Emergent dynamics in a robotic model based on the Caenorhabditis elegans connectome.

ABSTRACT: 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

SUBMITTER: Valencia Urbina CE 

PROVIDER: S-EPMC9868850 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature