Multifractal fluctuations in joint angles during infant spontaneous kicking reveal multiplicativity-driven coordination
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Newman_Multifractal fluctuations.pdf
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2.26 MB
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Author(s)
Stephen, Damian G.
Hsu, Wen-Hao
Young, Diana
Saltzman, Elliot L.
Holt, Kenneth G.
Wood, Robert J.
Nagpal, Radhika
Goldfield, Eugene C.
Newman, Dava J
Weinberg, Marc
Date Issued
September 2012
Journal
Chaos, Solitons & Fractals
Publisher
Elsevier
Citation
Stephen, Damian G. et al. “Multifractal Fluctuations in Joint Angles during Infant Spontaneous Kicking Reveal Multiplicativity-Driven Coordination.” Chaos, Solitons & Fractals 45.9–10 (2012): 1201–1219.
Version
Original manuscript
Abstract
Previous research has considered infant spontaneous kicking as a form of exploration. According to this view, spontaneous kicking provides information about motor degrees of freedom and may shape multijoint coordinations for more complex movement patterns such as gait. Recent work has demonstrated that multifractal, multiplicative fluctuations in exploratory movements index energy flows underlying perceptual-motor information. If infant spontaneous kicking is exploratory and occasions an upstream flow of information from the motor periphery, we expected not only that multiplicativity of fluctuations at the hip should promote multiplicativity of fluctuations at more distal joints (i.e., reflecting downstream effects of neural control) but also that multiplicativity at more distal joints should promote multiplicativity at the hip. Multifractal analysis demonstrated that infant spontaneous kicking in four typically developing infants for evidence of multiplicative fluctuations in multiple joint angles along the leg (i.e., hip, knee, and ankle) exhibited multiplicativity. Vector autoregressive modeling demonstrated that only one leg exhibited downstream effects but that both legs exhibited upstream effects. These results confirm the exploratory aspect of infant spontaneous kicking and suggest chaotic dynamics in motor coordination. They also resonate with existing models of chaos-controlled robotics and noise-based interventions for rehabilitating motor coordination in atypically developing patients.
MIT Department
Charles Stark Draper Laboratory
Massachusetts Institute of Technology. Department of Aeronautics and Astronautics
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Creative Commons Attribution-NonCommercial-NoDerivs License
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DOI of Published Version
https://doi.org/10.1016/j.chaos.2012.06.005
