Reduction of Metabolic Cost during Motor Learning of Arm Reaching Dynamics

It is often assumed that the CNS controls movements in a manner that minimizes energetic cost. While empirical evidence for actual metabolic minimization exists in locomotion, actual metabolic cost has yet to be measured during motor learning and/or arm reaching. Here, we measured metabolic power consumption using expired gas analysis, as humans learned novel arm reaching dynamics. We hypothesized that (1) metabolic power would decrease with motor learning and (2) muscle activity and coactivation would parallel changes in metabolic power. Seated subjects made horizontal planar reaching movements toward a target using a robotic arm. The novel dynamics involved compensating for a viscous curl force field that perturbed reaching movements. Metabolic power was measured continuously throughout the protocol. Subjects decreased movement error and learned the novel dynamics. By the end of learning, net metabolic power decreased by ∼20% (∼0.1 W/kg) from initial learning. Muscle activity and coactivation also decreased with motor learning. Interestingly, distinct and significant reductions in metabolic power occurred even after muscle activity and coactivation had stabilized and movement changes were small. These results provide the first evidence of actual metabolic reduction during motor learning and for a reaching task. Further, they suggest that muscle activity may not explain changes in metabolic cost as completely as previously thought. Additional mechanisms such as more subtle features of arm muscle activity, changes in activity of other muscles, and/or more efficient neural processes may also underlie the reduction in metabolic cost during motor learning.

[1]  J. E. Cotes,et al.  The energy expenditure and mechanical energy demand in walking. , 1960 .

[2]  Rodolfo Margaria,et al.  Biomechanics and Energetics of Muscular Exercise , 1976 .

[3]  K. R. Williams,et al.  The effect of stride length variation on oxygen uptake during distance running. , 1982, Medicine and science in sports and exercise.

[4]  G. Brooks,et al.  Exercise physiology: Human bioenergetics and its applications , 1984 .

[5]  J. F. Yang,et al.  Electromyographic amplitude normalization methods: improving their sensitivity as diagnostic tools in gait analysis. , 1984, Archives of physical medicine and rehabilitation.

[6]  J. Brockway Derivation of formulae used to calculate energy expenditure in man. , 1987, Human nutrition. Clinical nutrition.

[7]  J. Hamill,et al.  Predicting the minimal energy costs of human walking. , 1991, Medicine and science in sports and exercise.

[8]  F A Mussa-Ivaldi,et al.  Adaptive representation of dynamics during learning of a motor task , 1994, The Journal of neuroscience : the official journal of the Society for Neuroscience.

[9]  R. McN. Alexander,et al.  A minimum energy cost hypothesis for human arm trajectories , 1997, Biological Cybernetics.

[10]  Alexander Rm,et al.  A minimum energy cost hypothesis for human arm trajectories. , 1997 .

[11]  G. D. P. M. DipTP Introduction to Surface Electromyography , 1998 .

[12]  R Shadmehr,et al.  Electromyographic Correlates of Learning an Internal Model of Reaching Movements , 1999, The Journal of Neuroscience.

[13]  R. Kram,et al.  Mechanical and metabolic determinants of the preferred step width in human walking , 2001, Proceedings of the Royal Society of London. Series B: Biological Sciences.

[14]  S. Laughlin,et al.  An Energy Budget for Signaling in the Grey Matter of the Brain , 2001, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.

[15]  A. Kuo A simple model of bipedal walking predicts the preferred speed-step length relationship. , 2001, Journal of biomechanical engineering.

[16]  W. Sparrow,et al.  Practice effects on coordination and control, metabolic energy expenditure, and muscle activation. , 2002, Human movement science.

[17]  J. Donelan,et al.  Mechanical work for step-to-step transitions is a major determinant of the metabolic cost of human walking. , 2002, The Journal of experimental biology.

[18]  F. Underwood,et al.  The Effect of Repeated Bouts of Backward Walking on Physiologic Efficiency , 2002, Journal of strength and conditioning research.

[19]  Michael I. Jordan,et al.  Optimal feedback control as a theory of motor coordination , 2002, Nature Neuroscience.

