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      Regularity of center-of-pressure trajectories depends on the amount of attention invested in postural control

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          Abstract

          The influence of attention on the dynamical structure of postural sway was examined in 30 healthy young adults by manipulating the focus of attention. In line with the proposed direct relation between the amount of attention invested in postural control and regularity of center-of-pressure (COP) time series, we hypothesized that: (1) increasing cognitive involvement in postural control (i.e., creating an internal focus by increasing task difficulty through visual deprivation) increases COP regularity, and (2) withdrawing attention from postural control (i.e., creating an external focus by performing a cognitive dual task) decreases COP regularity. We quantified COP dynamics in terms of sample entropy (regularity), standard deviation (variability), sway-path length of the normalized posturogram (curviness), largest Lyapunov exponent (local stability), correlation dimension (dimensionality) and scaling exponent (scaling behavior). Consistent with hypothesis 1, standing with eyes closed significantly increased COP regularity. Furthermore, variability increased and local stability decreased, implying ineffective postural control. Conversely, and in line with hypothesis 2, performing a cognitive dual task while standing with eyes closed led to greater irregularity and smaller variability, suggesting an increase in the “efficiency, or “automaticity” of postural control”. In conclusion, these findings not only indicate that regularity of COP trajectories is positively related to the amount of attention invested in postural control, but also substantiate that in certain situations an increased internal focus may in fact be detrimental to postural control.

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          Approximate entropy as a measure of system complexity.

          Techniques to determine changing system complexity from data are evaluated. Convergence of a frequently used correlation dimension algorithm to a finite value does not necessarily imply an underlying deterministic model or chaos. Analysis of a recently developed family of formulas and statistics, approximate entropy (ApEn), suggests that ApEn can classify complex systems, given at least 1000 data values in diverse settings that include both deterministic chaotic and stochastic processes. The capability to discern changing complexity from such a relatively small amount of data holds promise for applications of ApEn in a variety of contexts.
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            Characterization of Strange Attractors

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              Testing for nonlinearity in time series: the method of surrogate data

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                Author and article information

                Contributors
                +31-20-5988532 , +31-20-5988529 , p.beek@fbw.vu.nl
                Journal
                Exp Brain Res
                Experimental Brain Research. Experimentelle Hirnforschung. Experimentation Cerebrale
                Springer-Verlag (Berlin/Heidelberg )
                0014-4819
                1432-1106
                31 March 2007
                July 2007
                : 181
                : 1
                : 1-11
                Affiliations
                [1 ]Faculty of Human Movement Sciences, VU University, Research Institute MOVE, Van der Boechorststraat 9, 1081 BT Amsterdam, The Netherlands
                [2 ]Department of Otorhinolaryngology, VU University Medical Center, Amsterdam, The Netherlands
                Article
                905
                10.1007/s00221-007-0905-4
                1914290
                17401553
                06f17138-9ede-499d-a488-d1ed6d0a9abe
                © Springer-Verlag 2007
                History
                : 10 August 2006
                : 2 February 2007
                Categories
                Research Article
                Custom metadata
                © Springer-Verlag 2007

                Neurosciences
                postural control,attention,center-of-pressure,regularity
                Neurosciences
                postural control, attention, center-of-pressure, regularity

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