Chaotic Frequency Scaling in a Coupled Oscillator Model for Free Rhythmic Actions

Author:

Raftery Aaron1,Cusumano Joseph2,Sternad Dagmar1

Affiliation:

1. Department of Kinesiology, Pennsylvania State University, University Park, PA 16802, U.S.A.

2. Department of Engineering Science and Mechanics, Pennsylvania State University, University Park, PA 16802, U.S.A.

Abstract

The question of how best to model rhythmic movements at self-selected amplitude-frequency combinations, and their variability, is a long-standing issue. This study presents a systematic analysis of a coupled oscillator system that has successfully accounted for the experimental result that humans' preferred oscillation frequencies closely correspond to the linear resonance frequencies of the biomechanical limb systems, a phenomenon known as resonance tuning or frequency scaling. The dynamics of the coupled oscillator model is explored by numerical integration in different areas of its parameter space, where a period doubling route to chaotic dynamics is discovered. It is shown that even in the regions of the parameter space with chaotic solutions, the model still effectively scales to the biomechanical oscillator's natural frequency. Hence, there is a solution providing for frequency scaling in the presence of chaotic variability. The implications of these results for interpreting variability as fundamentally stochastic or chaotic are discussed.

Publisher

MIT Press - Journals

Subject

Cognitive Neuroscience,Arts and Humanities (miscellaneous)

Cited by 9 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Preparing to move: Setting initial conditions to simplify interactions with complex objects;PLOS Computational Biology;2021-12-17

2. The primacy of rhythm: how discrete actions merge into a stable rhythmic pattern;Journal of Neurophysiology;2019-02-01

3. Stability and predictability in human control of complex objects;Chaos: An Interdisciplinary Journal of Nonlinear Science;2018-10

4. Dynamic primitives in the control of locomotion;Frontiers in Computational Neuroscience;2013

5. Dynamic primitives of motor behavior;Biological Cybernetics;2012-11-03

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