- Open Access
Effects of bihemispheric transcranial direct current stimulation on motor recovery in subacute stroke patients: a double-blind, randomized sham-controlled trial
Journal of NeuroEngineering and Rehabilitation volume 20, Article number: 27 (2023)
Bihemispheric transcranial direct current stimulation (tDCS) of the primary motor cortex (M1) can simultaneously modulate bilateral corticospinal excitability and interhemispheric interaction. However, how tDCS affects subacute stroke recovery remains unclear. We investigated the effects of bihemispheric tDCS on motor recovery in subacute stroke patients.
We enrolled subacute inpatients who had first-ever ischemic stroke at subcortical regions and moderate-to-severe baseline Fugl-Meyer Assessment of Upper Extremity (FMA-UE) score 2–56. Participants between 14 and 28 days after stroke were double-blind, randomly assigned (1:1) to receive real (n = 13) or sham (n = 14) bihemispheric tDCS (with ipsilesional M1 anode and contralesional M1 cathode, 20 min, 2 mA) during task practice twice daily for 20 sessions in two weeks. Residual integrity of the ipsilesional corticospinal tract was stratified between groups. The primary efficacy outcome was the change in FMA-UE score from baseline (responder as an increase ≥ 10). The secondary measures included changes in the Action Research Arm Test (ARAT), FMA-Lower Extremity (FMA-LE) and explorative resting-state MRI functional connectivity (FC) of target regions after intervention and three months post-stroke.
Twenty-seven participants completed the study without significant adverse effects. Nineteen patients (70%) had no recordable baseline motor-evoked potentials (MEP-negative) from the paretic forearm. Compared with the sham group, the real tDCS group showed enhanced improvement of FMA-UE after intervention (p < 0.01, effect size η2 = 0.211; responder rate: 77% vs. 36%, p = 0.031), which sustained three months post-stroke (p < 0.01), but not ARAT. Interestingly, in the MEP-negative subgroup analysis, the FMA-UE improvement remained but delayed. Additionally, the FMA-LE improvement after real tDCS was not significantly greater until three months post-stroke (p < 0.01). We found that the individual FMA-UE improvements after real tDCS were associated with bilateral intrahemispheric, rather than interhemispheric, FC strengths in the targeted cortices, while the improvements after sham tDCS were associated with predominantly ipsilesional FC changes after adjustment for age and sex (p < 0.01).
Bihemispheric tDCS during task-oriented training may facilitate motor recovery in subacute stroke patients, even with compromised corticospinal tract integrity. Further studies are warranted for tDCS efficacy and network-specific neuromodulation.
Trial registration: This study is registered with ClinicalTrials.gov: (ID: NCT02731508).
The randomized controlled trials (RCTs) of transcranial direct current stimulation (tDCS) applied to the primary motor cortex (M1) concurrently with rehabilitation therapy at the subacute stroke stage (> 7 days to 3 months) [1, 2], and even acute stage (1–7 days) [3,4,5], have demonstrated safety and potentials to promote motor recovery and neuromodulation of the underlying cortex . However, clinical translation of tDCS has been limited by heterogeneity in stroke lesions and tDCS setups across studies, so their effects on the augmentation of stroke recovery remain undetermined. Anodal low intensity (0.5–2 mA) stimulation usually increases corticospinal excitability , while cathodal stimulation may decrease corticospinal excitability but have substantial inter-subject variability and partially non-linear dose-dependent effect in healthy subjects [7,8,9,10]. Although the mechanisms of motor recovery after stroke are largely unclear, there are indications that mild-to-moderate patients with the good outcome have residual ipsilesional M1 corticospinal excitability [11,12,13]. In contrast, patients with severe hemiplegia have purely over-excitability of the contralsional M1 [13,14,15]. In the recent meta-analysis, three stimulation types have been compared with multi-session tDCS after stroke using Fugl-Meyer Assessment of Upper Extremity (FMA-UE) as the primary efficacy outcome : including (1) anodal tDCS over the ipsilesional M1 (with the cathode placed over the contralesional supraorbital region; eight RCTs with one acute, three subacute and four chronic stages), (2) cathodal tDCS over the contralesional M1 (with the anode placed over the ipsilesional supraorbital region; four RCTs with two subacute, one chronic and one mixed stage), and (3) bihemispheric (or dual) tDCS with the anode over the ipsilesional M1 and the cathode over the contralesional M1; seven RCTs with six chronic and one mixed stage. Among the stimulation types, bihemispheric tDCS seemed to have a relatively large effect size on motor recovery of the paretic upper extremity (UE) , mostly in chronic patients more than six months post-stroke [17,18,19,20,21]. However, the efficacy of bihemispheric tDCS for UE recovery in subacute or acute stroke patients remains unclear [3, 5, 22, 23]. Few studies reported insignificant effects for UE recovery in acute stroke patients [5, 22], while the other recent study found beneficial effects in combination with modified constraint-induced movement therapy in acute-to-subacute stroke patients with mild motor impairment . Specifically, there is good evidence that the subacute stroke phase coincides with a window of spontaneously enhanced neuroplasticity from preclinical and clinical studies [24, 25]. Applying bihemispheric tDCS during this critical window of enhanced neuroplasticity may be especially important to investigate.
Many factors may influence the tDCS effects on post-stroke motor recovery [16, 26], including the corticospinal tract (CST) integrity, adjunct therapy, and stimulation timing and doses. The CST integrity, measured by means of transcranial magnetic stimulation with the motor-evoked potential (MEP) recorded from the paretic UE, is a prognostic biomarker of post-stroke motor outcome and a predictive biomarker for tDCS responsiveness [27, 28]. Patients with preserved MEPs were usually responders to intensive training compared with those patients without MEPs [29, 30]. However, most tDCS RCTs have not stratified this key element at baseline [3, 5, 17,18,19,20,21]. Furthermore, adjunct therapy coupled with task-oriented training [17, 18, 31], rather than with simple joint exercise [19, 20], helped to improve UE motor functions. As for stimulation timing, concurrent tDCS with training resulted in better effects than tDCS applied before conventional therapy . Finally, dose-dependent stimulation with a higher current density or charge density has been suggested to enhance greater post-stroke motor improvement in the meta-analyses of multi-session tDCS RCTs [16, 32]. However, possible non-linear effects of tDCS in stroke patients shall also be considered. Collectively, we hypothesized that multi-session bihemispheric tDCS during task-oriented training would provide therapeutic potential in subacute stroke patients, even those with compromised CST integrity.
