Theta burst stimulation for enhancing upper extremity motor functions after stroke: a systematic review of clinical and mechanistic evidence
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Jack Jiaqi Zhang
,
Youxin Sui
Abstract
This systematic review aimed to evaluate the effects of different theta burst stimulation (TBS) protocols on improving upper extremity motor functions in patients with stroke, their associated modulators of efficacy, and the underlying neural mechanisms. We conducted a meta-analytic review of 29 controlled trials published from January 1, 2000, to August 29, 2023, which investigated the effects of TBS on upper extremity motor, neurophysiological, and neuroimaging outcomes in poststroke patients. TBS significantly improved upper extremity motor impairment (Hedge’s g = 0.646, p = 0.003) and functional activity (Hedge’s g = 0.500, p < 0.001) compared to controls. Meta-regression revealed a significant relationship between the percentage of patients with subcortical stroke and the effect sizes of motor impairment (p = 0.015) and functional activity (p = 0.018). Subgroup analysis revealed a significant difference in the improvement of upper extremity motor impairment between studies using 600-pulse and 1200-pulse TBS (p = 0.002). Neurophysiological studies have consistently found that intermittent TBS increases ipsilesional corticomotor excitability. However, evidence to support the regional effects of continuous TBS, as well as the remote and network effects of TBS, is still mixed and relatively insufficient. In conclusion, TBS is effective in enhancing poststroke upper extremity motor function. Patients with preserved cortices may respond better to TBS. Novel TBS protocols with a higher dose may lead to superior efficacy compared with the conventional 600-pulse protocol. The mechanisms of poststroke recovery facilitated by TBS can be primarily attributed to the modulation of corticomotor excitability and is possibly caused by the recruitment of corticomotor networks connected to the ipsilesional motor cortex.
1 Introduction
Theta burst stimulation (TBS), originally used as a neuroplasticity-induction paradigm to modulate the activity of hippocampal neurons, was first introduced for research on human motor plasticity in 2005 (Huang and Rothwell 2004; Huang et al. 2005). TBS has the advantage of short conditioning duration and has comparable neuromodulatory effects to conventional repetitive transcranial magnetic stimulation protocols. TBS has been increasingly utilized in neurorehabilitation, particularly in cases of poststroke hemiparetic upper-extremity rehabilitation (Lefaucheur et al. 2020). In 2007, an experimental study by Talelli et al. showed that intermittent TBS (iTBS) and continuous TBS (cTBS) had a robust effect on modulating corticospinal excitability and behavioral motor learning in patients who had suffered a stroke (Talelli et al. 2007). In clinical trials, TBS is now frequently used for stimulation-based brain priming before rehabilitation intervention to improve the readiness of the brain to re-learn motor skills during behavioral motor practice, thereby facilitating therapeutic benefits from rehabilitation training for patients after stroke (Cassidy et al. 2014).
Systematic reviews published on the effects of TBS on poststroke upper extremity motor functions generally report positive effects of TBS in promoting hemiparetic upper extremity functions (Chen et al. 2023; Gao et al. 2022; Huang et al. 2022; Tang et al. 2022; Xiang et al. 2019; Zhang et al. 2017). However, these reviews consistently have methodological limitations that need to be addressed. First, several articles mixed different outcomes in the meta-analysis, such as finger-tapping speed and clinical scores (Tang et al. 2022; Xiang et al. 2019; Zhang et al. 2017). Combining norms-based behavioral tests with performance-based clinical measures is unlikely to yield robust results (Moayyedi 2004). The responsiveness of these measures differed significantly, making it inappropriate to use the pooled effect size as a reference for clinical efficacy. Second, most of the systematic reviews used post-treatment scores rather than improvement scores in the meta-analyses of continuous variables (Chen et al. 2023; Huang et al. 2022; Tang et al. 2022; Xiang et al. 2019). This issue has been investigated in a study by Chhatbar et al., in which the results of a meta-analysis using postscores were not consistent because baseline differences were neglected when using postscores alone in the meta-analysis (Chhatbar et al. 2016). Third, the influence of possible modulators of efficacy, such as patient demographics and clinical profiles as well as the parameters of TBS protocols, on the effect sizes in association with TBS remains largely unexplored. These critical issues that previous meta-analytic reviews have not adequately addressed should be resolved through subgroup analyses and meta-regression. Finally, previous systematic reviews focused on clinical measures and ignored neuroimaging and neurophysiological outcomes, except for a few articles that reviewed TMS–electromyography (EMG) (Chen et al. 2023; Tang et al. 2022; Xiang et al. 2019). However, the neural mechanisms underlying the effects of TBS on poststroke rehabilitation have not been sufficiently described. Therefore, a comprehensive understanding of the neural mechanisms that explain the therapeutic benefits of TBS in poststroke rehabilitation, in terms of its regional, remote, and network effects, is needed.
The current meta-analytic review aims to (1) evaluate the effects of different TBS protocols on improving upper extremity motor impairment and functional activities in patients with stroke; (2) identify any significant associations between various TBS parameters, patient demographics, clinical profiles, and effect sizes using subgroup analyses and meta-regression; and (3) summarize and interpret the mechanisms underlying the therapeutic effects of TBS by qualitatively assessing studies using neuroimaging and/or neurophysiological outcome measurements.
2 Methods
2.1 Literature search
This review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) (Moher et al. 2009). The protocol for this review was registered in INPLASY (INPLASY202410069) after the initial database literature search and prior to our formal data analysis. A literature search was conducted for studies published from January 1, 2000, to August 29, 2023, which were indexed in four databases: PubMed, EMBASE, Web of Science, and Medline. The keywords used to identify TBS were “theta burst,” “theta burst stimulation,” and “theta burst transcranial magnetic stimulation.” The keywords used for identifying stroke included “stroke,” “cerebrovascular accident,” and “hemiplegia.” Medical subject heading terms were used when performing the PubMed search. Two authors (JZ and YS) independently read and identified all titles and excluded irrelevant studies. In addition, the reference lists of previously published reviews were manually screened to identify relevant articles.
2.2 Inclusion and exclusion criteria
We followed the PICOS framework for the inclusion of studies, that is, studies were considered for this review if they satisfied the following criteria. Population (P): studies that included adult participants diagnosed with stroke. Intervention (I): interventions that used TBS applied to the primary motor cortex (M1) cortical representations of the proximal or distal upper extremity. Comparison (C): sham TBS or no stimulation control. Outcomes (O): studies that provided at least one outcome assessing upper limb motor impairment, functional activity, or neural functions (neurophysiological or neuroimaging outcomes). According to expert consensus, motor impairment and activity limitations are deemed primary in poststroke rehabilitation trials (Kwakkel et al. 2017). Therefore, we selected the upper extremity subscores of the Fugl-Meyer assessment (FMA-UE), which is the gold standard for evaluating upper extremity motor impairment poststroke. For measuring poststroke activity limitations, the action research arm test (ARAT) was considered. If ARAT scores were not available, the Wolf motor function test or the Jebsen–Taylor hand function test were used in the meta-analysis because these two assessments involved a series of gross and fine motor tasks that were relatively comparable to the functional tasks utilized in the ARAT (Chen et al. 2019b). A similar meta-analystic methodology has been utilized in a previous review (van Lieshout et al. 2019). Study design (S): randomized or pseudorandomized controlled trials with either a parallel or crossover design. Studies meeting any of the following criteria were excluded: (1) the study recruited participants with concomitant neurological disorders other than stroke or neurologically healthy individuals; (2) studies published as conference abstracts, dissertations, or in books; and (3) studies not published in English.
