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

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.

[1]  J. Dingwell,et al.  Nonlinear time series analysis of normal and pathological human walking. , 2000, Chaos.

[2]  M. Turvey,et al.  Variability and Determinism in Motor Behavior , 2002, Journal of motor behavior.

[3]  J. Thompson,et al.  Nonlinear Dynamics and Chaos: Geometrical Methods for Engineers and Scientists , 1986 .

[4]  M. Turvey,et al.  Interlimb coupling in a simple serial behavior: A task dynamic approach , 1998 .

[5]  W. Warren,et al.  Resonance Tuning in Rhythmic Arm Movements. , 1996, Journal of motor behavior.

[6]  D Sternad,et al.  Dynamics of a bouncing ball in human performance. , 2000, Physical review. E, Statistical, nonlinear, and soft matter physics.

[7]  E. Saltzman,et al.  Space-time behavior of single and bimanual rhythmical movements: data and limit cycle model. , 1987 .

[8]  Peter J. Beek,et al.  Tools for constructing dynamical models of rhythmic movement , 1988 .

[9]  J. Hamill,et al.  The force-driven harmonic oscillator as a model for human locomotion , 1990 .

[10]  E. W. Scripture OBSERVATIONS ON RHYTHMIC ACTION. , 1899, Science.

[11]  M. E. Demont,et al.  Tuned oscillations in the swimming scallop Pecten maximus , 1990 .

[12]  Dagmar Sternad,et al.  Moving the Arm at Different Rates: Slow Movements are Avoided , 2009, Journal of motor behavior.

[13]  J. Hamill,et al.  Energetic Cost and Stability during Human Walking at the Preferred Stride Frequency , 1995 .

[14]  H. Haken,et al.  A stochastic theory of phase transitions in human hand movement , 1986, Biological Cybernetics.

[15]  Matthew M. Williamson,et al.  Neural control of rhythmic arm movements , 1998, Neural Networks.

[16]  Holger Kantz,et al.  Practical implementation of nonlinear time series methods: The TISEAN package. , 1998, Chaos.

[17]  C Basdogan,et al.  Presenting joint kinematics of human locomotion using phase plane portraits and Poincaré maps. , 1994, Journal of biomechanics.

[18]  A. Daffertshofer,et al.  Modeling Rhythmic Interlimb Coordination: Beyond the Haken–Kelso–Bunz Model , 2002, Brain and Cognition.

[19]  John M. Gosline,et al.  Mechanics of Jet Propulsion in the Hydromedusan Jellyfish, Polyorchis Penicillatus: II. Energetics of the Jet Cycle , 1988 .

[20]  H. Kantz,et al.  Nonlinear time series analysis , 1997 .

[21]  M. Turvey,et al.  Chaos in Human Rhythmic Movement. , 1997, Journal of motor behavior.

[22]  John M. Gosline,et al.  Mechanics of Jet Propulsion in the Hydromedusan Jellyfish, Polyorchis Pexicillatus: III. A Natural Resonating Bell; The Presence and Importance of a Resonant Phenomenon in the Locomotor Structure , 1988 .

[23]  P. Cvitanović Universality in Chaos , 1989 .

[24]  Philippe Lefèvre,et al.  A Computational Model for Rhythmic and Discrete Movements in Uni- and Bimanual Coordination , 2009, Neural Computation.

[25]  Y. Hurmuzlu,et al.  On the measurement of dynamic stability of human locomotion. , 1994, Journal of biomechanical engineering.

[26]  Nicholas G. Hatsopoulos,et al.  Coupling the Neural and Physical Dynamics in Rhythmic Movements , 1996, Neural Computation.

[27]  Nicole Wenderoth,et al.  Load dependence of simulated central tremor , 1999, Biological Cybernetics.

[28]  D B Marghitu,et al.  Nonlinear dynamics stability measurements of locomotion in healthy greyhounds. , 1996, American journal of veterinary research.

[29]  H. Haken,et al.  A theoretical model of phase transitions in human hand movements , 2004, Biological Cybernetics.

[30]  Dagmar Sternad,et al.  Task-effector asymmetries in a rhythmic continuation task. , 2003, Journal of experimental psychology. Human perception and performance.

[31]  B. Kay,et al.  Infant bouncing: the assembly and tuning of action systems. , 1993, Child development.

[32]  Elliot Saltzman,et al.  Discovery of the Pendulum and Spring Dynamics in the Early Stages of Walking , 2006, Journal of motor behavior.

[33]  M. Turvey,et al.  Advantages of Rhythmic Movements at Resonance: Minimal Active Degrees of Freedom, Minimal Noise, and Maximal Predictability , 2000, Journal of motor behavior.

[34]  H. Abarbanel,et al.  The role of chaos in neural systems , 1998, Neuroscience.

[35]  Emil Simiu Emil Simiu: Chaotic Transitions in Deterministic and Stochastic Dynamical Systems Chapter One , .