The University of Southampton
University of Southampton Institutional Repository

A Systematic Review of Neurofeedback for the Management of Motor Symptoms in Parkinson’s Disease

A Systematic Review of Neurofeedback for the Management of Motor Symptoms in Parkinson’s Disease
A Systematic Review of Neurofeedback for the Management of Motor Symptoms in Parkinson’s Disease

Background: Neurofeedback has been proposed as a treatment for Parkinson’s disease (PD) motor symptoms by changing the neural network activity directly linked with movement. However, the effectiveness of neurofeedback as a treatment for PD motor symptoms is unclear. Aim: To systematically review the literature to identify the effects of neurofeedback in people with idiopathic PD; as defined by measurement of brain activity; motor function; and performance. Design: A systematic review. Included Sources and Articles: PubMed; MEDLINE; Cinhal; PsychoInfo; Prospero; Cochrane; ClinicalTrials.gov; EMBASE; Web of Science; PEDro; OpenGrey; Conference Paper Index; Google Scholar; and eThos; searched using the Population-Intervention-Comparison-Outcome (PICO) framework. Primary studies with the following designs were included: randomized controlled trials (RCTs), non-RCTs; quasi-experimental; pre/post studies; and case studies. Results: This review included 11 studies out of 6197 studies that were identified from the literature search. Neuroimaging methods used were fMRI; scalp EEG; surface brain EEG; and deep brain EEG; where 10–15 Hz and the supplementary motor area were the most commonly targeted signatures for EEG and fMRI, respectively. Success rates for changing one’s brain activity ranged from 47% to 100%; however, both sample sizes and success criteria differed considerably between studies. While six studies included a clinical outcome; a lack of consistent assessments prevented a reliable conclusion on neurofeedback’s effectiveness. Narratively, fMRI neurofeedback has the greatest potential to improve PD motor symptoms. Two main limitations were found in the studies that contributed to the lack of a confident conclusion: (1) insufficient clinical information and perspectives (e.g., no reporting of adverse events), and (2) limitations in numerical data reporting (e.g., lack of explicit statistics) that prevented a meta-analysis. Conclusions: While fMRI neurofeedback was narratively the most effective treatment; the omission of clinical outcome measures in studies using other neurofeedback approaches limits comparison. Therefore, no single neurofeedback type can currently be identified as an optimal treatment for PD motor symptoms. This systematic review highlights the need to improve the inclusion of clinical information and more robust reporting of numerical data in future work. Neurofeedback appears to hold great potential as a treatment for PD motor symptoms. However, this field is still in its infancy and needs high quality RCTs to establish its effectiveness. Review Registration: PROSPERO (ID: CRD42020191097).

Electroen-cephalography, Movement, Neural network activity, Neurofeedback, Neuroimaging, Parkinson’s disease
2076-3425
1292
Anil, Krithika
2b2690a5-37f4-4b3e-9b4c-df721d12a2f3
Hall, Stephen D.
b2cfe95b-fbcb-45de-b53e-95ca463ec023
Demain, Sara
09b1124d-750a-4eb1-90c7-91f5f222fc31
Freeman, Jennifer A.
903a013e-c7da-497a-aed0-abe72a9692df
Ganis, Giorgio
5ce87555-e8ca-4bac-8f20-f68c00f1205d
Marsden, Jonathan
9cad2aad-a4a5-4f90-81b7-852b9f8d822c
Anil, Krithika
2b2690a5-37f4-4b3e-9b4c-df721d12a2f3
Hall, Stephen D.
b2cfe95b-fbcb-45de-b53e-95ca463ec023
Demain, Sara
09b1124d-750a-4eb1-90c7-91f5f222fc31
Freeman, Jennifer A.
903a013e-c7da-497a-aed0-abe72a9692df
Ganis, Giorgio
5ce87555-e8ca-4bac-8f20-f68c00f1205d
Marsden, Jonathan
9cad2aad-a4a5-4f90-81b7-852b9f8d822c

Anil, Krithika, Hall, Stephen D., Demain, Sara, Freeman, Jennifer A., Ganis, Giorgio and Marsden, Jonathan (2021) A Systematic Review of Neurofeedback for the Management of Motor Symptoms in Parkinson’s Disease. Brain Sciences, 11 (10), 1292, [1292]. (doi:10.3390/brainsci11101292).

