Human Movement Science 32 (2013) 877–879
Contents lists available at ScienceDirect
Human Movement Science
Editorial
Tackling the challenges posed by the human dynamic system Why don’t we fall when we trip? Why do we fall more often as we get older? How does back pain become chronic? How do our brain and spine interact when we learn new movements? Until recently, studying such questions tended to culminate a plethora of unconnected theories. Currently, however, new interdisciplinary approaches are being developed to tackle these questions of the human dynamic system, which is intrinsically nonlinear, in a more principled manner. Nonlinear dynamical approaches in the study of human movement allow for a fundamental understanding of the complex phenomena of human behavior, not only with regard to the neural control of movement but also with regard to the mechanical properties of the motor apparatus, in interaction with neural aspects of motor control. Active movements are generated by well-coordinated muscle contractions that are controlled and stabilized by neural circuits. In order to study the sensorimotor system, models need to be developed that allow for the analysis of the mechanical apparatus as well as the central nervous system by using the concepts and methods of dynamical systems theory. One important issue in understanding the human dynamic system is the influence of pain on the motor control system in general. Therefore, the present special issue represents a collaborative effort between the Center for Non-linear Science (CeNoS), Münster, Germany and a ‘‘chronic back pain’’ research network supported by the Federal Ministry of Education and Research (BMBF). The consortium is composed with the aim to cover the entire span of the complex interactions that are involved in chronic back pain. The present special issue is a collection of interdisciplinary approaches aimed at tackling the problems posed by the human dynamic system. The collection ranges from modeling approaches to experimental work, and from high-level brain mechanisms to spinal control. The overarching perspective on the human dynamic system is that the control of human movement is flexible and adaptive; it has to deal with issues such as neuronal and physiological noise, external perturbations, stability, compliance and variability, and that learning and development may be understood in terms of adaptive changes in motor control over shorter and longer time scales. How one can come to terms with the adaptive character of motor control and learning is exemplified by the contributions to this special issue, which – as a prelude – may be introduced as follows. A self-active recurrent neural network for a flexible motor memory Artificial neural networks have promised future success for many decennia, but thus far they have suffered notoriously from slow learning, low flexibility and limited biological and physiological relevance. Computers are immensely more powerful than they used to be only a short time ago. Importantly, however, a new generation of neural networks with so-called reservoir computing has evolved that can learn rapidly and flexibly. Boström et al. explore the flexibility and the interpolation abilities of a physiologically plausible reservoir neural network with a recurrent architecture for motor memory. The study illustrates how the model can flexibly interpolate patterns into new ones and cope with sensory feedback in a dynamic manner. 0167-9457/$ - see front matter Ó 2013 Published by Elsevier B.V. http://dx.doi.org/10.1016/j.humov.2013.11.001
878
Editorial / Human Movement Science 32 (2013) 877–879
Movement variability near goal-equivalent manifolds An unresolved issue in motor control pertains to the relation between the spatiotemporal structure of motor variability and the spatiotemporal structure of required end point accuracy. Cusumano and Dingwell employ a model-based framework to describe the inter-trial fluctuations to characterize end-point error-correcting control for specific motor tasks. Brain activity for visual judgment of lifted weight Human observers are remarkably proficient at judging delicate aspects of visually displayed actions. A case in point is the capability to judge the weight lifted by an actor from an abstract pointlight display. Ritter et al. hypothesized that human observers use their own sensorimotor experience in handling heavy objects to judge the weight lifted by others. If so, observing someone lifting a weight should activate the same centers in the somatosensory and motor regions as when actively performing these actions, which is what the functional imaging (fMRI) data collected demonstrated. Impaired visual perception of hurtful actions in patients with chronic lower back pain An important aspect of high-level motor control is the tight link with other high-level functions like the perception of movements made by others. Chronic back pain is generally accompanied with fear of movement, changes in the sensation of the affected regions and changes in sensorimotor brain structures. De Lussanet et al. examined whether these changes in chronic back pain make that patients are impaired even when judging a weight lifted by others. In a control experiment it was verified that the chronic back pain patients were not impaired in visual judgments or deficits in attention. Influence of delayed muscle reflexes on spinal stability Chronic back pain also has severe influences on the spinal control of movement. Liebetrau et al. combined a numerical computational approach with experimental reflex measurements. Previous experimental findings indicated that chronic back pain affects stability and reflex characteristics. The authors developed a