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dc.contributor.authorBengoechea Arrese, Ana María
dc.contributor.authorLeurs, Françoise
dc.contributor.authorHoellinger, Thomas
dc.contributor.authorCebolla, Ana M.
dc.contributor.authorDan, Bernard
dc.contributor.authorMcIntyre, Joseph
dc.contributor.authorCheron, Guy
dc.date.accessioned2015-10-27T13:08:58Z
dc.date.available2015-10-27T13:08:58Z
dc.date.issued2014-09-17
dc.identifier.citationFrontiers in computational neuroscience 8 : (2014) // Article ID 100es
dc.identifier.issn1662-5188
dc.identifier.issn10.3389/fncom.2014.00100
dc.identifier.urihttp://hdl.handle.net/10810/15994
dc.description.abstractIn this study we employed a dynamic recurrent neural network (DRNN) in a novel fashion to reveal characteristics of control modules underlying the generation of muscle activations when drawing figures with the outstretched arm. We asked healthy human subjects to perform four different figure-eight movements in each of two workspaces (frontal plane and sagittal plane). We then trained a DRNN to predict the movement of the wrist from information in the EMG signals from seven different muscles. We trained different instances of the same network on a single movement direction, on all four movement directions in a single movement plane, or on all eight possible movement patterns and looked at the ability of the DRNN to generalize and predict movements for trials that were not included in the training set. Within a single movement plane, a DRNN trained on one movement direction was not able to predict movements of the hand for trials in the other three directions, but a DRNN trained simultaneously on all four movement directions could generalize across movement directions within the same plane. Similarly, the DRNN was able to reproduce the kinematics of the hand for both movement planes, but only if it was trained on examples performed in each one. As we will discuss, these results indicate that there are important dynamical constraints on the mapping of EMG to hand movement that depend on both the time sequence of the movement and on the anatomical constraints of the musculoskeletal system. In a second step, we injected EMG signals constructed from different synergies derived by the PCA in order to identify the mechanical significance of each of these components. From these results, one can surmise that discrete-rhythmic movements may be constructed from three different fundamental modules, one regulating the co-activation of all muscles over the time span of the movement and two others elliciting patterns of reciprocal activation operating in orthogonal directions.es
dc.description.sponsorshipThis work was funded by the Belgian Federal Science Policy Office, the European Space Agency, (AO-2004, 118), the Belgian National Fund for Scientific Research (FNRS), the research funds of the Universite Libre de Bruxelles and of the Universite de Mons (Belgium), the FEDER support (BIOFACT), and the MINDWALKER project (FP7 - 2007-2013) supported by the European Commission.es
dc.language.isoenges
dc.publisherFrontiers Research Foundationes
dc.rightsinfo:eu-repo/semantics/openAccesses
dc.subjectrhythmic movement;es
dc.subjectmuscular synergyes
dc.subjectdynamic recurrent neuronal networkes
dc.subjectprincipal component analysises
dc.subjectupper limbes
dc.subjectfigure-eightes
dc.subjectmuscle activation patternses
dc.subjectnatural motor behaviorses
dc.subjectcomplex movementses
dc.subjectsynergieses
dc.subjectmodeles
dc.subjecttimees
dc.subjecthandes
dc.subjectrepresentationes
dc.subjectcombinationses
dc.subjectorganizationes
dc.titlePhysiological modules for generating discrete and rhythmic movements: action identification by a dynamic recurrent neural networkes
dc.typeinfo:eu-repo/semantics/articlees
dc.rights.holder© 2014 Bengoetxea, Leurs, Hoellinger, Cebolla, Dan, McIntyre and Cheron. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.es
dc.relation.publisherversionhttp://journal.frontiersin.org/article/10.3389/fncom.2014.00100/abstractes
dc.departamentoesFisiologíaes_ES
dc.departamentoeuFisiologiaes_ES
dc.subject.categoriaCELLULAR AND MOLECULAR NEUROSCIENCE
dc.subject.categoriaNEUROSCIENCES


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