Study Results
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Basic Information
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COMPLETED
12 participants
OBSERVATIONAL
2023-08-17
2024-02-28
Brief Summary
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Detailed Description
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Each NF session will consist of one anatomical scan, one localizer run, and four functional NF runs. The localizer run will be used to identify individualized brain activation patterns in the participants. Each NF run is a measurement sequence that will consist of ten blocks: five regulation blocks and five rest blocks. The participants will be asked to upregulate (increase) their brain activity, which will be displayed on a thermometer bar, during the regulation blocks. During the rest blocks, the participants will be asked to relax. The study will employ a crossover design with two conditions. In one condition the participants will receive feedback on the thermometer bar from the SMA region and in the second condition the participants will receive feedback from the basal ganglia region. Two of the NF runs will be with the SMA condition and two will be with the basal ganglia condition. Both runs in each condition will take place consecutively, i.e., either the first two runs will be SMA and the second two runs will be basal ganglia or vice versa. The sessions will be counter balanced.
At the last NF session, a post-training assessment will be conducted during which the participants will be debriefed about the study. NF is an individualized training method, and therefore, individual differences in learning success are expected during the study, which can lead to different expectations from the subjects. However, since this is an investigation of the feasibility of the approach, all forms of performance are useful datapoints and participants will be debriefed about their valuable contribution to make sure that no outcome is conceived as negative.
Conditions
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Study Design
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CASE_ONLY
PROSPECTIVE
Study Groups
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Patient cohort
All patients will undergo both the SMA and the basal ganglia condition
Neurofeedback
Participants will be shown their brain activity measured in real-time using an MRI scanner. They can then use mental strategies, such as imagination to influence and regulate this activity.
Interventions
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Neurofeedback
Participants will be shown their brain activity measured in real-time using an MRI scanner. They can then use mental strategies, such as imagination to influence and regulate this activity.
Other Intervention Names
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Eligibility Criteria
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Inclusion Criteria
* Disease stage 1-3 according to the Hoehn and Yahr Scale
Exclusion Criteria
* Current use of illegal drugs (any in the last four weeks)
* Current excessive alcohol consumption that interferes with daily functioning
* Advanced cognitive impairment (MoCA \<24) or dementia
18 Years
ALL
No
Sponsors
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Maastricht University
OTHER
Responsible Party
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Principal Investigators
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David EJ Linden, Prof.
Role: PRINCIPAL_INVESTIGATOR
Maastricht University
Locations
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Maastricht University
Maastricht, , Netherlands
Countries
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References
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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.2015.09.042. Epub 2015 Sep 28.
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.
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.
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.
Linden DE. Neurofeedback and networks of depression. Dialogues Clin Neurosci. 2014 Mar;16(1):103-12. doi: 10.31887/DCNS.2014.16.1/dlinden.
Linden DE, Habes I, Johnston SJ, Linden S, Tatineni R, Subramanian L, Sorger B, Healy D, Goebel R. Real-time self-regulation of emotion networks in patients with depression. PLoS One. 2012;7(6):e38115. doi: 10.1371/journal.pone.0038115. Epub 2012 Jun 4.
MacDuffie KE, MacInnes J, Dickerson KC, Eddington KM, Strauman TJ, Adcock RA. Single session real-time fMRI neurofeedback has a lasting impact on cognitive behavioral therapy strategies. Neuroimage Clin. 2018 Jun 9;19:868-875. doi: 10.1016/j.nicl.2018.06.009. eCollection 2018.
Mehler DMA, Sokunbi MO, Habes I, Barawi K, Subramanian L, Range M, Evans J, Hood K, Luhrs M, Keedwell P, Goebel R, Linden DEJ. Targeting the affective brain-a randomized controlled trial of real-time fMRI neurofeedback in patients with depression. Neuropsychopharmacology. 2018 Dec;43(13):2578-2585. doi: 10.1038/s41386-018-0126-5. Epub 2018 Jun 23.
