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From spontaneous motor activity to coordinated behaviour: a developmental model.

Marques HG, Bharadwaj A, Iida F - PLoS Comput. Biol. (2014)

Bottom Line: Our model is tested in a simulated musculoskeletal leg actuated by six muscles arranged in a number of different ways.Hopping is used as a case study of coordinated behaviour.In addition, our results show that our model can naturally adapt to different morphological changes and perform behavioural transitions.

View Article: PubMed Central - PubMed

Affiliation: Dept. of Mechanical and Process Engineering, ETH, Zurich, Switzerland.

ABSTRACT
In mammals, the developmental path that links the primary behaviours observed during foetal stages to the full fledged behaviours observed in adults is still beyond our understanding. Often theories of motor control try to deal with the process of incremental learning in an abstract and modular way without establishing any correspondence with the mammalian developmental stages. In this paper, we propose a computational model that links three distinct behaviours which appear at three different stages of development. In order of appearance, these behaviours are: spontaneous motor activity (SMA), reflexes, and coordinated behaviours, such as locomotion. The goal of our model is to address in silico four hypotheses that are currently hard to verify in vivo: First, the hypothesis that spinal reflex circuits can be self-organized from the sensor and motor activity induced by SMA. Second, the hypothesis that supraspinal systems can modulate reflex circuits to achieve coordinated behaviour. Third, the hypothesis that, since SMA is observed in an organism throughout its entire lifetime, it provides a mechanism suitable to maintain the reflex circuits aligned with the musculoskeletal system, and thus adapt to changes in body morphology. And fourth, the hypothesis that by changing the modulation of the reflex circuits over time, one can switch between different coordinated behaviours. Our model is tested in a simulated musculoskeletal leg actuated by six muscles arranged in a number of different ways. Hopping is used as a case study of coordinated behaviour. Our results show that reflex circuits can be self-organized from SMA, and that, once these circuits are in place, they can be modulated to achieve coordinated behaviour. In addition, our results show that our model can naturally adapt to different morphological changes and perform behavioural transitions.

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The default musculoskeletal model used in our experiments.a) The leg model comprises six muscles, the iliacus (), the rectus femoris (), the vastus intermedius (), the gluteus maximus (), the long biceps (), and the short biceps ();  and  represent the height of the end-effector and the ground respectively, and  represents the height of the hip.  and  show the centers of mass of the pelvis, femur and tibia, respectively.  and  are the lengths of the femur and the tibia, respectively; the centers of mass of these bodies are located in the geometrical center of the body. b) The 3-element muscle model used; it consists of a spring () and a damper () in parallel to the contractile element ().
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pcbi-1003653-g003: The default musculoskeletal model used in our experiments.a) The leg model comprises six muscles, the iliacus (), the rectus femoris (), the vastus intermedius (), the gluteus maximus (), the long biceps (), and the short biceps (); and represent the height of the end-effector and the ground respectively, and represents the height of the hip. and show the centers of mass of the pelvis, femur and tibia, respectively. and are the lengths of the femur and the tibia, respectively; the centers of mass of these bodies are located in the geometrical center of the body. b) The 3-element muscle model used; it consists of a spring () and a damper () in parallel to the contractile element ().

Mentions: The musculoskeletal system consists of a leg model comprising three rigid segments: pelvis, femur and tibia (see Figure 3a). The model is implemented in MATLAB SimMechanics and visualized using the 3D Animation Toolbox (also from MATLAB). The system is actuated primarily by six muscles, but in one of the experiments we use a four-muscle configuration (see Results). The masses of the rigid segments are set to the lengths of the femur, and tibia are set to which is their approximate length in a human with [31] p.302. The hip and knee joints are simulated as revolute joints. An additional joint is added to the hip in order to restrict the movement of the pelvis to a vertical motion. This joint also prevents the rotation of the pelvis. We call this prismatic constraint, the hopping axis (see Figure3a). It is worth mentioning that our model is intrinsically a 3D model, in the sense that every point in it (e.g. the joint locations as well as the attachment points of the muscles) is defined by three coordinates. However, in practice, given that the hip and knee joints are both hinge joints aligned along a single plane, the motions of all the rigid bodies are restricted to 2D movements.


From spontaneous motor activity to coordinated behaviour: a developmental model.

Marques HG, Bharadwaj A, Iida F - PLoS Comput. Biol. (2014)

The default musculoskeletal model used in our experiments.a) The leg model comprises six muscles, the iliacus (), the rectus femoris (), the vastus intermedius (), the gluteus maximus (), the long biceps (), and the short biceps ();  and  represent the height of the end-effector and the ground respectively, and  represents the height of the hip.  and  show the centers of mass of the pelvis, femur and tibia, respectively.  and  are the lengths of the femur and the tibia, respectively; the centers of mass of these bodies are located in the geometrical center of the body. b) The 3-element muscle model used; it consists of a spring () and a damper () in parallel to the contractile element ().
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4109855&req=5

pcbi-1003653-g003: The default musculoskeletal model used in our experiments.a) The leg model comprises six muscles, the iliacus (), the rectus femoris (), the vastus intermedius (), the gluteus maximus (), the long biceps (), and the short biceps (); and represent the height of the end-effector and the ground respectively, and represents the height of the hip. and show the centers of mass of the pelvis, femur and tibia, respectively. and are the lengths of the femur and the tibia, respectively; the centers of mass of these bodies are located in the geometrical center of the body. b) The 3-element muscle model used; it consists of a spring () and a damper () in parallel to the contractile element ().
Mentions: The musculoskeletal system consists of a leg model comprising three rigid segments: pelvis, femur and tibia (see Figure 3a). The model is implemented in MATLAB SimMechanics and visualized using the 3D Animation Toolbox (also from MATLAB). The system is actuated primarily by six muscles, but in one of the experiments we use a four-muscle configuration (see Results). The masses of the rigid segments are set to the lengths of the femur, and tibia are set to which is their approximate length in a human with [31] p.302. The hip and knee joints are simulated as revolute joints. An additional joint is added to the hip in order to restrict the movement of the pelvis to a vertical motion. This joint also prevents the rotation of the pelvis. We call this prismatic constraint, the hopping axis (see Figure3a). It is worth mentioning that our model is intrinsically a 3D model, in the sense that every point in it (e.g. the joint locations as well as the attachment points of the muscles) is defined by three coordinates. However, in practice, given that the hip and knee joints are both hinge joints aligned along a single plane, the motions of all the rigid bodies are restricted to 2D movements.

Bottom Line: Our model is tested in a simulated musculoskeletal leg actuated by six muscles arranged in a number of different ways.Hopping is used as a case study of coordinated behaviour.In addition, our results show that our model can naturally adapt to different morphological changes and perform behavioural transitions.

View Article: PubMed Central - PubMed

Affiliation: Dept. of Mechanical and Process Engineering, ETH, Zurich, Switzerland.

ABSTRACT
In mammals, the developmental path that links the primary behaviours observed during foetal stages to the full fledged behaviours observed in adults is still beyond our understanding. Often theories of motor control try to deal with the process of incremental learning in an abstract and modular way without establishing any correspondence with the mammalian developmental stages. In this paper, we propose a computational model that links three distinct behaviours which appear at three different stages of development. In order of appearance, these behaviours are: spontaneous motor activity (SMA), reflexes, and coordinated behaviours, such as locomotion. The goal of our model is to address in silico four hypotheses that are currently hard to verify in vivo: First, the hypothesis that spinal reflex circuits can be self-organized from the sensor and motor activity induced by SMA. Second, the hypothesis that supraspinal systems can modulate reflex circuits to achieve coordinated behaviour. Third, the hypothesis that, since SMA is observed in an organism throughout its entire lifetime, it provides a mechanism suitable to maintain the reflex circuits aligned with the musculoskeletal system, and thus adapt to changes in body morphology. And fourth, the hypothesis that by changing the modulation of the reflex circuits over time, one can switch between different coordinated behaviours. Our model is tested in a simulated musculoskeletal leg actuated by six muscles arranged in a number of different ways. Hopping is used as a case study of coordinated behaviour. Our results show that reflex circuits can be self-organized from SMA, and that, once these circuits are in place, they can be modulated to achieve coordinated behaviour. In addition, our results show that our model can naturally adapt to different morphological changes and perform behavioural transitions.

Show MeSH