Brain network involved in visual processing of movement stimuli used in upper limb robotic training: an fMRI study
Identifieur interne : 002563 ( Main/Merge ); précédent : 002562; suivant : 002564Brain network involved in visual processing of movement stimuli used in upper limb robotic training: an fMRI study
Auteurs : Federico Nocchi [Italie] ; Simone Gazzellini [Italie] ; Carmela Grisolia [Italie] ; Maurizio Petrarca [Italie] ; Vittorio Cannatà [Italie] ; Paolo Cappa [Italie] ; Tommaso D Lessio [Italie] ; Enrico Castelli [Italie]Source :
- Journal of NeuroEngineering and Rehabilitation [ 1743-0003 ] ; 2012.
Abstract
The potential of robot-mediated therapy and virtual reality in neurorehabilitation is becoming of increasing importance. However, there is limited information, using neuroimaging, on the neural networks involved in training with these technologies. This study was intended to detect the brain network involved in the visual processing of movement during robotic training. The main aim was to investigate the existence of a common cerebral network able to assimilate biological (human upper limb) and non-biological (abstract object) movements, hence testing the suitability of the visual non-biological feedback provided by the InMotion2 Robot.
A visual functional Magnetic Resonance Imaging (fMRI) task was administered to 22 healthy subjects. The task required observation and retrieval of motor gestures and of the visual feedback used in robotic training. Functional activations of both biological and non-biological movements were examined to identify areas activated in both conditions, along with differential activity in upper limb vs. abstract object trials. Control of response was also tested by administering trials with congruent and incongruent reaching movements.
The observation of upper limb and abstract object movements elicited similar patterns of activations according to a caudo-rostral pathway for the visual processing of movements (including specific areas of the occipital, temporal, parietal, and frontal lobes). Similarly, overlapping activations were found for the subsequent retrieval of the observed movement. Furthermore, activations of frontal cortical areas were associated with congruent trials more than with the incongruent ones.
This study identified the neural pathway associated with visual processing of movement stimuli used in upper limb robot-mediated training and investigated the brain’s ability to assimilate abstract object movements with human motor gestures. In both conditions, activations were elicited in cerebral areas involved in visual perception, sensory integration, recognition of movement, re-mapping on the somatosensory and motor cortex, storage in memory, and response control. Results from the congruent vs. incongruent trials revealed greater activity for the former condition than the latter in a network including cingulate cortex, right inferior and middle frontal gyrus that are involved in the go-signal and in decision control. Results on healthy subjects would suggest the appropriateness of an abstract visual feedback provided during motor training. The task contributes to highlight the potential of fMRI in improving the understanding of visual motor processes and may also be useful in detecting brain reorganisation during training.
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DOI: 10.1186/1743-0003-9-49
PubMed: 22828181
PubMed Central: 3443433
