Are muscle synergies useful for neural control?

Frontiers in Computational Neuroscience

Volumn , Issue MAR, 2013, Pages

  de Rugy, Aymar ^a   Loeb, Gerald E ^b   Carroll, Timothy J ^a  

^a UNIVERSITY OF QUEENSLAND   (Australia)

^b University of Southern California ^*  (United States)

Author keywords

Aiming movement; Biomechanics; Motor control; Muscle coordination; Optimal control

Indexed keywords

AIMING MOVEMENT; BIOMECHANICAL SYSTEMS; MOTOR CONTROL; MUSCLE BIOMECHANICS; MUSCLE COORDINATION; MUSCLE RECONSTRUCTION; NEURAL CONTROL SYSTEM; OPTIMAL CONTROLS;

ALGORITHMS; BIOMECHANICS; BIOPHYSICS; DIGITAL STORAGE; ERRORS; OPTIMIZATION; REDUNDANCY;

MUSCLE;

ADULT; AIMING ERROR; ARTICLE; BIOMECHANICS; COORDINATION; ELBOW; ELECTROMYOGRAM; ERROR; HUMAN; HUMAN EXPERIMENT; MALE; MOTOR CONTROL; MUSCLE CONTRACTION; NORMAL HUMAN; TASK PERFORMANCE; WRIST;

EID: 84875059365     PISSN: 16625188     EISSN: None     Source Type: Journal    
DOI: 10.3389/fncom.2013.00019     Document Type: Article

References (68)