model to make quantitative predictions for the relation between delay and amplitude of reflexes of the superficial, multi-joint back muscles. These predictions were well supported by empirical reflex data. The findings are of clinical relevance for the treatment of chronic back pain. Coping with disturbances Evidence suggests that self-stability in the presence of mechanical perturbations contributes to safe guarding the proper operation of the motor system. Blickhan et al. report experiments on the kinematic responses of standing subjects to sudden pulls inflicted by a motor, as well as on the kinetics of runners crossing a track with a bump. In both cases the first responses are dominated by system compliance, which might help to avoid motor failure and subsequent damage. Likewise, being in preparation to an ensuing disturbance seems to be aimed at enhancement of the reaction scope rather than rapid compensation. Understanding the increased risk of falling in older adults using dynamic walking models Failure to cope with the dynamic requirements to the motor system is common in elderly people and expresses itself, among other manifestations, in an increased risk of falling. It has long been unclear whether this increased risk of falling is due primarily to motor variance or to slowing down. In the latter case, the slowing would reflect a maladaptive strategy evoked by fear of movement. Roos and Dingwell adopted a numerical modeling approach to solve this issue. The results indicate that the slowing down is adaptive and that increased motor variance is the fundamental factor. Conclusion The present collection of studies illustrates the importance of integrated computational and experimental approaches as well as the need to consider multiple levels of control. With the help of modern techniques achieving this advanced goal come into reach, as are viable applications of motor theory to medical problems of the sensorimotor system, such as chronic back pain and aging. We wish the readers much gratification and insight in working their way through this issue. Acknowledgments The guest editor would like to thank the following reviewers for helping to improve the work reported in this special issue:
Editorial / Human Movement Science 32 (2013) 877–879
879
Ramesh Balasubramaniam, University of California (United States of America) Sjoerd Bruijn, VU University Amsterdam (Netherlands) Ansgar Büschges, University of Cologne (Germany) Stephen Grossberg (United States of America) At Hof, University of Groningen (Netherlands) Miriam Kunz, University of Bamberg (Germany) Michael L. Madigan (United States of America) Lars Michels, University Hospital Zurich (Switzerland) Norman Reeves (United States of America) Sverker Runeson (Sweden)
Heiko Wagner Institute of Sport and Exercise Sciences, University of Muenster, Horstmarer Landweg 62b, 48149 Muenster, Germany
Contents lists available at ScienceDirect
Human Movement Science
Editorial
Tackling the challenges posed by the human dynamic system Why don’t we fall when we trip? Why do we fall more often as we get older? How does back pain become chronic? How do our brain and spine interact when we learn new movements? Until recently, studying such questions tended to culminate a plethora of unconnected theories. Currently, however, new interdisciplinary approaches are being developed to tackle these questions of the human dynamic system, which is intrinsically nonlinear, in a more principled manner. Nonlinear dynamical approaches in the study of human movement allow for a fundamental understanding of the complex phenomena of human behavior, not only with regard to the neural control of movement but also with regard to the mechanical properties of the motor apparatus, in interaction with neural aspects of motor control. Active movements are generated by well-coordinated muscle contractions that are controlled and stabilized by neural circuits. In order to study the sensorimotor system, models need to be developed that allow for the analysis of the mechanical apparatus as well as the central nervous system by using the concepts and methods of dynamical systems theory. One important issue in understanding the human dynamic system is the influence of pain on the motor control system in general. Therefore, the present special issue represents a collaborative effort between the Center for Non-linear Science (CeNoS), Münster, Germany and a ‘‘chronic back pain’’ research network supported by the Federal Ministry of Education and Research (BMBF). The consortium is composed with the aim to cover the entire span of the complex interactions that are involved in chronic back pain. The present special issue is a collection of interdisciplinary approaches aimed at tackling the problems posed by the human dynamic system. The collection ranges from modeling approaches to experimental work, and from high-level brain mechanisms to spinal control. The overarching perspective on the human dynamic system is that the control of human movement is flexible and adaptive; it has to deal with issues such as neuronal and physiological noise, external perturbations, stability, compliance and variability, and that learning and development may be understood in terms of adaptive changes in motor control over shorter and longer time scales. How one can come to terms with the adaptive character of motor control and learning is exemplified by the contributions to this special issue, which – as a prelude – may be introduced as follows. A self-active recurrent neural network for a flexible motor memory Artificial neural networks have promised future success for many decennia, but thus far they have suffered notoriously from slow learning, low flexibility and limited biological and physiological relevance. Computers are immensely more powerful than they used to be only a short time ago. Importantly, however, a new generation of neural networks with so-called reservoir computing has evolved that can learn rapidly and flexibly. Boström et al. explore the flexibility and the interpolation abilities of a physiologically plausible reservoir neural network with a recurrent architecture for motor memory. The study illustrates how the model can flexibly interpolate patterns into new ones and cope with sensory feedback in a dynamic manner. 0167-9457/$ - see front matter Ó 2013 Published by Elsevier B.V. http://dx.doi.org/10.1016/j.humov.2013.11.001
