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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 hip trajectory and the mean and standard deviation of the kinematic and dynamic variables obtained for the default leg model.Kinematic and dynamic variables obtained for the system with a) an appropriate set of gains, and b) an inappropriate set of gains. S refers to the stance phase (when the end effector is in touch with the ground) and F refers to the flight phase (when the end effector is in the air). In b, because each hop has a different duration, the data relative to each hop has been linearly interpolated to match the durations across different hops. Note that in this plot the time indicated for the stance-to-flight transition is only relative to the first hop. In subsequent hops, and because they progressively decrease in duration, this transition occurs earlier than illustrated by the marker. The hip trajectory recorded for the system with c) an appropriate set of gains, and d) an inappropriate set of gains.
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pcbi-1003653-g006: The hip trajectory and the mean and standard deviation of the kinematic and dynamic variables obtained for the default leg model.Kinematic and dynamic variables obtained for the system with a) an appropriate set of gains, and b) an inappropriate set of gains. S refers to the stance phase (when the end effector is in touch with the ground) and F refers to the flight phase (when the end effector is in the air). In b, because each hop has a different duration, the data relative to each hop has been linearly interpolated to match the durations across different hops. Note that in this plot the time indicated for the stance-to-flight transition is only relative to the first hop. In subsequent hops, and because they progressively decrease in duration, this transition occurs earlier than illustrated by the marker. The hip trajectory recorded for the system with c) an appropriate set of gains, and d) an inappropriate set of gains.

Mentions: Figure 6a shows the mean and five times the standard deviation of the main kinematic and dynamic variables collected after hops carried out with an appropriate set of gains (see also Movie S1.IV). These variables are the muscle forces, the hip and knee angles and the ground force (see Figure S2 for similar results achieved using the reflex circuits obtained with a twitching amplitude of ). All the variables have been aligned with respect to initial contact with the ground (). As can be seen, the standard deviation of each parameter is relatively low, demonstrating that the hopping pattern is stable (). We can also see that the hopping height is conserved as indicated by the low value of (Figure 6c).


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

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

The hip trajectory and the mean and standard deviation of the kinematic and dynamic variables obtained for the default leg model.Kinematic and dynamic variables obtained for the system with a) an appropriate set of gains, and b) an inappropriate set of gains. S refers to the stance phase (when the end effector is in touch with the ground) and F refers to the flight phase (when the end effector is in the air). In b, because each hop has a different duration, the data relative to each hop has been linearly interpolated to match the durations across different hops. Note that in this plot the time indicated for the stance-to-flight transition is only relative to the first hop. In subsequent hops, and because they progressively decrease in duration, this transition occurs earlier than illustrated by the marker. The hip trajectory recorded for the system with c) an appropriate set of gains, and d) an inappropriate set of gains.
© Copyright Policy
Related In: Results  -  Collection

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

pcbi-1003653-g006: The hip trajectory and the mean and standard deviation of the kinematic and dynamic variables obtained for the default leg model.Kinematic and dynamic variables obtained for the system with a) an appropriate set of gains, and b) an inappropriate set of gains. S refers to the stance phase (when the end effector is in touch with the ground) and F refers to the flight phase (when the end effector is in the air). In b, because each hop has a different duration, the data relative to each hop has been linearly interpolated to match the durations across different hops. Note that in this plot the time indicated for the stance-to-flight transition is only relative to the first hop. In subsequent hops, and because they progressively decrease in duration, this transition occurs earlier than illustrated by the marker. The hip trajectory recorded for the system with c) an appropriate set of gains, and d) an inappropriate set of gains.
Mentions: Figure 6a shows the mean and five times the standard deviation of the main kinematic and dynamic variables collected after hops carried out with an appropriate set of gains (see also Movie S1.IV). These variables are the muscle forces, the hip and knee angles and the ground force (see Figure S2 for similar results achieved using the reflex circuits obtained with a twitching amplitude of ). All the variables have been aligned with respect to initial contact with the ground (). As can be seen, the standard deviation of each parameter is relatively low, demonstrating that the hopping pattern is stable (). We can also see that the hopping height is conserved as indicated by the low value of (Figure 6c).

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