AI Article Synopsis
- The central pattern generator (CPG) is a group of neurons that acts as a nonlinear oscillator, controlling rhythmic movements in animals.
- The study explores how the structure and strength of connections between identical neurons in a CPG influence its oscillation characteristics, like frequency and amplitude, through a concept called multivariable harmonic balance.
- A method is introduced for designing CPGs to create specific oscillation profiles, utilizing the relationship between eigenvalues and eigenvectors to predict and control the desired outcomes.
Article Abstract
The central pattern generator (CPG) is a nonlinear oscillator formed by a group of neurons, providing a fundamental control mechanism underlying rhythmic movements in animal locomotion. We consider a class of CPGs modeled by a set of interconnected identical neurons. Based on the idea of multivariable harmonic balance, we show how the oscillation profile is related to the connectivity matrix that specifies the architecture and strengths of the interconnections. Specifically, the frequency, amplitudes, and phases are essentially encoded in terms of a pair of eigenvalue and eigenvector. This basic principle is used to estimate the oscillation profile of a given CPG model. Moreover, a systematic method is proposed for designing a CPG-based nonlinear oscillator that achieves a prescribed oscillation profile.
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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2712753 | PMC |
| http://dx.doi.org/10.1016/j.automatica.2008.05.024 | DOI Listing |
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