Here, we stratified stroke patients by the paretic UE severity and CST integrity, utilizing a double-blind, randomized, sham-controlled design to elucidate the effects of multi-session task-concurrent bihemispheric tDCS on domain-specific FMA-UE and FMA-Lower Extremity (FMA-LE), Action Research Arm Test (ARAT). Moreover, we explored neural correlates underlying bihemispheric tDCS on the targeted sensorimotor network using resting-state functional magnetic resonance imaging (fMRI) in these subacute stroke patients. Our previous study demonstrated that a single-session bihemispheric tDCS simultaneously modulated bilateral corticospinal excitability in subacute stroke patients with preserved MEPs, in which electrophysiological changes were predicted by the baseline contralesional-to-ipsilesional transcallosal inhibition ratio between the M1s . Post-stroke resting-state functional connectivity (FC) between the M1s was shown to be positively correlated with better motor recovery [34,35,36,37]. Hence, we hypothesized that bihemispheric tDCS might modulate interhemispheric and/or intrahemispheric FC of the target M1s, respectively, in correlation with tDCS-induced FMA-UE change scores. Addressing the lack of studies on FC changes by bihemispheric tDCS after stroke, our results can provide insights into the neuromodulation of functional networks by non-invasive brain stimulation.
Materials and methods
Study design and participants
We conducted a double-blind, randomized, sham-controlled study to investigate the efficacy and safety of bihemispheric tDCS for motor recovery in subacute stroke patients. The ethics committee approved the study at the Taipei Veterans General Hospital (VGHIRB No. 2015-03-003C) and registered with ClinicalTrials.gov (NCT02731508). We screened 282 consecutive inpatients between September 2015 and June 2021 and validated their eligibility for the following inclusion criteria (Fig. 1): (1) age between 20 and 80 years; (2) acute first-ever unilateral infarction confirmed by diffusion-weighted MRI; (3) consciousness clear and able to sign the informed consent form. The exclusion criteria were: (1) sensorimotor cortical infarcts; (2) too mild or too severe FMA-UE scores, i.e. > 56 or < 2 (0–66, where 0 is no function and 66 is maximum) ; (3) sensory or motor aphasia; (4) severe medical diseases (advanced malignancy, end-stage heart, liver or kidney failure, etc.) with premorbid modified Rankin Scale (mRS) > 1; (5) major neuropsychiatric diseases (dementia, epilepsy, parkinsonism, cerebellar ataxia, major depression, etc.); (6) contraindications to transcranial magnetic stimulation (TMS) for increased risk (presence of metallic implants, pregnancy); and (7) participating in other interventional studies.
Sample size estimation
The G*Power software (v22.214.171.124; Franz Faul, University of Kiel, Kiel, Germany) was used for sample size estimation. Based on a previous study using 15 sessions of bihemispheric tDCS during occupational therapy in stroke patients (current density: 0.08 mA/cm2; total stimulation time: 450 min) , the effect size on the improvement of FMA-UE was 1.4. If the effect size was assumed as Cohen’s d = 1.4 (equal to Pearson’s r = 0.57 for nonparametric statistics), the estimated sample size was n = 11 per group to achieve a statistical power of 80% and a 2-tailed test with α = 0.05. Given a possible drop-out rate of 15%, at least 13 participants for each group were required.
Randomization, concealment, stratification and blinding
We randomly assigned the eligible participants within 2–4 weeks after stroke onset to ensure the groups were matched for baseline UE impairment. Computerized randomization minimization was used to balance the stratification factors between groups , including age, lesioned side, baseline FMA-UE score , and the ipsilesional CST integrity . To determine the residual CST integrity, single-pulse TMS was administrated using a Rapid2 stimulator (Magstim, Whitland, UK) with a double-cone coil (126 mm in diameter) after a safety screening as previously described . An absence of MEP recorded from the paretic extensor carpi radialis (MEP-negative) was defined as a lack of potentials with an amplitude of at least 50 μV when using the maximal stimulator output. The randomization process was conducted by a person who was unaware of the study hypotheses. Both the participants and the assessors who performed outcome measures were blinded to group allocation.
Bihemispheric tDCS intervention
A NeuroConn DC stimulator (Ilmenau, Germany) was used to deliver direct current through two conductive rubber electrodes wrapped in normal saline-soaked sponges (5 × 5 cm2) with wires placed towards the posterior head. The real tDCS group received 20 min (including ramp-up and ramp-down for 30 s each) of 2-mA tDCS (current density 0.08 mA/cm2) with anodal and cathodal electrodes placed over the ipsilesional and contralesional M1 of the hand, respectively, based on anatomical C3 and C4 locations (e.g. the 10–20 system) as previously described . Sessions were conducted prior to regular conventional therapy twice daily for ten workdays (total stimulation time: 400 min; Fig. 2A). The sham tDCS settings were similar except that the direct current ceased after 2 min (including 30 s ramp-up) to keep blindness that the session started with real direct current to induce participants habituated to the tDCS-induced feelings on the scalp. During 20-min tDCS (or sham), the participant simultaneously practiced occupational therapist-led UE tasks, including shoulder and scapular movements, elbow flexion and extension, forearm supination and pronation, wrist movements, or grasp and release objects, tailored to meet individualized mobility and goals following the principles of task-oriented therapy  with minimal physical support if possible. For paralyzed muscle groups, training was initiated using single-joint tasks with eliminated gravity position, followed by anti-gravity position and multi-joint tasks when possible. The researchers (SPH and IJK) were responsible for the administration of tDCS intervention at the bedside and interviewing participants for any adverse events . Afterwards, all inpatients received 90-min sessions of regular conventional therapy twice daily, including occupational therapy (UE range of motion exercise and strengthening, hand skill training, and balance training) and physical therapy (lower extremity mobility and strengthening, aerobic exercise, and gait training) before discharge.
