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Rationale: Current treatment of patients with Parkinson's disease (PD) is mainly based on the modulation of neural activity in the motor circuits of the basal ganglia and cerebral cortex by either drug intervention (dopamine replacement therapy or dopaminergic medication) or deep brain stimulation (DBS). However, many Parkinson patients have an insufficient (long-term) response to medical treatments, and DBS is an invasive procedure with resource implications and potential side effects. Moreover, not all patients are eligible for DBS. Therefore, new ways of administering neuromodulation are needed. A potential avenue may be self-regulation of brain circuits through neurofeedback. Self-regulation of motor circuits through mental imagery and neurofeedback using real-time functional MRI (fMRI) signals has already been shown to be feasible, and there are also preliminary data on clinical benefits of such self-regulation training. We here aim to use the non-invasive fMRI-neurofeedback method to train patients in the regulation of brain circuits that are implicated in successful drug treatment and/or DBS.
Objective: To investigate brain mechanisms and efficacy of an fMRI-neurofeedback protocol that targets the brain's motor circuits through the basal ganglia.
Study design: Randomised controlled trial Study population: Patients with Parkinson's disease Investigation: In the experimental group, fMRI-neurofeedback will be administered in 4 separate sessions of about 2 hours each over approximately one month. The MRI measurement in each session will be approximately 60 minutes long and include upregulation training of brain activity in specific target areas by mental imagery. The fMRI signals are processed such that the patients get visual feedback about the success of the upregulation. In addition, patients are asked to practice the self-regulation strategies on a daily basis at home between the neurofeedback sessions. The control intervention will consist of mental imagery without neurofeedback.
Main study parameters/endpoints: Post-interventional improvement of motor symptoms of PD as assessed by the Movement Disorder Society Unified Parkinson's Disease Rating Scale (MDS-UPDRS) motor scale in the on-medication state.
Nature and extent of the burden and risks associated with participation, benefit and group relatedness: This is a low-risk study where the main burden is participation time and MRI scans.
Parkinson's disease (PD) is associated with progressive neurodegeneration of dopaminergic neurons of the substantia nigra. It is characterized by both motor and non-motor system manifestations. Dopamine replacement therapy or dopaminergic medication are the key therapeutic strategies, but deep brain stimulation (DBS) is increasingly being used in cases where drug response is/ has become insufficient or hampered by unacceptable side effects.
Neurofeedback (NF) entails training of self-regulation of brain regions or networks via mental imagery and real-time feedback of neural signals, for example obtained by functional MRI (fMRI). NF enables patients to develop personal strategies that are most effective in self-regulating brain areas and networks. Thereby, it can provide an individually tailored intervention. NF is a highly sustainable form of non-invasive neuromodulation because, once learnt, the self-regulation strategies can in principle be applied by patients whenever needed to overcome disease symptomology.
NF can be used to train patients to change their brain activity in different directions, or to modulate patterns of co-activation between regions. Mental imagery of moving one's own body (also called kinaesthetic imagery) can potentially be used to improve motor functions and neuroplasticity in PD. Kinaesthetic imagery is also a suitable strategy for increasing activation in the brain's motor network, and motor imagery training can be reinforced through combination with NF. A NF paradigm involving upregulation training of motor areas through kinaesthetic imagery thus has good plausibility for PD. The PI's group has shown proof-of-concept of such an fMRI-NF training (targeting the supplementary motor area, SMA) in PD and has recently completed a feasibility study of fMRI-NF targeting the putamen in 12 PD patients (NCT05627895). The aim of the current investigator-initiated study is to investigate the effects of putamen upregulation training on motor function and other outcome parameters in PD.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Neurofeedback | Experimental | Four weekly MRI sessions where they will learn to upregulate the activity of the putamen during motor imagery via fMRI neurofeedback. |
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| Kinesthetic imagery | Active Comparator | Four weekly MRI sessions with motor imagery without fMRI neurofeedback. |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Neurofeedback | Other | The participants will be instructed to use cognitive strategies to upregulate (increase) their brain activity in the selected brain region, with the suggestion that motor imagery may be particularly effective, for example, mental imagery of swimming or playing a musical instrument. During the rest blocks, the participants will be instructed to relax. The instructions to start and stop the regulation and rest blocks are visualized on a screen in the scanner, and the brain activity of the putamen will be displayed in real-time using a thermometer bar for visualization. |
| Measure | Description | Time Frame |
|---|---|---|
| MDS-UPDRS (Unified Parkinson's Disease Rating Scale) | Pre versus Post-interventional change in the MDS-UPDRS (Unified Parkinson's Disease Rating Scale) motor scale will be compared using t statistics. The MDS-UPDRS contains 65 scores, each with a range from 0 (no impairment) to 4 (severe impairment). The total scale ranges between 0 - 260, with 0 indicating no impairment and 260 indicating the highest level of impairment. As primary outcome measure we will use Part III: Motor Examination, which has 33 scores. The measurement at the last MRI session will be the primary endpoint. | After screening, after the last MRI session (approx. 5 weeks after screening) and at follow up session (approx. 4 weeks after final MRI session) |
| Measure | Description | Time Frame |
|---|---|---|