2.3 Quality assessment and data extraction
Two independent authors (JZ and YS) conducted data extraction and quality assessment of the included studies. The quality assessment was assessed using the Physiotherapy Evidence Database (PEDro) scale – a scoring system for measuring methodological reporting quality of rehabilitation trials (Bhogal et al. 2005). Discrepancies were resolved through a discussion with a third author (ZB).
2.4 Data analysis
Statistical analyses were performed using Comprehensive Meta-analysis software version 3.0. The authors were contacted by email if meta-analyzable data were missing. In the case of a lack of response from the authors, a graph digitizer (http://getdata-graph-digitizer.com/) was used to extract graphically reported data. Hedge’s g and 95 % confidence interval (CI) were computed for all meta-analyses (Higgins et al. 2003). Reported standard errors were converted to standard deviations (SD) using the formula SD = SEM × √n (n = sample size). Between-study heterogeneity was examined using Higgins I2 statistic (Higgins et al. 2003). Inverse variance method was applied in the estimation of the weight of each study. Owing to the limited number of studies with follow-up data and the heterogeneity in the length of follow-up, we only focused on the effect of TBS post-intervention in the meta-analysis. Improvement scores, i.e., post-intervention minus baseline, were used to estimate individual effect sizes to minimize the influence of baseline differences between groups (Chhatbar et al. 2016). According to Brydges (2019), effect sizes measured by Hedge’s g values of 0.15, 0.40, and 0.75 are typically interpreted as indicating small, medium, and large effects, respectively. Meta-regression analysis was performed to identify any association between effect size and TBS parameters in at least five studies per subgroup (Zhang et al. 2019). Univariate meta-regression was performed with various patients’ demographics, i.e., age and sex (expressed as the percentage of male patients), clinical information, i.e., the chronicity of stroke (mean months after stroke), the baseline severity (mean baseline severity scores), the percentage of subcortical patients, the percentage of ipsilesional motor evoked potential (MEP) positive patients, and the percentage of patients with cerebral infarction, as well as TBS parameters, including the total number of applied pulses, the number of sessions, the number of pulses per session, and stimulation intensity (presented as % resting motor threshold [RMT], action motor threshold [AMT] was transformed to RMT using 70 % RMT = 80 % AMT (Goldsworthy et al. 2012)). Meta-regression was conducted to investigate the potential association between the aforementioned variables and the weighted Hedge’s g values at the study level. Publication bias was investigated using Egger’s test. A sensitivity analysis was performed using the leave-one-out method to obtain significant results. The statistical threshold was set at p < 0.05 (two-tailed), except that a two-tailed threshold p < 0.1 (two-tailed) was used for Egger’s test (Egger et al. 1997).
3 Results
3.1 Study selection
The selection process is illustrated in Figure S1. We included 29 studies with 779 patients in the systematic review (Ackerley et al. 2010, 2014, 2016; Bai et al. 2023; Bonnì et al. 2020; Chen et al. 2019a, 2021, Di Lazzaro et al. 2013, 2016; Diekhoff-Krebs et al. 2017; Ding et al. 2021, 2022; Dionísio et al. 2021; Hsu et al. 2013; Khan et al. 2019; Kuzu et al. 2021; Lai et al. 2015; Meehan et al. 2011; Meng et al. 2020; Neva et al. 2019; Nicolo et al. 2018; Sung et al. 2013; Talelli et al. 2007, 2012; Vink et al. 2023; Volz et al. 2016; Wadden et al. 2019; Wang et al. 2014; Watanabe et al. 2018; Zhang et al. 2022), of which 20 were included in the meta-analyses of upper extremity motor outcomes (Ackerley et al. 2016; Chen et al. 2019a, 2021, Di Lazzaro et al. 2013, 2016; Dionísio et al. 2021; Hsu et al. 2013; Khan et al. 2019; Lai et al. 2015; Meehan et al. 2011; Meng et al. 2020; Neva et al. 2019; Nicolo et al. 2018; Sung et al. 2013; Talelli et al. 2012; Vink et al. 2023; Wang et al. 2014; Watanabe et al. 2018; Zhang et al. 2022). The characteristics of the included studies are summarized in Table 1.
Characteristics of the included studies.
| Study | Design | Population | TBS protocol | Motor outcomes | Time points | ||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Group size | Chronicity | Severity of hemiplegia | Nature of lesion and the status of ipsilesional MEP | Protocol | Intensity | Duration | Stimulation target | Control | Combined intervention | Clinical | Behavioral | Neural (by technique) | |||
| Talelli et al. (2007) | Cross-over | iTBS-ipsi M1 (n = 6) cTBS-contra M1 (n = 6) Sham (n = 6) |
Chronic (≥12 months) |
Mild (ARAT: 41–57/57) |
MCA infarction, 3 cortical involved/3 pure subcortical Ipsi-MEP+: 100.00 % |
iTBS-600 cTBS-300 |
80 % AMT | 1 session | Ipsi-M1 (iTBS) Contral-M1 (cTBS) |
90° flipped coil with 50 % MMO | No | No | RT; grip strength | TMS-EMG | Baseline, Post |
| Ackerley et al. (2010) | Cross-over | iTBS-ipsi M1 (n = 10) cTBS-contra M1 (n = 10) Sham (n = 10) |
Chronic (≥6 months) |
Mild to moderate (FMA-UE wrist/hand subscores 12–28/32) |
8 ischemic and 2 hemorrhagic stroke, 2 cortical involved/8 pure subcortical Ipsi-MEP+: 100.00 % |
iTBS-600 cTBS-600 |
90 % AMT | 1 session | Ipsi-M1 (iTBS) Contral-M1 (cTBS) |
Sham coil | Precision grip movements | ARAT | Preload force and duration | TMS-EMG | Baseline, post |
| Meehan et al. (2011) | Parallel | cTBS-contra M1 (n = 4) cTBS-contra S1 (n = 4) Sham (n = 4) |
Chronic (≥12 months) |
