Abstract

Introduction

Stroke is a leading cause of severe long-term disability. Spontaneous recovery typically plateaus within three to six months, but rehabilitation can be effective at improving motor outcome, even in the chronic phase. Motor rehabilitation approaches vary widely, but there is increasing support for programs that encourage active movement and use neuroscience principles of motor learning to facilitate progression (1). Although greater intensity and duration of training leads to greater recovery (2), delivery of one-to-one training is time consuming and expensive. Thus, there is increasing interest in adjunct therapies to enhance responses (3).

Rehabilitation-mediated recovery depends largely on processes of learning and plasticity (4, 5), so manipulations that promote plasticity might be expected to enhance rehabilitation outcomes. For example, anodal transcranial direct current stimulation (tDCS) to the motor cortex is known to enhance excitability (6), reduce local inhibition (7), and facilitate motor learning (8, 9) in healthy individuals. We therefore predicted that application of anodal tDCS to ipsilesional motor cortex, when paired with motor training, would enhance rehabilitation outcomes after stroke by facilitating brain plasticity.

Although the effects of serial sessions using other tDCS configurations have been reported (10–12), there is limited evidence on the use of ipsilesional anodal tDCS. Two recent systematic reviews (13, 14) provide tentative support for the use of ipsilesional anodal tDCS in chronic stroke, but studies have not used serial sessions of anodal tDCS concurrent with motor training. We therefore performed a double-blind randomised controlled trial of anodal tDCS as an adjunct to a daily motor training program, the graded repetitive arm supplementary programme (GRASP) (15), delivered over 9 consecutive working days. In addition, serial multi-modal MRI was undertaken in order to test whether an effective intervention was associated with increased activation of the ispilesional hemisphere and associated structural changes. Long-term follow-up clinical and imaging assessments tested the persistence of observed changes in motor function.

Results

We conducted a stratified, double-blind, sham-controlled, parallel-group study designed to test the effects of anodal tDCS as an adjunct to motor training in chronic stroke patients (at least one month post single stroke affecting motor function). Of 1191 patients assessed for eligibility, 26 were randomized to receive either anodal tDCS or sham treatment, and 24 completed the intervention (fig. S1). Details of stroke patients who completed the intervention are given in Table 1 and location of lesions is shown in figure S2. Patient sex, age at intervention, time post stroke, lesion side, type and volume did not differ between the anodal tDCS and sham groups (Table 1). No lesions included primary motor cortex (fig. S2).

Clinical assessments and MRI were carried out at multiple time points before and after the intervention period (fig. S3). Neuroimaging measures were also taken before and after the intervention. During the intervention period participants conducted daily, supervised one-hour sessions of the Graded Repetitive Arm Supplementary Program (GRASP) (15) over 9 days. For the first 20 minutes of each session tDCS electrodes were positioned on the participant’s scalp to deliver either brain stimulation via tDCS or sham treatment.

Improved clinical test scores in the anodal tDCS group compared to sham group

Clinical outcomes were assessed at multiple timepoints following the intervention (fig. S3) using three clinical measures: Upper Extremity Fugl-Meyer Assessment (UEFM) (16), Action Research Arm Test (ARAT) (17) and Wolf Motor Function Test (WMFT) (18). Mean scores for each group and each timepoint on these clinical measures are shown in Table 2.

Table 2

Mean scores for functional assessment measures for anodal tDCS and sham treatment groups.

	Anodal tDCS Mean (SD)	Sham Mean (SD)
Baseline UEFM	38.90 (15.89)	36.42 (17.38)
Day 10 UEFM	50.36 (11.16)	45.53 (14.62)
1 Week UEFM	48.91 (11.90)	45.92 (15.52)
1 Month UEFM	49.73 (12.67)	46.46 (14.35)
3 Month UEFM	48.18 (14.35)	43.15 (16.29)
Baseline ARAT	20.27 (17.37)	26.27 (20.17)
Day 10 ARAT	29.91 (21.54)	32.54 (21.54)
1 Week ARAT	30.45 (20.67)	33.08 (21.84)
1 Month ARAT	30.27 (21.91)	31.92 (20.64)
3 Month ARAT	30.45 (20.92)	31.31 (21.84)
Baseline WMFT	37.91 (20.21)	39.65 (25.39)
Day 10 WMFT	47.18 (17.46)	48.00 (23.42)
1 Week WMFT	49.45 (20.30)	48.92 (24.44)
1 Month WMFT	49.18 (19.08)	46.54 (23.12)
3 Month WMFT	48.36 (18.19)	43.09 (23.78)

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In all assessments, higher scores indicate better performance. The UEFM ranges from 0-66, ARAT ranges from 0-57, and WMFT ranges from 0-75. Results are shown as mean ± SD.