Record type: Article

Abstract

Background: Neurofeedback has been proposed as a treatment for Parkinson’s disease (PD) motor symptoms by changing the neural network activity directly linked with movement. However, the effectiveness of neurofeedback as a treatment for PD motor symptoms is unclear. Aim: To systematically review the literature to identify the effects of neurofeedback in people with idiopathic PD; as defined by measurement of brain activity; motor function; and performance. Design: A systematic review. Included Sources and Articles: PubMed; MEDLINE; Cinhal; PsychoInfo; Prospero; Cochrane; ClinicalTrials.gov; EMBASE; Web of Science; PEDro; OpenGrey; Conference Paper Index; Google Scholar; and eThos; searched using the Population-Intervention-Comparison-Outcome (PICO) framework. Primary studies with the following designs were included: randomized controlled trials (RCTs), non-RCTs; quasi-experimental; pre/post studies; and case studies. Results: This review included 11 studies out of 6197 studies that were identified from the literature search. Neuroimaging methods used were fMRI; scalp EEG; surface brain EEG; and deep brain EEG; where 10–15 Hz and the supplementary motor area were the most commonly targeted signatures for EEG and fMRI, respectively. Success rates for changing one’s brain activity ranged from 47% to 100%; however, both sample sizes and success criteria differed considerably between studies. While six studies included a clinical outcome; a lack of consistent assessments prevented a reliable conclusion on neurofeedback’s effectiveness. Narratively, fMRI neurofeedback has the greatest potential to improve PD motor symptoms. Two main limitations were found in the studies that contributed to the lack of a confident conclusion: (1) insufficient clinical information and perspectives (e.g., no reporting of adverse events), and (2) limitations in numerical data reporting (e.g., lack of explicit statistics) that prevented a meta-analysis. Conclusions: While fMRI neurofeedback was narratively the most effective treatment; the omission of clinical outcome measures in studies using other neurofeedback approaches limits comparison. Therefore, no single neurofeedback type can currently be identified as an optimal treatment for PD motor symptoms. This systematic review highlights the need to improve the inclusion of clinical information and more robust reporting of numerical data in future work. Neurofeedback appears to hold great potential as a treatment for PD motor symptoms. However, this field is still in its infancy and needs high quality RCTs to establish its effectiveness. Review Registration: PROSPERO (ID: CRD42020191097).

Text
brainsci-11-01292 - Version of Record
Available under License Creative Commons Attribution.
Download (373kB)
Text
A systematic review of neurofeedback for the management of motor symptoms in Parkinson’s disease
Restricted to Repository staff only
Request a copy

More information

Accepted/In Press date: 27 September 2021
Published date: October 2021
Keywords: Electroen-cephalography, Movement, Neural network activity, Neurofeedback, Neuroimaging, Parkinson’s disease

Identifiers

Local EPrints ID: 453392
URI: http://eprints.soton.ac.uk/id/eprint/453392
ISSN: 2076-3425
PURE UUID: 0d48ea24-ba5c-4e68-a33b-0c9945115f70
ORCID for Krithika Anil: ORCID iD orcid.org/0000-0002-8027-1665

Catalogue record

Date deposited: 13 Jan 2022 18:20
Last modified: 16 Mar 2024 14:25

Export record

Altmetrics

Contributors

Author: Krithika Anil ORCID iD
Author: Stephen D. Hall
Author: Sara Demain
Author: Jennifer A. Freeman
Author: Giorgio Ganis
Author: Jonathan Marsden

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×