1. Allen, J.L., and Neptune, R.R. (2012). Three-dimensional modular control of human walking. Journal of biomechanics 45, 2157-2163.
2. Andersen, R.A., Essick, G.K., and Siegel, R.M. (1985). Encoding of spatial location by posterior parietal neurons. Science 230, 456-458.
3. Baraduc, P., Guigon, E., and Burnod, Y. (2001). Recoding arm position to learn visuomotor transformations. Cereb Cortex 11, 906-917.
4. Berniker, M., Jarc, A., Bizzi, E., and Tresch, M.C. (2009). Simplified and effective motor control based on muscle synergies to exploit musculoskeletal dynamics. Proc Natl Acad Sci U S A 106, 7601-7606.
5. Bernstein, N.A. (1967). The coordination and regulation of movements. Oxford, UK: Pergamon Press.
6. Brown, I.E., Cheng, E.J., and Loeb, G.E. (1999). Measured and modeled properties of mammalian skeletal muscle. II. The effects of stimulus frequency on force-length and force-velocity relationships. Journal of Muscle Research and Cell Motility 20, 627-643.
7. Burkholder, T.J., and Van, A.K.W. (2012). Practical limits on muscle synergy identification by non-negative matrix factorization in systems with mechanical constraints. Medical and Biological Engineering and Computing.
8. Chanaud, C.M., Pratt, C.A., and Loeb, G.E. (1991a). Functionally complex muscles of the cat hindlimb. II. Mechanical and architectural heterogenity within the biceps femoris. Experimental brain research. Experimentelle Hirnforschung. Experimentation cerebrale 85, 257-270.
9. Chanaud, C.M., Pratt, C.A., and Loeb, G.E. (1991b). Functionally complex muscles of the cat hindlimb. V. The roles of histochemical fiber-type regionalization and mechanical heterogeneity in differential muscle activation. Experimental brain research. Experimentelle Hirnforschung. Experimentation cerebrale 85, 300-313.
10. Cheng, E.J., and Loeb, G.E. (2008). On the use of musculoskeletal models to interpret motor control strategies from performance data. J Neural Eng 5, 232-253.
11. Cheung, V.C., D'avella, A., Tresch, M.C., and Bizzi, E. (2005). Central and sensory contributions to the activation and organization of muscle synergies during natural motor behaviors. J Neurosci 25, 6419-6434.
12. Chhabra, M., and Jacobs, R.A. (2006). Properties of synergies arising from a theory of optimal motor behavior. Neural Computation 18, 2320-2342.
13. Chiel, H.J., Ting, L.H., Ekeberg, O., and Hartmann, M.J. (2009). The brain in its body: motor control and sensing in a biomechanical context. The Journal of neuroscience: the official journal of the Society for Neuroscience 29, 12807-12814.
14. Clark, D.J., Ting, L.H., Zajac, F.E., Neptune, R.R., and Kautz, S.A. (2010). Merging of healthy motor modules predicts reduced locomotor performance and muscle coordination complexity post-stroke. Journal of Neurophysiology 103, 844-857.
15. D'avella, A., Fernandez, L., Portone, A., and Lacquaniti, F. (2008). Modulation of phasic and tonic muscle synergies with reaching direction and speed. Journal of Neurophysiology 100, 1433-1454.
16. D'avella, A., Portone, A., Fernandez, L., and Lacquaniti, F. (2006). Control of fast-reaching movements by muscle synergy combinations. J Neurosci 26, 7791-7810.
17. D'avella, A., Saltiel, P., and Bizzi, E. (2003). Combinations of muscle synergies in the construction of a natural motor behavior. Nat Neurosci 6, 300-308.
18. Davoodi, R., Brown, I.E., and Loeb, G.E. (2003). Advanced modeling environment for developing and testing FES control systems. Med Eng Phys 25, 3-9.
19. Davoodi, R., Brown, I.E., Todorov, E., and Loeb, G.E. (Year). "A biomechanical model of the partially paralyzed human arm", in: the 7th Annual Conference of the International Functional Electric Stimulation Society).
20. Davoodi, R., Kleiman, D., Murakata, T., and Loeb, G.E. (Year). "A biomechanical model of the elbow, forearm and wrist", in: the 4th World Congress of Biomechanics).
21. de Rugy, A. (2010). Generalization of visuomotor adaptation to different muscles is less efficient: experiment and model. Human Movement Science 29, 684-700.
22. de Rugy, A., Davoodi, R., and Carroll, T.J. (2012a). Changes in wrist muscle activity with forearm posture: Implications for the study of sensorimotor transformations. Journal of Neurophysiology 108, 2884-2895.