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Onofrio 4, Rome, Italy</nlm:aff><country xml:lang="fr">Italie</country><wicri:regionArea>Clinical Technology Innovations Research Area, Bambino Gesù Children’s Hospital, IRCCS, Piazza S. 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Onofrio 4, Rome, Italy</nlm:aff><country xml:lang="fr">Italie</country><wicri:regionArea>Clinical Technology Innovations Research Area, Bambino Gesù Children’s Hospital, IRCCS, Piazza S. Onofrio 4, Rome</wicri:regionArea><placeName><settlement type="city">Rome</settlement><region nuts="2">Latium</region></placeName></affiliation><affiliation wicri:level="3"><nlm:aff id="I2">Department of Applied Electronics, University Roma Tre, Via della Vasca Navale 84, Rome, Italy</nlm:aff><country xml:lang="fr">Italie</country><wicri:regionArea>Department of Applied Electronics, University Roma Tre, Via della Vasca Navale 84, Rome</wicri:regionArea><placeName><settlement type="city">Rome</settlement><region nuts="2">Latium</region></placeName></affiliation></author><author><name sortKey="Gazzellini, Simone" sort="Gazzellini, Simone" uniqKey="Gazzellini S" first="Simone" last="Gazzellini">Simone Gazzellini</name><affiliation wicri:level="3"><nlm:aff id="I3">Department of Neuroscience and Neurorehabilitation, Bambino Gesù Children’s Hospital, IRCCS, Via Torre di Palidoro, Passoscuro, Rome, Italy</nlm:aff><country xml:lang="fr">Italie</country><wicri:regionArea>Department of Neuroscience and Neurorehabilitation, Bambino Gesù Children’s Hospital, IRCCS, Via Torre di Palidoro, Passoscuro, Rome</wicri:regionArea><placeName><settlement type="city">Rome</settlement><region nuts="2">Latium</region></placeName></affiliation><affiliation wicri:level="3"><nlm:aff id="I4">MARlab (Movement Analysis and Robotics Laboratory), Neurorehabilitation Division of Bambino Gesù Children’s Hospital, IRCCS, Via Torre di Palidoro, Passoscuro, Rome, Italy</nlm:aff><country xml:lang="fr">Italie</country><wicri:regionArea>MARlab (Movement Analysis and Robotics Laboratory), Neurorehabilitation Division of Bambino Gesù Children’s Hospital, IRCCS, Via Torre di Palidoro, Passoscuro, Rome</wicri:regionArea><placeName><settlement type="city">Rome</settlement><region nuts="2">Latium</region></placeName></affiliation></author><author><name sortKey="Grisolia, Carmela" sort="Grisolia, Carmela" uniqKey="Grisolia C" first="Carmela" last="Grisolia">Carmela Grisolia</name><affiliation wicri:level="3"><nlm:aff id="I3">Department of Neuroscience and Neurorehabilitation, Bambino Gesù Children’s Hospital, IRCCS, Via Torre di Palidoro, Passoscuro, Rome, Italy</nlm:aff><country xml:lang="fr">Italie</country><wicri:regionArea>Department of Neuroscience and Neurorehabilitation, Bambino Gesù Children’s Hospital, IRCCS, Via Torre di Palidoro, Passoscuro, Rome</wicri:regionArea><placeName><settlement type="city">Rome</settlement><region nuts="2">Latium</region></placeName></affiliation><affiliation wicri:level="3"><nlm:aff id="I4">MARlab (Movement Analysis and Robotics Laboratory), Neurorehabilitation Division of Bambino Gesù Children’s Hospital, IRCCS, Via Torre di Palidoro, Passoscuro, Rome, Italy</nlm:aff><country xml:lang="fr">Italie</country><wicri:regionArea>MARlab (Movement Analysis and Robotics Laboratory), Neurorehabilitation Division of Bambino Gesù Children’s Hospital, IRCCS, Via Torre di Palidoro, Passoscuro, Rome</wicri:regionArea><placeName><settlement type="city">Rome</settlement><region nuts="2">Latium</region></placeName></affiliation></author><author><name sortKey="Petrarca, Maurizio" sort="Petrarca, Maurizio" uniqKey="Petrarca M" first="Maurizio" last="Petrarca">Maurizio Petrarca</name><affiliation wicri:level="3"><nlm:aff id="I3">Department of Neuroscience and Neurorehabilitation, Bambino Gesù Children’s Hospital, IRCCS, Via Torre di Palidoro, Passoscuro, Rome, Italy</nlm:aff><country xml:lang="fr">Italie</country><wicri:regionArea>Department of Neuroscience and Neurorehabilitation, Bambino Gesù Children’s Hospital, IRCCS, Via Torre di Palidoro, Passoscuro, Rome</wicri:regionArea><placeName><settlement type="city">Rome</settlement><region nuts="2">Latium</region></placeName></affiliation><affiliation wicri:level="3"><nlm:aff id="I4">MARlab (Movement Analysis and Robotics Laboratory), Neurorehabilitation Division of Bambino Gesù Children’s Hospital, IRCCS, Via Torre di Palidoro, Passoscuro, Rome, Italy</nlm:aff><country xml:lang="fr">Italie</country><wicri:regionArea>MARlab (Movement Analysis and Robotics Laboratory), Neurorehabilitation Division of Bambino Gesù Children’s Hospital, IRCCS, Via Torre di