Nonlinear dynamics of an oscilattory neural network acting as a motor central pettern generator
In vertebrates, the central nervous system processes sensorial input from surroundings and in most of the cases determines motor responses accordingly. There exist specialized synaptic circuits or neural networks for generating and maintaining periodic motor signals necessary for the animal’s locomo...
- Autores:
-
Hurtado López, Julián
Ramirez-Moreno, David Fernando
- Tipo de recurso:
- Article of journal
- Fecha de publicación:
- 2013
- Institución:
- Universidad Autónoma de Occidente
- Repositorio:
- RED: Repositorio Educativo Digital UAO
- Idioma:
- eng
- OAI Identifier:
- oai:red.uao.edu.co:10614/14205
- Acceso en línea:
- https://hdl.handle.net/10614/14205
https://red.uao.edu.co/
- Palabra clave:
- Redes neuronales (Computadores)
Neural networks
Dynamical system analysis
Nonlinear dynamics
Hopf bifurcation
Branch point bifurcation
Central pattern generator
- Rights
- openAccess
- License
- Derechos reservados - World Scientific Publishing Company, 2013
| Summary: | In vertebrates, the central nervous system processes sensorial input from surroundings and in most of the cases determines motor responses accordingly. There exist specialized synaptic circuits or neural networks for generating and maintaining periodic motor signals necessary for the animal’s locomotion as walking, trotting, running or swimming. Recent works have addressed the study of animal locomotion by modeling the neural networks in charge of controlling the rhythmic movements of legs and motor appendices in bipeds, quadrupeds and hexapods [Kiehn et al., 2008]. These works have been extended to modeling and controlling the movements of legged robots [Teng et al., 2012; Mondal et al., 2011]. These synaptic circuits and neural networks or central pattern generators (CPG) [McCrea & Rybak, 2008] exhibit a nonlinear dynamics leading to nonlinear oscillations. |
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