Mild to severe (FMA-UE ≥ 15/66) |
Ischemic stroke Unclear nature Ipsi-MEP+: 100.00 % |
cTBS-600 | 80 % AMT | 3-Session | Contral-M1 (cTBS) Contral-S1 (cTBS) |
Sham coil | Serial targeting task | WMFT | Movement kinematics | No | Baseline, 1 day post |
| Talelli et al. (2012) | Parallel | iTBS-ipsi M1 (n = 13) cTBS-contra M1 (n = 12) Sham iTBS (n = 12) Sham cTBS (n = 12) |
Chronic (≥12 months) |
Mild to moderate hand weaknessa | Ischemic stroke, 26 cortical involved/23 pure subcortical Ipsi-MEP+: 83.67 % |
iTBS-600 cTBS-600 |
80 % AMT | 10 sessions | Ipsi-M1 (iTBS) Contral-M1 (cTBS) |
90° flipped coil with 50 % MMO | Upper limb physical therapy | NHPT; JTT; grasp and pinch grip strength | No | No | Baseline, 4-day post, 30-day post, 90-day post |
| Sung et al. (2013) | Parallel | LF rTMS + iTBS (n = 15) iTBS-ipsi M1 (n = 12) LF rTMS + sham iTBS (n = 13) Sham (n = 14) |
Subacute (3–12 months) |
Moderate to severe hand weakness (MRC in the finger flexor of the paretic hand ≤ 3/5) |
35 ischemic and 19 hemorrhagic stroke, 35 cortical involved/19 pure subcortical Ipsi-MEP+: 51.85 % |
iTBS-600 | 80 % AMT | 20 sessions | Ipsi-M1 (iTBS) |
Sham coil | Conventional rehabilitation | FMA-UE WMFT MRC |
RT, finger tapping | TMS-EMG | Baseline, mid, post |
| Hsu et al. (2013) | Parallel | iTBS-ipsi M1 (n = 6) Sham (n = 6) |
Acute (2–4 weeks) |
Mild to moderate hand weakness (NIHSS arm score: 1–3) | Ischemic stroke, MCA infarction, unclear nature Ipsi-MEP+: 75.00 % |
iTBS-1200 | 80 % AMT | 10 sessions | Ipsi-M1 (iTBS) |
90° flipped coil | Conventional rehabilitation | NIHSS ARAT FMA-UE |
No | MEG, TMS-EMG | Baseline, post, 2–4 weeks post |
| Di Lazzaro et al. (2013) | Parallel | cTBS-ipsi M1 (n = 6) Sham (n = 6) |
Chronic (≥12 months) |
Moderate hand weaknessb | Ischemic stroke, 11 cortical involved/1 pure subcortical Ipsi-MEP+: 66.67 % |
cTBS-600 | 80 % AMT | 10 sessions | Ipsi-M1 (cTBS) |
Sham coil | Physical therapy | ARAT JTT NHPT |
Grasp and pinch grip strength | TMS-EMG | Baseline Post 30-day post 90-day post |
| Ackerley et al. (2014) | Cross-over | cTBS-contra M1 (n = 13) iTBS-ipsi M1 (n = 13) Sham (n = 13) |
Chronic (≥6 months) |
Mild to severe (FMA-UE: 25–55/66; ARAT: 6–57/57) |
10 ischemic and 3 hemorrhagic stroke, 11 subcortical/2 MCA territory involved. Ipsi-MEP+: 100.00 % |
iTBS-600 cTBS-600 |
90 % AMT | 1 session | Ipsi-M1 (iTBS) Contra-M1 (cTBS) |
Sham coil | Precision grip movements | ARAT | Preload force and duration | TMS-EMG | Baseline Post |
| Wang et al. (2014) | Parallel | LF rTMS-contra-M1 prior to iTBS-ipsi M1 (n = 17) iTBS-ipsi M1 prior to LF rTMS-contra-M1 (n = 16) Sham (n = 15) |
Subacute (2–6 months) |
MRC≤3 | Ischemic stroke, 22 subcortical/23 cortical/3 unknown Ipsi-MEP+: unclear |
iTBS-600 | 80 % AMT | 10 sessions | Ipsi-M1 (iTBS) |
Sham coil | Conventional physiotherapy | WMFT MRC FMA-UE |
No | TMS-EMG | Baseline Post 10 sessions Post 20 sessions 3-month post |
| Lai et al. (2015) | Parallel | iTBS-ipsi M1 (n = 55) Sham (n = 17) |
Chronic (10.5 ± 5 months after stroke) |
Unclear | 45 subcortical/27 cortical involved Ipsi-MEP+: 29.17 % |
iTBS-600 | 80 % AMT | 10 sessions | Ipsi-M1 (iTBS) |
Sham coil | Conventional physiotherapy | WMFT | RT; FT | TMS-EMG | Baseline Mid Post |
| Ackerley et al. (2016) | Parallel | iTBS-ipsi M1 (n = 9) Sham (n = 9) |
Chronic (≥6 months) |
Mild to severe (FMA-UE: 21–63) |
Subcortical Ipsi-MEP+: 72.22 % |
iTBS-600 | 90 % AMT | 10 sessions | Ipsi-M1 (iTBS) Contra-M1 (cTBS) |
Sham coil | Upper limb physical therapy | ARAT FMA-UE |
No | TMS-EMG; fMRI | Baseline Mid Post 1 month post 3 months post |
| Di Lazzaro et al. (2016) | Parallel | cTBS-ipsi M1 (n = 8) Sham (n = 9) |
Chronic (≥12 months) |
Severe (FMA-UE: 3–28) |
Ischemic stroke Unclear nature Ipsi-MEP+: unclear |
cTBS-600 | 80 % AMT | 10 sessions | Contra-M1 (cTBS) | 90° flipped coil | Robot-assisted shoulder and elbow training | FMA-UE | Movement kinematics | No | Baseline Post 1 month post 3 months post |
| Volz et al. (2016) | Parallel | iTBS-ipsi M1 (n = 13) Sham (n = 13) |
Acute (Within 2 weeks) |
Unclear | Ischemic stroke (21 subcortical and 5 cortical involved) Ipsi-MEP+: 73.08 % |
iTBS-600 | 70 % RMT | 5 sessions | Ipsi M1 (iTBS) | Parieto-occipital cortex | Physiotherapy | JTT | Hand grip | TMS-EMG; fMRI | Baseline Post 3–6 months post |
| Diekhoff-Krebs et al. (2017) | Cross-over | iTBS-ipsi M1 (n = 14) Sham (n = 14) |
Chronic (≥12 months) |
Mild to severe ARAT: 24–57 |
Ischemic stroke Ipsi-MEP+: 96.43 % |
iTBS-600 | 80 % AMT | 1 session | Ipsi M1 (iTBS) | Parieto-occipital cortex | No | JTT | Finger tapping, grip strength | TMS-EMG; fMRI | Baseline Post |
| Nicolo et al. (2018) | Parallel | cTBS-contra M1 (n = 14) Sham (n = 13) |
Acute to subacute (<10 weeks) |
Mild to severe (FMA-UE: 3–48) |
23 ischemic/4 hemorrhagic stroke, 10 subcortical/17 cortical involved Ipsi-MEP+: unclear |
cTBS-600 | 80 % RMT | 9 sessions | Contra-M1 (cTBS) | Sham coil | Physical therapy | FMA BBT NHPT |
No | EEG | Baseline Post 30 days post |
| Watanabe et al. (2018) | Parallel | iTBS-ipsi M1 (n = 8) Sham (n = 6) |
Acute (<7 days) |
Moderate to severe (Brunnstrom stage for the upper extremity: I–III) |
Ischemic stroke, Capsular infarction only Ipsi-MEP: inclear |
iTBS-600 | 80 % RMT | 10 sessions | Ipsi-M1 (iTBS) | Separated by a 10-cm plastic band | Conventional rehabilitation | FMA | Grip strength | TMS-EMG | Baseline 12 week post |
| Chen et al. 2019a | Parallel | iTBS-ipsi M1 (n = 12) Sham (n = 11) |
Chronic (≥6 months) |
Unclear | 5 ischemic and 17 hemorrhagic stroke, 7 supratentorial/15 infratentorial Ipsi-MEP+: unclear |
