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Towards more biologically plausible central-pattern-generator models.

V Baruzzi¹, M Lodi¹, M Storace¹

¹Department of Electrical, Electronics and Telecommunication Engineering and Naval Architecture, University of Genoa, 16145 Genoa, Italy.

Physical Review. E

|January 15, 2022

Summary

This study introduces a new method for designing central pattern generator (CPG) models. The method uses synaptic plasticity to enable biologically plausible gait transitions in quadruped locomotion simulations.

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Area of Science:

Neuroscience
Robotics
Computational Biology

Background:

Central pattern generators (CPGs) are neural networks crucial for rhythmic motor activities like locomotion.
Understanding CPGs is key to developing bio-inspired robots and prosthetic devices.
Existing CPG models often struggle with dynamic gait transitions.

Purpose of the Study:

To develop a systematic method for designing CPG models.
To enable biologically plausible gait transitions using short-term synaptic plasticity.
To validate the method using a quadruped locomotion model.

Main Methods:

A novel method for CPG model design was defined.
Short-term synaptic plasticity mechanisms were implemented.
A CPG model for quadruped locomotion was created and tested.

Main Results:

The designed CPG model successfully reproduced three out of four standard quadruped gaits.
Gait reproduction accuracy extended to limb sequence, frequency, duty cycle, and phase lags.
The model demonstrated biologically plausible gait transitions.

Conclusions:

The proposed method effectively designs CPGs capable of realistic gait transitions.
Short-term synaptic plasticity is a viable mechanism for achieving dynamic locomotion control in CPGs.
This approach advances the development of sophisticated bio-inspired locomotion systems.