Neuromechanical tuning of nonlinear postural control dynamics Lena H. Ting,1,2 Keith W. van Antwerp,1 Jevin E. Scrivens,3 J. Lucas McKay,2 Torrence D. J. Welch,1 Jeffrey T. Bingham,3 and Stephen P. DeWeerth1,2 1W. H. Coulter Department of Biomedical Engineering, Emory University and Georgia Institute of Technology, Atlanta, Georgia 30332-0535, USA 2School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332-0535, USA 3Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332-0535, USA Received 4 March 2009 accepted 4 May 2009 published online 29 June 2009 Postural control may be an ideal physiological motor task for elucidating general questions about the organization, diversity, flexibility, and variability of biological motor behaviors using nonlinear dynamical analysis techniques. Rather than presenting ���problems��� to the nervous system, the re- dundancy of biological systems and variability in their behaviors may actually be exploited to allow for the flexible achievement of multiple and concurrent task-level goals associated with movement. Such variability may reflect the constant ���tuning��� of neuromechanical elements and their interac- tions for movement control. The problem faced by researchers is that there is no one-to-one mapping between the task goal and the coordination of the underlying elements. We review recent and ongoing research in postural control with the goal of identifying common mechanisms under- lying variability in postural control, coordination of multiple postural strategies, and transitions between them. We present a delayed-feedback model used to characterize the variability observed in muscle coordination patterns during postural responses to perturbation. We emphasize the sig- nificance of delays in physiological postural systems, requiring the modulation and coordination of both the instantaneous, ���passive��� response to perturbations as well as the delayed, ���active��� re- sponses to perturbations. The challenge for future research lies in understanding the mechanisms and principles underlying neuromechanical tuning of and transitions between the diversity of pos- tural behaviors. Here we describe some of our recent and ongoing studies aimed at understanding variability in postural control using physical robotic systems, human experiments, dimensional analysis, and computational models that could be enhanced from a nonlinear dynamics approach. �� 2009 American Institute of Physics. DOI: 10.1063/1.3142245 Successful postural control is both a precursor to and an integral component of locomotion in humans and other animals. Babies can only walk once they are able to stand, and constant postural corrections are necessary during locomotion to negotiate real environments. The ability to maintain standing balance in itself is a challeng- ing problem that may provide a framework for address- ing fundamental questions regarding the organization, diversity, and flexibility of biological motor behaviors in general. Evidence suggests that postural control dynam- ics are constantly being modified or ���tuned��� by the ner- vous system in response to prior and anticipated postural challenges. Moreover, a range of postural strategies con- tributes to our ability to maintain balance: swaying, step- ping, or reaching. Therefore, the true postural capacity of an organism may not be captured by models assuming invariant parameter values or experiments examining only averaged postural responses. Here, we present a pos- sible dynamical system framework for interpreting���and eventually understanding���the physiological mechanisms underlying postural stability. An important physiological property to consider is the long conduction delays present in transmitting the sensory and motor commands be- tween the muscles and the nervous system. This property ensures that there are always at least two different mechanisms involved in maintaining posture in response to a perturbation. The initial movement and joint torques in response to perturbations are due to the intrinsic me- chanical properties of the body. These properties are de- termined by feedforward activation levels of muscles prior to the perturbation. The latter movement and joint torques include the effects of sensory feedback that change the muscle activity after a delay. Because of the overlap in the effects of these two mechanisms, they must be carefully unraveled and explicitly accounted for in or- der to understand the flexible control of posture observed in physiological systems. I. INTRODUCTION To maintain standing balance, the nervous system must confront the classic ���degrees of freedom��� problem in motor control posed by Bernstein 1967 that arises from the vast redundancy in the musculoskeletal system. This redundancy requires not only a large number of elements to be coordi- nated in performing a task but also a method for selecting one possible solution amongst many. In balance control, the muscles and joints across the limbs, trunk, and neck must be CHAOS 19, 026111 2009 1054-1500/2009/19 2 /026111/12/$25.00 �� 2009 American Institute of Physics 19, 026111-1 Author complimentary copy. Redistribution subject to AIP license or copyright, see http://cha.aip.org/cha/copyright.jsp

