Space-by-Time Modular Decomposition Effectively Describes Whole-Body Muscle Activity During Upright Reaching in Various Directions
The modular control hypothesis suggests that motor commands are built from precoded modules whose specific combined recruitment can allow the performance of virtually any motor task. Despite considerable experimental support, this hypothesis remains tentative as classical findings of reduced dimensi...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2018-04-01
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| Series: | Frontiers in Computational Neuroscience |
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| Online Access: | http://journal.frontiersin.org/article/10.3389/fncom.2018.00020/full |
| _version_ | 1819268553712336896 |
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| author | Pauline M. Hilt Pauline M. Hilt Ioannis Delis Thierry Pozzo Thierry Pozzo Bastien Berret Bastien Berret Bastien Berret |
| author_facet | Pauline M. Hilt Pauline M. Hilt Ioannis Delis Thierry Pozzo Thierry Pozzo Bastien Berret Bastien Berret Bastien Berret |
| author_sort | Pauline M. Hilt |
| collection | DOAJ |
| description | The modular control hypothesis suggests that motor commands are built from precoded modules whose specific combined recruitment can allow the performance of virtually any motor task. Despite considerable experimental support, this hypothesis remains tentative as classical findings of reduced dimensionality in muscle activity may also result from other constraints (biomechanical couplings, data averaging or low dimensionality of motor tasks). Here we assessed the effectiveness of modularity in describing muscle activity in a comprehensive experiment comprising 72 distinct point-to-point whole-body movements during which the activity of 30 muscles was recorded. To identify invariant modules of a temporal and spatial nature, we used a space-by-time decomposition of muscle activity that has been shown to encompass classical modularity models. To examine the decompositions, we focused not only on the amount of variance they explained but also on whether the task performed on each trial could be decoded from the single-trial activations of modules. For the sake of comparison, we confronted these scores to the scores obtained from alternative non-modular descriptions of the muscle data. We found that the space-by-time decomposition was effective in terms of data approximation and task discrimination at comparable reduction of dimensionality. These findings show that few spatial and temporal modules give a compact yet approximate representation of muscle patterns carrying nearly all task-relevant information for a variety of whole-body reaching movements. |
| first_indexed | 2024-12-23T21:34:54Z |
| format | Article |
| id | doaj.art-e3b2d4ca519b491db0cb64938920b746 |
| institution | Directory Open Access Journal |
| issn | 1662-5188 |
| language | English |
| last_indexed | 2024-12-23T21:34:54Z |
| publishDate | 2018-04-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Computational Neuroscience |
| spelling | doaj.art-e3b2d4ca519b491db0cb64938920b7462022-12-21T17:30:21ZengFrontiers Media S.A.Frontiers in Computational Neuroscience1662-51882018-04-011210.3389/fncom.2018.00020295746Space-by-Time Modular Decomposition Effectively Describes Whole-Body Muscle Activity During Upright Reaching in Various DirectionsPauline M. Hilt0Pauline M. Hilt1Ioannis Delis2Thierry Pozzo3Thierry Pozzo4Bastien Berret5Bastien Berret6Bastien Berret7Institut National de la Santé et de la Recherche Médicale, U1093, Cognition Action Plasticité Sensorimotrice, Dijon, FranceItalian Institute of Technology CTNSC@UniFe (Center of Translational Neurophysiology for Speech and Communication), Ferrara, ItalyDepartment of Biomedical Engineering, Columbia University, New York, NY, United StatesInstitut National de la Santé et de la Recherche Médicale, U1093, Cognition Action Plasticité Sensorimotrice, Dijon, FranceItalian Institute of Technology CTNSC@UniFe (Center of Translational Neurophysiology for Speech and Communication), Ferrara, ItalyCIAMS, Université Paris-Sud, Université Paris-Saclay, Orsay, FranceCIAMS, Université d'Orléans, Orléans, FranceInstitut Universitaire de France, Paris, FranceThe modular control hypothesis suggests that motor commands are built from precoded modules whose specific combined recruitment can allow the performance of virtually any motor task. Despite considerable experimental support, this hypothesis remains tentative as classical findings of reduced dimensionality in muscle activity may also result from other constraints (biomechanical couplings, data averaging or low dimensionality of motor tasks). Here we assessed the effectiveness of modularity in describing muscle activity in a comprehensive experiment comprising 72 distinct point-to-point whole-body movements during which the activity of 30 muscles was recorded. To identify invariant modules of a temporal and spatial nature, we used a space-by-time decomposition of muscle activity that has been shown to encompass classical modularity models. To examine the decompositions, we focused not only on the amount of variance they explained but also on whether the task performed on each trial could be decoded from the single-trial activations of modules. For the sake of comparison, we confronted these scores to the scores obtained from alternative non-modular descriptions of the muscle data. We found that the space-by-time decomposition was effective in terms of data approximation and task discrimination at comparable reduction of dimensionality. These findings show that few spatial and temporal modules give a compact yet approximate representation of muscle patterns carrying nearly all task-relevant information for a variety of whole-body reaching movements.http://journal.frontiersin.org/article/10.3389/fncom.2018.00020/fullmodularitymuscle synergiesspace-by-time decompositiontask discriminationwhole-body pointingsingle-trial analysis |
| spellingShingle | Pauline M. Hilt Pauline M. Hilt Ioannis Delis Thierry Pozzo Thierry Pozzo Bastien Berret Bastien Berret Bastien Berret Space-by-Time Modular Decomposition Effectively Describes Whole-Body Muscle Activity During Upright Reaching in Various Directions Frontiers in Computational Neuroscience modularity muscle synergies space-by-time decomposition task discrimination whole-body pointing single-trial analysis |
| title | Space-by-Time Modular Decomposition Effectively Describes Whole-Body Muscle Activity During Upright Reaching in Various Directions |
| title_full | Space-by-Time Modular Decomposition Effectively Describes Whole-Body Muscle Activity During Upright Reaching in Various Directions |
| title_fullStr | Space-by-Time Modular Decomposition Effectively Describes Whole-Body Muscle Activity During Upright Reaching in Various Directions |
| title_full_unstemmed | Space-by-Time Modular Decomposition Effectively Describes Whole-Body Muscle Activity During Upright Reaching in Various Directions |
| title_short | Space-by-Time Modular Decomposition Effectively Describes Whole-Body Muscle Activity During Upright Reaching in Various Directions |
| title_sort | space by time modular decomposition effectively describes whole body muscle activity during upright reaching in various directions |
| topic | modularity muscle synergies space-by-time decomposition task discrimination whole-body pointing single-trial analysis |
| url | http://journal.frontiersin.org/article/10.3389/fncom.2018.00020/full |
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