Primary and secondary outcomes
Based on the tDCS target of UE M1 with electrode locations over C3 and C4, the primary efficacy outcome was the change in FMA-UE scores assessing UE mobility , including a proximal subscale (0–42) for the shoulder/elbow/forearm and a distal subscale (0–24) for the wrist/hand. The minimal clinically important difference (MCID) for change in FMA-UE has been suggested as 10 points after intervention , which we used to define treatment responders . The secondary outcomes included changes in the Action Research Arm Test (ARAT) assessing UE activity (0–57, maximum score 57) , Fugl-Meyer Assessment of Lower Extremity (FMA-LE) for lower extremity mobility (0–34, maximum score 34) , mRS for global function after stroke (0–6) , and resting-state FC of the target network after intervention (see below). The FMA-LE was assessed for the occurrence of off-target effects. All above measurements were administered at three timepoints: pre-intervention baseline (T1), immediately post-intervention (T2), and three months post-stroke (T3) (Fig. 2A).
For the safety outcome, the Adverse Effects Questionnaire was used after each tDCS session, which includes 11 questions about occurrence of headache, neck pain, scalp pain, tingling, itching, burning sensation, skin redness, sleepiness, trouble concentrating, acute mood change, or other specified conditions .
Brain MRI and resting-state fMRI acquisition and preprocessing
Brain images were acquired with a 3.0-T GE Discovery 750 MRI scanner (GE Healthcare, Chicago, IL). Participants were asked to keep their eyes open without thinking or moving during the scan. A standard head coil (eight channels) with foam padding was used to restrict head motion. All imaging was acquired along the anterior–posterior commissural plane, as identified by multiplanar T1-weighted BRAVO anatomical images (repetition time, 12.2 ms; echo time, 5.2 ms; flip angle, 12°; voxel size, 1 × 1 × 1 mm3; field of view 256 × 256 mm2). For resting-state fMRI, blood oxygenation level-dependent (BOLD) signals from a task-free run were recorded with a T2* gradient-echo echo-planar imaging sequence (repetition time/echo time, 3000/30 ms; flip angle, 90°; field of view, 222 × 222 mm2; matrix size, 64 × 64; slice thickness, 3 mm; 47 slices; 124 volumes) as previously described . The aforementioned scanning time was approximately 15 min. Participants were scanned at the aforementioned three timepoints if available (Fig. 2A).
Briefly, the fMRI data were preprocessed with Statistical Parametric Mapping (SPM12; https://www.fil.ion.ucl.ac.uk/spm/) in the following order: correction of slice timing (the 47th slice as reference), realignment to the mean image for correcting head motion with a 6-parameter rigid-body transformation, flipping realigned BOLD images and anatomical T1 images for those with left hemispheric strokes to the right, coregistration of the mean BOLD image to the anatomical image, spatial normalization to the Asian brain template with affine registration, and smoothing using a 6-mm full-width half-maximum Gaussian kernel. The first four volumes of BOLD images were discarded from the subsequent analyses. Nuisance signals, including the six head movement parameters, the mean signal of cerebrospinal fluid, white matter, and global signal, were regressed out from the smoothed images, and low-frequency signals (0.01–0.1 Hz) were extracted using MATLAB software (2018b; Mathworks, Natick, MA) and an in-house scripts .
Target regions of interest and seed-based analysis of functional connectivity
A region of interest (ROI)-to-ROI approach was adopted to investigate the resting-state sensorimotor network primarily. Twelve ROIs (with corresponding MNI coordinates) with 6-mm radii were predefined for the paretic hand representation from a meta-analysis of movement-related fMRI in 472 patients with various impairment from acute to chronic phase after ischemic stroke , including contralesional M1 (cM1, − 38, − 24, 58), ipsilesional M1 (iM1, 42, − 14, 52), contralesional S1 (cS1; − 36, − 30, 60), ipsilesional S1 (iS1; 40, − 28, 52), contralesional supplementary motor area (cSMA; − 4, − 6, 54), ipsilesional SMA (iSMA; 4, − 6, 54), contralesional dorsolateral premotor cortex (cPMd; − 42, − 10, 58), ipsilesional PMd (iPMd; 42, − 6, 56), contralesional ventrolateral premotor cortex (cPMv; − 46, − 10, 48), ipsilesional PMv (iPMv; 42, − 6, 48), contralesional anterior intraparietal sulcus (cIPS; − 42, − 40, 50), and ipsilesional IPS (iIPS; 42, − 40, 50). The 12 cortical ROIs were not overlapped with any subcortical lesions. Hence, we didn’t remove lesion voxels from individual ROIs. The averaged BOLD signals of all voxels in each ROI were extracted and ROI pairwise associations were calculated using Pearson’s correlation coefficients (r; 66 pairs in total among 12 ROIs). The FC strength between each ROI pair was then calculated as the transformed r-values (i.e. z-scores) using Fisher r-to-z transformation. The FC between ROIs was expressed as “FCROI-ROI” and FC changes as “△FCROI-ROI”. ROI pairs and their anatomical locations were visualized by means of BrainNet Viewer 1.7 (https://www.nitrc.org/projects/bnv/).
An intention-to-treat procedure was used to deal with possible missing data. Analyses were performed using SPSS 24 (IBM, Armonk, NY) and MATLAB 2018b. The demographic and baseline characteristics were compared using a 2-sample t-test, Mann–Whitney U test, or χ2 test. After the normality test, we adopted the mixed-design, repeated measures analysis of covariance (ANCOVA) to exam the time, group, and the group-by-time interaction effects on primary and secondary outcomes, using the baseline score as a covariate in the ANCOVA  with a post hoc Bonferroni correction for multiple comparisons. The effect size of experimental tDCS was estimated using eta square (η2), where the large, medium, and small effect sizes η2 were set at 0.138, 0.056, and 0.01 , respectively. In addition, patients who had no recordable baseline MEP from the paretic wrist extensors were defined as MEP-negative participants who have compromised CST integrity and relatively poor prognosis . Therefore, we conducted an MEP-negative subgroup analysis to test tDCS effects on their primary outcome using the aforementioned ANCOVA.
We performed a stepwise multivariate regression analysis to investigate the relationship between the altered functional sensorimotor network and the primary outcome of FMA-UE improvement (T2–T1 and T3–T1 as the dependent variables) in the real tDCS group and the sham group, respectively, as previously described . To avoid an overfitting model, only the altered FC (z scores with large Cohen’s f2 > 0.5) estimated by simple linear regression for FMA-UE improvements were included in the multivariate regression model with adjustment for age and sex . The performance of generated linear regression models was assessed by the goodness-of-fit (R2) and F statistic with p < 0.05 as significance. An independent variable was considered significant if p < 0.05. The amount of multicollinearity in a set of multiple regression variables was examined to remove redundant FC changes with variance inflation factor > 10 . Finally, we compared the tDCS-related connectivity changes between groups (T2–T1 and T3–T1) using the 2-sample t-test with Bonferroni correction. For intra-group changes over time, the significant regressors (FC changes) for the FMA-UE improvement from the multivariate regression model were examined using the paired t-test with Bonferroni correction.