iTBS-600 | 80 % AMT | 10 sessions | Ipsi-M1 (iTBS) | Reversed coil + 60 % AMT | Conventional rehabilitation | FMA-UE ARAT BBT |
No | No | Baseline Post |
| Wadden et al. (2019) | Parallel | cTBS-contra M1 (n = 9) cTBS-contra S1 (n = 11) Sham (n = 8) |
Chronic (≥6 months) |
Mild to severe (FMA-UE: 7–63) |
7 cortical involved/21 subcortical Ipsi-MEP+: NR |
cTBS-600 | 80 % AMT | 5 sessions | Contra-M1 (cTBS) Contra-S1 (cTBS) |
Sham coil | Skilled motor practice | No | RTT | DTI | Baseline During 1 day post |
| Khan et al. (2019) | Parallel | cTBS-contraM1+iTBS-ipsiM1 (n = 20) Control (n = 20) |
Acute (Within 10–30 days) |
Moderate to severe (MRC of the upper limb muscle <3) |
Ischemic stroke, MCA infarction Unclear nature Ipsi-MEP+: 47.50 % |
cTBS-600 iTBS-600 |
60 % RMT | 12 sessions | Contra-M1 (cTBS) Ipsi-M1 (iTBS) |
No TBS | Physical therapy | FMA-UE | Noo | TMS-EMG | Baseline Post 1 month post 3-month post 6-month post 1 year post |
| Neva et al. (2019) | Parallel | cTBS-contra M1 (n = 12) cTBS-contra S1 (n = 13) Sham (n = 12) |
Chronic (≥6 months) |
Mild to severe (FMA-UE: 7 to 66) |
6 cortical/20 subcortical/3 cerebellar/7 unclear Ipsi-MEP+: 72.00 % |
cTBS-600 iTBS-600 |
80 % AMT | 5 sessions | Contra-M1 (cTBS) Contra-S1 (cTBS) |
Sham coil | Skilled motor practice | WMFT | RTT | TMS-EMG | Baseline During 1–2 days post |
| Meng et al. (2020) | Parallel | LF rTMS + iTBS (n = 10) LF rTMS + sham iTBS (n = 10) Sham (n = 8) |
Acute (30–60 days) |
NIHSS: 1–15 points | 16 ischemic/12 hemorrhagic stroke; 18 basal ganglia/10 others Ipsi-MEP+: 71.43 % |
iTBS-1200 | 60–80 % RMT | 10 sessions | Ipsi-M1 (iTBS) | Flipped coil | Conventional rehabilitation | FMA-UE | No | TMS-EMG | Baseline Post |
| Chen et al. (2021) | Parallel | iTBS-ipsi M1 (n = 12) Sham (n = 11) |
Subacute and chronic | Mild to moderate (Brunnstrom stage ≥3) |
8 ischemic and 15 hemorrhagic stroke, 5 cortical involved/18 subcortical Ipsi-MEP+: 65.22 % |
iTBS-600 | 80 % AMT | 15 sessions | Ipsi-M1 (iTBS) | Reversed coil + 60 % AMT | VCT | FMA-UE ARAT BBT NHPT MAL |
No | No | Baseline Post |
| Dionísio et al. (2021) | Parallel | cTBS-contra M1 (n = 5) Sham (n = 5) |
Acute (Within 7 ± 3 days) |
Unclear | Ischemic stroke, MCA stroke Ipsi-MEP+: 70.00 % |
cTBS-600 | 100 % AMT | Single-session | Contra-M1 (cTBS) |
Intensity reduction and sham noise generator | No | WMFT | No | TMS-EMG; EEG | Baseline Post 3-month post |
| Ding et al. (2021) | Parallel | iTBS-ipsi M1 (n = 15) Sham (n = 15) |
Acute to chronic (1–18 months) | Mild to severe (FMA-UE: 4–64) |
24 ischemic/6 hemorrhagic stroke Ipsi-MEP+: 43.33 % |
iTBS-600 | 70 % RMT | Single-session | Ipsi M1 (iTBS) | 90° flipped coil | No | No | No | EEG | Baseline Post |
| Kuzu et al. (2021) | Parallel | cTBS-contra M1 (n = 7) Sham (n = 6) |
Chronic (6 months–2 years) |
Mild to moderate (Brunnstrom stage for the upper extremity 3–5) |
Ischemic stroke, 6 cortical involved/7 subcortical Ipsi-MEP+: NR |
cTBS-600 | 80 % AMT | 10 sessions | Contra-M1 (cTBS) |
Sham coil | Physical therapy | FMA MAL |
No | No | Baseline Post 4-week post |
| Ding et al. (2022) | Parallel | iTBS-ipsi M1 (n = 11) Sham (n = 11) |
Acute to chronic (1–18 months) | Mild to severe (FMA-UE: 4–66) |
18 ischemic/4 hemorrhagic stroke Ipsi-MEP+: 50.00 % |
iTBS-600 | 70 % RMT | Single-session | Ipsi M1 (iTBS) | 90° flipped coil | No | No | No | TMS-EEG | Baseline Post |
| Zhang et al. (2022) | Parallel | cTBS + iTBS-ipsi M1 (n = 14) iTBS-ipsi M1 (n = 14) Sham (n = 14) |
Chronic (≥12 months) |
Mild to severe (FTUHE: 2–7) |
24 ischemic and 18 hemorrhagic stroke, 10 cortical involved/31 subcortical/1 unknown Ipsi-MEP+: unclear |
cTBS-600 iTBS-600 |
70 % RMT | 10 sessions | Ipsi M1 (cTBS + iTBS and iTBS) | Intensity reduction | Robot-assisted arm and hand training | FMA-UE ARAT |
Movement kinematics | EEG | Baseline Mid Post 2-week post |
| Bai et al. (2023) | Cross-over | iTBS-ipsi M1 (n = 20) Sham (n = 20) |
Chronic stroke (≥6 months) |
Mild (FMA-UE: 56–66) |
12 ischemic/8 hemorrhagic stroke Ipsi-MEP+: 100.00 % |
iTBS-600 | 70 % RMT | 1 session | Ipsi M1 (iTBS) | Coil away from the scalp | No | No | No | TMS-EEG | Baseline Post |
| Vink et al. (2023) | Parallel | cTBS-contra M1 (n = 28) Sham (n = 31) |
Acute (≤3 weeks) |
Mild to severe (MI: 9–99) |
50 ischemic stroke and 9 hemorrhagic stroke Ipsi-MEP: 33.90 % |
cTBS-600 | 70 % RMT | 10 sessions | Contra-M1 (cTBS) | Intensity reduction | Individualized upper limb exercises | ARAT; FMA-UE; JTT; NHPT; | No | No | Baseline 1-week 1-month 3-month 6-month 1-year |
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Abbreviations: AMT, active motor threshold; ARAT, action research arm rest; BBT, box and block test; BI, Barthel index; cTBS, continuous theta burst stimulation; EEG, electroencephalography; FMA-UE, upper extremity scores of Fugl-Meyer assessment; fMRI, functional magnetic resonance imaging; FT, finger tapping; iTBS, intermittent theta burst stimulation; JTT, Jebsen-Taylor test; M1, primary motor cortex; MAL, motor activity log; MEG, magnetoencephalography; MEP+, motor-evoked potential positive; MI, Motricity index; MMO, maximal machine output; NHPT, Nine Hole Peg Test; RT, reaction time; S1, primary somatosensory cortex; TMS–EMG, transcranial magnetic stimulation–electromyography; VCT, virtual reality-based cycling training; WMFT, Wolf motor function test. aDefined as grasp strength ≥5 % of the unaffected hand, preserved extension at the wrist (≥20°), and baseline score in Nine Hole Peg Test (NHPT) ≤70 % of the unaffected hand. bDefined as grasp strength ≥1 % of the unaffected hand, preserved extension at the wrist (≥20°), and baseline score in Nine Hole Pegboard Test (NHPT) ≤70 % of the unaffected hand.
