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Eur J Phys Rehabil Med
Eur J Phys Rehabil Med
EJPRM
European Journal of Physical and Rehabilitation Medicine
1973-9087
1973-9095
Edizioni Minerva Medica

38864711
8431
10.23736/S1973-9087.24.08431-4
Article
Modulating low-frequency oscillations in post-stroke brains using priming intermittent theta burst stimulation
ZHANG Jack J. 1 *
BAI Zhongfei 2
MEHLER David M. 3 4
KWONG Patrick W. 1
LAM Tommy L. 5
FONG Kenneth N. 1
1Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hong Kong SAR, China; 2Department of Occupational Therapy, Shanghai YangZhi Rehabilitation Hospital (Shanghai Sunshine Rehabilitation Center), Tongji University School of Medicine, Shanghai, China; 3RWTH Aachen University, Medical School, Department of Psychiatry, Psychotherapy and Psychosomatics, Aachen, Germany; 4Institute for Translational Psychiatry, Department of Psychiatry, University of Münster, Münster, Germany; 5University Research Facility in Behavioral and Systems Neuroscience, The Hong Kong Polytechnic University, Hong Kong SAR, China
* Corresponding author: Jack J. Zhang, Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hong Kong SAR, China. E-mail: jack-jq.zhang@connect.polyu.hk
Authors’ contributions: Jack J. Zhang and Zhongfei Bai contributed equally. Jack J. Zhang and Kenneth N. Fong designed this study. Jack J. Zhang and Zhongfei Bai collected and analyzed the data. Jack J. Zhang, Zhongfei Bai, and Kenneth N. Fong wrote the first draft. David M. Mehler, Patrick W. Kwong, and Tommy L. Lam revised the manuscript. All the authors approved the final version of the manuscript.

12 6 2024
8 2024
60 4 591593
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06 5 2024
20 1 2024
2024 THE AUTHORS
https://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution Non-Commercial No Derivatives (CC BY-NC-ND) 4.0 License.
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pmcPoststroke interhemispheric asymmetry in cortical oscillations is well-documented in electroencephalography (EEG) studies, showing increased low-frequency oscillations over the ipsilesional hemisphere.1 Low-frequency oscillations in the delta rhythm (1-4 Hz) are biomarkers of stroke-induced injury and post-stroke recovery; however, previous evidence was primarily derived from EEG power and coherence analyses.2 Graph-theory-based network analyses can evaluate the strength and separation of functional connectivity as well as global efficiency, thereby contributing to the understanding of the role of delta oscillations in regional and whole-brain networks. However, the network metric has rarely been applied as an outcome measure.

Repetitive transcranial magnetic stimulation (rTMS) has been often applied in combination of motor rehabilitation to facilitate motor relearning outcomes in patients after stroke3 and theta burst stimulation (TBS) has been the most frequently used patterned form of rTMS in clinical indications nowadays.4 An innovative priming TBS protocol, by utilizing an inhibitory priming session using continuous TBS (cTBS) followed by an excitatory conditioning session using intermittent TBS (iTBS), has been found with a stronger facilitative effect on enhancing corticomotor excitability in healthy individuals5 and patients after stroke,6 than the nonpriming (standard) iTBS. The rationale behind this procedural format is that cTBS could lower the threshold of long-term potentiation (LTP) induction via the induction of therapeutically beneficial metaplasticity,7 thereby creating a stronger potential for inducing an LTP-like effect during the following iTBS,8 However, it remains unknown whether the superiority of efficacy of priming iTBS can be reflected in the modulation of delta oscillations in individuals with post-stroke brains.

The objective of the present study was to examine the modulatory effect of priming iTBS in delta oscillations in patients after chronic stroke. We hypothesized that the facilitatory effect associated with priming iTBS could lead to the normalization of delta oscillations. The process of normalization may involve the establishment of interhemispheric symmetry in terms of regional powers and strength of connectivity, as well as enhanced functional integration and segregation. These changes could also be correlated with clinical improvement in poststroke patients.