Twenty-seven eligible participants (mean age [standard deviation]: 59.2 [11.4] years, 15 males, all right-handed, 15 with right hemispheric infarcts, mean baseline FMA-UE 31.2 [18.8]) were randomly assigned to receive real tDCS (n = 13) or sham stimulation (n = 14). All participants completed the 3-month clinical follow-up (Fig. 1). The baseline demographic and neurophysiological characteristics were comparable between groups (Table 1). Nineteen participants (70.4%; real n = 9 vs. sham n = 10) had no recordable MEP from the paretic wrist extensors across all timepoints, except for one person in the real group and one person in the sham group who regained the MEP at post-intervention and three months post-stroke, respectively. MRI showed that participants of both groups primarily had subcortical infarctions along the CST, particularly at the corona radiate and the internal capsule (n = 21), or the ventral brainstem (n = 6) (Fig. 2B).
The doses of regular rehabilitation after intervention were comparable between groups. Seven and eight participants in the real (54%) and sham (57%) groups, respectively, continued high-frequency hospitalized rehabilitation (4–5 days per week) until three months post-stroke, while the other six participants in both the real (46%) and sham (43%) groups maintained a low-to-moderate frequency of outpatient rehabilitation (≤ 3 days per week) until three months post-stroke.
Safety and blindness
All participants tolerated 20 sessions of real or sham tDCS without significant adverse events, comparable to the recent review . There were three participants in the real group and two in the sham group that reported tingling feelings, and two participants in each group reported itching. One participant receiving real tDCS showed transient redness of the scalp at the anodal site. The risks of the aforementioned events were similar between groups (p = 1.0). The success of blinding status was assessed post-intervention: two and three participants in the real and sham group, respectively, assumed themselves to be receiving a placebo.
Bihemispheric tDCS during task-oriented therapy promoted motor recovery after stroke
The primary efficacy outcome of FMA-UE improvements showed significant time effect (p < 0.001), group effect (p < 0.001) and group-by-time interaction effect (p < 0.001, η2 = 0.327) (Table 2). After a post hoc analysis, the real tDCS group demonstrated greater increases in FMA-UE scores after the 2-week intervention (mean difference [95% confidence interval]: real 13.5 [9.1–17.8] vs. sham 8.4 [5.8–10.5]; p = 0.018, η2 = 0.211) and at three months post-stroke (real 19.1 [15.9–22.2] vs. sham 9.4 [6.3–12.5]; p < 0.001, η2 = 0.522), respectively, than the sham group (Fig. 3A, B). Notably, in the MEP-negative subgroup analysis (real n = 9 vs. sham n = 10), their FMA-UE improvements also showed significant time effect (p < 0.001), group effect (p = 0.004), and group-by-time effects (p = 0.002, η2 = 0.332). The real tDCS MEP-negative subgroup had a greater long-term improvement at three months post-stroke compared with the sham MEP-negative subgroup (real 18.9 [14.9–22.8] vs. sham 8.1 [4.4–11.8]; p < 0.001, η2 = 0.545), but not immediately after the 2-week intervention (real 11.3 [7.1–15.5] vs. sham 6.9 [2.9–10.9]; p = 0.156, η2 = 0.122), with a reduced sample size and power. Overall, the real group had a higher probability of being responders after intervention (real 76.9% vs. sham 35.7%; p = 0.031) and sustained the effect until 3 months post-stroke (real 100% vs. sham 50%; p = 0.012) (Fig. 3B).
The secondary outcome of ARAT improvements showed significant time effect (p = 0.002) and group effect (p = 0.012), but not group-by-time interaction effect (p = 0.062) with a medium effect size (η2 = 0.122, Table 2). Both groups had significant ARAT improvements in parallel after the 2-week intervention (mean difference [95% confidence interval]: real 11.9 [7.1–16.7] vs sham 5.9 [2.9–9]; group difference: p = 0.004, η2 = 0.294) and at 3 months post-stroke (real 17.2 [12.2–22.2] vs sham 10.3 [4.2–16.4]; group difference: p = 0.06, η2 = 0.139). However, the inter-group difference at three months post-stroke became insignificant, which needs further and larger studies (Fig. 3C, D). Likewise, the secondary outcome of FMA-LE improvements exhibited significant time effect (p < 0.001), group effect (p = 0.007) and group-by-time interaction effect (p = 0.013, η2 = 0.165, Table 2). Compared with the sham group, the real tDCS group didn’t have greater increases in FMA-LE scores after the intervention (real 7.2 [5–9.3] vs. sham 4.8 [2.8–6.8]; p = 0.06, η2 = 0.139) until at 3 months post-stroke (real 9.9 [7–12.7] vs. sham 6.3 [4–8.6]; p = 0.006, η2 = 0.276, Fig. 3E, F), suggesting an indirect off-target effect. Although 100% of the participants after real tDCS had a favorable outcome (mRS 0–2) at three months in comparison to 76.9% of the sham group, there was no significant intergroup difference in the proportion (p = 0.25).
Individual FMA-UE improvements after tDCS were associated with bilateral intrahemispheric, rather than interhemispheric, connectivity changes
Of the 27 participants, 23 (real 12 vs. sham 11) received baseline fMRI, 21 (real 11 vs. sham 10) completed the post-intervention scanning, and 19 (real nine vs. sham ten) finished the follow-up scanning. Dropouts for fMRI were due to claustrophobia, the COVID-19 pandemic, or technical problems. The baseline characteristics of the 23 patients who underwent fMRI did not differ from those of the 27 patients (p = 0.15–1.0), and there was no baseline difference between groups in the 23 patients. Among them, the significant time, group, and group-by-time effects remained (all p ≦ 0.001). Real tDCS group had greater FMA-UE improvements after the 2-week intervention (13.2 [9.4–16.7] vs. sham 7.6 [3.8–11.5]; p = 0.018) and at three months post-stroke (18.9 [15.7–22.2] vs. sham 8.5 [5.1–11.8]; p < 0.001), respectively. The FC analyses in the reduced subpopulation should therefore be representative of all 27 patients in this study.
