Physiological modules for generating discrete and rhythmic movements: Component analysis of EMG signals.

A central question in Neuroscience is that of how the nervous system generates the spatiotemporal commands needed to realize complex gestures, such as handwriting. A key postulate is that the CNS builds up complex movements from a set of simpler motor primitives or control modules. In this study we...

Full description

Bibliographic Details
Main Authors: Ana eBengoetxea, Françoise eLeurs, Thomas eHoellinger, Ana Maria eCebolla, Bernard eDan, Guy eCheron, Joseph eMcIntyre
Format: Article
Language:English
Published: Frontiers Media S.A. 2015-01-01
Series:Frontiers in Computational Neuroscience
Subjects:
Online Access:http://journal.frontiersin.org/Journal/10.3389/fncom.2014.00169/full
id doaj-998e30d3bdf74d7da0625a8b05214541
record_format Article
spelling doaj-998e30d3bdf74d7da0625a8b052145412020-11-24T22:40:14ZengFrontiers Media S.A.Frontiers in Computational Neuroscience1662-51882015-01-01810.3389/fncom.2014.00169109558Physiological modules for generating discrete and rhythmic movements: Component analysis of EMG signals.Ana eBengoetxea0Ana eBengoetxea1Françoise eLeurs2Thomas eHoellinger3Ana Maria eCebolla4Bernard eDan5Bernard eDan6Guy eCheron7Guy eCheron8Joseph eMcIntyre9Joseph eMcIntyre10Université Libre de BruxellesUniversidad del Pais Vasco/Euskal Herriko UnibertsitateaUniversité Libre de BruxellesUniversité Libre de BruxellesUniversité Libre de BruxellesUniversité Libre de BruxellesHôpital Universitaire des Enfants Reine FabiolaUniversité Libre de BruxellesUniversité de Mons-HainautFundacion Tecnalia Research and InnovationIKERBASQUE Science FoundationA central question in Neuroscience is that of how the nervous system generates the spatiotemporal commands needed to realize complex gestures, such as handwriting. A key postulate is that the CNS builds up complex movements from a set of simpler motor primitives or control modules. In this study we examined the control modules underlying the generation of muscle activations when performing different types of movement: discrete, point-to-point movements in eight different directions and continuous figure-eight movements in both the normal, upright orientation and rotated 90°. To test for the effects of biomechanical constraints, movements were performed in the frontal-parallel or sagittal planes, corresponding to two different nominal flexion/abduction postures of the shoulder. In all cases we measured limb kinematics and surface EMG signals for seven different muscles acting around the shoulder.We first performed principal component analysis (PCA) of the EMG signals on a movement-by-movement basis. We found a surprisingly consistent pattern of muscle groupings across movement types and movement planes, although we could detect systematic differences between the PCs derived from movements performed in each shoulder posture and between the principal components associated with the different orientations of the figure. Unexpectedly we found no systematic differences between the figure eights and the point-to-point movements. The first three principal components could be associated with a general co-contraction of all seven muscles plus two patterns of reciprocal activation. From these results, we surmise that both ‘discrete-rhythmic movements’ such as the figure eight, and discrete point-to-point movement may be constructed from three different fundamental modules, one regulating the impedance of the limb over the time span of the movement and two others operating to generate movement, one aligned with the vertical and the other aligned with the horizontal.http://journal.frontiersin.org/Journal/10.3389/fncom.2014.00169/fullPrincipal Component AnalysisUpper limbfigure-eightrhythmic movementmuscular synergyvarimax factor analysis
collection DOAJ
language English
format Article
sources DOAJ
author Ana eBengoetxea
Ana eBengoetxea
Françoise eLeurs
Thomas eHoellinger
Ana Maria eCebolla
Bernard eDan
Bernard eDan
Guy eCheron
Guy eCheron
Joseph eMcIntyre
Joseph eMcIntyre
spellingShingle Ana eBengoetxea
Ana eBengoetxea
Françoise eLeurs
Thomas eHoellinger
Ana Maria eCebolla
Bernard eDan
Bernard eDan
Guy eCheron
Guy eCheron
Joseph eMcIntyre
Joseph eMcIntyre
Physiological modules for generating discrete and rhythmic movements: Component analysis of EMG signals.
Frontiers in Computational Neuroscience
Principal Component Analysis
Upper limb
figure-eight
rhythmic movement