3.2 Methodological quality assessment
The methodological quality of the included studies was rated using the PEDro scale (Table S1). The mean score was 7.83, ranging from 6 to 10, indicating the moderate to high methodological quality of the included articles (Table 2).
Summary of modulatory effects of TBS in people with stroke.
| Study | Comparisons | Outcome measurements | Significant results |
|---|---|---|---|
| Tallelli et al. (2007) | iTBS (ipsi-M1) versus cTBS (contra-M1) versus sham |
TMS–EMG:
(1) MEP; (2) area under the I/O curves |
iTBS (ipsi-M1):
MEP (ipsi-M1) ↑ Area under the I/O curves↑ cTBS (contra-M1): No significant finding was found in TMS–EMG outcomes |
| Ackerley et al. (2010) | iTBS (ipsi-M1) versus sham | TMS–EMG: (1) MEP |
iTBS (ipsi-M1): MEP (ipsi-M1) ↑ |
| cTBS (contra-M1) versus sham |
cTBS (contra-M1):
MEP (contra-M1) ↓ |
||
| Hsu et al. (2013) | iTBS (ipsi-M1) versus sham |
TMS–EMG:
(1) AMT; (2) MEP MEG: (1) Post movement ERS (2) Movement-related ERD |
iTBS (ipsi-M1): Post movement ERS (ipsi-M1)↑ |
| Di Lazzaro et al. (2013) | cTBS (ipsi-M1) versus sham |
TMS–EMG:
(1) AMT; (2) MEP |
cTBS (ipsi-M1):
No significant finding was found in TMS–EMG outcomes |
| Sung et al. (2013) | iTBS (ipsi-M1) versus sham |
TMS–EMG:
(1) RMT; (2) MEP; (3) motor map area |
iTBS (ipsi-M1):
Motor map area (ipsi-M1) ↑ Motor map area (contra-M1) ↓ |
| Ackerley et al. (2014) | iTBS (ipsi-M1) versus sham |
TMS–EMG:
(1) MEP; (2) SAI |
iTBS (ipsi-M1): MEP (ipsi-M1) ↑ SAI (ipsi-M1) ↑ MEP (contra-M1) ↓ |
| cTBS (contra-M1) versus sham |
cTBS (contra-M1):
MEP (ipsi-M1) ↑ |
||
| Wang et al. (2014) | iTBS (ipsi-M1) versus sham |
TMS–EMG:
(1) RMT; (2) MEP; (3) motor map area |
iTBS (ipsi-M1): MEP (ipsi-M1) ↑ Motor map area (ipsi-M1) ↑ Motor map area (contra-M1) ↓ |
| Lai et al. (2015) | iTBS (ipsi-M1) versus sham |
TMS–EMG:
(1) MEP; (2) motor map area |
iTBS (ipsi-M1): Motor map area (contra-M1) ↓ |
| Ackerley et al. (2016) | iTBS (ipsi-M1) versus sham |
fMRI:
Activation over M1, S1, PMC, and SMA during paretic hand movement. |
iTBS (ipsi-M1): No significant pre-post change in laterality index of activation over all ROIs. |
| Volz et al. (2016) | iTBS (ipsi-M1) versus control stimulation |
fMRI:
(1) rsFC TMS–EMG: (1) MEP |
iTBS ipsi-M1: rsFC ↑ (Ipsi-M1 with ipsi-SMA, ipsi-MCC, contra-SMA, contra-dPMC, and contra-M1) |
| Diekhoff-Krebs et al. (2017) | iTBS (ipsi-M1) versus sham |
TMS–EMG:
(1) MEP |
iTBS ipsi-M1: MEP (ipsi-M1) ↑ MEP (contra-M1) ↓ |
| Nicolo et al. (2018) | cTBS (contra-M1) versus sham |
EEG:
(1) EC (PDC); (2) FC (imagery part of coherence); (3) node strength |
cTBS (contra-M1):
PDC (from contra-M1 to ipsi-M1, beta rhythm) ↓ |
| Watanabe et al. (2018) | iTBS (ipsi-M1) versus sham |
TMS–EMG:
(1) MEP |
iTBS (ipsi-M1): MEP (ipsi-M1) ↑ |
| Wadden et al. (2019) | cTBS (contra-M1) versus sham |
MRI:
(1) DTI of constrained motor connectome |
No significant finding was reported in DTI outcomes |
| cTBS (contra-S1) versus sham | |||
| Neva et al. (2019) | cTBS (contra-M1) versus sham |
TMS–EMG:
(1) RMT; (2) SICI; (3) ICF; (4) iSP |
cTBS (contra-M1):
No significant finding was reported in TMS-EMG outcomes |
| Khan et al. (2019) | Bilateral TBS versus No TBS |
TMS–EMG:
(1) RMT |
Bilateral TBS:
RMT (ipsi-M1) ↓ RMT (contra-M1) ↑ |
| Meng et al. (2020) | LF rTMS (contra-M1) + iTBS (ipsi-M1) versus LF rTMS (contra-M1) + sham |
TMS–EMG:
(1) MEP (abductor brevis pollicis, extensor Digitorum communis, and biceps brachii) |
LF rTMS (contra-M1) + iTBS (ipsi-M1) versus LF rTMS (contra-M1) + sham:
MEP (ipsi-M1) ↑ |
| Ding et al. (2021) | iTBS (ipsi-M1) versus sham |
EEG:
(1) Spectral power; (2) sensorimotor FC-coherence; (3) global efficiency |
iTBS (ipsi-M1):
Sensorimotor FC (delta and theta rhythms)↑ Global efficiency (delta and beta rhythms) ↑ |
| Dionísio et al. (2021) | cTBS (contra-M1) versus sham |
EEG:
(1) Movement-related ERD TMS–EMG: (1) MEP |
cTBS (contra-M1)
Movement-related ERD over the ipsilesional hemisphere↑ |
| Ding et al. (2022) | iTBS (ipsi-M1) versus sham |
TMS–EEG:
(1) Local mean field power; (2) global mean field power; (3) TMS-induced ERS/ERD; (4) natural frequency |
iTBS (ipsi-M1):
Natural frequency (ipsi-M1)↑ |
| Zhang et al. (2022) | Priming iTBS (ipsi-M1) versus sham |
EEG:
(1) MVF-induced ERD; (2) movement-related ERD |
Priming iTBS (ipsi-M1):
MVF-induced ERD (ipsi-M1, high beta rhythm)↑ |
| iTBS (ipsi-M1) versus sham |
iTBS (ipsi-M1):
No significant finding in the EEG outcomes. |
||
| Bai et al. (2023) | iTBS (ipsi-M1) versus sham |
TMS–EEG:
(1) TEP; (2) TMS-induced ERS/ERD; (3) TMS-induced network properties TMS–EMG: (1) MEP; (2) CSP; (3) ICF; (4) SICI |
iTBS (ipsi-M1):
MEP (ipsi-M1)↑ P30 in TEP (ipsi-M1)↑ |