On the individual-level of the tDCS-induced after effects, we linearly correlated 66 pairs of FC changes (△FC) with the concurrent FMA-UE changes, including 12 ROIs in the sensorimotor network (Fig. 4A) using stepwise multivariate regression analyses (Table 3, exclusion details of insignificant FC are listed in the Additional file 1: Table S1). Interestingly, after the 2-week real tDCS, individual △FCcM1-cS1 and △FCiM1-iS1 were positively and synergistically correlated with their FMA-UE improvement, which jointly explained 72% of the variance of UE motor recovery (adjusted R2 = 0.72, p = 0.005, Fig. 4B). By contrast, after the 2-week sham tDCS, only the ipsilesional △FCiS1-iIPS was negatively correlated with their FMA-UE improvement (adjusted R2 = 0.45, p = 0.02), and additionally including age as an independent factor increased the prediction accuracy to 70% (adjusted R2 = 0.70, p = 0.006, Fig. 4B). The results suggest that spontaneous recovery following task training alone was related to age and ipsilesional connectivity changes, while enhanced recovery after concurrent bihemispheric tDCS likely involved intrahemispheric FC in bilateral hemispheres rather than interhemispheric FC changes. At three months post-stroke, individual △FCcS1-cPMd and △FCiPMv-iIPS after real tDCS were correlated with long-term FMA-UE improvement (adjusted R2 = 0.95, p = 0.00005, Fig. 4C), while only individual △FCiM1-iPMd after sham tDCS was correlated with FMA-UE recovery (adjusted R2 = 0.68, p = 0.002). Age and sex did not significantly influence UE recovery at this phase.
At the group level, there were no intergroup differences in FCiM1-iS1, FCcM1-cS1, FCiM1-cM1, FCiS1-iIPS, FCcS1-cPMd, FCiPMv-iIPS, or FCiM1-iPMd at baseline (Additional file 1: Table S2) after correction (all uncorrected p = 0.038–0.984, corrected threshold = 0.007). Also, there were no significant intragroup changes in △FCiM1-iS1, △FCcM1-cS1, △FCiM1-cM1, △FCiS1-iIPS, △FCcS1-cPMd, △FCiPMv-iIPS, or △FCiM1-iPMd over time after correction (all uncorrected p = 0.014–0.47, corrected threshold = 0.003), nor were there intergroup differences in the above FC changes after correction (all uncorrected p = 0.023–0.971, corrected threshold = 0.003, Additional file 1: Table S2), which were likely attributed to the small sample size and large inter-individual variations.
We demonstrated that, for the first time, concurrent bihemispheric tDCS during task-oriented training conferred benefits on motor recovery of the paretic UE, compared to sham stimulation in early subacute stroke patients. These individual UE improvements were associated with bilateral intrahemispheric FC changes in the targeted motor network. However, there was high variability of individual FC changes and no significant difference between groups. The results suggest that the neural circuits involved in tDCS-related subacute recovery are likely reorganized in the bilateral cortices. Importantly, our RCT of bihemispheric tDCS stratified patients according to the residual CST integrity, a prognostic biomarker for motor recovery . Among the patients with compromised CST integrity (MEP-negative), the real tDCS group showed greater but delayed UE improvement than the sham group at three months post-stroke. The subcortical or brainstem infarctions along the CST may be compensated by circuits elsewhere in the sensorimotor network. Although the compensatory role of the contralesional M1 for or against interhemispheric competition remains elusive, depending on stroke severity and the ipsilesional CST integrity, early bihemispheric tDCS may promote immediate and lasting motor recovery after stroke.
Our findings of bihemispheric tDCS for UE motor recovery are in line with previous studies in chronic stroke patients [17, 21, 31]. Lindenberg et al. . and Alisar et al. . found that, using 5–15 sessions of similar bihemispheric tDCS settings during conventional therapy in chronic patients after three months post-stroke, the FMA-UE improvement rate was 20.7–35.2% (vs. 3.2–6.6% with sham stimulation) from baseline. In the present study with subacute patients around one-month post-stroke, the FMA-UE improvement rate after real tDCS was 42.5% (vs. 27.5% with sham stimulation) and it increased to 62.4% (vs. 29.6% with sham stimulation) at three months post-stroke. Furthermore, immediately after real tDCS, the mean FMA-UE improvement reached MCID (13.5), in contrast to those after sham tDCS (8.4). Taken together, our study implies that applying bihemispheric tDCS may safely augment the effects of subacute stroke rehabilitation, particularly clinically meaningful UE improvement.
The effect of bihemispheric tDCS on ARAT was not as prominent as FMA-UE, although there was greater improvement of ARAT immediately after real tDCS compared with sham tDCS. One explanation could be that ARAT has stronger floor effect and ceiling effect than FMA-UE in acute and subacute stroke patients [52, 53]. In other words, it renders ARAT unable to discriminate participants at either extreme of the scale. The ARAT items require more integral UE function of reaching and grasping compared to FMA-UE . Specifically, a larger sample of 30 participants is recommended according to our estimated effect size (η2 = 0.122).
The mechanisms of bihemispheric tDCS for motor recovery in subacute stroke patients remain unclear. In our analysis of functional networks underlying motor recovery, bihemispheric tDCS-induced individual UE improvements were associated with intrahemispheric FCiM1-iS1 and FCcM1-cS1 changes bilaterally, while spontaneous UE improvements after sham stimulation were associated with ipsilesional FCiS1-iIPS changes. These findings indicate that motor network reorganization at the near-stimulated regions possibly play a role of bihemipheric tDCS effects. In healthy subjects, bihemispheric tDCS over the M1s during a motor task has been shown to enhance motor learning accompanied by similarly increased BOLD signals  and regional cerebral blood flow  at the bilateral peri-rolandic regions. However, we did not observe significant inter-group differences of the FC changes following bihemispheric tDCS. Previous stroke studies have suggested that the increased resting-state interhemispheric FCiM1-cM1 positively correlated with spontaneous motor recovery after stroke [35,36,37]. Our patient selection of moderate-to-severe UE paresis with mostly compromised CST integrity  in early subacute stage  could partly explain this discrepancy.
