Performance, complexity and dynamics of force maintenance and modulation in young and older adults
Autoři:
Hester Knol aff001; Raoul Huys aff003; Jean-Jacques Temprado aff001; Rita Sleimen-Malkoun aff001
Působiště autorů:
Institut des Sciences du Mouvement, Centre National de la Recherche Scientifique (CNRS), Aix-Marseille Université, Marseille, France
aff001; Department of Applied Cognitive Psychology, Universität Ulm, Ulm, Germany
aff002; Centre de Recherche Cerveau & Cognition, UPS, CHU Purpan, Université de Toulouse, Toulouse, France
aff003
Vyšlo v časopise:
PLoS ONE 14(12)
Kategorie:
Research Article
prolekare.web.journal.doi_sk:
https://doi.org/10.1371/journal.pone.0225925
Souhrn
The present study addresses how task constraints and aging influence isometric force control. We used two tasks requiring either force maintenance (straight line target force) or force modulation (sine-wave target force) around different force levels and at different modulation frequencies. Force levels were defined relative the individual maximum voluntary contraction. A group of young adults (mean age ± SD = 25 ± 3.6 years) and a group of elderly (mean age = 77 ± 6.4 years) took part in the study. Age- and task-related effects were assessed through differences in: (i) force control accuracy, (ii) time-structure of force fluctuations, and (iii) the contribution of deterministic (predictable) and stochastic (noise-like) dynamic components to the expressed behavior. Performance-wise, the elderly showed a pervasive lower accuracy and higher variability than the young participants. The analysis of fluctuations showed that the elderly produced force signals that were less complex than those of the young adults during the maintenance task, but the reverse was observed in the modulation task. Behavioral complexity results suggest a reduced adaptability to task-constraints with advanced age. Regarding the dynamics, we found comparable generating mechanisms in both age groups for both tasks and in all conditions, namely a fixed-point for force maintenance and a limit-cycle for force modulation. However, aging increased the stochasticity (noise-driven fluctuations) of force fluctuations in the cyclic force modulation, which could be related to the increased complexity found in elderly for this same task. To our knowledge this is the first time that these different perspectives to motor control are used simultaneously to characterize force control capacities. Our findings show their complementarity in revealing distinct aspects of sensorimotor adaptation to task constraints and age-related declines. Although further research is still needed to identify the physiological underpinnings, the used task and methodology are shown to have both fundamental and clinical applications.
Klíčová slova:
Age groups – Geriatrics – Aging – Elderly – Young adults – Entropy – Mass diffusivity – Sine waves
Zdroje
1. Sleimen-Malkoun R, Temprado JJ, Hong SL. Aging induced loss of complexity and dedifferentiation: Consequences for coordination dynamics within and between brain, muscular and behavioral levels. Front Aging Neurosci. 2014;6(140):1–17.
2. Morrison S, Newell KM. Aging, neuromuscular decline, and the change in physiological and behavioral complexity of upper-limb movement dynamics. J Aging Res. 2012; 2012: 891218. doi: 10.1155/2012/891218 22900179
3. Vieluf S, Sleimen-Malkoun R, Voelcker-Rehage C, Jirsa VK, Reuter E-M, Godde B, et al. Dynamical signatures of isometric force control as a function of age, expertise, and task constraints. J Neurophysiol. 2017;118(1):176–186. doi: 10.1152/jn.00691.2016 28356479
4. Clark BC, Manini TM. Sarcopenia = / = dynapenia. J Gerontol A Biol Sci Med Sci. 2008;63(8):829–34. doi: 10.1093/gerona/63.8.829 18772470
5. Clark BC, Manini TM. What is dynapenia? Nutrition. 2012;28(5):495–503. doi: 10.1016/j.nut.2011.12.002 22469110
6. Manini TM, Clark BC. Dynapenia and aging: an update. J Gerontol A Biol Sci Med Sci. 2012;67(1):28–40. doi: 10.1093/gerona/glr010 21444359
7. Klein CS, Rice CL, Marsh GD. Normalized force, activation, and coactivation in the arm muscles of young and old men. J Appl Physiol Bethesda Md 1985. 2001;91(3):1341–9.
8. Lexell J. Ageing and human muscle: observations from Sweden. / Le vieillissement et le muscle humain: observations suedoises. Can J Appl Physiol. 1993;18(1):2–18.
9. Thompson LV. Age-related muscle dysfunction. Exp Gerontol. 2009 Jan;44(1–2):106–11. doi: 10.1016/j.exger.2008.05.003 18657920
10. Kyriazis M. Practical applications of chaos theory to the modulation of human ageing: Fractals Interdiscip J Complex Geom Nat. 2003;75–90.
11. Lipsitz L a. Physiological complexity, aging, and the path to frailty. Sci Aging Knowl Environ SAGE KE. 2004;2004(16):pe16.