muscular synergy
varimax factor analysis
author_facet Ana eBengoetxea
Ana eBengoetxea
Françoise eLeurs
Thomas eHoellinger
Ana Maria eCebolla
Bernard eDan
Bernard eDan
Guy eCheron
Guy eCheron
Joseph eMcIntyre
Joseph eMcIntyre
author_sort Ana eBengoetxea
title Physiological modules for generating discrete and rhythmic movements: Component analysis of EMG signals.
title_short Physiological modules for generating discrete and rhythmic movements: Component analysis of EMG signals.
title_full Physiological modules for generating discrete and rhythmic movements: Component analysis of EMG signals.
title_fullStr Physiological modules for generating discrete and rhythmic movements: Component analysis of EMG signals.
title_full_unstemmed Physiological modules for generating discrete and rhythmic movements: Component analysis of EMG signals.
title_sort physiological modules for generating discrete and rhythmic movements: component analysis of emg signals.
publisher Frontiers Media S.A.
series Frontiers in Computational Neuroscience
issn 1662-5188
publishDate 2015-01-01
description A central question in Neuroscience is that of how the nervous system generates the spatiotemporal commands needed to realize complex gestures, such as handwriting. A key postulate is that the CNS builds up complex movements from a set of simpler motor primitives or control modules. In this study we examined the control modules underlying the generation of muscle activations when performing different types of movement: discrete, point-to-point movements in eight different directions and continuous figure-eight movements in both the normal, upright orientation and rotated 90°. To test for the effects of biomechanical constraints, movements were performed in the frontal-parallel or sagittal planes, corresponding to two different nominal flexion/abduction postures of the shoulder. In all cases we measured limb kinematics and surface EMG signals for seven different muscles acting around the shoulder.We first performed principal component analysis (PCA) of the EMG signals on a movement-by-movement basis. We found a surprisingly consistent pattern of muscle groupings across movement types and movement planes, although we could detect systematic differences between the PCs derived from movements performed in each shoulder posture and between the principal components associated with the different orientations of the figure. Unexpectedly we found no systematic differences between the figure eights and the point-to-point movements. The first three principal components could be associated with a general co-contraction of all seven muscles plus two patterns of reciprocal activation. From these results, we surmise that both ‘discrete-rhythmic movements’ such as the figure eight, and discrete point-to-point movement may be constructed from three different fundamental modules, one regulating the impedance of the limb over the time span of the movement and two others operating to generate movement, one aligned with the vertical and the other aligned with the horizontal.
topic Principal Component Analysis
Upper limb
figure-eight
rhythmic movement
muscular synergy
varimax factor analysis
url http://journal.frontiersin.org/Journal/10.3389/fncom.2014.00169/full
work_keys_str_mv AT anaebengoetxea physiologicalmodulesforgeneratingdiscreteandrhythmicmovementscomponentanalysisofemgsignals
AT anaebengoetxea physiologicalmodulesforgeneratingdiscreteandrhythmicmovementscomponentanalysisofemgsignals
AT francoiseeleurs physiologicalmodulesforgeneratingdiscreteandrhythmicmovementscomponentanalysisofemgsignals
AT thomasehoellinger physiologicalmodulesforgeneratingdiscreteandrhythmicmovementscomponentanalysisofemgsignals
AT anamariaecebolla physiologicalmodulesforgeneratingdiscreteandrhythmicmovementscomponentanalysisofemgsignals
AT bernardedan physiologicalmodulesforgeneratingdiscreteandrhythmicmovementscomponentanalysisofemgsignals
AT bernardedan physiologicalmodulesforgeneratingdiscreteandrhythmicmovementscomponentanalysisofemgsignals
AT guyecheron physiologicalmodulesforgeneratingdiscreteandrhythmicmovementscomponentanalysisofemgsignals
AT guyecheron physiologicalmodulesforgeneratingdiscreteandrhythmicmovementscomponentanalysisofemgsignals
AT josephemcintyre physiologicalmodulesforgeneratingdiscreteandrhythmicmovementscomponentanalysisofemgsignals
AT josephemcintyre physiologicalmodulesforgeneratingdiscreteandrhythmicmovementscomponentanalysisofemgsignals
_version_ 1725705335077863424