Repetitive Transcranial Magnetic Stimulation for Musculoskeletal Pain in Patients With Parkinson's Disease：Efficacy and Safety, Electrophysiological Mechanisms and Influence on Motor and Other Non-motor Symptoms
Phase: NA
Conditions: Parkinson's Disease, Musculoskeletal Pain, Repetitive Transcranial Magnetic Stimulation, Primary Motor Cortex, Electroencephalography, Neuromodulation
Sponsor: Second Affiliated Hospital of Soochow University

 
1 
 
Repetitive Transcranial Magnetic Stimulation for Musculoskeletal Pain in Patients 
with Parkinson's Disease 
 
Clinical Trial Protocol and Statistical Analysis Plan 
 
 
 
 
 
JD-LK-2021-132-01 
 NCT number: NCT05537597 
 
 
 
 
 
 
 
 
 
Document date: 2022-09 

 
2 
LIST OF ABBREVIATIONS 
EEG         electroencephalogram 
ESS         Epworth Sleeping Scale 
FDR         false discovery rate 
FC           functional connectivity 
fMRI         functional magnetic resonance imaging 
fALFF        fractional amplitude of low-frequency fluctuations 
HAMA       Hamilton Anxiety Scale 
HAMD       Hamilton Depression Scale 
ITT          Intention-to-treat 
LEDD        levodopa-equivalent daily dose 
MDS-UPDRS   MDS–Unified PD Rating Scale 
MS            Microstate 
MMSE         mini-mental state examination score 
MKPPS         Modified King’s Parkinson’s Disease Pain Scale 
MDS           Movement Disorder Society 
MSP            Musculoskeletal pain 
NRS            numeric rating scale 
PD             Parkinson’s disease 
PDQ-39         Parkinson's Disease Questionnaire-39 
PDSS-2          PD Sleep Scale–2 
PET             positron emission tomography 
M1              primary motor cortex 
RCT             randomized controlled trial 
rTMS            Repetitive transcranial magnetic stimulation 
RMT            resting motor threshold 
SCOUP-AUT    Scale for Outcomes in Parkinson's disease for Autonomic Symptoms 
sTMS          Single-pulse TMS 
            

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TABLE OF CONTENTS 
LIST OF ABBREVIATIONS .......................................................................................................... 2 
1. Summary ............................................................................................................................... 3 
2. Background ........................................................................................................................... 6 
3. Study Design ......................................................................................................................... 8 
4. Objectives ............................................................................................................................. 9 
5. Study Subjects ....................................................................................................................... 9 
5.1 Inclusion criteria: ................................................................................................................ 9 
5.2 Exclusion criteria: ............................................................................................................... 9 
6. Randomization and Recruitment ......................................................................................... 10 
7. Interventions ....................................................................................................................... 10 
7.1   Interventions for the experimental group ..................................................................... 10 
7.2   Interventions for the control group............................................................................... 11 
8. Data Collection ................................................................................................................... 11 
8.1   Questionnaire ............................................................................................................... 11 
8.2   Resting-EEG Recording ............................................................................................... 11 
8.3   TMS-EEG Recording ................................................................................................... 11 
8.4   MRI data acquisition .................................................................................................... 11 
9. Methods of Data Measurement ........................................................................................... 12 
9.1   Clinical measures ......................................................................................................... 12 
9.2   Resting-EEG Recording ............................................................................................... 13 
9.3   TMS-EEG Recording ................................................................................................... 13 
9.4   MRI data acquisition .................................................................................................... 14 
10. Outcomes .......................................................................................................................... 14 
11. Assessment of Outcomes ................................................................................................... 15 
12. Statistical Power and Sample Size .................................................................................... 15 
13. Data management .............................................................................................................. 15 
14. Statistical Analysis Plan .................................................................................................... 15 
14.1   clinical data analysis .................................................................................................. 15 
14.2   Time-varying network analysis of TMS-EEG ............................................................ 16 
14.3   Electroencephalography Preprocessing ...................................................................... 16 

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14.4   Microstate analysis ..................................................................................................... 17 
14.5   Relative power ........................................................................................................... 18 
14.6   fMRI data pre-processing and fractional amplitude of low-frequency fluctuations 
analysis .................................................................................................................................... 18 
15. Quality Control ................................................................................................................. 19 
15.1   Preparation phase ....................................................................................................... 19 
15.2   Screening and recruitment phase ................................................................................ 19 
15.3   Implementation stage ................................................................................................. 19 
16. Security Monitoring .......................................................................................................... 20 
16.1   Adverse events and reports ........................................................................................ 20 
16.2   Data security .............................................................................................................. 20 
17. Research Organization ...................................................................................................... 20 
18. Ethical considerations ....................................................................................................... 21 
19. Reference .......................................................................................................................... 21 
 
 
 
 

