Emergent dynamics in a robotic model based on the Caenorhabditis elegans connectome
We analyze the neural dynamics and their relation with the emergent actions of a robotic vehicle that is controlled by a neural network numerical simulation based on the nervous system of the nematode Caenorhabditis elegans. The robot interacts with the environment through a sensor that transmits th...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2023-01-01
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| Series: | Frontiers in Neurorobotics |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fnbot.2022.1041410/full |
| _version_ | 1828068085886615552 |
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| author | Carlos E. Valencia Urbina Sergio A. Cannas Pablo M. Gleiser Pablo M. Gleiser Pablo M. Gleiser |
| author_facet | Carlos E. Valencia Urbina Sergio A. Cannas Pablo M. Gleiser Pablo M. Gleiser Pablo M. Gleiser |
| author_sort | Carlos E. Valencia Urbina |
| collection | DOAJ |
| description | We analyze the neural dynamics and their relation with the emergent actions of a robotic vehicle that is controlled by a neural network numerical simulation based on the nervous system of the nematode Caenorhabditis elegans. The robot interacts with the environment through a sensor that transmits the information to sensory neurons, while motor neurons outputs are connected to wheels. This is enough to allow emergent robot actions in complex environments, such as avoiding collisions with obstacles. Working with robotic models makes it possible to simultaneously keep track of the dynamics of all the neurons and also register the actions of the robot in the environment in real time, while avoiding the complex technicalities of simulating a real environment. This allowed us to identify several relevant features of the neural dynamics associated with the emergent actions of the robot, some of which have already been observed in biological worms. These results suggest that some basic aspects of behaviors observed in living beings are determined by the underlying structure of the associated neural network. |
| first_indexed | 2024-04-10T23:56:22Z |
| format | Article |
| id | doaj.art-1274da00689541e2bbdaec02115859f7 |
| institution | Directory Open Access Journal |
| issn | 1662-5218 |
| language | English |
| last_indexed | 2024-04-10T23:56:22Z |
| publishDate | 2023-01-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Neurorobotics |
| spelling | doaj.art-1274da00689541e2bbdaec02115859f72023-01-10T12:24:21ZengFrontiers Media S.A.Frontiers in Neurorobotics1662-52182023-01-011610.3389/fnbot.2022.10414101041410Emergent dynamics in a robotic model based on the Caenorhabditis elegans connectomeCarlos E. Valencia Urbina0Sergio A. Cannas1Pablo M. Gleiser2Pablo M. Gleiser3Pablo M. Gleiser4Medical Physics Department, Centro Atómico Bariloche, Instituto Balseiro, Universidad Nacional de Cuyo, Río Negro, ArgentinaFacultad de Matemática, Astronomía, Física y Computación, Universidad Nacional de Córdoba, Instituto de Física Enrique Gaviola (IFEG-CONICET), Ciudad Universitaria, Córdoba, ArgentinaMedical Physics Department, Centro Atómico Bariloche, Instituto Balseiro, Universidad Nacional de Cuyo, Río Negro, ArgentinaFacultad de Matemática, Astronomía, Física y Computación, Universidad Nacional de Córdoba, Instituto de Física Enrique Gaviola (IFEG-CONICET), Ciudad Universitaria, Córdoba, ArgentinaLaboratorio de Neurociencia de Sistemas Complejos, Departamento de Ciencias de la Vida, Instituto Tecnològico de Buenos Aires (ITBA), Buenos Aires, ArgentinaWe analyze the neural dynamics and their relation with the emergent actions of a robotic vehicle that is controlled by a neural network numerical simulation based on the nervous system of the nematode Caenorhabditis elegans. The robot interacts with the environment through a sensor that transmits the information to sensory neurons, while motor neurons outputs are connected to wheels. This is enough to allow emergent robot actions in complex environments, such as avoiding collisions with obstacles. Working with robotic models makes it possible to simultaneously keep track of the dynamics of all the neurons and also register the actions of the robot in the environment in real time, while avoiding the complex technicalities of simulating a real environment. This allowed us to identify several relevant features of the neural dynamics associated with the emergent actions of the robot, some of which have already been observed in biological worms. These results suggest that some basic aspects of behaviors observed in living beings are determined by the underlying structure of the associated neural network.https://www.frontiersin.org/articles/10.3389/fnbot.2022.1041410/fullself-organized systemssynchronizationconnectomeC. elegansrobot |
| spellingShingle | Carlos E. Valencia Urbina Sergio A. Cannas Pablo M. Gleiser Pablo M. Gleiser Pablo M. Gleiser Emergent dynamics in a robotic model based on the Caenorhabditis elegans connectome Frontiers in Neurorobotics self-organized systems synchronization connectome C. elegans robot |
| title | Emergent dynamics in a robotic model based on the Caenorhabditis elegans connectome |
| title_full | Emergent dynamics in a robotic model based on the Caenorhabditis elegans connectome |
| title_fullStr | Emergent dynamics in a robotic model based on the Caenorhabditis elegans connectome |
| title_full_unstemmed | Emergent dynamics in a robotic model based on the Caenorhabditis elegans connectome |
| title_short | Emergent dynamics in a robotic model based on the Caenorhabditis elegans connectome |
| title_sort | emergent dynamics in a robotic model based on the caenorhabditis elegans connectome |
| topic | self-organized systems synchronization connectome C. elegans robot |
| url | https://www.frontiersin.org/articles/10.3389/fnbot.2022.1041410/full |
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