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Updated: Jun 24, 2025

An Experimental Platform to Study the Closed-loop Performance of Brain-machine Interfaces

An Experimental Platform to Study the Closed-loop Performance of Brain-machine Interfaces

Published on: March 10, 2011

Phase autoencoder for limit-cycle oscillators.

Koichiro Yawata¹, Kai Fukami², Kunihiko Taira²

¹Department of Systems and Control Engineering, Tokyo Institute of Technology, Tokyo 152-8552, Japan.

Chaos (Woodbury, N.Y.)

|June 3, 2024

Summary

This summary is machine-generated.

We developed a phase autoencoder to estimate oscillator phase and sensitivity from time-series data. This method enables model-free analysis and synchronization of limit-cycle oscillators.

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Area of Science:

Nonlinear dynamics
Dynamical systems theory
Computational neuroscience

Background:

Limit-cycle oscillators are fundamental to understanding synchronization in various systems.
Characterizing oscillator dynamics often requires detailed mathematical models.
Estimating asymptotic phase and phase sensitivity from data is challenging.

Purpose of the Study:

To introduce a novel phase autoencoder for encoding asymptotic phase.
To enable model-free estimation of oscillator properties like phase and sensitivity.
To demonstrate a method for synchronizing oscillators using the autoencoder.

Main Methods:

Training a phase autoencoder to map time-series data to latent phase variables.
Utilizing the trained autoencoder for phase and phase sensitivity function estimation.
Reconstructing oscillator states from learned phase representations.

Main Results:

The phase autoencoder successfully encodes the asymptotic phase of limit-cycle oscillators.
Accurate estimation of asymptotic phase and phase sensitivity from time-series data.
Successful reconstruction of oscillator states from phase information.
Demonstration of a novel, simple method for global oscillator synchronization.

Conclusions:

Phase autoencoders offer a powerful, model-free approach to analyze oscillator dynamics.
This method simplifies the estimation of critical parameters like phase and sensitivity.
The autoencoder provides a practical tool for controlling and synchronizing oscillatory systems.