FMRI-neurofeedback in Parkinson's Disease

Официальное название

MOTOR-NF - a Randomized Controlled Trial of FMRI-based Neurofeedback for Motor Symptoms of Parkinson's Disease

Обзор

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.

Подробное описание

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.

Вмешательства

• Другое Neurofeedback
  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
• Другое Kinesthetic imagery
  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.

Первичные конечные точки

• MDS-UPDRS (Unified Parkinson's Disease Rating Scale) [Срок оценки: After screening, after the last MRI session (approx. 5 weeks after screening) and at follow up session (approx. 4 weeks after final MRI session)]

Вторичные конечные точки (4)

• Performance of Putamen neurofeedback training (fMRI analysis) [Срок оценки: Measurements will be recorded at each MRI session (approx. 1 week intervals after screening and inclusion)]
• Whole brain activation pattern changes (fMRI analysis) [Срок оценки: Measurements will be recorded at each MRI session (approx. 1 week intervals after screening and inclusion)]
• Neurofeedback training effects on non-motor symptoms [Срок оценки: 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) [Срок оценки: After screening, after the last MRI session (approx. 5 weeks after screening) and at follow up session (approx. 4 weeks after final MRI session)]

Критерии участия

Критерии включения

• Diagnosis of Parkinson's disease.
• Disease stage 1-3 according to the Hoehn and Yahr Scale
• Age: 18 years or more

Критерии исключения

• Exclusion criteria for MRI (e.g., cardiac pacemaker, certain metallic implants)
• History of psychotic disorder, bipolar disorder, or psychotic depression
• Current use of illegal drugs (any in the last four weeks)
• Current excessive alcohol consumption that interferes with daily functioning
• A score on the Montreal Cognitive Assessment (MoCA) below 24/30.
• Any disorder that would interfere with accurate and usable data acquisition.

Критерии приведены из реестра в оригинале (на английском). Окончательную оценку соответствия проводит исследовательский центр.

Здоровые добровольцы: Нет

Дизайн исследования

Распределение

Рандомизированное

Модель

Параллельные группы

Маскирование

Простое слепое

Основная цель

Лечение

Центры проведения

Германия · 1 центр

• Uniklinik Köln — Cologne

Нидерланды · 1 центр

• Maastricht University — Maastricht

Публикации

• 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. PMID 35013372
• Emmert K, Kopel R, Sulzer J, Bruhl AB, Berman BD, Linden DEJ, Horovitz SG, Breimhorst M, Caria A, Frank S, Johnston S, Long Z, Paret C, Robineau F, Veit R, Bartsch A, Beckmann CF, Van De Ville D, Haller S. Meta-analysis of real-time fMRI neurofeedback studies using individual participant data: How is brain regulation mediated? Neuroimage. 2016 Jan 1;124(Pt A):806-812. doi: 10.1016/j.neuroimage.201 PMID 26419389
• 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
• Faul F, Erdfelder E, Lang AG, Buchner A. G*Power 3: a flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behav Res Methods. 2007 May;39(2):175-91. doi: 10.3758/bf03193146. PMID 17695343
• Hamilton JP, Glover GH, Bagarinao E, Chang C, Mackey S, Sacchet MD, Gotlib IH. Effects of salience-network-node neurofeedback training on affective biases in major depressive disorder. Psychiatry Res Neuroimaging. 2016 Mar 30;249:91-6. doi: 10.1016/j.pscychresns.2016.01.016. Epub 2016 Jan 19. PMID 26862057
• Jaeckle T, Williams SCR, Barker GJ, Basilio R, Carr E, Goldsmith K, Colasanti A, Giampietro V, Cleare A, Young AH, Moll J, Zahn R. Self-blame in major depression: a randomised pilot trial comparing fMRI neurofeedback with self-guided psychological strategies. Psychol Med. 2023 May;53(7):2831-2841. doi: 10.1017/S0033291721004797. Epub 2021 Dec 2. PMID 34852855
• Johnston SJ, Boehm SG, Healy D, Goebel R, Linden DE. Neurofeedback: A promising tool for the self-regulation of emotion networks. Neuroimage. 2010 Jan 1;49(1):1066-72. doi: 10.1016/j.neuroimage.2009.07.056. Epub 2009 Jul 29. PMID 19646532
• Karch, S., Keeser, D., Paolini, M., Hümmer, S., Konrad, J., Haller, D., Kirsch, V., Koller, G., Kupka, M., Blautzik, J., & Pogarell, O. (2015). Real-time fMRI neurofeedback: Applica-tion in patients with substance use disorder. Pharmacopsychiatry, 25(6), A77. https://doi.org/10.1055/s-0035-1558015

Идентификаторы

NCT: NCT06582355 · NL86308.068.24

Первоисточники (государственные реестры)

• ClinicalTrials.gov (NIH, США)

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