Palidoro, Passoscuro, Rome</wicri:regionArea><placeName><settlement type="city">Rome</settlement><region nuts="2">Latium</region></placeName></affiliation></author><author><name sortKey="Cannata, Vittorio" sort="Cannata, Vittorio" uniqKey="Cannata V" first="Vittorio" last="Cannatà">Vittorio Cannatà</name><affiliation wicri:level="3"><nlm:aff id="I1">Clinical Technology Innovations Research Area, Bambino Gesù Children’s Hospital, IRCCS, Piazza S. Onofrio 4, Rome, Italy</nlm:aff><country xml:lang="fr">Italie</country><wicri:regionArea>Clinical Technology Innovations Research Area, Bambino Gesù Children’s Hospital, IRCCS, Piazza S. Onofrio 4, Rome</wicri:regionArea><placeName><settlement type="city">Rome</settlement><region nuts="2">Latium</region></placeName></affiliation></author><author><name sortKey="Cappa, Paolo" sort="Cappa, Paolo" uniqKey="Cappa P" first="Paolo" last="Cappa">Paolo Cappa</name><affiliation wicri:level="3"><nlm:aff id="I4">MARlab (Movement Analysis and Robotics Laboratory), Neurorehabilitation Division of Bambino Gesù Children’s Hospital, IRCCS, Via Torre di Palidoro, Passoscuro, Rome, Italy</nlm:aff><country xml:lang="fr">Italie</country><wicri:regionArea>MARlab (Movement Analysis and Robotics Laboratory), Neurorehabilitation Division of Bambino Gesù Children’s Hospital, IRCCS, Via Torre di Palidoro, Passoscuro, Rome</wicri:regionArea><placeName><settlement type="city">Rome</settlement><region nuts="2">Latium</region></placeName></affiliation><affiliation wicri:level="3"><nlm:aff id="I5">Department of Mechanical and Aerospace Engineering, Sapienza University of Rome, Via Eudossiana 4, Rome, Italy</nlm:aff><country xml:lang="fr">Italie</country><wicri:regionArea>Department of Mechanical and Aerospace Engineering, Sapienza University of Rome, Via Eudossiana 4, Rome</wicri:regionArea><placeName><settlement type="city">Rome</settlement><region nuts="2">Latium</region></placeName></affiliation></author><author><name sortKey="D Lessio, Tommaso" sort="D Lessio, Tommaso" uniqKey="D Lessio T" first="Tommaso" last="D Lessio">Tommaso D Lessio</name><affiliation wicri:level="3"><nlm:aff id="I2">Department of Applied Electronics, University Roma Tre, Via della Vasca Navale 84, Rome, Italy</nlm:aff><country xml:lang="fr">Italie</country><wicri:regionArea>Department of Applied Electronics, University Roma Tre, Via della Vasca Navale 84, Rome</wicri:regionArea><placeName><settlement type="city">Rome</settlement><region nuts="2">Latium</region></placeName></affiliation></author><author><name sortKey="Castelli, Enrico" sort="Castelli, Enrico" uniqKey="Castelli E" first="Enrico" last="Castelli">Enrico Castelli</name><affiliation wicri:level="3"><nlm:aff id="I3">Department of Neuroscience and Neurorehabilitation, Bambino Gesù Children’s Hospital, IRCCS, Via Torre di Palidoro, Passoscuro, Rome, Italy</nlm:aff><country xml:lang="fr">Italie</country><wicri:regionArea>Department of Neuroscience and Neurorehabilitation, Bambino Gesù Children’s Hospital, IRCCS, Via Torre di Palidoro, Passoscuro, Rome</wicri:regionArea><placeName><settlement type="city">Rome</settlement><region nuts="2">Latium</region></placeName></affiliation><affiliation wicri:level="3"><nlm:aff id="I4">MARlab (Movement Analysis and Robotics Laboratory), Neurorehabilitation Division of Bambino Gesù Children’s Hospital, IRCCS, Via Torre di Palidoro, Passoscuro, Rome, Italy</nlm:aff><country xml:lang="fr">Italie</country><wicri:regionArea>MARlab (Movement Analysis and Robotics Laboratory), Neurorehabilitation Division of Bambino Gesù Children’s Hospital, IRCCS, Via Torre di Palidoro, Passoscuro, Rome</wicri:regionArea><placeName><settlement type="city">Rome</settlement><region nuts="2">Latium</region></placeName></affiliation></author></analytic><series><title level="j">Journal of NeuroEngineering and Rehabilitation</title><idno type="eISSN">1743-0003</idno><imprint><date when="2012">2012</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><sec><title>Background</title><p>The potential of robot-mediated therapy and virtual reality in neurorehabilitation is becoming of increasing importance. However, there is limited information, using neuroimaging, on the neural networks involved in training with these technologies. This study was intended to detect the brain network involved in the visual processing of movement during robotic training. The main aim was to investigate the existence of a common cerebral network able to assimilate biological (human upper limb) and non-biological (abstract object) movements, hence testing the suitability of the visual non-biological feedback provided by the InMotion2 Robot.