[20]  R. McNeill Alexander Energetics and optimization of human walking and running: The 2000 Raymond Pearl memorial lecture , 2002, American journal of human biology : the official journal of the Human Biology Council.

[21]  Paul L Gribble,et al.  Role of cocontraction in arm movement accuracy. , 2003, Journal of neurophysiology.

[22]  M. Kawato,et al.  Adaptation to Stable and Unstable Dynamics Achieved By Combined Impedance Control and Inverse Dynamics Model , 2003 .

[23]  R. Kram,et al.  Energy cost and muscular activity required for propulsion during walking. , 2003, Journal of applied physiology.

[24]  M. Kawato,et al.  Impedance control balances stability with metabolically costly muscle activation. , 2004, Journal of neurophysiology.

[25]  C. W. Radcliffe,et al.  Predicting metabolic cost of level walking , 1978, European Journal of Applied Physiology and Occupational Physiology.

[26]  H. Ralston,et al.  Optimization of energy expenditure during level walking , 2004, European Journal of Applied Physiology and Occupational Physiology.

[27]  W. L. Nelson Physical principles for economies of skilled movements , 1983, Biological Cybernetics.

[28]  H. Ralston Energy-speed relation and optimal speed during level walking , 1958, Internationale Zeitschrift für angewandte Physiologie einschließlich Arbeitsphysiologie.

[29]  W. Sparrow,et al.  Aging effects on the metabolic and cognitive energy cost of interlimb coordination. , 2005, The journals of gerontology. Series A, Biological sciences and medical sciences.

[30]  W A Sparrow,et al.  The metabolic and cognitive energy costs of stabilising a high-energy interlimb coordination task. , 2005, Human movement science.

[31]  Alena M. Grabowski,et al.  Independent metabolic costs of supporting body weight and accelerating body mass during walking. , 2005, Journal of applied physiology.

[32]  Brook Galna,et al.  Learning to Minimize Energy Costs and Maximize Mechanical Work in a Bimanual Coordination Task , 2006, Journal of motor behavior.

[33]  Raul Benitez,et al.  Motor adaptation as a greedy optimization of error and effort. , 2007, Journal of neurophysiology.

[34]  D. Ostry,et al.  Muscle cocontraction following dynamics learning , 2008, Experimental Brain Research.

[35]  Daniel P. Ferris,et al.  Mechanics and energetics of level walking with powered ankle exoskeletons , 2008, Journal of Experimental Biology.

[36]  Rieko Osu,et al.  CNS Learns Stable, Accurate, and Efficient Movements Using a Simple Algorithm , 2008, The Journal of Neuroscience.

[37]  Reza Shadmehr,et al.  Motor Adaptation as a Process of Reoptimization , 2008, The Journal of Neuroscience.

[38]  Pierre J. Magistretti,et al.  Low-Cost Travel in Neurons , 2009, Science.

[39]  Steven H Collins,et al.  Dynamic arm swinging in human walking , 2009, Proceedings of the Royal Society B: Biological Sciences.

[40]  H. Houdijk,et al.  The energy cost for balance control during upright standing. , 2009, Gait & posture.

[41]  Jeremy D Wong,et al.  The central nervous system does not minimize energy cost in arm movements. , 2010, Journal of neurophysiology.

[42]  T. Sejnowski,et al.  Metabolic cost as a unifying principle governing neuronal biophysics , 2010, Proceedings of the National Academy of Sciences.

[43]  A. Burden How should we normalize electromyograms obtained from healthy participants? What we have learned from over 25 years of research. , 2010, Journal of electromyography and kinesiology : official journal of the International Society of Electrophysiological Kinesiology.

[44]  Dominic James Farris,et al.  The mechanics and energetics of human walking and running: a joint level perspective , 2012, Journal of The Royal Society Interface.

[45]  Christopher J. Arellano,et al.  The effects of step width and arm swing on energetic cost and lateral balance during running. , 2011, Journal of biomechanics.

[46]  Claire T. Farley,et al.  Energetically optimal stride frequency in running: the effects of incline and decline , 2011, Journal of Experimental Biology.