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1. Summary 
Title 
Repetitive Transcranial Magnetic Stimulation for Musculoskeletal Pain in 
Patients with Parkinson's Disease 
Background 
Pain is an increasingly recognized non-motor symptom of Parkinson’s 
disease (PD), with significant prevalence and negative impact on the quality 
of life of patients. Repetitive transcranial magnetic stimulation (rTMS) is a 
non-invasive brain stimulation technique that may be useful for the 
treatment of various psychiatric and neurological disorders. However, very 
few placebo-controlled studies have been performed specifically to relieve 
pain in Parkinson’s disease. 
Objectives 
The overall objective of this study is to test the analgesia of 20 Hz-rTMS 
delivered to primary motor cortex (M1) in PD patients with chronic 
musculoskeletal pain. The secondary objective is to evaluate the efficacy 
and safety of 20 Hz-rTMS delivered to M1 on PD related symptoms, and 
elucidate its underlying neurophysiological mechanisms through functional 
magnetic resonance imaging (fMRI) and electroencephalogram (EEG).  
Study Design 
The study is a blinded endpoint, parallel design, randomized controlled trial 
planned to enroll sixty-two PD patients with musculoskeletal pain. All 
participants will be allocated into two arms by randomization in a 2:1 ratio. 
Based on the anti-parkinsonism medications, active-rTMS will be given to 
the intervention group and sham-rTMS will be given to the control group. 
The therapeutic effect of M1-rTMS will be evaluated after 7 sessions of 
intervention by comparing the magnitude of clinical scales reduction from 
baseline over a 2-month period. Alongside clinical evaluations, we 
collected resting-state EEG, TMS-EEG and fMRI data of PD patients 
before and after treatment at the same time. 
Study 
Subjects 
Inclusion Criteria: 
 Idiopathic PD was diagnosed according to the 2015 Movement 
Disorder Society (MDS) clinical diagnostic criteria  

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 Hoehn and Yahr stages of I to III. 
 musculoskeletal pain was detected based on the Ford classification 
system for pain in PD. Pain duration of at least 3 months, with 
continuous moderate intensity pain (≥ 3/10 on a 0-10 numerical 
rating scale) occurring at least three days per week.  
 stable antiparkinsonian therapy for ≥4 weeks. 
Exclusion Criteria： 
 Contraindications to rTMS. 
 unstable ongoing psychiatric disorder, history of substance abuse 
(alcohol, drugs). 
 Prior treatment with any form of rTMS.  
 Mini-mental State Examination scores ≤24. 
 Other pain conditions, such as apparent osteoarthritis, or rheumatoid 
arthritis depended on laboratory or imaging findings. 
Interventions 
The M1 target was defined as the “hand knob” region, which corresponded 
to the motor cortical representation of the hand, regardless of pain location. 
The coil was centered over the scalp above the M1 target contralateral to 
the maximal pain area or positioned left side in case of bilateral pain. 
Intervention programs 
A MagPro X100 machine (Magventure, Farum) connected to an MCF-B70 
figure-of-eight coil delivered TMS during the real stimulation condition. 
Control programs 
Sham stimulation was delivered using an MCF-P-B65 figure-of-eight coil 
(Magventure), which produces an auditory percept similar to real TMS 
without inducing cortical activation. 
Outcomes 
The outcome is the clinical assessments and relevant brain changes in PD 
patients with pain following 20 Hz M1-rTMS over the course of 2 months.  
Primary outcome： 
• 
Change in the Modified King’s Parkinson’s Disease Pain Scale 
(MKPPS)-Domain 1 score. 

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• 
Change in a 0-10 numeric rating scale (NRS). 
• 
Proportion of participants who achieved treatment response 
(defined as a ≥30% reduction in MKPPS Domain 1 score from 
baseline).   
Secondary outcome： 
 
Change in MDS–Unified PD Rating Scale (MDS-UPDRS) I, II, III, 
IV. 
 
Change in the 24 items Hamilton Depression Scale (HAMD). 
 
Change in the 14 items Hamilton Anxiety Scale (HAMA). 
 
Change in the Scale for Outcomes in Parkinson's disease for 
Autonomic Symptoms (SCOUP-AUT).  
 
Change in the PD Sleep Scale–2 (PDSS-2) 
 
Change in the Epworth Sleeping Scale (ESS) 
 
Change in the Parkinson's Disease Questionnaire-39 (PDQ-39) 
 
Changes in time-varying EEG network dynamics 
 
Changes in EEG microstates. 
 
Changes in EEG relative power 
 
Changes in fractional amplitude of low-frequency fluctuations 
Sample Size 
The sample size was determined as a priori using G*Power3.1 (Faul, 
Erdf-elder, Buchner& Lang, 2009). To estimate the within-between 
interaction for repeated measures, we calculated that 52 patients would be 
required to achieve 80% power in a medium effect size of 0.25 at an alpha 
risk of 0.01. Considering the attrition rate of 20%, the minimum sample 
size required for total groups was 62. 
Statistical 
Analysis 
The study will be analyzed in accordance with the intention-to-treat (ITT) 
principle. To ensure comparability between the two groups, between-group 
comparisons of the characteristics of the study participants will be 
conducted using Student's t-tests or chi-square tests. Comparisons of each 
study outcome between groups will be performed using a mixed-effects 
model to correct for correlation between repeated measures data and 
potential confounding effects. Confounding variables will include 
pre-intervention values, and pain location. For comparison of brain metrics 
between the sham and M1-rTMS groups, independent samples t-tests or 
Mann-Whitney U tests were employed, as appropriate. Within-group 

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comparisons before and after rTMS were performed using paired samples 
t-tests or Wilcoxon signed-rank tests. A false discovery rate (FDR) 
correction was applied to adjust for multiple comparisons. All statistical 
tests were two-sided, and P value of <0.05 was considered statistically 
significant. All analyses were performed using SPSS software (version 26; 
SPSS, Chicago, IL, USA). 
 