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Abbreviations: AMT, active motor threshold; CSP, cortical silent period; cTBS, continuous theta burst stimulation; DTI, diffusion tensor imaging; EC, effective connectivity; ERD, event-related desynchronization; ERS, event-related synchronization; FA, fractional anisotropy; FC, functional connectivity; fMRI, functional magnetic resonance imaging; I/O curve, input–output curve; ICF, intracortical facilitation; ISP, Ipsilateral silent period; iTBS, intermittent theta burst stimulation; LF rTMS, low-frequency repetitive transcranial magnetic stimulation; M1, primary motor cortex; MEP, motor evoked potential; MRI, magnetic resonance imaging; PDC, partial directed coherence; PMC, premotor cortex; RMT, resting motor threshold; ROI, region of interest; rsFC, resting-state functional connectivity; S1, primary somatosensory cortex; SAI, short-latency afferent inhibition; SICI, short-interval intracortical inhibition; SMA, supplementary motor cortex; TMS-EEG, transcranial magnetic stimulation-electroencephalography; TMS–EMG, transcranial magnetic stimulation–electromyography; TEP, transcranial magnetic stimulation evoked electroencephalography potential.
3.3 TBS protocols
Most studies used standard 600-pulse iTBS for the ipsilesional M1 or 600-pulse cTBS for the contralesional M1. A bilateral TBS protocol (cTBS to the contralesional M1 + iTBS to the ipsilesional M1) was used by Khan et al. (2019), while other two studies utilized low-frequency rTMS to the contralesional M1 before iTBS to the ipsilesional M1 (Meng et al. 2020; Wang et al. 2014). cTBS was applied to the ipsilesional M1 in two studies by Di Lazzaro et al. (2016, 2013) to induce a metaplastic interaction between cTBS and subsequent motor training, while another study applied a priming iTBS protocol, which involved applying cTBS to the ipsilesional M1 before iTBS over the ipsilesional M1 to induce a stronger facilitative effect of iTBS via therapeutic beneficial metaplasticity (Zhang et al. 2022). A 1200-pulse iTBS protocol to the ipsilesional M1 was applied in Hsu et al. (2013) and Meng et al. (2020).
Results of meta-analysis.
| Protocol | Outcome | n | Effect size | Heterogeneity | |||
|---|---|---|---|---|---|---|---|
| Hedge’s g | 95 % CI | p | I 2 | p | |||
| All TBS protocols | FMA-UE | 14 | 0.646 | 0.213 to 1.079 | 0.003** | 76.15 % | <0.001*** |
| Excitatory TBS | 10 | 0.470 | 0.121 to 0.818 | 0.001** | 44.97 % | 0.060 | |
| Inhibitory TBS | 3 | 0.300 | −0.080 to 0.680 | 0.122 | 0.00 % | 0.812 | |
| Bilateral TBS | 1 | 3.521 | 2.539 to 4.503 | <0.001*** | 0.00 % | >0.999 | |
| All TBS protocols | Functional activity | 19 | 0.500 | 0.272 to 0.729 | <0.001*** | 34.21 % | 0.072 |
| Excitatory TBS | 11 | 0.609 | 0.270 to 0.948 | <0.001*** | 52.68 % | 0.020* | |
| Inhibitory TBS | 8 | 0.344 | 0.053 to 0.636 | 0.021 | 0.00 % | 0.747 | |
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Abbreviations: TBS, theta burst stimulation; FMA-UE, Fugl-Meyer assessment upper extremity. *p < 0.05; **p < 0.01; ***p < 0.001.
3.4 Upper extremity motor impairment
Table 3 summarized the results of our meta-analyses. A total of 12 studies with 14 units of analysis were included in the meta-analysis of FMA-UE scores (Chen et al. 2019a, 2021; Di Lazzaro et al. 2016; Hsu et al. 2013; Khan et al. 2019; Meng et al. 2020; Nicolo et al. 2018; Sung et al. 2013; Vink et al. 2023; Wang et al. 2014; Watanabe et al. 2018; Zhang et al. 2022). Overall, improved upper extremity impairment was found after TBS intervention compared to the control group (Hedge’s g = 0.646, p = 0.003, I2 = 76.15 %; Figure 1A), and the overall significance was robust to leave-one-out sensitivity analysis (Hedge’s g from 0.402 to 0.715, which consistently indicated medium effect sizes during sensitivity analysis). Subgroup analysis showed that excitatory and bilateral TBS protocols significantly improved upper extremity motor impairment (excitatory: Hedge’s g = 0.470, p = 0.001, I2 = 44.97 %; bilateral: Hedge’s g = 3.521, p < 0.001, I2 = 0.00 %), but the effect of inhibitory TBS protocols was not significant (Hedge’s g = 0.300, p = 0.122, I2 = 0.00 %). Between-subgroup differences (excitatory vs. inhibitory) were not statistically significant (Q = 0.34, p = 0.56). There was no sign of publication bias according to the non-significant results of the Egger’s test (p = 0.12). Univariate meta-regression analysis revealed that the percentage of patients with subcortical lesions (p = 0.015) was a significant predictor of the effect size of TBS (Figure 2A). Furthermore, the Q-test revealed a significant between-group difference between studies with 600-pulse TBS and 1200-pulse TBS (Q = 9.59, p = 0.002; Figure 2C).