12. Temprado J-J, Vieluf S, Bricot N, Berton E, Sleimen-Malkoun R. Performing Isometric Force Control in Combination with a Cognitive Task: A Multidimensional Assessment. PLOS ONE. 2015;10(11):1–13.
13. Voelcker-Rehage C, Stronge AJ, Alberts JL. Age-related differences in working memory and force control under dual-task conditions. Neuropsychol Dev Cogn B Aging Neuropsychol Cogn. 2006;13(3–4):366–84. doi: 10.1080/138255890969339 16887779
14. Keogh J, Morrison S, Barrett R. Age-related differences in inter-digit coupling during finger pinching. Eur J Appl Physiol. 2006;97(1):76–88. doi: 10.1007/s00421-006-0151-7 16496196
15. Keogh JW, Morrison S, Barrett R. Strength Training Improves the Tri-Digit Finger-Pinch Force Control of Older Adults. Arch Phys Med Rehabil. 2007;88(8):1055–1063. doi: 10.1016/j.apmr.2007.05.014 17678670
16. Christou E a Carlton LG. Old Adults Exhibit Greater Motor Ouput Variability Than Young Adults Only During Rapid Discrete Isometric Contractions. J Gerontol Biol Sci. 2001;56(12):524–532.
17. Enoka RM, Christou EA, Hunter SK, Kornatz KW, Semmler JG, Taylor AM, et al. Mechanisms that contribute to differences in motor performance between young and old adults. J Electromyogr Kinesiol. 2003;13(1):1–12. doi: 10.1016/s1050-6411(02)00084-6 12488083
18. Vaillancourt DE, Newell KM. Aging and the time and frequency structure of force output variability. J Appl Physiol. 2003;94(3):903–12. doi: 10.1152/japplphysiol.00166.2002 12571125
19. Hausdorff JM. Gait dynamics, fractals and falls: Finding meaning in the stride-to-stride fluctuations of human walking. Hum Mov Sci. 2007;26(4):555–589. doi: 10.1016/j.humov.2007.05.003 17618701
20. Lipsitz LA, Goldberger AL. Loss of “Complexity” and Aging: Potential applications of fractals and chaos theory to senescence. Jama. 1992;267(13):1806. 1482430
21. Nardelli M, Lanata A, Bertschy G, Scilingo EP, Valenza G. Heartbeat complexity modulation in bipolar disorder during daytime and nighttime. Scientific reports. 2017;7(1):17920. doi: 10.1038/s41598-017-18036-z 29263393
22. Costa MD, Henriques T, Munshi MN, Segal AR, Goldberger AL. Dynamical glucometry: use of multiscale entropy analysis in diabetes. Chaos: An Interdisciplinary Journal of Nonlinear Science. 2014;24(3):033139.
23. Jin Y, Chen C, Cao Z, Sun B, Lo IL, Liu TM, et al. Entropy change of biological dynamics in COPD. International journal of chronic obstructive pulmonary disease. 2017;12:2997. doi: 10.2147/COPD.S140636 29066881
24. Vaillancourt DE, Newell KM. Changing complexity in human behavior and physiology through aging and disease. Neurobiol aging. 2002;23(1):1–11. doi: 10.1016/s0197-4580(01)00247-0 11755010
25. Vieluf S, Temprado J-J, Berton E, Jirsa VK, Sleimen-Malkoun R. Effects of task and age on the magnitude and structure of force fluctuations: insights into underlying neuro-behavioral processes. BMC Neurosci. 2015;16(1):12.
26. Costa M, Goldberger AL, Peng CK. Multiscale Entropy Analysis of Complex Physiologic Time Series. Phys Rev Lett. 2002;89(6):6–9.
27. Courtiol J, Perdikis D, Petkoski S, Müller V, Huys R, Sleimen-Malkoun R, et al. The multiscale entropy: Guidelines for use and interpretation in brain signal analysis. J Neurosci Methods. 2016;273:175–90. doi: 10.1016/j.jneumeth.2016.09.004 27639660
28. Frank TD, Friedrich R, Beek PJ. Stochastic order parameter equation of isometric force production revealed by drift-diffusion estimates. Phys Rev E—Stat Nonlinear Soft Matter Phys. 2006;74(5):1–11.
29. Newell KM. Constraints on the development of coordination. In: Wade M., Whiting H.T.A., editors. Motor development in children: aspects of coordination and control. Boston, MA: Martinus Nijhoff; 1986. p. 232–56.
30. Slifkin AB, Newell KM. Noise, information transmission, and force variability. J Exp Psychol Hum Percept Perform. 1999;25(3):837–51. doi: 10.1037//0096-1523.25.3.837 10385989
31. Nasreddine ZS, Phillips NA, Bedirian V, Charbonneau S, Whitehead V, Collin I, et al. The Montreal Cognitive Assessment, MoCA: A Brief Screening Tool For Mild Cognitive Impairment. J Am Geriatr Soc. 2005;53(4):695–699. doi: 10.1111/j.1532-5415.2005.53221.x 15817019
32. Mardia KV. Statistics of Directional Data. 1975;37(3):349–93.
33. De Wu S, Wu CW, Lin SG, Wang CC, Lee KY. Time series analysis using composite multiscale entropy. Entropy. 2013;15(3):1069–84.