2. Background 
Parkinson disease (PD) is a complex neurodegenerative disorder that involves multiple 
systems, which affects up to 2% of the general population older than 65 years. Chronic Pain is 
among the most frequently reported nonmotor symptoms, with a prevalence ranging from 
40% to 85%1,2. Musculoskeletal pain (MSP) affects over 80% of patients, occurring both in 
prodromal phases and during subsequent stages of the disease, imposing a tremendous 
burden3. However, literature reports that only a maximum of 50% of PD patients receive any 
form of pain therapy4. The treatment of pain is often insufficient, partly due to an incomplete 
interpretation of the underlying neural mechanisms. Currently, no level A evidence-based 
recommendations exist for treating PD-related pain. Therefore, identifying new safe and 
effective treatments for pain is imperative and it is also crucial to further supplement the 
current evidence for the treatment of PD-related pain. 
In recent years, new approaches based on non-invasive brain stimulation, particularly 
repetitive transcranial magnetic stimulation (rTMS), have emerged as therapeutic 
interventions for various neurological and psychiatric disorders. Level A evidence supports 
the efficacy of rTMS for neuropathic pain, while level B evidence exists for fibromyalgia5, 
and rTMS has also demonstrated clinical efficacy for PD-related symptoms, including 
freezing of gait6 and depression7. However, few well-designed randomized controlled trials 
(RCTs) have specifically investigated rTMS for relieving MSK pain in PD, particularly using 
functional magnetic resonance imaging (fMRI)-guided individualized targeting. The bulk of 
evidence indicates that optimal rTMS stimulation parameters for inducing analgesia include a 
frequency of 10-20 Hz, an intensity of 80-120% of the resting motor threshold (RMT), 
1000-2000 pulses per session, and 5-10 sessions5,8. The primary motor cortex (M1) is the 
main target for chronic pain treatment with rTMS, as it is considered interconnected with 
cognitive, affective, and somatosensory networks9. When TMS is delivered over M1, a brief 

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high-intensity magnetic field induces an electrical current in underlying cortical tissue by 
electromagnetic induction. This local cortical stimulation has been able to exert changes in the 
functioning of distant brain areas. Furthermore, rTMS has the capacity to induce persistent 
changes in cortical activity extending beyond the immediate stimulation period10. 
Analgesic effects persist beyond the duration of rTMS sessions, appear correlated with 
restoration of normal cortical excitability, and depend on modulation of brain regions 
involved in pain processing, specifically descending antinociceptive systems11. Moreover, 
TMS–positron emission tomography (PET) studies demonstrated that high-frequency motor 
cortex stimulation increases dopamine release12. Concurrent TMS/fMRI research 
revealed that M1 stimulation evokes activation in key networks including the insular, while 
modulating domain-general networks such as the default mode network (DMN) and attention 
network13.Multiple neurotransmitters are involved in pain processing steps, including 
gamma-aminobutyric acid (GABA), the major brain inhibitory neurotransmitter14. 
Meta-analyses established significant associations between prefrontal gamma-band 
oscillations and chronic pain15. Previous systematic reviews of molecular changes following 
rTMS in humans indicate potential increases in brain derived neurotrophic factor (BDNF), 
GABA, and beta-endorphin16. The pathophysiology of pain in PD exhibits considerable 
heterogeneity, potentially involving dopamine depletion along with dysfunctional pain 
processing and modulation pathways1. Longitudinal neuroimaging comparisons hold 
significant promise for selecting TMS candidates and monitoring treatment efficacy.  
Based on behavioral measures alone, it is impossible to reveal extra-motor areas and entire 
brain networks reflecting the impact of TMS. Thus, establishing a causal link between the 
neuromodulation of cortical targets and chronic pain treatments necessitates integrating rTMS 
techniques with brain imaging and network dynamics analysis. For example, fMRI has 
assisted in identifying TMS-induced modifications in functional connectivity (FC) and 
regional activation patterns, mapping pain-related network plasticity. Concurrently, 
electroencephalography (EEG) has contributed to capture neuromodulatory effects of TMS, 
such as alterations in oscillatory dynamics and cortical excitability, reflecting transient or 
sustained 
neural 
reorganization17. 
Recent 
advancements 
in 
TMS-compatible 
electroencephalography 
(TMS-EEG) 
enable 
straightforwardly 
measuring 
effective 
connectivity within cortical circuits, bypassing sensory and motor pathways18. Combining 