coordinated to maintain the body���s center of mass CoM over the feet that form the base of support. These many degrees of freedom at the actuation or execution level are generally thought to pose a problem to the nervous system because the task requirements are not sufficient to uniquely specify how each muscle and joint must be controlled. How- ever, as neural systems are both adaptive and must perform tasks in parallel, this redundancy may be necessary to allow flexibility in motor tasks such as posture and balance control. Therefore, seemingly simple behaviors may not be definable in terms of one-to-one mappings between the task goal and the coordination of the underlying elements. Whereas the term ���postural control��� often refers to the restoration of a particular body configuration, in the context of standing balance in a gravity environment we define pos- tural control as the suite of dynamic neuromechanical pro- cesses that maintain the body���s CoM over the base of sup- port. In certain types of motor tasks, such as controlling the location of the hand when reaching to an object, it may be sufficient to maintain a particular kinematic configuration or body scheme see Massion, 1994 . However, in standing bal- ance, returning the posture of the body to the original con- figuration following a perturbation may or may not be suffi- cient to avoid falling down. For example, when balance is disturbed or disrupted, various postural control strategies can be used, such as maintaining balance with the feet in place, taking a step, or grabbing a handhold. Even with a particular motor strategy, the execution of the task can be highly vari- able at many levels, including body motion Bernstein, 1967 , muscle activation Gottlieb, 1998 , and activity of neural circuits Churchland et al., 2006 Horn et al., 2004 both within and across subjects. Moreover, postural re- sponses to identical perturbations can vary significantly within an individual and are influenced by the condition of the previous trials, habituation, anticipation, cognitive load, and emotion Carpenter et al., 2006 Woollacott and Shumway-Cook, 2002 . Recent evidence suggests that movement variability is not random but organized to allow the organism to flexibly reconfigure execution-level elements to achieve task-level goals. Variability in muscle activity or joint angles during postural and other motor tasks may be organized to minimize variability in task-level variables such as CoM movement or target attainment Krishnamoorthy et al., 2004 Scholz et al., 2002 Scholz and Schoner, 1999 Torres-Oviedo and Ting, 2007 d���Avella et al., 2003 Ting and Macpherson, 2005 Tresch et al., 1999 Welch and Ting, 2008 . Thus, in their normal functioning, biological systems may use the multiple ���correct��� solutions defined by manifolds appropriate for any given task Latash et al., 2007 Ting and McKay, 2007 . While important stochastic variations also exist in sensation and actuation Hamilton et al., 2004 Harris and Wolpert, 1998 , motor variability may be more attributable to optimal feedback processes that balance the opposing demands of achieving a task-level performance goal versus minimizing energy expenditure Kording, 2007 Lockhart and Ting, 2007 Shadmehr and Krakauer, 2008 Ting and McKay, 2007 Todorov and Jordan, 2002 . Open questions remain as to 1 how and why global, task-level goals of regulating endpoint trajectory, CoM movement, or energetic efficiency vary across different contexts and 2 how such task-level goals are flexibly achieved by redundant execution-level commands at the level of neurons, muscles, and joints. In this communication we present our perspective of im- portant physiological postural control mechanisms as well as some experimental results that must be taken into consider- ation when formulating models of postural control. First, we review important aspects of the balance control literature with respect to nonlinear dynamical system analysis. Signifi- cant advances in understanding postural control may be achievable though nonlinear dynamical analyses of postural control models that reflect an appropriate level of complexity of the physiological systems involved. Then, with the goal of identifying common neural mechanisms, we review the cur- rent postural control literature addressing different experi- mental conditions: quiet standing, and postural responses to both continuous and discrete perturbations. We present a de- layed linear feedback model that may be useful in unifying these different postural behaviors. Finally, we present our recent and current work from robotic, human, animal, and computational studies that demonstrate how neural and me- chanical neuromechanical tuning can alter postural perfor- mance and induce transitions across postural strategies. It is our hope that this review will stimulate future research to develop experimental, computational, and analytical tech- niques that will help understand how the global goal of bal- ance control is achieved through the flexible integration and coordination of multiple neuromechanical elements. II. BALANCE CONTROL AS A NONLINEAR DYNAMICAL SYSTEM A nonlinear dynamical system perspective may be useful for understanding how variability and diversity in the coor- dination of execution-level elements contribute biological postural control. To understand postural variability requires studying the precise tuning of the underlying neuromechani- cal elements and not just reproducing the task-level functions of the postural control system. While single parameter varia- tions are useful and necessary for investigating relevant non- linear behaviors in biological systems, it is important to maintain the perspective that the nervous system is perhaps capable of simultaneously tuning all parameters that may contribute to task-level goals. From a physiological perspec- tive, we present several important execution-level neurome- chanical elements that contribute to postural control dynam- ics and their relevant features and characteristics. Next, a conceptual framework is given that may help illustrate how nonlinear dynamic analyses might contribute to our under- standing of how these elements are coordinated during pos- tural control. Feedforward and feedback execution-level neurome- chanical mechanisms are necessary to navigate the long de- lays associated with neural pathways that mediate sensory input and motor output Fig. 1 . We define feedforward neu- romechanical elements to be those that adjust the intrinsic mechanical stability of the musculoskeletal system, requiring an anticipation of a postural perturbation. We define feedback neuromechanical elements to be those that activate muscles 026111-2 Ting et al. Chaos 19, 026111 2009 Author complimentary copy. Redistribution subject to AIP license or copyright, see http://cha.aip.org/cha/copyright.jsp