), group (categorical), baseline (metric) and all corresponding interactions. To account for unsystematic individual differences a random-intercept and a random-slope was entered. Linear mixed-effects models were chosen over an ANOVA-framework to allow for a detailed evaluation of learning slopes in consideration of baseline performance by means of regression-coefficients. According to our hypotheses, the factor group was effect-coded with the sham-group being the reference of comparison. Regression parameters of the linear mixed-effect models and their corresponding z-value and significance are reported. It should be noted that, for interpreting differences between groups across the complete training, all regression-coefficients have to be added up. Accordingly, coefficients can be counterintuitively negative when they are canceled out by other positive coefficients, e.g. higher interactions. If significant differences in learning rates were found between tDCS and sham, post-hoc comparisons of training gains (i.e. baseline corrected performance) at specific sessions were performed by independent t-Tests (two-tailed).
To test the superiority of stimulation linked with the assumed task-dependent neuronal activity, we first compared learning in subjects receiving task-congruent tDCS (right dlPFC during spatial and left dlPFC during verbal WM training) with learning during task-incongruent tDCS (right dlPFC during verbal and left dlPFC during spatial WM training) and learning without concurrent tDCS (sham).
Effects of the stimulation on the follow-up session of the training task and the transfer effects (on T4 and follow-up) were examined by submitting the performance outcome (mean n and d') of the training-and 3-backs task to ANCOVAs with the performance at the respective training session (T4 or follow-up) as dependent variable, baseline performance as covariate and group as between-subjects factor 83 . When significant effects were revealed, regression parameters of the underlying linear regression were reported to identify the specific impact of the significant variables.
Correlations between training task baseline performance of participants and the sample demographic data were evaluated by a simple linear regression with baseline performance as dependent variable and age, sex, education, right-handedness and IQ as predictors. Blinding of group allocation was checked via a χ 2 -Test. Changes of affect as assessed by the PANAS were analyzed for the positive and negative scale separately using an ANOVA on change scores with training session (T1-T3) as within-subjects variable, group as between-subjects variable and the session × group interaction. Kruskal-Wallis tests for each aspect of adverse effect were calculated with group as between-subject factor to control for differences between groups. Regarding the effect size of main effects and interactions of the ANCOVAs, Eta-squared (η 2 ) and partial Eta-squared (η p 2 ) are reported 84 . Cohens d was calculated for all post-hoc t-Test comparisons. For all analyses the alpha level of statistical significance was set to p < 0.05.