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fMRI and EEG, particularly TMS real-time EEG, provides more temporal and spatial 
information for investigating TMS intervention effects, which helps us to have a deeper 
understanding of the specific mechanism behind its action. 
By a double-blind, sham-controlled and randomized study, we aimed to investigate the 
structural and functional neurophysiological basis underlying the clinical efficacy of 
M1-rTMS for pain in PD patients. We expected to confirm that M1-rTMS, but not sham 
stimulation, significantly alleviates clinical pain and improves overall disease severity. In 
addition, we planned to integrate multimodal data - including resting state EEG, TMS 
real-time EEG, and fMRI-related parameters - linking these measures to clinical outcomes. 
This integration will elucidate how TMS modulates key neural circuits to relieve PD-related 
MSK pain and produce clinical benefits. We hypothesized that clinical efficacy would be 
associated with significant changes in cortical functional changes induced by stimulation and 
pain modulation systems. 
3. Study Design 
The study is a single-center, blinded-endpoint, parallel-controlled, randomized clinical trial 
planning to recruit 62 PD patients with MSP from the Movement Disorders Clinic at the 
Second Affiliated Hospital of Soochow University. All participants will be consecutively 
recruited and randomly assigned to either the active rTMS group or sham stimulation group 
with a 2:1ratio (Figure.1a). In addition to the conventional anti-parkinsonism medications, 
the control group will receive sham-rTMS treatment and the intervention group will receive 
active-rTMS treatment. To longitudinally assess clinical and physiological measures, 
participants were assessed across treatment and follow-up phases at four time points: baseline 
(T0); after completion of all rTMS or sham stimulation sessions on Day 8 (T1); 1 month 
post-treatment (T2); and 2 months post-treatment (T3) (Figure.2). Assessments involved the 

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completion of standardized questionnaires, fMRI and EEG acquisition. 
Figure.1 Schematic representation of the study 
Figure.2 Timeline of procedures. Treatment assessments were performed in the day before 
(T0) and after completion of all rTMS or sham stimulation sessions (T1). Follow-up 
assessments occurred at 1 to 2 months post-treatment (T2 and T3, respectively). rTMS 
therapy was provided on 7 consecutive days. 
4. Objectives 
The overall objective of this study is to test the efficacy and safety of 7 sessions of 20 
Hz-rTMS delivered to primary motor cortex (M1) in PD patients with chronic MSP. The 
secondary objective is to elucidate its underlying neurophysiological mechanisms through 
fMRI and EEG. 
5. Study Subjects 
This study is planned to enroll 62 PD patients with MSP. 
5.1 Inclusion criteria: 
 Idiopathic PD was diagnosed according to the 2015 Movement Disorder Society 
(MDS) clinical diagnostic criteria  
 Hoehn and Yahr stages of I to III. 
 musculoskeletal pain was detected based on the Ford classification system for pain in 
PD. Pain duration of at least 3 months, with continuous moderate intensity pain (≥ 
3/10 on a 0-10 numerical rating scale) occurring at least three days per week.  
 stable antiparkinsonian therapy for ≥4 weeks. 
5.2 Exclusion criteria: 
 Contraindications to rTMS. 
 unstable ongoing psychiatric disorder, history of substance abuse (alcohol, drugs). 

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 Prior treatment with any form of rTMS.  
 Mini-mental State Examination scores ≤24. 
 Other pain conditions, such as apparent osteoarthritis, or rheumatoid arthritis 
depended on laboratory or imaging findings. 
6. Randomization and Recruitment 
Patients will be randomised to receive either active or sham-rTMS according to a 2:1 ratio. 
The randomization list is generated by the Microsoft Office Excel 2021 (Microsoft, USA) 
software and kept confidential until eligible study subjects enrolled. After being fully 
informed about the protocol of this study and signing the informed consent form, the study 
subjects will receive a free physical and mini-mental state examination score (MMSE) 
assessment to determine if they meet the eligibility criteria. After providing the enrollment 
number of the study subjects, the physician will have access to the randomization outcome. 
7. Interventions 
All participants sat in a comfortable reclining chair and remained as relaxed as possible, 
protected by earplugs during all procedures. Each participant received 7 sessions of treatment 
once a day at the same time continuously for 7 days. Anti-parkinsonism drugs remained 
unchanged throughout the whole study.  
Neuronavigation（Northern Digital Inc., Polaris Spectra, Canada）with an optical tracking 
system (TMS Navigator, Localite GmbH ) monitored coil positioning throughout all rTMS 
sessions. High resolution T1-weighted MRI (1.5 tesla) slices of each participant were 
integrated to allow individually tridimensional brain reconstruction prior to the first session 
(Fig.1e). An infrared camera facilitated precise coil positioning over the target area under 
real-time visualization. The M1 target was defined as the “hand knob” region, which 
corresponded to the motor cortical representation of the hand, regardless of pain location. The 
coil was centered over the scalp above the M1 target contralateral to the maximal pain area or 
positioned left side in case of bilateral pain. 
7.1   Interventions for the experimental group 
A MagPro X100 machine (Magventure, Farum) connected to an MCF-B70 figure-of-eight 
coil delivered TMS during the real stimulation condition. The stimulation paradigm consisted 
of 100 trains of TMS pulses delivered at 20Hz with an11-second intertrain interval, resulting 
in 2,000 pulses per session. Stimulation intensity was set to 80% of the RMT, determined as 

