Study of real-time biomimetic CPG on FPGA: behavior and evolution

Authors
Timothée Levi, Yanchen Guo, Kazuyuki Aihara, Takashi Kohno
Corresponding Author
Timothée Levi
Available Online 31 March 2018.
DOI
https://doi.org/10.2991/jrnal.2018.4.4.9How to use a DOI?
Keywords
Biomimetic neural network, CPG, FPGA, Silicon neuron
Abstract
Locomotion is one of the most basic abilities in animals. Neurobiologists have established that locomotion results from the activity of half-center oscillators that provides alternation of bursts. Central Pattern Generators (CPGs) are neural networks capable of producing rhythmic patterned outputs without rhythmic sensory or central input. We propose a network of several biomimetic CPGs using biomimetic neuron model and synaptic plasticity. This network is implemented on a FPGA (Field Programmable Gate Array). The network implementation architecture operates on a single computation core and in real-time. The real-time implementation of this CPGs network is validated by comparing it with biological data of leech heartbeat neural network. From these biomimetic CPGs, we use them for robotic applications and also for biomedical research to restore lost synaptic connections.

Copyright
© 2018, the Authors. Published by ALife Robotics Corp. Ltd.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).