Lower complexity of motor primitives ensures robust control of high-speed human locomotion
Walking and running are mechanically and energetically different locomotion modes. For selecting one or another, speed is a parameter of paramount importance. Yet, both are likely controlled by similar low-dimensional neuronal networks that reflect in patterned muscle activations called muscle syner...
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| Format: | Article |
| Language: | English |
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Elsevier
2020-10-01
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| Series: | Heliyon |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2405844020322209 |
| _version_ | 1818149203526811648 |
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| author | Alessandro Santuz Antonis Ekizos Yoko Kunimasa Kota Kijima Masaki Ishikawa Adamantios Arampatzis |
| author_facet | Alessandro Santuz Antonis Ekizos Yoko Kunimasa Kota Kijima Masaki Ishikawa Adamantios Arampatzis |
| author_sort | Alessandro Santuz |
| collection | DOAJ |
| description | Walking and running are mechanically and energetically different locomotion modes. For selecting one or another, speed is a parameter of paramount importance. Yet, both are likely controlled by similar low-dimensional neuronal networks that reflect in patterned muscle activations called muscle synergies. Here, we challenged human locomotion by having our participants walk and run at a very broad spectrum of submaximal and maximal speeds. The synergistic activations of lower limb locomotor muscles were obtained through decomposition of electromyographic data via non-negative matrix factorization. We analyzed the duration and complexity (via fractal analysis) over time of motor primitives, the temporal components of muscle synergies. We found that the motor control of high-speed locomotion was so challenging that the neuromotor system was forced to produce wider and less complex muscle activation patterns. The motor modules, or time-independent coefficients, were redistributed as locomotion speed changed. These outcomes show that humans cope with the challenges of high-speed locomotion by adapting the neuromotor dynamics through a set of strategies that allow for efficient creation and control of locomotion. |
| first_indexed | 2024-12-11T13:03:18Z |
| format | Article |
| id | doaj.art-0ca740e8cfcc45acb8fedcce9f68bf50 |
| institution | Directory Open Access Journal |
| issn | 2405-8440 |
| language | English |
| last_indexed | 2024-12-11T13:03:18Z |
| publishDate | 2020-10-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Heliyon |
| spelling | doaj.art-0ca740e8cfcc45acb8fedcce9f68bf502022-12-22T01:06:24ZengElsevierHeliyon2405-84402020-10-01610e05377Lower complexity of motor primitives ensures robust control of high-speed human locomotionAlessandro Santuz0Antonis Ekizos1Yoko Kunimasa2Kota Kijima3Masaki Ishikawa4Adamantios Arampatzis5Department of Training and Movement Sciences, Humboldt-Universität zu Berlin, 10115 Berlin, Germany; Berlin School of Movement Science, Humboldt-Universität zu Berlin, 10115 Berlin, Germany; Corresponding author.Department of Training and Movement Sciences, Humboldt-Universität zu Berlin, 10115 Berlin, Germany; Berlin School of Movement Science, Humboldt-Universität zu Berlin, 10115 Berlin, GermanyGraduate School of Sport and Exercise Sciences, Osaka University of Health and Sport Sciences, 590-0459 Osaka, JapanGraduate School of Sport and Exercise Sciences, Osaka University of Health and Sport Sciences, 590-0459 Osaka, JapanGraduate School of Sport and Exercise Sciences, Osaka University of Health and Sport Sciences, 590-0459 Osaka, JapanDepartment of Training and Movement Sciences, Humboldt-Universität zu Berlin, 10115 Berlin, Germany; Berlin School of Movement Science, Humboldt-Universität zu Berlin, 10115 Berlin, GermanyWalking and running are mechanically and energetically different locomotion modes. For selecting one or another, speed is a parameter of paramount importance. Yet, both are likely controlled by similar low-dimensional neuronal networks that reflect in patterned muscle activations called muscle synergies. Here, we challenged human locomotion by having our participants walk and run at a very broad spectrum of submaximal and maximal speeds. The synergistic activations of lower limb locomotor muscles were obtained through decomposition of electromyographic data via non-negative matrix factorization. We analyzed the duration and complexity (via fractal analysis) over time of motor primitives, the temporal components of muscle synergies. We found that the motor control of high-speed locomotion was so challenging that the neuromotor system was forced to produce wider and less complex muscle activation patterns. The motor modules, or time-independent coefficients, were redistributed as locomotion speed changed. These outcomes show that humans cope with the challenges of high-speed locomotion by adapting the neuromotor dynamics through a set of strategies that allow for efficient creation and control of locomotion.http://www.sciencedirect.com/science/article/pii/S2405844020322209NeurosciencePhysiologyBiomedical engineeringBiomechanicsBiomechanical engineeringBehavioral neuroscience |
| spellingShingle | Alessandro Santuz Antonis Ekizos Yoko Kunimasa Kota Kijima Masaki Ishikawa Adamantios Arampatzis Lower complexity of motor primitives ensures robust control of high-speed human locomotion Heliyon Neuroscience Physiology Biomedical engineering Biomechanics Biomechanical engineering Behavioral neuroscience |
| title | Lower complexity of motor primitives ensures robust control of high-speed human locomotion |
| title_full | Lower complexity of motor primitives ensures robust control of high-speed human locomotion |
| title_fullStr | Lower complexity of motor primitives ensures robust control of high-speed human locomotion |
| title_full_unstemmed | Lower complexity of motor primitives ensures robust control of high-speed human locomotion |
| title_short | Lower complexity of motor primitives ensures robust control of high-speed human locomotion |
| title_sort | lower complexity of motor primitives ensures robust control of high speed human locomotion |
| topic | Neuroscience Physiology Biomedical engineering Biomechanics Biomechanical engineering Behavioral neuroscience |
| url | http://www.sciencedirect.com/science/article/pii/S2405844020322209 |
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