Failure of Arm Movement Control in Stroke Patients, Characterized by Loss of Complexity

We study the mechanism of human arm-posture control by means of nonlinear dynamics and quantitative time series analysis methods. Utilizing linear and nonlinear measures in combination, we find that pathological tremors emerge in patient dynamics and serve as a main feature discriminating between normal and patient groups. The deterministic structure accompanied with loss of complexity inherent in the tremor dynamics is also revealed. To probe the underlying mechanism of the arm-posture dynamics, we further analyze the coupling patterns between joints and components, and discuss their roles in breaking of the organization structure. As a result, we elucidate the mechanisms in the arm-posture dynamics of normal subjects responding to the gravitational force and for the reduction of the dynamic degrees of freedom in the patient dynamics. This study provides an integrated framework for the origin of the loss of complexity in the dynamics of patients as well as the coupling structure in the arm-posture dynamics.

[1]  Yanqing Chen,et al.  Long Memory Processes ( 1 / f α Type) in Human Coordination , 1997 .

[2]  Tim Kiemel,et al.  Control and estimation of posture during quiet stance depends on multijoint coordination. , 2007, Journal of neurophysiology.

[3]  L. Faes,et al.  Quantifying the contribution of arm postural tremor to the outcome of goal-directed pointing task by displacement measures , 2004, Journal of Neuroscience Methods.

[4]  R. C. Harwell,et al.  Physiologic tremor and microsurgery , 1983, Microsurgery.

[5]  T. Flash,et al.  The coordination of arm movements: an experimentally confirmed mathematical model , 1985, The Journal of neuroscience : the official journal of the Society for Neuroscience.

[6]  Karl M Newell,et al.  The dynamics of resting and postural tremor in Parkinson's disease , 2000, Clinical Neurophysiology.

[7]  Jeffrey M. Hausdorff,et al.  Fluctuation and synchronization of gait intervals and gait force profiles distinguish stages of Parkinson's disease. , 2007, Physica A.

[8]  Michael Schanz,et al.  A theoretical model of sinusoidal forearm tracking with delayed visual feedback , 1995 .

[9]  Danilo P Mandic,et al.  Multivariate multiscale entropy: a tool for complexity analysis of multichannel data. , 2011, Physical review. E, Statistical, nonlinear, and soft matter physics.

[10]  J. Richman,et al.  Physiological time-series analysis using approximate entropy and sample entropy. , 2000, American journal of physiology. Heart and circulatory physiology.

[11]  John G Milton,et al.  On-off intermittency in a human balancing task. , 2002, Physical review letters.

[12]  J. A. Stewart,et al.  Nonlinear Time Series Analysis , 2015 .

[13]  D. Ruelle,et al.  Fundamental limitations for estimating dimensions and Lyapunov exponents in dynamical systems , 1992 .

[14]  N. Stergiou,et al.  Human movement variability, nonlinear dynamics, and pathology: is there a connection? , 2011, Human movement science.

[15]  Theiler,et al.  Spurious dimension from correlation algorithms applied to limited time-series data. , 1986, Physical review. A, General physics.

[16]  Zhongke Gao,et al.  A directed weighted complex network for characterizing chaotic dynamics from time series , 2012 .

[17]  P. Morasso Spatial control of arm movements , 2004, Experimental Brain Research.

[18]  Zhong-Ke Gao,et al.  Multi-frequency complex network from time series for uncovering oil-water flow structure , 2015, Scientific Reports.

[19]  C. Essex,et al.  Delayed stochastic differential model for quiet standing. , 2001, Physical review. E, Statistical, nonlinear, and soft matter physics.

[20]  C. Stam,et al.  Nonlinear dynamical analysis of EEG and MEG: Review of an emerging field , 2005, Clinical Neurophysiology.

[21]  O. Bock Load compensation in human goal-directed arm movements , 1990, Behavioural Brain Research.

[22]  P. F. Meier,et al.  Dimensional complexity and spectral properties of the human sleep EEG , 2003, Clinical Neurophysiology.

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

[24]  Anil K. Seth,et al.  The MVGC multivariate Granger causality toolbox: A new approach to Granger-causal inference , 2014, Journal of Neuroscience Methods.

[25]  Zhong-Ke Gao,et al.  Multiscale complex network for analyzing experimental multivariate time series , 2015 .

[26]  G. Crooks On Measures of Entropy and Information , 2015 .

[27]  Akira Hirose,et al.  Influence of Neural Delay in Sensorimotor Systems on the Control Performance and Mechanism in Bicycle Riding , 2007, ICONIP.

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

[29]  C. Granger Investigating causal relations by econometric models and cross-spectral methods , 1969 .

[30]  Zhong-Ke Gao,et al.  Multivariate weighted complex network analysis for characterizing nonlinear dynamic behavior in two-phase flow , 2015 .

[31]  J. Collins,et al.  Random walking during quiet standing. , 1994, Physical review letters.

[32]  P. Grassberger,et al.  Measuring the Strangeness of Strange Attractors , 1983 .

[33]  M. Kawato,et al.  Formation and control of optimal trajectory in human multijoint arm movement , 1989, Biological Cybernetics.

[34]  Madalena Costa,et al.  Multiscale entropy analysis of complex physiologic time series. , 2002, Physical review letters.

[35]  Schreiber,et al.  Improved Surrogate Data for Nonlinearity Tests. , 1996, Physical review letters.

[36]  Martin Lakie,et al.  The influence of muscle tremor on shooting performance , 2010, Experimental physiology.

[37]  P. Grassberger,et al.  Estimation of the Kolmogorov entropy from a chaotic signal , 1983 .

[38]  C. Marsden,et al.  Physiological and pathological tremors and rhythmic central motor control. , 2000, Brain : a journal of neurology.

[39]  Charles S. Layne,et al.  Dimensionality in rhythmic bimanual coordination. , 2013, Human movement science.

[40]  J. Côté,et al.  Effects of additional external weight on posture and movement adaptations to fatigue induced by a repetitive pointing task. , 2014, Human movement science.

[41]  James Theiler,et al.  Testing for nonlinearity in time series: the method of surrogate data , 1992 .

[42]  R. Elble Central mechanisms of tremor. , 1996, Journal of clinical neurophysiology : official publication of the American Electroencephalographic Society.

[43]  D. Winter,et al.  Stiffness control of balance in quiet standing. , 1998, Journal of neurophysiology.

[44]  Klaus Pawelzik,et al.  Criticality of adaptive control dynamics. , 2011, Physical review letters.

[45]  Yasuyuki Suzuki,et al.  Intermittent control with ankle, hip, and mixed strategies during quiet standing: a theoretical proposal based on a double inverted pendulum model. , 2012, Journal of theoretical biology.

[46]  G. Kerr,et al.  Bilateral tremor relations in Parkinson's disease: effects of mechanical coupling and medication. , 2008, Parkinsonism & related disorders.

[47]  J. Milton,et al.  Noise-induced transitions in human postural sway. , 1996, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics.

[48]  Nicholas Stergiou,et al.  A Nonlinear Dynamic Approach for Evaluating Postural Control , 2005, Sports medicine.

[49]  F. Takens Detecting strange attractors in turbulence , 1981 .