Document Detail


Identification of the nonlinear state-space dynamics of the action-perception cycle for visually induced postural sway.
MedLine Citation:
PMID:  8991458     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
Human subjects standing in a sinusoidally moving visual environment display postural sway with characteristic dynamical properties. We analyzed the spatiotemporal properties of this sway in an experiment in which the frequency of the visual motion was varied. We found a constant gain near 1, which implies that the sway motion matches the spatial parameters of the visual motion for a large range of frequencies. A linear dynamical model with constant parameters was compared quantitatively with the data. Its failure to describe correctly the spatiotemporal properties of the system led us to consider adaptive and nonlinear models. To differentiate between possible alternative structures we directly fitted nonlinear differential equations to the sway and visual motion trajectories on a trial-by-trial basis. We found that the eigenfrequency of the fitted model adapts strongly to the visual motion frequency. The damping coefficient decreases with increasing frequency. This indicates that the system destabilizes its postural state in the inertial frame. This leads to a faster internal dynamics which is capable of synchronizing posture with fast-moving visual environments. Using an algorithm which allows the identification of essentially nonlinear terms of the dynamics we found small nonlinear contributions. These nonlinearities are not consistent with a limit-cycle dynamics, accounting for the robustness of the amplitude of postural sway against frequency variations. We interpret out results in terms of active generation of postural sway specified by sensory information. We derive also a number of conclusions for a behavior-oriented analysis of the postural system.
Authors:
M A Giese; T M Dijkstra; G Schöner; C C Gielen
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Publication Detail:
Type:  Journal Article; Research Support, Non-U.S. Gov't    
Journal Detail:
Title:  Biological cybernetics     Volume:  74     ISSN:  0340-1200     ISO Abbreviation:  Biol Cybern     Publication Date:  1996 May 
Date Detail:
Created Date:  1997-01-13     Completed Date:  1997-01-13     Revised Date:  2006-11-15    
Medline Journal Info:
Nlm Unique ID:  7502533     Medline TA:  Biol Cybern     Country:  GERMANY    
Other Details:
Languages:  eng     Pagination:  427-37     Citation Subset:  IM; S    
Affiliation:
Institut für Neuroinformatik, Ruhr-Universität Bochum, Germany.
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MeSH Terms
Descriptor/Qualifier:
Humans
Models, Biological
Motion
Nonlinear Dynamics*
Posture / physiology*
Spatial Behavior / physiology*
Visual Perception / physiology*

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