Meta-analysis of the effect of theta burst stimulation on (A) upper extremity motor impairment and (B) functional activity. The studies were represented by symbols whose area was proportional to the study’s weight in the analysis.
Meta-regression of the association between (A) the percentage of subcortical stroke patients and the effect sizes of FMA-UE and (B) the percentage of patients with subcortical lesions and the effect sizes of the outcomes assessing functional activity. (C) Between-group differences in the effect sizes of FMA-UE using 600-pulse protocols and 1200-pulse protocols. Each study was represented by a circle proportional to its weight in the analysis. FMA-UE: Fugl-Meyer assessment-upper extremity.
3.5 Upper extremity functional activity
A total of 14 studies with 19 units of analysis were included in the meta-analysis of upper extremity functional activity (Ackerley et al. 2016; Chen et al. 2019a, 2021; Di Lazzaro et al. 2013; Dionísio et al. 2021; Hsu et al. 2013; Lai et al. 2015; Meehan et al. 2011; Neva et al. 2019; Sung et al. 2013; Talelli et al. 2012; Vink et al. 2023; Wang et al. 2014; Zhang et al. 2022). A meta-analysis demonstrated that TBS significantly improved upper limb functional activity compared with sham stimulation (Hedge’s g = 0.500, p < 0.001, I2 = 34.12 %; Figure 1B). The overall significance was also robust to leave-one-out sensitivity analysis (Hedge’s g from 0.408 to 0.528, which consistently indicated medium effect sizes during sensitivity analysis). The subgroup analysis showed that both excitatory and inhibitory TBS protocols yielded a more significant effect than sham stimulation on improving upper limb functional activity (excitatory: Hedge’s g = 0.609, p < 0.001, I2 = 52.68 %; inhibitory: Hedge’s g = 0.344, p = 0.021, I2 = 0.00 %). Between-subgroup differences were not statistically significant (Q = 1.32, p = 0.251). There was no sign of publication bias according to Egger’s test (p = 0.964). Univariate meta-regression revealed a significantly positive relationship between the percentage of subcortical patients and the effect size (p = 0.018; Figure 2B). Tables S2 and S3 summarize the results of the univariate meta-regression.
3.6 Neural modulatory effects of TBS
A total of 22 studies included in this review used neuroimaging or neurophysiological outcomes (Ackerley et al. 2010, 2014, 2016; Bai et al. 2023; Di Lazzaro et al. 2013; Diekhoff-Krebs et al. 2017; Ding et al. 2021, 2022; Dionísio et al. 2021; Hsu et al. 2013; Khan et al. 2019; Lai et al. 2015; Meng et al. 2020; Neva et al. 2019; Nicolo et al. 2018; Sung et al. 2013; Talelli et al. 2007; Volz et al. 2016; Wadden et al. 2019; Wang et al. 2014; Watanabe et al. 2018; Zhang et al. 2022). TMS–EMG outcomes were the most frequently used (Ackerley et al. 2010, 2014; Bai et al. 2023; Di Lazzaro et al. 2013; Diekhoff-Krebs et al. 2017; Khan et al. 2019; Lai et al. 2015; Meng et al. 2020; Neva et al. 2019; Talelli et al. 2007; Wang et al. 2014; Watanabe et al. 2018), followed by electroencephalography (EEG)/TMS–EEG/magnetoencephalography (MEG) (Bai et al. 2023; Ding et al. 2021, Ding et al. 2022; Dionísio et al. 2021; Hsu et al. 2013; Nicolo et al. 2018; Zhang et al. 2022), and structural and functional magnetic resonance imaging (fMRI) (Ackerley et al. 2016; Volz et al. 2016; Wadden et al. 2019). Overall, iTBS over the ipsilesional M1 increased ipsilesional corticomotor excitability, whereas cTBS over the contralesional M1 decreased contralesional corticomotor excitability, as measured by the amplitude of MEP (Ackerley et al. 2010, 2014; Bai et al. 2023; Diekhoff-Krebs et al. 2017; Meng et al. 2020; Talelli et al. 2007; Wang et al. 2014; Watanabe et al. 2018), motor map area (Lai et al. 2015; Sung et al. 2013; Wang et al. 2014), input–output curve (Talelli et al. 2007), P30 in the TMS-evoked potential on EEG (Bai et al. 2023), and movement event-related desynchronization (ERD) (Dionísio et al. 2021). Furthermore, iTBS or iTBS priming over the ipsilesional M1 enhances the sensory permissiveness of M1, as measured by short-interval afferent inhibition (Ackerley et al. 2014) and mirror visual feedback-induced ERD (Zhang et al. 2022).
Apart from the regional effects, TBS demonstrated remote effects in poststroke brains. Specifically, iTBS over the ipsilesional M1 was found to increase the functional connectivity between the ipsilesional M1 and other parts of the cortical motor system over the bilateral hemispheres, as measured by resting-state fMRI (Volz et al. 2016) and intra-and interhemispheric sensorimotor coherence in EEG (Ding et al. 2021). Moreover, cTBS over the contralesional M1 decreases directional connectivity from the contralesional to ipsilesional M1 (Nicolo et al. 2018). Regarding network effects, one study using iTBS on the ipsilesional M1 showed an increase in global efficacy (defined as the reciprocal of the shortest path length between whole-brain connections) in subacute stroke patients (Ding et al. 2021). However, another study using the same protocol did not find any significant effects of modulating network properties in chronic stroke patients (Bai et al. 2023).
4 Discussion
The meta-analysis presented here revealed that (1) both ipsilesional iTBS and contralesional cTBS significantly improved upper limb functional activities in patients after stroke, as compared to sham stimulation. (2) iTBS significantly improved upper limb motor impairment after stroke compared to sham stimulation or no stimulation; however, the evidence to support the effect of cTBS was still limited. (3) A significant association was found between the number of patients with subcortical lesions and the magnitude of the effect size of TBS, indicating that lesion location may be a factor determining individual treatment responsiveness to TBS, with pure subcortical stroke patients benefitting most from the cortical TBS therapy. (4) TBS with a higher number of pulses, i.e., 1200-pulse, seems to lead to superior efficacy compared to conventional 600-pulse protocols. (5) The neural mechanisms underlying TBS in poststroke rehabilitation can be attributed to the modulation of corticomotor excitability and may be related to the recruitment of corticomotor networks connected to the ipsilesional M1.