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the minimum intensity required to elicit an electromyographic response ≥50μV in the first 
dorsal interosseus muscle of the hand in at least 5 out of 10 trials.  
7.2   Interventions for the control group 
Sham stimulation was delivered using an MCF-P-B65 figure-of-eight coil (Magventure), 
which produces an auditory percept similar to real TMS without inducing cortical activation. 
The stimulation paradigm consisted of 100 trains of TMS pulses delivered at 20Hz with 
an11-second intertrain interval, resulting in 2,000 pulses per session. Stimulation intensity 
was set to 80% of the RMT.  
8. Data Collection 
Data collection is carried out by trained and visited doctors and investigators, and the 
screening, baseline, and follow-up programs and the schedule for data collection are shown in 
Table 1. Monitoring of intervention effects are collected from study subjects through clinical 
scores, resting-EEG, TMS-EEG and fMRI. The specific methods are shown below: 
8.1   Questionnaire 
• Demographic data: age, sex and education.  
• Medical history: disease duration, levodopa-equivalent daily dose (LEDD), Primary 
symptoms (tremor/rigidity/bradykinesia).  
• Pain symptoms: pain locations, MKPPS domain 1, NRS. 
• PD related symptoms: MDS-UPDRS I, II, III, IV. H-Y stage, HAMA, HAMD, PDSS-2, 
ESS, SCOPA-AUT, PDQ-39.  
• Adverse events: dizziness, headaches, tinnitus, etc. 
8.2   Resting-EEG Recording  
The EEG recording protocol consisted of a 5-minute resting-state paradigm without any task 
involvement.   
8.3   TMS-EEG Recording 
The EEG recording protocol consisted of a 20-minute session comprising approximately 120 
TMS trials at an intensity of 120% RMT. 
8.4   MRI data acquisition  
Resting-state fMRI. 
Table 1. Visiting Assessment Schedule. 
Data collection 
Screening 
Stage 1 Treatment 
Stage 2 Follow-up 
baseline 
Day 8 
1 month 
2month 

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Screening form 
× 
 
 
 
 
MMSE 
× 
 
 
 
 
Informed consent 
 
× 
 
 
 
Demographic data 
× 
× 
 
 
 
Medical history 
× 
× 
 
 
 
Pain symptoms 
× 
× 
× 
× 
× 
PD related symptoms 
 
× 
× 
× 
× 
Resting-EEG data 
 
× 
× 
 
 
TMS-EEG data 
 
× 
× 
 
 
MRI data 
 
× 
× 
 
 
Adverse events 
 
× 
× 
× 
× 
 
9. Methods of Data Measurement 
9.1   Clinical measures 
Clinical assessments were performed at 4 time points: T0, T1, T2 and T3 (Figure.2). All 
participants were evaluated during their “ON” medication states at approximately the same 
time of day. A face-to-face survey is conducted by a trained and qualified investigator with 
each participant, using a standardized, self-administered questionnaire to collect demographic 
information (age, sex, education), medical history (disease duration, LEDD, primary 
symptoms). Standardized scales are used to assess pain symptoms and PD related symptoms.  
Specifically, LEDD = (Standard-release levodopa × 1) + (Controlled-release levodopa × 0.75) 
+ (Pergolide × 100) + [(Standard-release levodopa × 1) + (Controlled-release levodopa × 
0.75)] × 0.33 (with concurrent Entacapone) + (Piribedil × 1) + (Pramipexole × 100) + 
(Selegiline × 10) + (Rasagiline × 100) + (Amantadine × 1). Pain intensity was assessed over 
the past 24 hours using a 0-10 numeric rating scale (NRS), where 0 indicating no pain and 10 
indicating maximal pain. The Modified KING’S PD Pain Scale (MKPPS), adapted for 
suitability in a Chinese population and incorporating Ford’s pain subtypes based on the 
original KPPS, comprises 16 items divided into 5 separate domains. MKPPS Domain 1 was 
specifically used to evaluate MSK pain and divided into 5 items (neck, back, upper and lower 
extremities, buttock) according to location. Each item was scored by multiplying severity (0-3) 
by frequency (0-4), resulting in a total possible score range from 0 to 60. The scales used to 

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assess motor symptoms are parts III (ranging from 0 to 132) and IV (ranging from 0 to 24) of 
the MDS–Unified PD Rating Scale (MDS-UPDRS), with higher scores indicating more 
severe symptoms. The scales used to assess non-motor symptoms included parts I (ranging 
from 0 to 52) and II (ranging from 0 to 52) of the MDS-UPDRS, with higher scores indicating 
more severe symptoms. The depression score (ranging from 0 to 76 with higher scores 
indicating more severe depression) from the 24 items Hamilton Depression Scale (HAMD). 
The anxiety score (ranging from 0 to 60 with higher scores indicating more severe anxiety) 
from the 14 items Hamilton Anxiety Scale (HAMA). The Scale for Outcomes in Parkinson's 
disease for Autonomic Symptoms (SCOUP-AUT, ranging from 0 to 67, with higher scores 
indicating higher autonomic nervous system dysfunction). The sleep problem index (from 0 to 
68 with higher scores indicating more severe sleep problem) from the PD Sleep Scale–2 
(PDSS-2). The daytime sleepiness will be assessed by the Epworth Sleeping Scale (ESS), 
which has a score range of 0–24, with higher scores indicating more severe symptoms. We 
will also assess change in quality of life from the Parkinson's Disease Questionnaire-39 
(PDQ-39), ranging from 0 to 156 with higher scores indicating more serious influence. 
9.2   Resting-EEG Recording 
For each patient, resting-EEG data were collected at T0 and T1 (Figure.2). Participants were 
asked to wash and brush their hair. During EEG recordings, participants sat alone in a quiet 
room and were requested to minimize body movements, mostly with their eyes closed. EEG 
data were recorded using a TMS-compatible EEG amplifier (Neuracle, NSH0128, Changzhou, 
China) and a cap (Greentek, Wuhan, China) equipped with 64 TMS-compatible coated 
electrodes arranged according to the international 10/20 system. Skin/electrode impedance 
was maintained below 10KΩ. The resting-EEG recording protocol consisted of a 5-minute 
resting-state paradigm without any task involvement (Figure.1d).  
9.3   TMS-EEG Recording 
For each patient, TMS-EEG data were collected at T0 and T1 (Figure.2). Single-pulse TMS 
(sTMS) was delivered to M1 during EEG recording by means of a figure-of-eight coil 
oriented to elicit a posterolateral-anteromedial current flow in the brain. The interval of each 
sTMS was set at 4 seconds to prevent habituation with repeated stimulation. The EEG signal 
was bandpass filtered (0.1-100Hz) and digitized at 16 kHz. Participants wore inserted 
earplugs to avoid signals contamination from the TMS discharge click. Additionally, a 0.5 mm 

