Show simple item record

dc.contributor.author
Riahi, Nader
dc.contributor.author
Ruth, William
dc.contributor.author
D'Arcy, Ryan C.N.
dc.contributor.author
Menon, Carlo
dc.date.accessioned
2023-03-13T15:25:13Z
dc.date.available
2023-01-04T16:17:43Z
dc.date.available
2023-01-16T08:31:07Z
dc.date.available
2023-03-13T15:25:13Z
dc.date.issued
2023
dc.identifier.issn
1534-4320
dc.identifier.issn
1558-0210
dc.identifier.other
10.1109/tnsre.2022.3218514
en_US
dc.identifier.uri
http://hdl.handle.net/20.500.11850/590299
dc.identifier.doi
10.3929/ethz-b-000590299
dc.description.abstract
Mental imagery (MI) is gaining attention as a strategy towards endogenous brain stimulation for improving motor skill. Neurofeedback (NF) is commonly used to guide MI in order to activate the relevant brain networks. The current study investigates an individualized EEG-based method for NF through broad consideration of interactions between different brain networks. We selected the change in brain functional connectivity (FC) as an objective neurophysiological measure of change in motor skill during a longitudinal physical training (PT) program. Digital tracing tasks were developed for skill training and the spatial error in tracing was used to gauge the change in skill. We used partial least squares algorithms to find the most robust contributing networks towards correlation between the resting state FC and the acquired motor skill. We used the network with the largest margin for increasing FC as the candidate for NF training while experimenting with MI during a neurofeedback training program. The participant was informed of the changes in instantaneous FC through real-time audio feedback to help guide the MI. We showed over 20% reduction in tracing error through neurofeedback training alone, without any additional PT. We also showed retention of improvement in skill for several days after the completion of neurofeedback training. Our proposed methodology shows promise for a highly individualized approach towards improvement in motor skill. Given that EEG is an accessible health and wellness technology, such a method could provide a practical complementary option towards personalized therapeutic strategies to improve motor function.
en_US
dc.format
application/pdf
en_US
dc.language.iso
en
en_US
dc.publisher
IEEE
en_US
dc.rights.uri
http://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subject
Training
en_US
dc.subject
Particle measurements
en_US
dc.subject
Noise measurement
en_US
dc.subject
Electroencephalography
en_US
dc.subject
Atmospheric measurements
en_US
dc.subject
Task analysis
en_US
dc.subject
Neurofeedback
en_US
dc.subject
Functional Connectivity
en_US
dc.subject
Partial Least Squares
en_US
dc.subject
Mental Imagery
en_US
dc.subject
Neurofeedback
en_US
dc.subject
EEG
en_US
dc.subject
Motor Skill
en_US
dc.title
A Method for Using Neurofeedback to Guide Mental Imagery for Improving Motor Skill
en_US
dc.type
Journal Article
dc.rights.license
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
dc.date.published
2022-11-01
ethz.journal.title
IEEE Transactions on Neural Systems and Rehabilitation Engineering
ethz.journal.volume
31
en_US
ethz.pages.start
130
en_US
ethz.pages.end
138
en_US
ethz.version.deposit
publishedVersion
en_US
ethz.identifier.wos
ethz.identifier.pubmed
36318564
ethz.publication.place
New York, NY
en_US
ethz.publication.status
published
en_US
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02070 - Dep. Gesundheitswiss. und Technologie / Dep. of Health Sciences and Technology::09715 - Menon, Carlo / Menon, Carlo
en_US
ethz.leitzahl.certified
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02070 - Dep. Gesundheitswiss. und Technologie / Dep. of Health Sciences and Technology::09715 - Menon, Carlo / Menon, Carlo
en_US
ethz.date.deposited
2023-01-04T16:17:44Z
ethz.source
FORM
ethz.eth
yes
en_US
ethz.availability
Open access
en_US
ethz.rosetta.installDate
2023-03-13T15:25:14Z
ethz.rosetta.lastUpdated
2024-02-02T20:58:37Z
ethz.rosetta.versionExported
true
ethz.COinS
ctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.atitle=A%20Method%20for%20Using%20Neurofeedback%20to%20Guide%20Mental%20Imagery%20for%20Improving%20Motor%20Skill&rft.jtitle=IEEE%20Transactions%20on%20Neural%20Systems%20and%20Rehabilitation%20Engineering&rft.date=2023&rft.volume=31&rft.spage=130&rft.epage=138&rft.issn=1534-4320&1558-0210&rft.au=Riahi,%20Nader&Ruth,%20William&D'Arcy,%20Ryan%20C.N.&Menon,%20Carlo&rft.genre=article&rft_id=info:doi/10.1109/tnsre.2022.3218514&
 Search print copy at ETH Library

Files in this item

Thumbnail

Publication type

Show simple item record