Mehler DMA, Williams AN, Krause F, Luhrs M, Wise RG, Turner DL, Linden DEJ, Whittaker JR. The BOLD response in primary motor cortex and supplementary motor area during kinesthetic motor imagery based graded fMRI neurofeedback. Neuroimage. 2019 Jan 1;184:36-44. doi: 10.1016/j.neuroimage.2018.09.007. Epub 2018 Sep 8.
Paret C, Zaehringer J, Ruf M, Ende G, Schmahl C. The orbitofrontal cortex processes neurofeedback failure signals. Behav Brain Res. 2019 Sep 2;369:111938. doi: 10.1016/j.bbr.2019.111938. Epub 2019 May 6.
Postuma RB, Berg D, Stern M, Poewe W, Olanow CW, Oertel W, Obeso J, Marek K, Litvan I, Lang AE, Halliday G, Goetz CG, Gasser T, Dubois B, Chan P, Bloem BR, Adler CH, Deuschl G. MDS clinical diagnostic criteria for Parkinson's disease. Mov Disord. 2015 Oct;30(12):1591-601. doi: 10.1002/mds.26424.
Sitaram R, Ros T, Stoeckel L, Haller S, Scharnowski F, Lewis-Peacock J, Weiskopf N, Blefari ML, Rana M, Oblak E, Birbaumer N, Sulzer J. Closed-loop brain training: the science of neurofeedback. Nat Rev Neurosci. 2017 Feb;18(2):86-100. doi: 10.1038/nrn.2016.164. Epub 2016 Dec 22.
Skottnik L, Linden DEJ. Mental Imagery and Brain Regulation-New Links Between Psychotherapy and Neuroscience. Front Psychiatry. 2019 Oct 30;10:779. doi: 10.3389/fpsyt.2019.00779. eCollection 2019.
Skottnik L, Sorger B, Kamp T, Linden D, Goebel R. Success and failure of controlling the real-time functional magnetic resonance imaging neurofeedback signal are reflected in the striatum. Brain Behav. 2019 Mar;9(3):e01240. doi: 10.1002/brb3.1240. Epub 2019 Feb 20.
Subramanian L, Hindle JV, Johnston S, Roberts MV, Husain M, Goebel R, Linden D. Real-time functional magnetic resonance imaging neurofeedback for treatment of Parkinson's disease. J Neurosci. 2011 Nov 9;31(45):16309-17. doi: 10.1523/JNEUROSCI.3498-11.2011.
Subramanian L, Morris MB, Brosnan M, Turner DL, Morris HR, Linden DE. Functional Magnetic Resonance Imaging Neurofeedback-guided Motor Imagery Training and Motor Training for Parkinson's Disease: Randomized Trial. Front Behav Neurosci. 2016 Jun 8;10:111. doi: 10.3389/fnbeh.2016.00111. eCollection 2016.
Young KD, Siegle GJ, Zotev V, Phillips R, Misaki M, Yuan H, Drevets WC, Bodurka J. Randomized Clinical Trial of Real-Time fMRI Amygdala Neurofeedback for Major Depressive Disorder: Effects on Symptoms and Autobiographical Memory Recall. Am J Psychiatry. 2017 Aug 1;174(8):748-755. doi: 10.1176/appi.ajp.2017.16060637. Epub 2017 Apr 14.
Zahn R, Weingartner JH, Basilio R, Bado P, Mattos P, Sato JR, de Oliveira-Souza R, Fontenelle LF, Young AH, Moll J. Blame-rebalance fMRI neurofeedback in major depressive disorder: A randomised proof-of-concept trial. Neuroimage Clin. 2019;24:101992. doi: 10.1016/j.nicl.2019.101992. Epub 2019 Aug 25.
Other Identifiers
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NL82024.068.22
Identifier Type: -
Identifier Source: org_study_id
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