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foam pad was attached to the TMS coil to minimize electrode movement and bone-conducted 
auditory artifacts. The TMS-EEG recording protocol consisted of a 20-minute session 
comprising approximately 120 TMS trials at an intensity of 120% RMT (Figure.1d).  
9.4   MRI data acquisition 
MRI data were acquired at baseline and post-treatment using a 3.0-Tesla scanner (Siemens, 
Prisma, Germany) equipped with a 64-channel head coil (Figure.1c). During scanning, 
participants were instructed to remain still, keep their eyes closed without falling asleep, and 
think of nothing in particular. Tight yet comfortable foam padding and earplugs were used to 
minimize head motion and reduce scanner noise. Resting-state fMRI was scanned using a 
gradient-recalled-echo planar imaging sequence with the following parameters: repetition 
time (TR)/echo time (TE) = 1240/32 milliseconds, flip angle (FA) = 67 ̊, matrix size = 86×86, 
field of view (FOV) = 215 mm×215 mm, slice thickness/gap =2.5/0 mm, 57 slices, 300 
volumes and  an acquisition time of 384 s. High-resolution brain T1-weighted (T1w) MRI 
was obtained using a sagittal 3D magnetization-prepared rapid gradient echo (MPRAGE) 
sequence: TR/TE = 2300/2.34 milliseconds, FA = 8 ̊, matrix = 256×256, FOV = 256 mm×
256 mm, slice thickness/gap =1.0/0 mm, voxel size = 1×1×1 mm3, 240 volumes and an 
acquisition time of 234 s.  
10. Outcomes 
This study is designed to investigate the structural and functional neurophysiological basis 
underlying the clinical efficacy of M1-rTMS for pain in PD patients. The outcomes include 
the changes in clinical scores and relevant brain metrics.  
Primary outcome： 
• 
Change in the MKPPS-Domain 1 score. 
• 
Change in NRS. 
• 
Proportion of participants who achieved treatment response (defined as a ≥30% reduction 
in MKPPS Domain 1 score from baseline).  
Secondary outcome： 
 
Change in MDS-UPDRS I, II, III, IV. 
 
Change in HAMD. 
 
Change in HAMA. 
 
Change in SCOUP-AUT.  

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 
Change in PDSS-2. 
 
Change in ESS. 
 
Change in PDQ-39. 
 
Changes in time-varying EEG network dynamics 
 
Changes in EEG microstates. 
 
Changes in EEG relative power 
 
Changes in fractional amplitude of low-frequency fluctuations 
11. Assessment of Outcomes 
In this study, outcomes are assessed using standardized, internationally accepted measures. 
Blindness (the follow-up assessors are unaware of the grouping of study subjects) is used in 
the outcome assessment process. 
12. Statistical Power and Sample Size 
The sample size was determined as a priori using G*Power3.1 (Faul, Erdf-elder, Buchner& 
Lang, 2009). To estimate the within-between interaction for repeated measures, we calculated 
that 52 patients would be required to achieve 80% power in a medium effect size of 0.25 at an 
alpha risk of 0.01. Considering the attrition rate of 20%, the minimum sample size required 
for total groups was 62. 
13. Data management 
All data are entered into the electronic database in the department of neurology, the second 
affiliated hospital of Soochow University by trained and qualified doctors or investigators. 
The data entered are reviewed for a final data check and quality control. 
14. Statistical Analysis Plan 
14.1   clinical data analysis 
Intention to treat (ITT) analyses will be conducted, in which study outcomes will be compared 
between participants according to their randomization assignment, regardless of their actual 
adherence to the intervention. To compare the two groups for comparability, between-group 
comparisons of the characteristics of the study participants will be performed using Student's 
t-tests or chi-square tests as appropriate. A generalized mixed-effects model for repeated 
measures was applied to estimate rTMS effects on clinical outcomes with time expressed as a 
continuous variable, group (M1-and sham-rTMS), group by time interaction as fixed effects, 
baseline values and pain location as covariates, and subjects as random effects. All tests will 