To test whether clinical scores increased in the anodal tDCS group compared to the sham group, each clinical score was subjected to multiple regression using the general linear model. The model variables were group (sham and anodal tDCS) and individual participant baseline scores for the respective clinical measure. By including baseline scores in the model we ensured that variability in starting scores was taken into account. Plots of clinical scores for each group and for each of the post-intervention timepoints are shown in Figure 1.

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Figure 1

Increased clinical scores in the anodal tDCS group compared to the sham treatment group.

We assessed UEFM, ARAT, and WMFT clinical scale ratings before and at multiple time points after rehabilitation and either anodal tDCS or sham treatment. Shown are changes in scores from baseline for UEFM (A), ARAT (B), and WMFT (C) for anodal tDCS (green, n=11) and sham treatment (blue, n=13) groups, for the four post-intervention timepoints, after regressing out the respective baselines. Error bars represent standard errors of the mean. Fisher’s combined probability tests showed greater scores in the anodal tDCS group compared to the sham treatment group combined across all tests and all timepoints (p=0.008). Considering each test separately, greater scores were found in the anodal tDCS group for both ARAT (p=0.031) and WMFT (p=0.037) but not for UEFM (p=0.329). For the timepoint of primary interest, the 3 month follow-up, Fisher’s combined probability test showed greater scores for the anodal tDCS group compared to the sham treatment group when combining across all tests (p=0.004). Considering each test separately, greater scores were found in the anodal tDCS group at the 3-month follow up for both ARAT (p=0.045) and WMFT (p=0.001), but not for UEFM (p=0.550). All p-values were corrected for multiple comparisons across measures/timepoints as appropriate. Changes in clinical scores from baseline in the anodal tDCS and sham treatment groups are shown separately in Figure S4.

To test for any effect of anodal tDCS on clinical outcomes, we first ran a single global test combining all three clinical measures and all four post-intervention timepoints, and tested for a difference between the anodal tDCS and sham group using Fisher’s combined probability test, assessed with permutations. This showed greater scores in the anodal tDCS group than the sham group [Fisher’s χ²(24)=71.00, p=0.008]. Next, we ran the same test for each clinical measure separately, pooling across all post intervention timepoints. We found higher scores for the anodal tDCS group compared to the sham group for both ARAT [χ²(8)=28.88, p=0.031, corrected for the 3 measures considered], and WMFT [χ²(8)=27.91, corrected p=0.037] but not for UEFM [χ²(8)=14.22, corrected p=0.329].

The timepoint of primary interest was the 3 month followup. At this timepoint, pooling across all clinical measures revealed greater scores in the anodal tDCS group compared to the sham group [χ²(6)=29.06, p=0.004, correcting for 4 timepoints]. At the 3month followup, the mean absolute difference in the change in clinical scores from baseline between anodal tDCS and sham groups was 2.898 for UEFM [95% CI: -2.136 to 7.932; t(21)=1.20; p=0.550)] 5.763 for ARAT [95% CI: 1.560 to 9.966; t(21)=2.85, p=0.045], and 6.871 for WMFT [95% CI: 3.411 to 10.331; t(21)=4.13; p=0.001; these p-values were corrected for family-wise error rate across all tests, i.e., 4 timepoints, 3 clinical scores]. At earlier timepoints and pooling across clinical measures using Fisher’s test, we observed similar trends but these failed to reach significance after correction for the 4 timepoints [immediately post: χ²(6)=13.23, corrected p=0.195; 1 week: χ²(6)=12.05, corrected p=0.248; 1 month: χ²(6)=16.66, corrected p=0.092].

Increased activity and gray matter volume in ipsilesional motor areas in the anodal tDCS compared to sham treatment group

MRI data were unavailable for patient 08 (due to claustrophobia) and patient 23 (due to scheduling constraints), both of whom were in the sham group. Neuroimaging analysis was therefore based on 11 participants per group. We considered fMRI measures of activity during passive movement of the affected hand, voxel-based morphometry (VBM) measures of gray matter volume, and fractional anisotropy (FA) asymmetry measures of the corticospinal tract. For all voxel-wise analyses, images from patients with right hemispheric strokes were flipped about the midline after registration to standard space so that all lesions appeared on the left side.

We first tested for correlations between clinical sores and imaging measures at baseline. No correlations were found for gray matter volume or movement-related fMRI activity. However, baseline asymmetry of corticospinal tract FA correlated negatively with all baseline clinical scores (Spearman’s test: ARAT ρ=-0.77, p< 0.001; UEFM ρ=-0.79, p<0.001; WMFT ρ=-0.78, p<0.001).

