Morphological Computation Increases From Lower- to Higher-Level of Biological Motor Control Hierarchy
Voluntary movements, like point-to-point or oscillatory human arm movements, are generated by the interaction of several structures. High-level neuronal circuits in the brain are responsible for planning and initiating a movement. Spinal circuits incorporate proprioceptive feedback to compensate for...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2020-10-01
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| Series: | Frontiers in Robotics and AI |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/frobt.2020.511265/full |
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| author | Daniel F. B. Haeufle Katrin Stollenmaier Isabelle Heinrich Syn Schmitt Keyan Ghazi-Zahedi |
| author_facet | Daniel F. B. Haeufle Katrin Stollenmaier Isabelle Heinrich Syn Schmitt Keyan Ghazi-Zahedi |
| author_sort | Daniel F. B. Haeufle |
| collection | DOAJ |
| description | Voluntary movements, like point-to-point or oscillatory human arm movements, are generated by the interaction of several structures. High-level neuronal circuits in the brain are responsible for planning and initiating a movement. Spinal circuits incorporate proprioceptive feedback to compensate for deviations from the desired movement. Muscle biochemistry and contraction dynamics generate movement driving forces and provide an immediate physical response to external forces, like a low-level decentralized controller. A simple central neuronal command like “initiate a movement” then recruits all these biological structures and processes leading to complex behavior, e.g., generate a stable oscillatory movement in resonance with an external spring-mass system. It has been discussed that the spinal feedback circuits, the biochemical processes, and the biomechanical muscle dynamics contribute to the movement generation, and, thus, take over some parts of the movement generation and stabilization which would otherwise have to be performed by the high-level controller. This contribution is termed morphological computation and can be quantified with information entropy-based approaches. However, it is unknown whether morphological computation actually differs between these different hierarchical levels of the control system. To investigate this, we simulated point-to-point and oscillatory human arm movements with a neuro-musculoskeletal model. We then quantify morphological computation on the different hierarchy levels. The results show that morphological computation is highest for the most central (highest) level of the modeled control hierarchy, where the movement initiation and timing are encoded. Furthermore, they show that the lowest neuronal control layer, the muscle stimulation input, exploits the morphological computation of the biochemical and biophysical muscle characteristics to generate smooth dynamic movements. This study provides evidence that the system's design in the mechanical as well as in the neurological structure can take over important contributions to control, which would otherwise need to be performed by the higher control levels. |
| first_indexed | 2024-12-14T00:37:12Z |
| format | Article |
| id | doaj.art-dce6427168c84d32bca7c99cc1b5a57a |
| institution | Directory Open Access Journal |
| issn | 2296-9144 |
| language | English |
| last_indexed | 2024-12-14T00:37:12Z |
| publishDate | 2020-10-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Robotics and AI |
| spelling | doaj.art-dce6427168c84d32bca7c99cc1b5a57a2022-12-21T23:24:34ZengFrontiers Media S.A.Frontiers in Robotics and AI2296-91442020-10-01710.3389/frobt.2020.511265511265Morphological Computation Increases From Lower- to Higher-Level of Biological Motor Control HierarchyDaniel F. B. Haeufle0Katrin Stollenmaier1Isabelle Heinrich2Syn Schmitt3Keyan Ghazi-Zahedi4Multi-Level Modeling in Motor Control and Rehabilitation Robotics, Hertie-Institute for Clinical Brain Research, University of Tübingen, Tübingen, GermanyMulti-Level Modeling in Motor Control and Rehabilitation Robotics, Hertie-Institute for Clinical Brain Research, University of Tübingen, Tübingen, GermanyMulti-Level Modeling in Motor Control and Rehabilitation Robotics, Hertie-Institute for Clinical Brain Research, University of Tübingen, Tübingen, GermanyStuttgart Center for Simulation Science, Institute for Modelling and Simulation of Biomechanical Systems, University of Stuttgart, Stuttgart, GermanyInformation Theory of Cognitive Systems, Max-Planck Institute for Mathematics in the Sciences, Leipzig, GermanyVoluntary movements, like point-to-point or oscillatory human arm movements, are generated by the interaction of several structures. High-level neuronal circuits in the brain are responsible for planning and initiating a movement. Spinal circuits incorporate proprioceptive feedback to compensate for deviations from the desired movement. Muscle biochemistry and contraction dynamics generate movement driving forces and provide an immediate physical response to external forces, like a low-level decentralized controller. A simple central neuronal command like “initiate a movement” then recruits all these biological structures and processes leading to complex behavior, e.g., generate a stable oscillatory movement in resonance with an external spring-mass system. It has been discussed that the spinal feedback circuits, the biochemical processes, and the biomechanical muscle dynamics contribute to the movement generation, and, thus, take over some parts of the movement generation and stabilization which would otherwise have to be performed by the high-level controller. This contribution is termed morphological computation and can be quantified with information entropy-based approaches. However, it is unknown whether morphological computation actually differs between these different hierarchical levels of the control system. To investigate this, we simulated point-to-point and oscillatory human arm movements with a neuro-musculoskeletal model. We then quantify morphological computation on the different hierarchy levels. The results show that morphological computation is highest for the most central (highest) level of the modeled control hierarchy, where the movement initiation and timing are encoded. Furthermore, they show that the lowest neuronal control layer, the muscle stimulation input, exploits the morphological computation of the biochemical and biophysical muscle characteristics to generate smooth dynamic movements. This study provides evidence that the system's design in the mechanical as well as in the neurological structure can take over important contributions to control, which would otherwise need to be performed by the higher control levels.https://www.frontiersin.org/articles/10.3389/frobt.2020.511265/fullmorphological computationcontrol hierarchyarmmotor controlmusclespreflexes |
| spellingShingle | Daniel F. B. Haeufle Katrin Stollenmaier Isabelle Heinrich Syn Schmitt Keyan Ghazi-Zahedi Morphological Computation Increases From Lower- to Higher-Level of Biological Motor Control Hierarchy Frontiers in Robotics and AI morphological computation control hierarchy arm motor control muscles preflexes |
| title | Morphological Computation Increases From Lower- to Higher-Level of Biological Motor Control Hierarchy |
| title_full | Morphological Computation Increases From Lower- to Higher-Level of Biological Motor Control Hierarchy |
| title_fullStr | Morphological Computation Increases From Lower- to Higher-Level of Biological Motor Control Hierarchy |
| title_full_unstemmed | Morphological Computation Increases From Lower- to Higher-Level of Biological Motor Control Hierarchy |
| title_short | Morphological Computation Increases From Lower- to Higher-Level of Biological Motor Control Hierarchy |
| title_sort | morphological computation increases from lower to higher level of biological motor control hierarchy |
| topic | morphological computation control hierarchy arm motor control muscles preflexes |
| url | https://www.frontiersin.org/articles/10.3389/frobt.2020.511265/full |
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