A Reliability Study on Brain Activation During Active and Passive Arm Movements Supported by an MRI-Compatible Robot
dc.contributor.author
Estévez, Natalia
dc.contributor.author
Yu, Ningbo
dc.contributor.author
Brügger, Mike
dc.contributor.author
Villiger, Michael
dc.contributor.author
Hepp-Reymond, Marie-Claude
dc.contributor.author
Riener, Robert
dc.contributor.author
Kollias, Spyros
dc.date.accessioned
2021-05-05T15:21:20Z
dc.date.available
2017-06-11T06:19:43Z
dc.date.available
2021-05-05T14:41:33Z
dc.date.available
2021-05-05T15:21:20Z
dc.date.issued
2014-11
dc.identifier.issn
0896-0267
dc.identifier.issn
1573-6792
dc.identifier.other
10.1007/s10548-014-0355-9
en_US
dc.identifier.uri
http://hdl.handle.net/20.500.11850/81868
dc.identifier.doi
10.3929/ethz-b-000081868
dc.description.abstract
In neurorehabilitation, longitudinal assessment of arm movement related brain function in patients with motor disability is challenging due to variability in task performance. MRI-compatible robots monitor and control task performance, yielding more reliable evaluation of brain function over time. The main goals of the present study were first to define the brain network activated while performing active and passive elbow movements with an MRI-compatible arm robot (MaRIA) in healthy subjects, and second to test the reproducibility of this activation over time. For the fMRI analysis two models were compared. In model 1 movement onset and duration were included, whereas in model 2 force and range of motion were added to the analysis. Reliability of brain activation was tested with several statistical approaches applied on individual and group activation maps and on summary statistics. The activated network included mainly the primary motor cortex, primary and secondary somatosensory cortex, superior and inferior parietal cortex, medial and lateral premotor regions, and subcortical structures. Reliability analyses revealed robust activation for active movements with both fMRI models and all the statistical methods used. Imposed passive movements also elicited mainly robust brain activation for individual and group activation maps, and reliability was improved by including additional force and range of motion using model 2. These findings demonstrate that the use of robotic devices, such as MaRIA, can be useful to reliably assess arm movement related brain activation in longitudinal studies and may contribute in studies evaluating therapies and brain plasticity following injury in the nervous system.
en_US
dc.format
application/pdf
en_US
dc.language.iso
en
en_US
dc.publisher
Springer
en_US
dc.rights.uri
http://rightsstatements.org/page/InC-NC/1.0/
dc.subject
Elbow flexion/extension
en_US
dc.subject
fMRI
en_US
dc.subject
MRI-Compatible robotic devices
en_US
dc.subject
Neurorehabilitation
en_US
dc.subject
Reliability
en_US
dc.subject
Sensorimotor network
en_US
dc.title
A Reliability Study on Brain Activation During Active and Passive Arm Movements Supported by an MRI-Compatible Robot
en_US
dc.type
Journal Article
dc.rights.license
In Copyright - Non-Commercial Use Permitted
dc.date.published
2014-04-10
ethz.journal.title
Brain Topography
ethz.journal.volume
27
en_US
ethz.journal.issue
6
en_US
ethz.journal.abbreviated
Brain Topogr
ethz.pages.start
731
en_US
ethz.pages.end
746
en_US
ethz.version.deposit
publishedVersion
en_US
ethz.notes
It was possible to publish this article open access thanks to a Swiss National Licence with the publisher.
en_US
ethz.identifier.wos
ethz.identifier.scopus
ethz.identifier.nebis
000514826
ethz.publication.place
New York, NY
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::02140 - Dep. Inf.technologie und Elektrotechnik / Dep. of Inform.Technol. Electrical Eng.::02631 - Institut für Biomedizinische Technik / Institute for Biomedical Engineering::03628 - Prüssmann, Klaas P. / Prüssmann, Klaas P.
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::03654 - Riener, Robert / Riener, Robert
en_US
ethz.leitzahl.certified
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02140 - Dep. Inf.technologie und Elektrotechnik / Dep. of Inform.Technol. Electrical Eng.::02631 - Institut für Biomedizinische Technik / Institute for Biomedical Engineering::03628 - Prüssmann, Klaas P. / Prüssmann, Klaas P.
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::03654 - Riener, Robert / Riener, Robert
ethz.date.deposited
2017-06-11T06:20:30Z
ethz.source
ECIT
ethz.identifier.importid
imp593651bc49a4617220
ethz.ecitpid
pub:129081
ethz.eth
yes
en_US
ethz.availability
Open access
en_US
ethz.rosetta.installDate
2017-07-15T01:08:46Z
ethz.rosetta.lastUpdated
2024-02-02T13:37:54Z
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true
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