Postural constraints recruit shorter-timescale processes into the non-Gaussian cascade processes

NEUROSCIENCE LETTERS

卷:741

Article

Furmanek, Mariusz P.^1,2  Mangalam, Madhur¹  Kelty-Stephen, Damian G.³  Juras, Grzegorz² 

[1] Northeastern Univ, Dept Phys Therapy Movement & Rehabil Sci, Boston, MA 02115 USA

[2] Jerzy Kukuczka Acad Phys Educ, Inst Sport Sci, PL-40065 Katowice, Poland

[3] Grinnell Coll, Dept Psychol, Grinnell, IA 50112 USA

关键词: Center of pressure;    Inverse power law;    Postural control;    Quite stance;    Scale invariance;   

DOI  :  10.1016/j.neulet.2020.135508

来源: Elsevier

【 摘 要 】

Healthy human postural sway exhibits strong intermittency, reflecting a richly interactive foundation of postural control. From a linear perspective, intermittent fluctuations might be interpreted as engagement and disengagement of complementary control processes at distinct timescales or from a nonlinear perspective, as cascadelike interactions across many timescales at once. The diverse control processes entailed by cascade-like multiplicative dynamics suggest specific non-Gaussian distributional properties at different timescales. Multiscale probability density function (PDF) analysis showed that when standing quietly while balancing a sand-filled tube with the two arms elicited non-Gaussianity profiles showing a negative-quadratic crossover between short and long timescales. A more stringent task of balancing a water-filled tube elicited simpler monotonic decreases in non-Gaussianity, that is, a positive-quadratic cancellation of the negative-quadratic crossover. Multiple known indices of postural sway governed the appearance or disappearance of the crossover. Finally, both tasks elicited lognormal distributions over progressively larger timescales. These results provide the first evidence that more stringent postural constraints recruit shorter-timescale processes into the non-Gaussian cascade processes, that indices of postural sway moderate this recruitment, and that more stringent postural constraints show stronger statistical hallmarks of cascade structure.

【 授权许可】

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