23. de Rugy, A., Hinder, M.R., Woolley, D.G., and Carson, R.G. (2009). The synergistic organization of muscle recruitment constrains visuomotor adaptation. J Neurophysiol 101, 2263-2269.
24. de Rugy, A., Loeb, G.E., and Carroll, T.J. (2012b). Muscle coordination is habitual rather than optimal. The Journal of neuroscience 32, 7384-7391.
25. de Rugy, A., Loeb, G.E., and Carroll, T.J. (2012c). Virtual biomechanics: A new method for online reconstruction of force from EMG recordings. Journal of Neurophysiology 108, 3333-3341.
26. de Rugy, A., Riek, S., Oytam, Y., Carroll, T.J., Davoodi, R., and Carson, R.G. (2008). Neuromuscular and biomechanical factors codetermine the solution to motor redundancy in rhythmic multijoint arm movement. Exp Brain Res 189, 421-434.
27. Diedrichsen, J., Shadmehr, R., and Ivry, R.B. (2010). The coordination of movement: optimal feedback control and beyond. Trends Cogn Sci 14, 31-39.
28. Dominici, N., Ivanenko, Y.P., Cappellini, G., D'avella, A., Mondi, V., Cicchese, M., Fabiano, A., Silei, T., Di Paolo, A., Giannini, C., Poppele, R.E., and Lacquaniti, F. (2011). Locomotor primitives in newborn babies and their development. Science 334, 997-999.
29. Fagg, A.H., Shah, A., and Barto, A.G. (2002). A computational model of muscle recruitment for wrist movements. J Neurophysiol 88, 3348-3358.
30. Hargrove, L.J., Li, G., Englehart, K.B., and Hudgins, B.S. (2009). Principal components analysis preprocessing for improved classification accuracies in pattern-recognitionbased myoelectric control. IEEE Trans Biomed Eng 56, 1407-1414.
31. Hauschild, M., Mulliken, G.H., Fineman, I., Loeb, G.E., and Andersen, R.A. (2012). Cognitive signals for brain-machine interfaces in posterior parietal cortex include continuous 3D trajectory commands. Proceedings of the National Academy of Sciences of the United States of America 109, 17075-17080.
32. Hug, F. (2011). Can muscle coordination be precisely studied by surface electromyography? Journal of electromyography and kinesiology: official journal of the International Society of Electrophysiological Kinesiology 21, 1-12.
33. Jiang, N., Englehart, K.B., and Parker, P.A. (2009). Extracting simultaneous and proportional neural control information for multiple-DOF prostheses from the surface electromyographic signal. IEEE Transactions on Bio-medical Engineering 56, 1070-1080.
34. Kargo, W.J., Ramakrishnan, A., Hart, C.B., Rome, L.C., and Giszter, S.F. (2010). A simple experimentally based model using proprioceptive regulation of motor primitives captures adjusted trajectory formation in spinal frogs. Journal of Neurophysiology 103, 573-590.
35. Kuiken, T.A., Li, G., Lock, B.A., Lipschutz, R.D., Miller, L.A., Stubblefield, K.A., and Englehart, K.B. (2009). Targeted muscle reinnervation for real-time myoelectric control of multifunction artificial arms. JAMA: the journal of the American Medical Association 301, 619-628.
36. Kuiken, T.A., Miller, L.A., Lipschutz, R.D., Lock, B.A., Stubblefield, K., Marasco, P.D., Zhou, P., and Dumanian, G.A. (2007). Targeted reinnervation for enhanced prosthetic arm function in a woman with a proximal amputation: a case study. Lancet 369, 371-380.
37. Lee, D.D., and Seung, H.S. (2001). Adv. Nural Info. Proc. Syst. 13, 556-562.
38. Lockhart, D.B., and Ting, L.H. (2007). Optimal sensorimotor transformations for balance. Nature Neuroscience 10, 1329-1336.
39. Loeb, G.E. (1993). The distal hindlimb musculature of the cat: interanimal variability of locomotor activity and cutaneous reflexes. Experimental brain research. Experimentelle Hirnforschung. Experimentation cerebrale 96, 125-140.
40. Loeb, G.E. (1999). Asymmetry of hindlimb muscle activity and cutaneous reflexes after tendon transfers in kittens. J Neurophysiol 82, 3392-3405.
41. Loeb, G.E. (2000). Overcomplete musculature or underspecified tasks? Motor Control 4, 81-83; discussion 97-116.
42. Loeb, G.E. (2012). Optimal isn't good enough. Biological Cybernetics.
43. Loeb, G.E., and Davoodi, R. (2005). The functional reanimation of paralyzed limbs. IEEE Eng Med Biol Mag 24, 45-51.
44. Loeb, G.E., and Gans, C. (1986). Electromyography for Experimentalists. University of Chicago Press.
45. Macpherson, J.M. (1991). How flexible are muscle synergies?, in: Motor control: Concepts and issues. (ed.) H.-J.F. D.R. Humphrey. (New York: Wiley Press).