Hence, we performed a secondary analysis of resting-state EEG data collected from a published randomized controlled trial (RCT; clinical trial registration: NCT04034069; ethical approval number: HSEARS20190718003),6 using network analyses. Our previous publication exclusively examined the movement-related beta oscillations in response to iTBS.6 In contrast, the current study investigates outcomes from another important domain. Adult patients (18-75 years old) who have had a first-ever, ischemic, or hemorrhagic stroke, with a unilateral hemispheric involvement for more than 6 months were included. Participants with any rTMS contraindications9 or a previous diagnosis of any neurological disease excluding stroke were excluded.

The RCT included three parallel groups: 1) priming iTBS, which utilized real cTBS before real iTBS to induce therapeutically beneficial metaplasticity; 2) non-priming (standard) iTBS, which utilized sham cTBS before real iTBS; and 3) sham stimulation, which utilized sham cTBS before sham iTBS. All stimulation was applied to the ipsilesional primary motor cortex. Standard 600-pulse TBS was applied, i.e., 40-second cTBS and 192 seconds iTBS.10 The procedure for identifying the motor hotspot and resting motor threshold (RMT) has been described in Zhang et al.6 Real stimulation was applied at the intensity of 70% RMT of the unaffected M1, while sham stimulation used an intensity of 20% RMT which can be deemed as ineffective.5, 6 Immediately after the stimulation session, participants with chronic stroke received customized robot-assisted training. Each session of motor training consisted of a 20-minute proximal training session using an end-effector robot (ArmMotus, Fourier Intelligence Co. Ltd, Shanghai, China), and a 20-minute distal training session using an exoskeleton (HandyRehab, Zunosaki Co Ltd, Hong Kong SAR, China). To develop a comprehensive upper limb training program for patients with stroke, we incorporated both proximal and distal motor training in the current study. Additionally, previous research has documented the facilitatory effect of iTBS delivered to the hand representation of the affected M1 in improving both distal and proximal upper limb motor functions in patients with stroke, further justifying our inclusion of these training components.4 The interventional program lasted three sessions per week, for a total of 10 sessions. Three-minute resting-state EEG recordings (with eyes open) were obtained from a subset of 21 participants (N.=7 in each group) before and after completing the 10-session intervention.6

The weighted phase-lag index (wPLV) was selected as the connectivity metric because it is robust against volume conduction effects.11 The density-based threshold was initially employed to eliminate spurious connectivity. The connectivity matrices were thresholded to preserve between 50% and 5% of the highest wPLI values.12 The area under the curve was calculated by integrating the measures across the entire threshold range.

All network metrics were calculated using the Brain Connectivity Toolbox (www.brain-connectivity-toolbox.net). Three network metrics were then computed:

global efficiency (Eglobal) of functional connectivity over the entire brain (i.e., all 60 EEG channels) in the delta band, which is a measure of functional integration;

clustering coefficient of intra-and interhemispheric connectivity over the bilateral sensorimotor cortex (SMC), that is CCBiSMC. The clustering coefficient evaluated the functional segregation, which was computed as the geometric mean of all the triangles associated with each channel. Nine channels over the left SMC (FC5, FC3, FC1, C5, C3, C1, CP5, CP3 and CP1) and nine others over the right SMC (FC2, FC4, FC6, C2, C4, C6, T8, CP2, CP4 and CP6) were selected;

network strength of intra-and interhemispheric connectivity over the bilateral SMC, that is, SBiSMC, which was calculated as the sum of the edge weights connected to the channels. Nine channels over the left SMC (FC5, FC3, FC1, C5, C3, C1, CP5, CP3 and CP1) and nine others over the right SMC (FC2, FC4, FC6, C2, C4, C6, T8, CP2, CP4 and CP6) were selected.