</p></sec><sec><title>Methods</title><p>A visual functional Magnetic Resonance Imaging (fMRI) task was administered to 22 healthy subjects. The task required observation and retrieval of motor gestures and of the visual feedback used in robotic training. Functional activations of both biological and non-biological movements were examined to identify areas activated in both conditions, along with differential activity in upper limb vs. abstract object trials. Control of response was also tested by administering trials with congruent and incongruent reaching movements.</p></sec><sec><title>Results</title><p>The observation of upper limb and abstract object movements elicited similar patterns of activations according to a caudo-rostral pathway for the visual processing of movements (including specific areas of the occipital, temporal, parietal, and frontal lobes). Similarly, overlapping activations were found for the subsequent retrieval of the observed movement. Furthermore, activations of frontal cortical areas were associated with congruent trials more than with the incongruent ones.</p></sec><sec><title>Conclusions</title><p>This study identified the neural pathway associated with visual processing of movement stimuli used in upper limb robot-mediated training and investigated the brain’s ability to assimilate abstract object movements with human motor gestures. In both conditions, activations were elicited in cerebral areas involved in visual perception, sensory integration, recognition of movement, re-mapping on the somatosensory and motor cortex, storage in memory, and response control. Results from the congruent vs. incongruent trials revealed greater activity for the former condition than the latter in a network including cingulate cortex, right inferior and middle frontal gyrus that are involved in the go-signal and in decision control. Results on healthy subjects would suggest the appropriateness of an abstract visual feedback provided during motor training. The task contributes to highlight the potential of fMRI in improving the understanding of visual motor processes and may also be useful in detecting brain reorganisation during training.</p></sec></div></front><back><div1 type="bibliography"><listBibl><biblStruct><analytic><author><name sortKey="Adamovich, Sv" uniqKey="Adamovich S">SV Adamovich</name></author><author><name sortKey="Fluet, Gg" uniqKey="Fluet G">GG Fluet</name></author><author><name sortKey="Tunik, E" uniqKey="Tunik E">E Tunik</name></author><author><name sortKey="Merians, As" uniqKey="Merians A">AS Merians</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Castelli, E" uniqKey="Castelli E">E Castelli</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Henderson, A" uniqKey="Henderson A">A Henderson</name></author><author><name sortKey="Korner Bitensky, N" uniqKey="Korner Bitensky N">N Korner-Bitensky</name></author><author><name sortKey="Levin, M" 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Sp" uniqKey="Swinnen S">SP Swinnen</name></author><author><name sortKey="Schmidt, Ra" uniqKey="Schmidt R">RA Schmidt</name></author><author><name sortKey="Nicholson, De" uniqKey="Nicholson D">DE Nicholson</name></author><author><name sortKey="Shapiro, Dc" uniqKey="Shapiro D">DC Shapiro</name></author></analytic></biblStruct></listBibl></div1></back></TEI></record>Pour manipuler ce document sous Unix (Dilib)
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