We next tested whether baseline imaging measures correlated with subsequent change in clinical scores due to the intervention. No significant relationships were found for fMRI or VBM measures. FA asymmetry correlated with subsequent behavioral improvements for UEFM (ρ=0.51, p=0.015) such that greater corticospinal tract asymmetry at baseline was associated with greater intervention-mediated behavioral improvements. However, this relationship did not survive co-varying out the baseline UEFM score (r=-0.67, p=0.8).

Comparing changes in imaging measures from pre to post intervention between groups revealed greater increases in the anodal tDCS group compared to the sham group for fMRI activity and gray matter VBM but not for FA asymmetry. Specifically, larger increases in movement-related fMRI activation were found in the anodal tDCS group compared to the sham group (cluster p<0.05, corrected), in regions including ipsilesional motor areas, both immediately after the intervention (fig. 2A; Table S1) and at one month follow up (fig. 2B; Table S1). These fMRI results were similar after controlling for variation in gray matter (fig. S5). For gray matter VBM, greater increases were found immediately after the intervention in the anodal tDCS group relative to the sham group in ipsilesional premotor cortex, primary motor cortex and the contralesional postcentral gyrus (fig. 2C). Within this cluster, direction of mean change in gray matter volume was positive for the anodal tDCS group (0.0169±0.021) and negative for the sham group (-0.0210±0.023). However, when we tested across the whole brain for changes in gray matter volume from baseline in each group separately we did not find any significant clusters. Therefore, while our results show a greater increase in gray matter in the anodal tDCS group compared to the sham group, we did not have evidence regarding the direction of gray matter change in the absence of tDCS. No significant correlations were found between changes in clinical scores and changes in fMRI or VBM measures for any of the clusters. FA asymmetry values did not change after motor training (RM-ANOVA, main effect of time, and group x time interaction: p>=0.5).

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Figure 2

Increased fMRI activity and gray matter volume in the anodal tDCS group compared to the sham treatment group.

Shown are changes in fMRI activation and gray matter volume before and after intervention in stroke patients receiving motor rehabilitation plus anodal tDCS or sham treatment (post>pre, anodal>sham, voxel-wise General Linear Model, p<0.05 corrected). Images are in radiological convention (R – right), and all lesions appear on the left, the target for tDCS (yellow flash). The X or Y coordinates for each brain slice are given below the slice. (A) Brain regions showing increases in fMRI activity during affected hand movement from baseline to immediately post-intervention for the anodal tDCS group versus the sham treatment group. (B) Regions showing greater increases in movement-related fMRI activity for anodal tDCS versus sham group from baseline to one month follow-up. See table S1 for the location and Z statistic of peak voxels from fMRI analysis. (C) Brain regions showing increases in gray matter density as assessed by voxel-based morphometry (VBM), from baseline to immediately post-intervention for the anodal tDCS group versus the sham treatment group.

Discussion

We report long-term improvements in upper limb ability in patients receiving repeated sessions of anodal tDCS to the ipslesional motor cortex compared to the sham-treated group when tDCS was paired with motor training. We also found that these clinical improvements were associated with increased activation of ipsilesional motor cortical areas.

Previous proof-of-principle studies have shown that single sessions of anodal tDCS to the ipsilesional motor cortex temporarily improved motor function (19). For tDCS to have clinical relevance, however, it is critical that it be tested for long-term benefit. In healthy volunteers, repeated sessions of anodal tDCS paired with motor training provided long-lasting behavioral improvements (20). In chronic stroke patients, benefits have been found immediately or at one week after repeated sessions using other electrode configurations (10–12). One small study of sub-acute stroke patients found benefits of cathodal tDCS to contralesional motor cortex compared to sham treatment at six months of follow-up, but only a trend for beneficial long-term outcomes after anodal tDCS (21). However, it is unclear whether cathodal tDCS to the contralesional hemisphere is suitable for all patients as some patients may depend on contralesional activation for movement of the affected hand (22, 23). We therefore investigated the long-term effects of anodal tDCS on patients undergoing motor rehabilitation.

Clinical outcomes from a rehabilitation intervention can be manifest at different levels, including the domains of body function, activity, or participation. Focusing on a single domain may risk missing effects on other domains (24, 25). To maximise our chances of detecting effects that could then be followed up in future targeted trials, we considered outcomes using three clinical scales in the domains of body function (UEFM) and activity (ARAT, WMFT). While the GRASP program itself reduced impairment and improved activity (i.e., UEFM, ARAT and WMFT improved in both group), tDCS only modulated activity improvements. Our findings therefore suggest that anodal tDCS to the ipsilesional hemisphere may exert its effects by enhancing activity and reducing functional limitations, rather than by changing the impairment.