There are limitations of this study. First, because of the enrollment criteria for relatively homogenous stroke patients, the small sample size weakened external validity and further resting-state FC changes and subgroup analysis of tDCS responsiveness by patient-specific factors [26, 33, 59]. It should be cautious to interpret our findings. However, we found that our protocol might have a delayed long-term benefit on UE motor recovery for patients with compromised CST integrity (MEP-negative). The MEP status assessment was performed using a biphasic waveform pulse with a Magstim Rapid2 system. An approach to verify the ipsilesional CST integrity might be to explore CST lesion load or fractional anisotropy to provide further confidence in the results [59, 60]. Second, the target ROI-based analysis might underestimate FC changes outside the ROIs, and the inter-individual difference in stroke lesions may mask the modulatory effect of tDCS on resting-state FC . Further studies in large patient samples for the tDCS mechanisms are warranted. Finally, the 10–20 system anatomical landmarks for tDCS electrode positions (C3 and C4) may not be optimal for MEP-negative patients. Patient-tailored targets for tDCS modulation in those with compromised CST integrity needs to be further characterized. Movement-related electroencephalogram or functional near-infrared spectroscopy could be considered to guide electrode positions close to the hotspot .
In summary, bihemispheric tDCS is a promising approach in combination with task-oriented training for facilitating motor recovery in subacute stroke patients, including those with compromised residual CST integrity. The neural underpinnings of simultaneous neuromodulation of bilateral M1s might be mediated by intrahemispheric connectivity reorganization of the bilateral sensorimotor network. Further studies are required to validate the current findings.
Availability of data and materials
The dataset used during this study are available from the corresponding author on reasonable request.
Transcranial direct current stimulation
Primary motor cortex
Fugl-Meyer Assessment of Upper Extremity
Action Research Arm Test
Fugl-Meyer Assessment of Lower Extremity
Randomized controlled trial
Functional magnetic resonance imaging
Modified Rankin Scale
Transcranial magnetic stimulation
Minimal clinical important difference
Three months post-stroke
Blood oxygenation level-dependent
Region of interest
Contralesional/ipsilesional primary motor cortex
Contralesional/ipsilesional primary somatosensory cortex
Contralesional/ipsilesional supplementary motor area
Contralesional/ipsilesional dorsolateral premotor cortex
Contralesional/ipsilesional ventrolateral premotor cortex
Contralesional/ipsilesional intraparietal sulcus
Analysis of covariance
Mazzoleni S, Tran V-D, Dario P, Posteraro F. Effects of transcranial direct current stimulation (tDCS) combined with wrist robot-assisted rehabilitation on motor recovery in subacute stroke patients: a randomized controlled trial. IEEE Trans Neural Syst Rehabil Eng. 2019;27:1458–66.
Hesse S, Waldner A, Mehrholz J, Tomelleri C, Pohl M, Werner C. Combined transcranial direct current stimulation and robot-assisted arm training in subacute stroke patients: an exploratory, randomized multicenter trial. Neurorehabil Neural Repair. 2011;25:838–46.
Bolognini N, Russo C, Souza Carneiro MI, Nicotra A, Olgiati E, Spandri V, et al. Bi-hemispheric transcranial direct current stimulation for upper-limb hemiparesis in acute stroke: a randomized, double-blind, sham-controlled trial. Eur J Neurol. 2020;27:2473–82
Bornheim S, Croisier JL, Maquet P, Kaux JF. Transcranial direct current stimulation associated with physical-therapy in acute stroke patients—a randomized, triple blind, sham-controlled study. Brain Stimul. 2020;13:329–36.
Di Lazzaro V, Dileone M, Capone F, Pellegrino G, Ranieri F, Musumeci G, et al. Immediate and late modulation of interhemipheric imbalance with bilateral transcranial direct current stimulation in acute stroke. Brain Stimul. 2014;7:841–8.
Nitsche MA, Paulus W. Excitability changes induced in the human motor cortex by weak transcranial direct current stimulation. J Physiol. 2000;527(Pt 3):633–9.
Jamil A, Batsikadze G, Kuo HI, Labruna L, Hasan A, Paulus W, et al. Systematic evaluation of the impact of stimulation intensity on neuroplastic after-effects induced by transcranial direct current stimulation. J Physiol. 2017;595:1273–88.
Mosayebi Samani M, Agboada D, Jamil A, Kuo MF, Nitsche MA. Titrating the neuroplastic effects of cathodal transcranial direct current stimulation (tDCS) over the primary motor cortex. Cortex. 2019;119:350–61.
Batsikadze G, Moliadze V, Paulus W, Kuo MF, Nitsche MA. Partially non-linear stimulation intensity-dependent effects of direct current stimulation on motor cortex excitability in humans. J Physiol. 2013;591:1987–2000.
Shilo G, Lavidor M. Non-linear effects of cathodal transcranial direct current stimulation (tDCS) of the primary motor cortex on implicit motor learning. Exp Brain Res. 2019;237:919–25.
McDonnell MN, Stinear CM. TMS measures of motor cortex function after stroke: a meta-analysis. Brain Stimul. 2017;10:721–34.
van Assche M, Dirren E, Bourgeois A, Kleinschmidt A, Richiardi J, Carrera E. Periinfarct rewiring supports recovery after primary motor cortex stroke. J Cereb Blood Flow Metab. 2021;41:2174–84.
Rehme AK, Eickhoff SB, Rottschy C, Fink GR, Grefkes C. Activation likelihood estimation meta-analysis of motor-related neural activity after stroke. Neuroimage. 2012;59:2771–82.
Rehme AK, Eickhoff SB, Wang LE, Fink GR, Grefkes C. Dynamic causal modeling of cortical activity from the acute to the chronic stage after stroke. Neuroimage. 2011;55:1147–58.
Takechi U, Matsunaga K, Nakanishi R, Yamanaga H, Murayama N, Mafune K, et al. Longitudinal changes of motor cortical excitability and transcallosal inhibition after subcortical stroke. Clin Neurophysiol. 2014;125:2055–69.
Van Hoornweder S, Vanderzande L, Bloemers E, Verstraelen S, Depestele S, Cuypers K, et al. The effects of transcranial direct current stimulation on upper-limb function post-stroke: a meta-analysis of multiple-session studies. Clin Neurophysiol. 2021;132:1897–918.