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be two-sided, with a P value of <0.05 suggesting a statistical significance, and all statistical 
analyses will be performed using SPSS software (version 26; SPSS, Chicago, IL, USA). 
14.2   Time-varying network analysis of TMS-EEG 
TMS stimulates were utilized as stimulus labels, which time points corresponding to each 
label were set as time’0’. Then, the data corresponding to 0.5s before and 1s after the markers 
were extracted (a total of 1.5s for each segment). Eight-rate down-sampled segmentation was 
applied to reduce calculation load19. To examine dynamic information processing during 
TMS-evoked disturbances, an adaptive directed transfer function (ADTF) value was used to 
construct time-varying network20. Then a time-varying multivariate adaptive autoregressive 
(tv-MVAAR) model and the ADTF were calculated. The tv-MVAAR model coefficients were 
estimated by the Kalman filter algorithm, with the order of the model automatically 
determined by the Akaike Information Criterion21. 
14.3   Electroencephalography Preprocessing 
EEG preprocessing was performed offline using the EEGLAB toolbox (Delorme & Makeig, 
2004) implemented in MATLAB R2013b (The MathWorks Inc., Natick, Massachusetts, 
United States). Raw data were down-sampled to 512 Hz, re-referenced to the average of 
residual channels, bandpass filtered between 1 and 80 Hz, and a 50 Hz notch filter was 
applied. Independent component analysis (ICA) was used to remove components representing 
eye movements and muscle artifacts. Subsequently, all data sets were visually inspected, and 
remaining bad intervals were marked for rejection. Finally, EEG recordings of 3 minute were 
segmented for further analysis. 
In order to detect EEG power in different regions, the brain of 64-channel cap was divided 
into four regions (Figure 3): frontal (F, FPz FP1 FP2 AF7 AF3 AF4 AF8 F7 F5 F3 F1 Fz F2 
F4 F6 F8), central (C, FC5 FC3 FC1 FCz FC2 FC4 FC6 C5 C3 C1 Cz C2 C4 C6 CP5 CP3 
CP1 CP2 CP4 CP6 ), temporal (T, FT7 T7 TP7 FT8 T8 TP8), and posterior (P, P7 P5 P3 Pz 
P4 P6 P8 PO7 PO5 PO3 POz PO4 PO6 PO8 O1 Oz O2). 

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Figure.3 EEG electrode positions on the brain. 
14.4   Microstate analysis 
Microstate (MS) analysis was performed using CARTOOL software22 in three stages: 
individual-level clustering, group-level clustering, and backfitting. For each participant, EEG 
topographies at global field power (GFP) peaks, representing timepoints of the highest 
signal-to-noise ratio, were extracted and clustered with a modified k-means clustering, 
yielding a variable number of individual-level cluster topographies. Next, individual cluster 
topographies were concatenated and clustered at the group level. As an increasing number of 
studies was now using a data-driven approach, CARTOOL implemented meta-criterion was 
used as guidance to determine the optimal number of microstates. The original momentary 
maps from both groups were separately clustered into five MS classes. Topographies were 
visually inspected and compared with those reported in the literature. The first 4 topographies 
closely resembled the well-known “canonical” MS (class A to D). MS class A exhibited an 
upper left-bottom right orientation, class B an upper right-bottom left orientation, class C an 
anterior-posterior orientation, and class D a trend of increasing gradually from the front to the 
center to the maximum. The fifth topography, labeled MS class E, consistently demonstrated a 
left lateralized maximum as reported in more recent studies23-25. In order to compare the 
differences of groups, the following microstate parameters for each MS segmentation class 
were calculated: a) Mean Duration: Average time (milliseconds) of microstate segments; b) 
Time Coverage: Percentage of total time occupied by a microstate; c) Segment Count Density: 

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Number of times that a microstate recurs across all analysis epochs. 
14.5   Relative power 
The pre-processed data were segmented into consecutive, non-overlapping 2 s epochs. For 
each EEG epoch, we computed the fast Fourier transform (FFT) algorithm to convert to 
frequency domain. The power values were obtained for following five frequency bands: delta 
(1-4Hz), theta (4-8Hz), alpha(8-13Hz), beta(13-30Hz), gamma(30-80Hz). Relative power of 
each band of power from 1 to 80 Hz was averaged in each region and calculated by 
 
where P(.) indicates the power, RP(.) indicates the relative power, and f 1, f 2 indicate the low 
and high frequency, respectively. 
These EEG power values were compared using non-parametric Mann-Whitney U tests. The 
significance level of P < 0.05 was corrected by a false discovery rate (FDR) for multiple 
comparisons. 
14.6   fMRI data pre-processing and fractional amplitude of low-frequency 
fluctuations analysis 
All resting-state fMRI data were preprocessed using the Data Processing & Analysis for Brain 
Imaging (DPABI, http://rfmri.org/dpabi), a toolbox developed based on MATLAB. Briefly, 
the first 10 volumes of each scan were discarded to allow for magnetization equilibrium and 
participant adaptation. The remaining images were corrected for differences in slice 
acquisition timing, followed by realignment to adjust for head motion. Functional images 
were then normalized to the standard Montreal Neurological Institute (MNI) space and 
resampled to an isotropic voxel size of 3 × 3 × 3 mm³. To reduce non-neuronal confounds, 
nuisance signals including the Friston 24 head motion parameters, white matter, and 
cerebrospinal fluid were regressed out. 
To characterize regional spontaneous brain activity, the fractional amplitude of low-frequency 
fluctuations (fALFF) was computed. Specifically, the amplitude of low-frequency fluctuations 
(ALFF) was derived by transforming each voxel’s time series into the frequency domain 
using a fast Fourier transform and calculating the square root of the power within the 0.01–0.1 
Hz band. fALFF was then obtained by dividing ALFF by the total amplitude across the entire 
frequency range, thereby improving specificity by reducing nonspecific physiological noise. 