46. Mardia, K.V., Kent, J.T., and Bibby, J.M. (1979). Multivariate analysis. London: Academic.
47. Mckay, J.L., and Ting, L.H. (2008). Functional muscle synergies constrain force production during postural tasks. J Biomech 41, 299-306.
48. Mckay, J.L., and Ting, L.H. (2012). Optimization of muscle activity for task-level goals predicts complex changes in limb forces across biomechanical contexts. PLoS Computational Biology 8, e1002465.
49. Muceli, S., Boye, A.T., D'avella, A., and Farina, D. (2010). Identifying representative synergy matrices for describing muscular activation patterns during multidirectional reaching in the horizontal plane. Journal of Neurophysiology 103, 1532-1542.
50. Musallam, S., Corneil, B.D., Greger, B., Scherberger, H., and Andersen, R.A. (2004). Cognitive control signals for neural prosthetics. Science 305, 258-262.
51. Neptune, R.R., Clark, D.J., and Kautz, S.A. (2009). Modular control of human walking: a simulation study. Journal of biomechanics 42, 1282-1287.
52. Oliveira, A.S., Gizzi, L., Kersting, U.G., and Farina, D. (2012). Modular organization of balance control following perturbations during walking. Journal of Neurophysiology 108, 1895-1906.
53. Parker, P., Englehart, K., and Hudgins, B. (2006). Myoelectric signal processing for control of powered limb prostheses. Journal of Electromyography and Kinesiology 16, 541-548.
54. Pouget, A., and Snyder, L.H. (2000). Computational approaches to sensorimotor transformations. Nat Neurosci 3 Suppl, 1192-1198.
55. Pratt, C.A., Chanaud, C.M., and Loeb, G.E. (1991). Functionally complex muscles of the cat hindlimb. IV. Intramuscular distribution of movement command signals and cutaneous reflexes in broad, bifunctional thigh muscles. Experimental brain research. Experimentelle Hirnforschung. Experimentation cerebrale 85, 281-299.
56. Pratt, C.A., and Loeb, G.E. (1991). Functionally complex muscles of the cat hindlimb. I. Patterns of activation across sartorius. Experimental brain research. Experimentelle Hirnforschung. Experimentation cerebrale 85, 243-256.
57. Raphael, G., Tsianos, G.A., and Loeb, G.E. (2010). Spinal-like regulator facilitates control of a two-degree-of-freedom wrist. J Neurosci 30, 9431-9444.
58. Roh, J., Rymer, W.Z., and Beer, R.F. (2012). Robustness of muscle synergies underlying three-dimensional force generation at the hand in healthy humans. Journal of Neurophysiology 107, 2123-2142.
59. Salinas, E., and Abbott, L.F. (1995). Transfer of coded information from sensory to motor networks. J Neurosci 15, 6461-6474.
60. Staudenmann, D., Roeleveld, K., Stegeman, D.F., and Van, D.J.H. (2010). Methodological aspects of SEMG recordings for force estimation--a tutorial and review. Journal of electromyography and kinesiology: official journal of the International Society of Electrophysiological Kinesiology 20, 375-387.
61. Ting, L.H., and Chvatal, S.A. (2010). Decomposing muscle activity in motor tasks: methods and interpretation, in Motor control: Theories, experiments, and applications, ed. L.M.L. Danion F. (New York: Oxford University Press).
62. Ting, L.H., and Mckay, J.L. (2007). Neuromechanics of muscle synergies for posture and movement. Curr Opin Neurobiol 17, 622-628.
63. Todorov, E. (2004). Optimality principles in sensorimotor control. Nat Neurosci 7, 907-915.
64. Todorov, E., Li, W., and Pan, X. (2005). From task parameters to motor synergies: A hierarchical framework for approximately-optimal control of redundant manipulators. Journal of robotic systems 22, 691-710.
65. Torres-Oviedo, G., Macpherson, J.M., and Ting, L.H. (2006). Muscle synergy organization is robust across a variety of postural perturbations. Journal of Neurophysiology 96, 1530-1546.
66. Tresch, M.C., and Jarc, A. (2009). The case for and against muscle synergies. Current Opinion in Neurobiology 19, 601-607.
67. Tsianos, G.A., Raphael, G., and Loeb, G.E. (2011). Modeling the potentiality of spinal-like circuitry for stabilization of a planar arm system. Progress in Brain Research 194, 203-213.
68. Valero-Cuevas, F.J., Hoffmann, H., Kurse, M.U., Kutch, J.J., and Theodorou, E.A. (2009). Computational Models for Neuromuscular Function. IEEE reviews in biomedical engineering 2, 110-135.