1. Deciphering the functional role of spatial and temporal muscle synergies in whole-body movements
- Author
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Stefano Panzeri, Bastien Berret, Thierry Pozzo, Ioannis Delis, Pauline M. Hilt, Columbia University [New York], School of Biomedical Sciences, University of Leeds, Cognition, Action, et Plasticité Sensorimotrice [Dijon - U1093] (CAPS), Université de Bourgogne (UB)-Institut National de la Santé et de la Recherche Médicale (INSERM), Centro di Neurofisiologia traslazionale, Istituto Italiano di Tecnologia, Università di Ferrara, Istituto Italiano di Tecnologia (IIT), Neural Computation Laboratory, Complexité, Innovation, Activités Motrices et Sportives (CIAMS), Université Paris-Sud - Paris 11 (UP11)-Université d'Orléans (UO), Institut Universitaire de France (IUF), and Ministère de l'Education nationale, de l’Enseignement supérieur et de la Recherche (M.E.N.E.S.R.)
- Subjects
0301 basic medicine ,Functional role ,Adult ,Male ,spinal-cord ,Computer science ,Movement ,equilibrium-point hypothesis ,lcsh:Medicine ,emg patterns ,arm movements ,Temporal muscle ,Article ,interindividual variability ,primitives ,03 medical and health sciences ,0302 clinical medicine ,Spatio-Temporal Analysis ,medicine ,motor control ,Humans ,Muscle activity ,Muscle, Skeletal ,activation patterns ,lcsh:Science ,Multidisciplinary ,business.industry ,Electromyography ,lcsh:R ,Motor control ,Pattern recognition ,Spinal cord ,030104 developmental biology ,medicine.anatomical_structure ,Female ,[SDV.NEU]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC] ,lcsh:Q ,Artificial intelligence ,Whole body ,business ,sensorimotor control ,030217 neurology & neurosurgery ,information measures - Abstract
Voluntary movement is hypothesized to rely on a limited number of muscle synergies, the recruitment of which translates task goals into effective muscle activity. In this study, we investigated how to analytically characterize the functional role of different types of muscle synergies in task performance. To this end, we recorded a comprehensive dataset of muscle activity during a variety of whole-body pointing movements. We decomposed the electromyographic (EMG) signals using a space-by-time modularity model which encompasses the main types of synergies. We then used a task decoding and information theoretic analysis to probe the role of each synergy by mapping it to specific task features. We found that the temporal and spatial aspects of the movements were encoded by different temporal and spatial muscle synergies, respectively, consistent with the intuition that there should a correspondence between major attributes of movement and major features of synergies. This approach led to the development of a novel computational method for comparing muscle synergies from different participants according to their functional role. This functional similarity analysis yielded a small set of temporal and spatial synergies that describes the main features of whole-body reaching movements.
- Published
- 2018
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