Lindenberg R, Renga V, Zhu LL, Nair D, Schlaug G. Bihemispheric brain stimulation facilitates motor recovery in chronic stroke patients. Neurology. 2010;75:2176–84.
Bolognini N, Vallar G, Casati C, Latif LA, El-Nazer R, Williams J, et al. Neurophysiological and behavioral effects of tDCS combined with constraint-induced movement therapy in poststroke patients. Neurorehabil Neural Repair. 2011;25:819–29.
Straudi S, Fregni F, Martinuzzi C, Pavarelli C, Salvioli S, Basaglia N. tDCS and robotics on upper limb stroke rehabilitation: effect modification by stroke duration and type of stroke. Biomed Res Int. 2016;2016:5068127.
Beaulieu LD, Blanchette AK, Mercier C, Bernard-Larocque V, Milot MH. Efficacy, safety, and tolerability of bilateral transcranial direct current stimulation combined to a resistance training program in chronic stroke survivors: a double-blind, randomized, placebo-controlled pilot study. Restor Neurol Neurosci. 2019;37:333–46.
Alisar DC, Ozen S, Sozay S. Effects of bihemispheric transcranial direct current stimulation on upper extremity function in stroke patients: a randomized double-blind sham-controlled study. J Stroke Cerebrovasc Dis. 2020;29: 104454.
Klomjai W, Aneksan B, Chotik-Anuchit S, Jitkaew P, Chaichanudomsuk K, Piriyaprasarth P, et al. Effects of different montages of transcranial direct current stimulation on haemodynamic responses and motor performance in acute stroke: a randomized controlled trial. J Rehabil Med. 2022;54:jrm00331.
Garrido MM, Alvarez EE, Acevedo PF, Moyano VA, Castillo NN, Cavada ChG. Early transcranial direct current stimulation with modified constraint-induced movement therapy for motor and functional upper limb recovery in hospitalized patients with stroke: a randomized, multicentre, double-blind, clinical trial. Brain Stimul. 2023;16:40–7.
Murphy TH, Corbett D. Plasticity during stroke recovery: from synapse to behaviour. Nat Rev Neurosci. 2009;10:861–72.
Hordacre B, Austin D, Brown KE, Graetz L, Parees I, De Trane S, et al. Evidence for a window of enhanced plasticity in the human motor cortex following ischemic stroke. Neurorehabil Neural Repair. 2021;35:307–20.
Hordacre B, McCambridge AB, Ridding MC, Bradnam LV. Can transcranial direct current stimulation enhance poststroke motor recovery? development of a theoretical patient-tailored model. Neurology. 2021;97:170–80.
Byblow WD, Stinear CM, Barber PA, Petoe MA, Ackerley SJ. Proportional recovery after stroke depends on corticomotor integrity. Ann Neurol. 2015;78:848–59.
Kemlin C, Moulton E, Lamy JC, Houot M, Valabregue R, Leder S, et al. Elucidating the structural and functional correlates of upper-limb poststroke motor impairment. Stroke. 2019;50:3647–9.
Edwards DJ, Cortes M, Rykman-Peltz A, Chang J, Elder J, Thickbroom G, et al. Clinical improvement with intensive robot-assisted arm training in chronic stroke is unchanged by supplementary tDCS. Restor Neurol Neurosci. 2019;37:167–80.
Powell ES, Westgate PM, Goldstein LB, Sawaki L. Absence of motor-evoked potentials does not predict poor recovery in patients with severe-moderate stroke: an exploratory analysis. Arch Rehabil Res Clin Transl. 2019;1: 100023.
Goodwill AM, Teo WP, Morgan P, Daly RM, Kidgell DJ. Bihemispheric-tDCS and upper limb rehabilitation improves retention of motor function in chronic stroke: a pilot study. Front Hum Neurosci. 2016;10:258.
Chhatbar PY, Ramakrishnan V, Kautz S, George MS, Adams RJ, Feng W. Transcranial direct current stimulation post-stroke upper extremity motor recovery studies exhibit a dose-response relationship. Brain Stimul. 2016;9:16–26.
Kuo IJ, Tang CW, Tsai YA, Tang SC, Lin CJ, Hsu SP, et al. Neurophysiological signatures of hand motor response to dual-transcranial direct current stimulation in subacute stroke: a TMS and MEG study. J Neuroeng Rehabil. 2020;17:72.
Allman C, Amadi U, Winkler AM, Wilkins L, Filippini N, Kischka U, et al. Ipsilesional anodal tDCS enhances the functional benefits of rehabilitation in patients after stroke. Sci Transl Med. 2016;8:330re1.
Carter AR, Astafiev SV, Lang CE, Connor LT, Rengachary J, Strube MJ, et al. Resting interhemispheric functional magnetic resonance imaging connectivity predicts performance after stroke. Ann Neurol. 2010;67:365–75.
Lee J, Park E, Lee A, Chang WH, Kim DS, Kim YH. Alteration and role of interhemispheric and intrahemispheric connectivity in motor network after stroke. Brain Topogr. 2018;31:708–19.
Zhang Y, Liu H, Wang L, Yang J, Yan R, Zhang J, et al. Relationship between functional connectivity and motor function assessment in stroke patients with hemiplegia: a resting-state functional MRI study. Neuroradiology. 2016;58:503–11.
Fugl-Meyer AR, Jaasko L, Leyman I, Olsson S, Steglind S. The post-stroke hemiplegic patient. 1. A method for evaluation of physical performance. Scand J Rehabil Med. 1975;7:13–31.
Scott NW, McPherson GC, Ramsay CR, Campbell MK. The method of minimization for allocation to clinical trials. A review. Control Clin Trials. 2002;23:662–74.
van der Vliet R, Selles RW, Andrinopoulou ER, Nijland R, Ribbers GM, Frens MA, et al. Predicting upper limb motor impairment recovery after stroke: a mixture model. Ann Neurol. 2020;87:383–93.
Hubbard IJ, Parsons MW, Neilson C, Carey LM. Task-specific training: evidence for and translation to clinical practice. Occup Ther Int. 2009;16:175–89.
Brunoni AR, Amadera J, Berbel B, Volz MS, Rizzerio BG, Fregni F. A systematic review on reporting and assessment of adverse effects associated with transcranial direct current stimulation. Int J Neuropsychopharmacol. 2011;14:1133–45.