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To enhance the normality of the data distribution, voxel-wise z-score standardization was 
applied to the resulting fALFF maps before statistical analysis. 
15. Quality Control 
Quality control will be conducted by a team of investigators, key research staff, and project 
inspectors. Strict quality control will be implemented at every step of the study including 
project preparation, training, screening, intervention, and data collection. A manual of 
procedures will be developed to detail the standardized approaches used in the study, such as 
participant recruitment, intervention, doctor training (protocol-based treatment, health 
coaching, and follow-up), patient education (medication adherence), and other procedures of 
the study. All study personnel will be required to participate in a study training session prior to 
the initiation of any study procedures. The quality control team will review the study data 
regularly to ensure that all phases of the project are strictly implemented according to the 
study protocol and the authenticity, completeness, accuracy, and reliability of the research 
data. 
15.1   Preparation phase 
A manual of procedures will include detailed descriptions of all trial procedures and will be 
used for training purposes and as a reference for all study investigators and staff. Standard 
forms, devices, and procedures in the field for rTMS treatment and other data collection 
procedures will be standardized. Furthermore, standard event definitions and event validation 
procedures will be used. The project will purchase the devices used in the study which pass 
the national quality inspection. The study protocol, manual of procedures, study forms, 
training materials, and other written materials will be prepared centrally. 
15.2   Screening and recruitment phase 
• To conduct targeted health education sessions for potential participants and their 
families/caregivers, ensuring they fully understand the impact of musculoskeletal pain 
on quality of life in Parkinson’s disease. The goal is to build awareness that pain is a 
common but manageable non-motor symptom, and to encourage participation of all 
eligible individuals. 
• Enrolled patients will receive training to ensure they are able to accurately complete 
and submit required study materials using provided digital tools. 
15.3   Implementation stage 

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• Each enrolled patient will undergo daily rTMS sessions over 7 consecutive days, 
administered by certified TMS technicians. Stimulation parameters will follow the 
study protocol and be documented per session. 
• It is required that all EEG, MRI, and clinical scale data be completed for each patient 
before the first TMS session and within 24 hours after the final session. All 
responsible personnel are expected to coordinate proactively and upload data promptly 
to ensure the smooth progress of the study.  
• Dedicated follow-up appointments to reduce missed appointments. 
• Outcomes are assessed by applying a blinded method (the assessor is unaware of the 
grouping of study subjects). 
16. Security Monitoring 
16.1   Adverse events and reports 
The intervention program in this study is more feasible. Possible adverse events include 
dizziness, headaches and tinnitus, which have been monitored at treatment and follow-up, and 
other adverse events not listed are reported and registered by the study subjects and their 
families. 
16.2   Data security 
After reviewing and confirming that the database created is correct, the data are locked by the 
principal investigator, the sponsor, and the statistical analyst. No further changes are made to 
the data files after locking. Problems identified after data locking should be followed strictly 
by the process of unlocking and re-locking the data. The Data Safety Committee and Ethics 
Committee are responsible for monitoring. 
17. Research Organization 
The study is conducted jointly by the Department of Neurology, Clinical Neurophysiology 
and Radiology, The Second Affiliated Hospital of Soochow University, forming a 
multidisciplinary and multi-departmental collaborative team of researchers (Figure.4). 
Decision-making, protocol design, overall organization, management and coordination of the 
study are carried out by the study steering committee. Screening, recruitment and intervention 
management of the study subjects are implemented by the intervention team. Blinded 
assessment of the outcome is implemented by the follow-up team. Data quality control is 
implemented by the quality control team. Resting-EEG, TMS-EEG and MRI data acquisition 
are implemented by the Department of Clinical Neurophysiology and Radiology, respectively, 

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and statistical analysis and reporting of the results is carried out by the Data Analysis Centre. 
Statistical analysis and reporting of results are carried out by the Data Analysis Centre, and 
the Data Safety Management Committee supervised the entire implementation of the project. 
Adopting a management model of overall coordination and division of labor and 
responsibility, and implementing a job responsibility system. 
Figure 5. Study Organization Structure. 
18. Ethical considerations 
It is the responsibility of the principal investigator to ensure that this trial will be 
conducted in full compliance with the Declaration of Helsinki and the Chinese Code for 
Quality Management of Clinical Trials, as well as other relevant regulations. The study 
protocol was reviewed by the Institutional Review Board of the Second Affiliated Hospital of 
Soochow University, and all study subjects and their guardians signed an informed consent 
form. 
19. Reference 
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Marques, A. & Brefel-Courbon, C. Chronic pain in Parkinson's disease: Clinical and pathophysiological 
aspects. Rev Neurol (Paris) 177, 394-399 (2021). 
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Rukavina, K., et al. Musculoskeletal pain in Parkinson's disease: Association with dopaminergic 
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Buhmann, C., Kassubek, J. & Jost, W.H. Management of Pain in Parkinson's Disease. J Parkinsons Dis 10, 
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Department of Radiology 
Follow-up team 
Research Steering Committee 
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Neurophysiology 
Data Security Management 
 
Data Analysis Centre 
Intervention 
Quality control 

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