An fMRI pilot study to evaluate brain activation associated with locomotion adaptation.
Identifieur interne : 000D00 ( PubMed/Corpus ); précédent : 000C99; suivant : 000D01An fMRI pilot study to evaluate brain activation associated with locomotion adaptation.
Auteurs : Laura Marchal-Crespo ; Christoph Hollnagel ; Mike Brügger ; Spyros Kollias ; Robert RienerSource :
- IEEE ... International Conference on Rehabilitation Robotics : [proceedings] [ 1945-7901 ] ; 2011.
English descriptors
- KwdEn :
- MESH :
- methods : Magnetic Resonance Imaging.
- physiology : Brain, Locomotion.
- Humans.
Abstract
The goal of robotic therapy is to provoke motor plasticity via the application of robotic training strategies. Although robotic haptic guidance is the commonly used motor-training strategy to reduce performance errors while training, research on motor learning has emphasized that errors are a fundamental neural signal that drives motor adaptation. Thus, researchers have proposed robotic therapy algorithms that amplify movement errors rather than decrease them. Studying the particular brain regions involved in learning under different training strategies might help tailoring motor training conditions to the anatomical location of a focal brain insult. In this paper, we evaluate the brain regions involved in locomotion adaptation when training with three different conditions: without robotic guidance, with a random-varying force disturbance, and with repulsive forces proportional to errors. We performed an fMRI pilot study with four healthy subjects who stepped in an fMRI compatible walking robotic device. Subjects were instructed to actively synchronize their left leg with respect to their right leg (passively guided by the robot) while their left leg was affected by any of the three conditions. We observed activation in areas known to be involved in error processing. Although we found that all conditions required the similar cortical network to fulfill the task, we observed a tendency towards more activity in the motor/sensory network as more "challenged" the subjects were.
DOI: 10.1109/ICORR.2011.5975371
PubMed: 22275575
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pubmed:22275575Le document en format XML
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International Conference on Rehabilitation Robotics : [proceedings]</title><idno type="eISSN">1945-7901</idno><imprint><date when="2011" type="published">2011</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Brain (physiology)</term><term>Humans</term><term>Locomotion (physiology)</term><term>Magnetic Resonance Imaging (methods)</term></keywords><keywords scheme="MESH" qualifier="methods" xml:lang="en"><term>Magnetic Resonance Imaging</term></keywords><keywords scheme="MESH" qualifier="physiology" xml:lang="en"><term>Brain</term><term>Locomotion</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Humans</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">The goal of robotic therapy is to provoke motor plasticity via the application of robotic training strategies. Although robotic haptic guidance is the commonly used motor-training strategy to reduce performance errors while training, research on motor learning has emphasized that errors are a fundamental neural signal that drives motor adaptation. Thus, researchers have proposed robotic therapy algorithms that amplify movement errors rather than decrease them. Studying the particular brain regions involved in learning under different training strategies might help tailoring motor training conditions to the anatomical location of a focal brain insult. In this paper, we evaluate the brain regions involved in locomotion adaptation when training with three different conditions: without robotic guidance, with a random-varying force disturbance, and with repulsive forces proportional to errors. We performed an fMRI pilot study with four healthy subjects who stepped in an fMRI compatible walking robotic device. Subjects were instructed to actively synchronize their left leg with respect to their right leg (passively guided by the robot) while their left leg was affected by any of the three conditions. We observed activation in areas known to be involved in error processing. Although we found that all conditions required the similar cortical network to fulfill the task, we observed a tendency towards more activity in the motor/sensory network as more "challenged" the subjects were.</div></front></TEI><pubmed><MedlineCitation Owner="NLM" Status="MEDLINE"><PMID Version="1">22275575</PMID><DateCreated><Year>2012</Year><Month>01</Month><Day>25</Day></DateCreated><DateCompleted><Year>2012</Year><Month>07</Month><Day>19</Day></DateCompleted><Article PubModel="Print"><Journal><ISSN IssnType="Electronic">1945-7901</ISSN><JournalIssue CitedMedium="Internet"><Volume>2011</Volume><PubDate><Year>2011</Year></PubDate></JournalIssue><Title>IEEE ... International Conference on Rehabilitation Robotics : [proceedings]</Title><ISOAbbreviation>IEEE Int Conf Rehabil Robot</ISOAbbreviation></Journal><ArticleTitle>An fMRI pilot study to evaluate brain activation associated with locomotion adaptation.</ArticleTitle><Pagination><MedlinePgn>5975371</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.1109/ICORR.2011.5975371</ELocationID><Abstract><AbstractText>The goal of robotic therapy is to provoke motor plasticity via the application of robotic training strategies. Although robotic haptic guidance is the commonly used motor-training strategy to reduce performance errors while training, research on motor learning has emphasized that errors are a fundamental neural signal that drives motor adaptation. Thus, researchers have proposed robotic therapy algorithms that amplify movement errors rather than decrease them. Studying the particular brain regions involved in learning under different training strategies might help tailoring motor training conditions to the anatomical location of a focal brain insult. In this paper, we evaluate the brain regions involved in locomotion adaptation when training with three different conditions: without robotic guidance, with a random-varying force disturbance, and with repulsive forces proportional to errors. We performed an fMRI pilot study with four healthy subjects who stepped in an fMRI compatible walking robotic device. Subjects were instructed to actively synchronize their left leg with respect to their right leg (passively guided by the robot) while their left leg was affected by any of the three conditions. We observed activation in areas known to be involved in error processing. 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