878
Editorial / Human Movement Science 32 (2013) 877–879
Movement variability near goal-equivalent manifolds An unresolved issue in motor control pertains to the relation between the spatiotemporal structure of motor variability and the spatiotemporal structure of required end point accuracy. Cusumano and Dingwell employ a model-based framework to describe the inter-trial fluctuations to characterize end-point error-correcting control for specific motor tasks. Brain activity for visual judgment of lifted weight Human observers are remarkably proficient at judging delicate aspects of visually displayed actions. A case in point is the capability to judge the weight lifted by an actor from an abstract pointlight display. Ritter et al. hypothesized that human observers use their own sensorimotor experience in handling heavy objects to judge the weight lifted by others. If so, observing someone lifting a weight should activate the same centers in the somatosensory and motor regions as when actively performing these actions, which is what the functional imaging (fMRI) data collected demonstrated. Impaired visual perception of hurtful actions in patients with chronic lower back pain An important aspect of high-level motor control is the tight link with other high-level functions like the perception of movements made by others. Chronic back pain is generally accompanied with fear of movement, changes in the sensation of the affected regions and changes in sensorimotor brain structures. De Lussanet et al. examined whether these changes in chronic back pain make that patients are impaired even when judging a weight lifted by others. In a control experiment it was verified that the chronic back pain patients were not impaired in visual judgments or deficits in attention. Influence of delayed muscle reflexes on spinal stability Chronic back pain also has severe influences on the spinal control of movement. Liebetrau et al. combined a numerical computational approach with experimental reflex measurements. Previous experimental findings indicated that chronic back pain affects stability and reflex characteristics. The authors developed a model to make quantitative predictions for the relation between delay and amplitude of reflexes of the superficial, multi-joint back muscles. These predictions were well supported by empirical reflex data. The findings are of clinical relevance for the treatment of chronic back pain. Coping with disturbances Evidence suggests that self-stability in the presence of mechanical perturbations contributes to safe guarding the proper operation of the motor system. Blickhan et al. report experiments on the kinematic responses of standing subjects to sudden pulls inflicted by a motor, as well as on the kinetics of runners crossing a track with a bump. In both cases the first responses are dominated by system compliance, which might help to avoid motor failure and subsequent damage. Likewise, being in preparation to an ensuing disturbance seems to be aimed at enhancement of the reaction scope rather than rapid compensation. Understanding the increased risk of falling in older adults using dynamic walking models Failure to cope with the dynamic requirements to the motor system is common in elderly people and expresses itself, among other manifestations, in an increased risk of falling. It has long been unclear whether this increased risk of falling is due primarily to motor variance or to slowing down. In the latter case, the slowing would reflect a maladaptive strategy evoked by fear of movement. Roos and Dingwell adopted a numerical modeling approach to solve this issue. The results indicate that the slowing down is adaptive and that increased motor variance is the fundamental factor. Conclusion The present collection of studies illustrates the importance of integrated computational and experimental approaches as well as the need to consider multiple levels of control. With the help of modern techniques achieving this advanced goal come into reach, as are viable applications of motor theory to medical problems of the sensorimotor system, such as chronic back pain and aging. We wish the readers much gratification and insight in working their way through this issue. Acknowledgments The guest editor would like to thank the following reviewers for helping to improve the work reported in this special issue:
Editorial / Human Movement Science 32 (2013) 877–879
879
Ramesh Balasubramaniam, University of California (United States of America) Sjoerd Bruijn, VU University Amsterdam (Netherlands) Ansgar Büschges, University of Cologne (Germany) Stephen Grossberg (United States of America) At Hof, University of Groningen (Netherlands) Miriam Kunz, University of Bamberg (Germany) Michael L. Madigan (United States of America) Lars Michels, University Hospital Zurich (Switzerland) Norman Reeves (United States of America) Sverker Runeson (Sweden)
Heiko Wagner Institute of Sport and Exercise Sciences, University of Muenster, Horstmarer Landweg 62b, 48149 Muenster, Germany