TBS is frequently used for cortical conditioning (stimulation intensity <100 % RMT) in poststroke rehabilitation (Huang et al. 2005), and the level of the structural reserve of the cortical motor system appears to be important for responsiveness to TBS (Ding et al. 2023). The enhanced excitability of the M1 through iTBS or decreased interhemispheric inhibition from the contralesional to the ipsilesional M1 through contralesional cTBS can potentially increase the chances of activating specific cortico-subcortical neural circuits that are crucial for task-specific rehabilitation training. This, in turn, may result in more favorable therapeutic outcomes (Ding et al. 2023). Impairment of the cortical region, particularly the stimulated M1 region, can potentially nullify the impact of cortical conditioning during the TBS, thereby restricting facilitation along the corticospinal descending pathway (Ameli et al. 2009). Therefore, individuals with an intact cortex, specifically a preserved motor cortex, may exhibit a more favorable response to cortical conditioning using TBS.
Accelerated TBS protocols with more stimulation pulses (e.g., 1200-pulse) seemed to be more efficacious than the conventional 600-pulse protocol. However, it is worth mentioning that there are three types of 1200-pulse TBS protocols that have been reported in the previous literature: a higher dose iTBS (two sessions of 600-pulses iTBS delivered to the ipsilesional M1) (Hsu et al. 2013, Meng et al. 2020), priming iTBS (applying 600-pulse cTBS before 600-pulse iTBS and both were applied to the ipsilesional M1) (Zhang et al. 2022), and bilateral TBS (cTBS over the contralesional M1 and iTBS over the ipsilesional M1) (Khan et al. 2019). The underlying rationale for the use of different 1200-pulse TBS protocols differs; however, in general, novel TBS protocols have demonstrated improved efficacy compared to conventional protocols with lower number of overall pulses. It is, however, important to interpret the results with caution because all novel protocols have only been tested in small-scale clinical studies and have not been externally validated (Hsu et al. 2013; Khan et al. 2019; Meng et al. 2020; Zhang et al. 2022).
The timing of TBS intervention is a potentially influential factor in poststroke rehabilitation outcomes (Vink et al. 2023). A previous review on rTMS reported a significantly larger effect size in the acute stroke subgroup compared to the subacute and chronic stroke subgroups (van Lieshout et al. 2019). This finding aligns with the results in the present focused review of TBS literature, as we observed numerically higher effect sizes in studies involving patients in the earlier stages of stroke compared to those in later stages. However, due to variations in the literature regarding the specific cutoffs used to define the acute and post-acute phases poststroke, we employed a meta-regression analysis to investigate the relationship between time since stroke and effect size. However, no significant results were found, highlighting the lack of consistent evidence to determine the optimal timing of TBS intervention in poststroke patients.
The regional modulatory effect of TBS has been well-documented in the literature, primarily derived from neurophysiological evidence using EEG/MEG (Dionísio et al. 2021; Hsu et al. 2013; Zhang et al. 2022), TMS–EMG (Ackerley et al. 2014; Diekhoff-Krebs et al. 2017; Khan et al. 2019; Lai et al. 2015; Meng et al. 2020; Talelli et al. 2007; Wang et al. 2014; Watanabe et al. 2018), and TMS–EEG outcomes (Bai et al. 2023; Ding et al. 2022). However, the modulatory effect of single-target TBS on connectivity and networks is still under investigation, with limited evidence. Preliminary evidence using EEG or fMRI suggests that TBS (iTBS or cTBS) affects the corticomotor network connected to the ipsilesional M1 (Ding et al. 2021; Nicolo et al. 2018; Volz et al. 2016), although the underlying neural circuit remains unknown. The remote and network effects of single-target M1 TBS are largely unpredictable in healthy adults (Zhang 2024) and can be even more complicated in poststroke patients with impaired neural connectivity and networks. Studies may further explore the association between poststroke impairments of neural networks and the effect of TBS and then optimize the network effect of TBS through the use of multifocal TBS or combined with specific motor training that can recruit task-specific neural circuits.
The present study was not free from limitations. First, due to our inability to access the individual datasets from each study, i.e., individual participant data meta-analysis, we were unable to conduct a comprehensive analysis on the percentage of patients who achieved improvement scores exceeding the minimal clinically important difference. On the other hand, the heterogeneity of neural outcomes used across the studies prevented us from conducting a quantitative analysis. The current discussion regarding the neural mechanisms underlying TBS in poststroke rehabilitation was based on a qualitative interpretation of the findings.
5 Conclusions
TBS is an efficacious brain stimulation therapy that enhances the therapeutic benefits of poststroke upper extremity rehabilitation training. Patients with subcortical stroke show better responsiveness to TBS. Accelerated TBS protocols using higher doses may have superior efficacy. The mechanisms of recovery facilitated by TBS in poststroke rehabilitation can be attributed to the excitability modulation of the M1 and descending motor pathways and possibly to the recruitment of corticomotor networks connected to the ipsilesional M1.
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Research ethics: Not applicable. The submission is a review.
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Author contributions: Jack Jiaqi Zhang: Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization, Writing – original draft, Writing – review & editing. Youxin Sui: Data curation, Formal analysis, Investigation, Methodology, Writing – review & editing. Alexander T. Sack: Investigation, Methodology, Supervision, Validation, Writing – review & editing. Zhongfei Bai: Formal analysis, Methodology, Writing – original draft, Writing – review & editing. Patrick WH Kwong: Investigation, Methodology, Writing – review & editing. Dalinda Isabel Sanchez Vidana: Investigation, Methodology, Writing – review & editing. Li Xiong: Supervision, Writing – review & editing. Kenneth N. K. Fong: Methodology, Project administration, Supervision, Validation, Writing – review & editing. The authors have accepted responsibility for the entire content of this manuscript and approved its submission.
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Competing interests: Alexander T. Sack is chief scientific advisor for PlatoScience Medical, scientific advisor for Alpha Brain Technologies, Founder and CEO of Neurowear Medical, scientific director of the International Clinical TMS Certification Course, and president of the Academy of Brain Stimulation. He also received equipment support from MagVenture, Magstim, and Deymed Diagnostics. These activities and roles do not influence the work reported in this paper. Other authors also declare that there are no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper, and there are no additional relationships, patents, or activities to disclose.
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Research funding: The study was partially supported by the Start-up Fund for RAPs under the Strategic Hiring Scheme, The Hong Kong Polytechnic University (Grant number: P0048866) to JZ, and the Science and Technology Commission of Shanghai Municipality (23Y11900600) and the Shanghai Hospital Development Center (SHDC12023618) to ZB.
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Data availability: Data supporting the findings of this study are available from the corresponding author on request.
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Supplementary Material
This article contains supplementary material (https://doi.org/10.1515/revneuro-2024-0030).
© 2024 Walter de Gruyter GmbH, Berlin/Boston
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Articles in the same Issue
- Frontmatter
- The impact of poverty and socioeconomic status on brain, behaviour, and development: a unified framework
- A systematic review and meta-analysis of the preclinical and clinical results of low-field magnetic stimulation in cognitive disorders
- Research advancements on nerve guide conduits for nerve injury repair
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