Improvement in precision grip force control with self-modulation of primary motor cortex during motor imagery
dc.contributor.author
Blefari, Maria L.
dc.contributor.author
Sulzer, James
dc.contributor.author
Hepp-Reymond, Marie-Claude
dc.contributor.author
Kollias, Spyros
dc.contributor.author
Gassert, Roger
dc.date.accessioned
2019-08-30T11:51:21Z
dc.date.available
2017-06-11T15:55:01Z
dc.date.available
2019-08-30T11:51:21Z
dc.date.issued
2015-02-13
dc.identifier.issn
1662-5153
dc.identifier.other
10.3389/fnbeh.2015.00018
en_US
dc.identifier.uri
http://hdl.handle.net/20.500.11850/97497
dc.identifier.doi
10.3929/ethz-b-000097497
dc.description.abstract
Motor imagery (MI) has shown effectiveness in enhancing motor performance. This may be due to the common neural mechanisms underlying MI and motor execution (ME). The main region of the ME network, the primary motor cortex (M1), has been consistently linked to motor performance. However, the activation of M1 during motor imagery is controversial, which may account for inconsistent rehabilitation therapy outcomes using MI. Here, we examined the relationship between contralateral M1 (cM1) activation during MI and changes in sensorimotor performance. To aid cM1 activity modulation during MI, we used real-time fMRI neurofeedback-guided MI based on cM1 hand area blood oxygen level dependent (BOLD) signal in healthy subjects, performing kinesthetic MI of pinching. We used multiple regression analysis to examine the correlation between cM1 BOLD signal and changes in motor performance during an isometric pinching task of those subjects who were able to activate cM1 during motor imagery. Activities in premotor and parietal regions were used as covariates. We found that cM1 activity was positively correlated to improvements in accuracy as well as overall performance improvements, whereas other regions in the sensorimotor network were not. The association between cM1 activation during MI with performance changes indicates that subjects with stronger cM1 activation during MI may benefit more from MI training, with implications toward targeted neurotherapy.
en_US
dc.format
application/pdf
en_US
dc.language.iso
en
en_US
dc.publisher
Frontiers Media
dc.rights.uri
http://creativecommons.org/licenses/by/4.0/
dc.subject
Real-time fMRI
en_US
dc.subject
Neurofeedback
en_US
dc.subject
Motor imagery
en_US
dc.subject
Motor skill
en_US
dc.title
Improvement in precision grip force control with self-modulation of primary motor cortex during motor imagery
en_US
dc.type
Journal Article
dc.rights.license
Creative Commons Attribution 4.0 International
ethz.journal.title
Frontiers in Behavioral Neuroscience
ethz.journal.volume
9
en_US
ethz.journal.abbreviated
Front. Behav. Neurosci.
ethz.pages.start
18
en_US
ethz.size
11 p.
en_US
ethz.version.deposit
publishedVersion
en_US
ethz.identifier.wos
ethz.identifier.scopus
ethz.identifier.nebis
010194246
ethz.publication.place
Lausanne
ethz.publication.status
published
en_US
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich, direkt::00012 - Lehre und Forschung, direkt::00007 - Departemente, direkt::02140 - Departement Informationstechnologie und Elektrotechnik / Department of Information Technology and Electrical Engineering::02533 - Institut für Neuroinformatik (INI) / Institute of Neuroinformatics (INI)::03454 - Martin, Kevan A.C.
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::03827 - Gassert, Roger / Gassert, Roger
en_US
ethz.leitzahl.certified
ETH Zürich::00002 - ETH Zürich, direkt::00012 - Lehre und Forschung, direkt::00007 - Departemente, direkt::02140 - Departement Informationstechnologie und Elektrotechnik / Department of Information Technology and Electrical Engineering::02533 - Institut für Neuroinformatik (INI) / Institute of Neuroinformatics (INI)::03454 - Martin, Kevan A.C.
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::03827 - Gassert, Roger / Gassert, Roger
ethz.date.deposited
2017-06-11T15:55:37Z
ethz.source
ECIT
ethz.identifier.importid
imp593652e26bcd262618
ethz.ecitpid
pub:152464
ethz.eth
yes
en_US
ethz.availability
Open access
en_US
ethz.rosetta.installDate
2017-07-18T09:34:33Z
ethz.rosetta.lastUpdated
2024-02-02T09:14:26Z
ethz.rosetta.versionExported
true
ethz.COinS
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