Improvements in activity may be mediated not only by reductions in impairment, but also through motor learning achieved through repetitive training on specific motor tasks. In line with others (27–29), our rationale for combining training strategies with adjunctive approaches depends on the fact that motor training programs such as GRASP involve motor learning and motor learning is possible in stroke patients (30, 31). Anodal tDCS applied to motor cortex has been shown to improve motor learning in healthy subjects (20) in part through local disinhibition (7).

Improvements in activity may be considered as ‘compensation’ as distinct from ‘true recovery’, which can only occur if impairment is reduced and original pathways for movement are restored (4, 27, 32, 33). This distinction is theoretically useful for understanding the level through which tDCS exerted its effects and is important for conceptualising a theory-based rationale for how best to employ tDCS in stroke rehabilitation. However, even ‘compensation’ can be useful to the patient if it allows them to perform movement tasks more effectively than before.

If anodal tDCS exerts its beneficial effects by enhancing learning, it is important to establish whether patients simply improve performance of specific trained movements or whether improvements can be generalised to non-trained items (28). There was some overlap between specific items included in the GRASP training and elements of the ARAT/WMFT assessment, and so tDCS may in part have exerted its effects through boosting task-specific training. However, the specific movements trained in the GRASP program differ among patients depending on the level at which they enter the program, which was variable in this trial (number of patients at level1/level 2/level 3 were: anodal tDCS 5/2/4 patients; sham, 4/3/6 patients). Further, there are items included in ARAT/WMFT which do not feature in GRASP. For example, adjusting a trained pinch grip to accommodate a different shaped object requires at least some degree of generalisation. It will be important for future studies to design training and testing regimens in order to fully characterise the extent to which task-specific training versus generalisation can be boosted by tDCS.

To test whether changes in brain structure and function could explain any observed clinical variation, we assessed neuroimaging measures. At baseline, worse clinical scores were associated with greater asymmetry of cortico-spinal tract microstructure, whereas no correlations were found between baseline clinical scores and fMRI or gray matter volume. We tested whether baseline neuroimaging measures predicted response to motor training, as shown previously (34). This is a clinically important question as such measures could potentially be used to target interventions at those patients who are most likely to benefit. Although we found correlations between baseline measures of corticospinal tract integrity and response to the intervention, these relationships did not increase predictive power above what could be explained by baseline clinical scores alone. Studies in larger and more variable patient groups will be required to assess the added value of such measures for clinical decision making.

We found greater increases in fMRI activation and gray matter volume in ipsilesional motor cortical areas in the anodal tDCS group compared to the sham group. Similar fMRI changes have been reported after a single session of anodal tDCS (35), and for serial sessions of other electrode configurations (11, 12). A previous study reported an increase in gray matter with rehabilitative training alone (36), whereas here, although we found changes in gray matter between the two groups, within-group comparisons did not reveal clear evidence for a significant change over time for either group. We found no change in diffusion MRI measures of white matter microstructure with training between the groups, unlike a previous study showing new motor learning in healthy individuals (37).

Together with our previous observations of short-term training interventions (38), these findings suggest that the condition of residual brain pathways, as measured by diffusion MRI, may place some constraints on motor ability (as reflected by baseline correlations between FA asymmetry and clinical sores). In spite of this, further gains in function may be possible, and are more strongly associated with altered activation of motor cortical areas and gray matter structural changes, rather than with changes in white matter connectivity.

There are some limitations to this trial. First, although our sample size compares favourably to other studies of anodal tDCS in chronic stroke, a larger sample would provide greater power for identifying predictors of response. Second, the assessing researcher, who was blind to stimulation condition, also delivered the training. It is possible that knowledge of how participants had performed during the training session could have influenced their assessment of outcomes. Although we do not believe this would unblind the assessor, it could potentially inflate any differences between participants that began to be apparent during the training sessions. In addition, the treating assessor, who operated the tDCS equipment, was not blind to stimulation conditions. Although this experimenter played no role in the training, and was not present at assessment sessions, it is possible that their behavior may have influenced the patient or the training researcher during training sessions. Future studies could make use of tDCS equipment that allows for stimulation protocols to be pre-programmed using a code in order to ensure that all those present are blind to stimulation conditions. Furthermore, because our hypothesis concerned the use of anodal tDCS as an adjunct to motor training we included motor training in both arms of our study. Because we did not include an arm without motor training or tDCS we cannot comment about the effect of the motor training itself, although this has been studied previously (15). Finally, as we did not test any healthy controls, our data do not provide evidence on whether the changes seen here would also be seen in healthy individuals.

Future larger studies are required to assess whether patient characteristics, such as baseline clinical scores or brain measures, could be used to stratify patients for maximal benefit. In addition, while our study was well tolerated, future trials using a less-intensive training regimen, perhaps consisting of 2-3 sessions per week, will be important to translate these findings into a clinical setting.

Materials and Methods

Supplementary Material

Acknowledgments

Footnotes

References