Additionally, absolute EEG powers in the delta band over the ipsilesional and contralesional SMC were calculated. Between-group differences were tested using repeated-measures analysis of variance (ANOVA).

No significant differences among the three groups were observed in the demographics and clinical severity (measured by Fugl-Meyer Assessment-Upper Extremity, [FMA-UE]) at baseline (Group 1: 3F/4M, age: 57.00±8.50, FMA-UE: 39.00±17.11; 6 subcortical/1 cortical involved; Group 2: 2F/5M, age: 60.71±3.82, FMA-UE: 42.57±11.80; 6 subcortical/ 1 cortical involved; Group 3: 2F/5M, age: 64.4±7.25, FMA-UE: 44.7±14.29; 5 subcortical/2 cortical involved). Moreover, ANOVA revealed significant time (F=9.825, P=0.006) and interaction effects (F=9.376, P=0.002) when analyzing Eglobal. Post-hoc comparisons assessing between-group differences in the change from baseline revealed a significantly greater increase in Eglobal in the priming group compared to both the non-priming (P=0.001) and sham groups (P=0.003) (Figure 1A). Analysis of CCBiSMC demonstrated significant time (F=9.959, P=0.005) and interaction effects (F=6.770, P=0.006). Post-hoc comparisons of between-group differences using the change from baseline indicated that the increase in CCBiSMC was significantly larger in the priming group than in the non-priming (P=0.004) and sham groups (P=0.007) (Figure 1B).

Figure 1 —Results of neural network outcomes: A) global efficacy (Eglobal); B) clustering coefficient of intra-and interhemispheric connectivity over the bilateral the bilateral sensorimotor cortex (CCBiSMC); C) network strength of intra-and interhemispheric connectivity over the bilateral sensorimotor cortex (SBiSMC). *P<0.05; **P<0.01.

Analysis of SBiSMC demonstrated a significant time effect (F=5.871, P=0.026). Post-hoc comparisons of within-group differences between baseline and post-measurements displayed that priming iTBS significantly decreased SBiSMC (P=0.040) (Figure 1C). No significant effect was identified when the absolute delta power was used over either the ipsilesional (time effect: P=0.393; interaction effect: P=0.480) or contralesional SMC (time effect: P=0.375; interaction effect: P=0.280). Additionally, the changes from the baseline power and network metrics were not correlated with the improvement scores of FMA-UE after the 10-session intervention (all P>0.400) (Supplementary Digital Material 1: Supplementary Text File 1).

Delta oscillations are a pathological signature of acute brain injury; however, they also contribute to brain function after chronic stroke.2 Hence, delta oscillations could possibly serve as a biomarker for treatment response in patients with stroke undergoing intervention. We discovered that priming iTBS was superior in modulating delta oscillations in chronic stroke patients compared to non-priming and sham stimulation. Our findings are in line with those of a previous study in patients with acute stroke, in which iTBS enhanced functional networks but not delta powers.13 We further observed that the priming protocol reduced the overall strength of the network but improved functional separation. Additionally, priming iTBS enhanced the global efficiency of delta oscillations. These findings suggest that priming iTBS normalizes delta oscillations in post-stroke brains. However, the behavioral correlation of delta oscillations in poststroke survivors remains unknown and requires further investigation.

Supplementary Digital Material 1

Supplementary Text File 1

Global efficacy (E)

Acknowledgements

The authors acknowledged the University Facility of System and Behavioral Neuroscience (UBSN), The Hong Kong Polytechnic University for facility support.

Conflicts of interest: The authors certify that there is no conflict of interest with any financial organization regarding the material discussed in the manuscript.

Funding: This study was partially supported by the Start-up Fund for Research Assistant Professors under the Strategic Hiring Scheme to Jack J. Zhang (Grant number: P0048866), the Clinical Research Program of the Shanghai Municipal Health Commission (No. 20224Y0220), and the Medical Innovation Research Program of Shanghai Municipal Science and Technology (No. 23Y11900600) to Zhongfei Bai.
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