Arya KN, Verma R, Garg RK. Estimating the minimal clinically important difference of an upper extremity recovery measure in subacute stroke patients. Top Stroke Rehabil. 2011;18(Suppl 1):599–610.
Lyle RC. A performance test for assessment of upper limb function in physical rehabilitation treatment and research. Int J Rehabil Res. 1981;4:483–92.
van Swieten JC, Koudstaal PJ, Visser MC, Schouten HJ, van Gijn J. Interobserver agreement for the assessment of handicap in stroke patients. Stroke. 1988;19:604–7.
Cheng HL, Lin CJ, Soong BW, Wang PN, Chang FC, Wu YT, et al. Impairments in cognitive function and brain connectivity in severe asymptomatic carotid stenosis. Stroke. 2012;43:2567–73.
Lin BF, Yeh SC, Kao YCJ, Lu CF, Tsai PY. Functional remodeling associated with language recovery after repetitive transcranial magnetic stimulation in chronic aphasic stroke. Front Neurol. 2022;13: 809843.
Portney L, Watkins MP. Foundations of clinical research: applications to practice. 3rd ed. Upper Saddle River, NJ: Pearson/Prentice Hall; 2009.
Cohen J. Statistical power analysis for the behavioral sciences. 2nd ed. New York: Routledge; 1988.
Cohen J, Cohen P, West SG, Aiken LS. Apllied multiple regession/correlation analysis for the behavioral sciences. 3rd ed. Hillsdale, N.J.: Lawrence Erlbaum; 2003.
Russo C, Souza Carneiro MI, Bolognini N, Fregni F. Safety review of transcranial direct current stimulation in stroke. Neuromodulation. 2017;20:215–22.
Lin JH, Hsu MJ, Sheu CF, Wu TS, Lin RT, Chen CH, et al. Psychometric comparisons of 4 measures for assessing upper-extremity function in people with stroke. Phys Ther. 2009;89:840–50.
Rabadi MH, Rabadi FM. Comparison of the action research arm test and the Fugl-Meyer assessment as measures of upper-extremity motor weakness after stroke. Arch Phys Med Rehabil. 2006;87:962–6.
Alt Murphy M, Willen C, Sunnerhagen KS. Movement kinematics during a drinking task are associated with the activity capacity level after stroke. Neurorehabil Neural Repair. 2012;26:1106–15.
Waters S, Wiestler T, Diedrichsen J. Cooperation not competition: bihemispheric tDCS and fMRI show role for ipsilateral hemisphere in motor learning. J Neurosci. 2017;37:7500–12.
Shinde AB, Lerud KD, Munsch F, Alsop DC, Schlaug G. Effects of tDCS dose and electrode montage on regional cerebral blood flow and motor behavior. Neuroimage. 2021;237: 118144.
Carter AR, Patel KR, Astafiev SV, Snyder AZ, Rengachary J, Strube MJ, et al. Upstream dysfunction of somatomotor functional connectivity after corticospinal damage in stroke. Neurorehabil Neural Repair. 2012;26:7–19.
Chen JL, Schlaug G. Increased resting state connectivity between ipsilesional motor cortex and contralesional premotor cortex after transcranial direct current stimulation with physical therapy. Sci Rep. 2016;6:23271.
Lindenberg R, Zhu LL, Ruber T, Schlaug G. Predicting functional motor potential in chronic stroke patients using diffusion tensor imaging. Hum Brain Mapp. 2012;33:1040–51.
Feng W, Wang J, Chhatbar PY, Doughty C, Landsittel D, Lioutas VA, et al. Corticospinal tract lesion load: An imaging biomarker for stroke motor outcomes. Ann Neurol. 2015;78:860–70.
Nomura EM, Gratton C, Visser RM, Kayser A, Perez F, D’Esposito M. Double dissociation of two cognitive control networks in patients with focal brain lesions. Proc Natl Acad Sci U S A. 2010;107:12017–22.
Chang PW, Lu CF, Chang ST, Tsai PY. Functional near-infrared spectroscopy as a target navigator for rTMS modulation in patients with hemiplegia: a randomized control study. Neurol Therapy. 2022;11:103–21.
We thank all the participants of the study, and also like to thank our case manager Tzu-Ching Liu, the Pervasive Artificial Intelligence Research Lab, and the Clinical Research Core Laboratory for providing assistance, facilities and collecting stroke registry data, respectively.
This work was supported by the Taiwan Ministry of Science and Technology (MOST, 110-2320-B-075-002, 110-2634-F-008-007, 111-2320-B-075-010), the Taipei Veterans General Hospital (V109C-034, V110C-124, V111C-213, V112C-036), and the National Yang Ming Chiao Tung University (111W32408) from The Featured Areas Research Center Program within the framework of the Higher Education Sprout Project by the Taiwan Ministry of Education.
Ethics approval and consent to participate
This study was approved by the Institutional Review Board at the Taipei Veterans General Hospital (VGHIRB No. 2015-03-003C) and all participants provided written informed consent prior to participation.
Consent for publication
All the authors approved the publication of the article.
Dr. I-Hui Lee reports grants from the Taiwan Ministry of Science and Technology, the Taipei Veterans General Hospital, and the National Yang Ming Chiao Tung University during the conduct of the study. Dr. Kuo-Kai Shyu reports grants from government funding for the Pervasive Artificial Intelligence Research Lab, related to this work. The remaining authors have no potential conflicts to disclose.
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Additional file 1: Table S1.
The complementary information to Table 3 of insignificant functional connectivities after real or sham transcranial direct current stimulation (tDCS) in relation to individual FMA-UE improvements. They were excluded from the stepwise multivariate regression model by the level of significance. Table S2. Comparisons of resting-state functional connectivity (FC) changes at the transcranial direct current stimulation (tDCS)-related sensori-motor cortex after real versus sham intervention.
Rights and permissions
Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
About this article
Cite this article
Hsu, SP., Lu, CF., Lin, BF. et al. Effects of bihemispheric transcranial direct current stimulation on motor recovery in subacute stroke patients: a double-blind, randomized sham-controlled trial. J NeuroEngineering Rehabil 20, 27 (2023). https://doi.org/10.1186/s12984-023-01153-4
- Functional connectivity
- Upper extremity