| Performance of Putamen neurofeedback training (fMRI analysis) | To determine the performance of Putamen self-regulation, we will employ an region of interest (ROI) general linear model analysis, using a T-contrast of all blocks with the Putamen as the target region versus all the baseline blocks. This will allow us to assess recruitment of the Putamen during the training as well as regulation success. Furthermore we will use an ANOVA F-contrast to check for any interactions of the neurofeedback training with sessions (eg., if Session 4 shows improved neurofeedback success as compared to Session 1). |
| Measure | Description | Time Frame |
|---|---|---|
| Neurofeedback training effects on motor symptoms and experiences | Effect of neurofeedback training on motor symptoms and experiences will be assessed using the MDS-UPDRS part II and IV. The MDS-UPDRS contains 65 scores, each with a range from 0 (no impairment) to 4 (severe impairment). The Part II subscore, indicating nonmotor experiences of daily living has a total of 13 items with scores ranging between 0-52. The Part IV subscore, indicating nonmotor experiences of daily living has a total of 6 items with scores ranging between 0-24. |
Inclusion Criteria:
Exclusion Criteria:
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| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| David EJ Linden, Prof. | Contact | +31 43 3881021 | david.linden@maastrichtuniversity.nl |
| Name | Affiliation | Role |
|---|---|---|
| David EJ Linden, Prof. | Maastricht University | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Uniklinik Köln | Not yet recruiting | Cologne | Germany |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 35013372 | Background | Akram N, Li H, Ben-Joseph A, Budu C, Gallagher DA, Bestwick JP, Schrag A, Noyce AJ, Simonet C. Developing and assessing a new web-based tapping test for measuring distal movement in Parkinson's disease: a Distal Finger Tapping test. Sci Rep. 2022 Jan 10;12(1):386. doi: 10.1038/s41598-021-03563-7. | |
| 26419389 | Background |
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| ID | Term |
|---|---|
| D010300 | Parkinson Disease |
| ID | Term |
|---|---|
| D020734 | Parkinsonian Disorders |
| D001480 | Basal Ganglia Diseases |
| D001927 | Brain Diseases |
| D002493 | Central Nervous System Diseases |
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| ID | Term |
|---|---|
| D058765 | Neurofeedback |
| ID | Term |
|---|---|
| D001676 | Biofeedback, Psychology |
| D026441 | Mind-Body Therapies |
| D000529 | Complementary Therapies |
| D013812 | Therapeutics |
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The outcome assessor will be unaware of which condition the participant is in.
|
| Kinesthetic imagery | Other | The participants will be instructed to imagine movements during the active blocks. During the rest blocks, the participants will be instructed to relax. The instructions to start and stop the regulation and rest blocks are visualized on a screen in the scanner. No feedback is provided regarding brain activity. |
|
| Measurements will be recorded at each MRI session (approx. 1 week intervals after screening and inclusion) |
| Whole brain activation pattern changes (fMRI analysis) | We will investigate the whole brain level activation pattern changes due to neurofeedback training using self-regulation in PD patients. To determine these changes, we will look at the T-contrast of all regulation blocks vs all baseline blocks in all the fMRI runs with neurofeedback. This can give us insight into which brain networks contribute mechanistically to the training and if any of the training performance can be attributed to other factors, such as physiological measures, as compared to neurofeedback self-regulation. | Measurements will be recorded at each MRI session (approx. 1 week intervals after screening and inclusion) |
| Neurofeedback training effects on non-motor symptoms | Effect of neurofeedback training on non-motor symptoms will be assessed using the MDS-UPDRS part I, II, IV and the Hospital Anxiety and Depression Scale (HADS). The MDS-UPDRS contains 65 scores, each with a range from 0 (no impairment) to 4 (severe impairment). The Part I subscore, indicating nonmotor experiences of daily living has a total of 13 items with scores ranging between 0-52. The HADS is a widely used questionnaire designed to assess levels of anxiety and depression in patients. It consists of 14 items, with seven questions related to anxiety (HADS-A) and seven related to depression (HADS-D). Each item is scored on a scale from 0 to 3, with total scores ranging from 0 to 21 for each subscale. The HADS is commonly used in clinical settings to identify and measure the severity of anxiety and depression in patients, particularly in hospital environments. | After screening, after the last MRI session (approx. 5 weeks after screening) and at follow up session (approx. 4 weeks after final MRI session) |
| Correlation between NF success and distal finger tapping test (behavioral measure) | We will correlate neurofeedback success with the distal finger tapping (DFT) test scores to determine if NF success can lead to improvements in behavioral measures. Three kinetic parameters are generated by the DFT test: kinesia score (KS20), the number of keystrokes in a 20 second time period, reflecting speed; akinesia time (AT20), average dwell time that keys are depressed, reflecting akinesia; and incoordination score (IS20), the variance of travelling time between keystrokes, reflecting rhythm. A higher KS20 score represents improvement, a lower AT20 score represents improvement and a smaller variance in the IS20 score represents improvement. | After screening, after the last MRI session (approx. 5 weeks after screening) and at follow up session (approx. 4 weeks after final MRI session) |
| After screening, after the last MRI session (approx. 5 weeks after screening) and at follow up session (approx. 4 weeks after final MRI session) |
| Maastricht University | Recruiting | Maastricht | Netherlands |
|
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| Background | Esmail, S., & Linden, D. E. J. (2014). Neural Networks and Neurofeedback in Parkinson's Disease. NeuroRegulation, 1(3-4), 240-240. https://doi.org/10.15540/nr.1.3-4.240 |
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| D009422 | Nervous System Diseases |
| D009069 | Movement Disorders |
| D000080874 | Synucleinopathies |
| D019636 | Neurodegenerative Diseases |
| D001521 |
| Behavior Therapy |
| D011613 | Psychotherapy |
| D004191 | Behavioral Disciplines and Activities |
| D030141 | Feedback, Psychological |