34. Richman J, Moorman J. Physiological time-series analysis using approximate entropy and sample entropy. Am J Phsiology. 2000;278:H2039–H2049.
35. Costa M, Goldberger AL, Peng CK. Multiscale entropy analysis of biological signals. Phys Rev E—Stat Nonlinear Soft Matter Phys. 2005;71(2):1–18.
36. Costa M, Goldberger AL, Peng CK. Multiscale entropy analysis of complex physiologic time series. Physical review letters. 2002;89(6):068102. doi: 10.1103/PhysRevLett.89.068102 12190613
37. Costa M, Peng CK, Goldberger AL, Hausdorff JM. Multiscale entropy analysis of human gait dynamics. Phys Stat Mech Its Appl. 2003;330(1–2):53–60.
38. Daffertshofer A. Benefits and pitfalls in analyzing noise in dynamical systems—on stochastic differential equations and system identification. In: Huys R, Jirsa VK, editors. Nonlinear Dynamics in Human Behavior. Springer-Verlag; 2010. p. 35–68.
39. Friedrich R, Peinke J. Statistical properties of a turbulent cascade. Phys Nonlinear Phenom. 1997;102:147–55.
40. Vaillancourt DE, Newell KM. Aging and the time and frequency structure of force output variability. J Appl Physiol. 2003;94(3):903–912. doi: 10.1152/japplphysiol.00166.2002 12571125
41. Voelcker-Rehage C, Alberts JL. Age-related changes in grasping force modulation. Exp Brain Res. 2005;166(1):61–70. doi: 10.1007/s00221-005-2342-6 16096780
42. Ofori E, Samson JM, Sosnoff JJ. Age-related differences in force variability and visual display. Exp Brain Res. 2010;203(2):299–306. doi: 10.1007/s00221-010-2229-z 20352199
43. Sosnoff JJ, Newell KM. Information processing limitations with aging in the visual scaling of isometric force. Exp Brain Res. 2006;170(3):423–32. doi: 10.1007/s00221-005-0225-5 16328264
44. Tracy BL, Hitchcock LN, Welsh SJ, Paxton RJ, Feldman-Kothe CE. Visuomotor Correction is a Robust Contributor to Force Variability During Index Finger Abduction by Older Adults. Front Aging Neurosci. 2015;7:229. doi: 10.3389/fnagi.2015.00229 26696881
45. Lindberg P, Ody C, Feydy A, Maier MA. Precision in isometric precision grip force is reduced in middle-aged adults. Exp Brain Res. 2009;193(2):213–24. doi: 10.1007/s00221-008-1613-4 18953529
46. Cole KJ, Beck CL. The stability of precision grip force in older adults. J Mot Behav. 1994;26(2):171–7. doi: 10.1080/00222895.1994.9941671 15753069
47. Cole KJ. Grasp force control in older adults. J Mot Behav. 1991;23(4):251–8. doi: 10.1080/00222895.1991.9942036 14766507
48. Reuter EM, Voelcker-Rehage C, Vieluf S, Godde B. Touch perception throughout working life: Effects of age and expertise. Exp Brain Res. 2012;216(2):287–97. doi: 10.1007/s00221-011-2931-5 22080104
49. Vieluf S, Godde B, Reuter EM, Temprado JJ, Voelcker-Rehage C. Practice Effects in Bimanual Force Control: Does Age Matter? J Mot Behav. 2015;47(1):57–72. doi: 10.1080/00222895.2014.981499 25575223
50. Konczak J, Meeuwsen HJ, Cress ME. Changing affordances in stair climbing: The perception of maximum climbability in young and older adults. J Exp Psychol Hum Percept Perform. 1992;18(3):691. doi: 10.1037//0096-1523.18.3.691 1500869
51. Swinnen SP. Age-related deficits in motor learning and differences in feedback processing during the production of a bimanual coordination pattern. Cogn Neuropsychol. 1998;15(5):439–466. doi: 10.1080/026432998381104 28657466
52. Fozard JL, Gordon-Salant S. Changes in vision and hearing with aging. Handb Psychol Aging. 2001;5:241–266.
53. Snowden RJ, Kavanagh E. Motion perception in the ageing visual system: Minimum motion, motion coherence, and speed discrimination thresholds. Perception. 2006;35(1):9–24. doi: 10.1068/p5399 16491704
54. Welford AT. Signal, noise, performance, and age. Hum Factors. 1981;23(1):97–109. doi: 10.1177/001872088102300109 7228049
55. Kail R. The neural noise hypothesis: Evidence from processing speed in adults with multiple sclerosis. Aging Neuropsychol Cogn. 1997;4(3):157–165.
56. Newell KM, Vaillancourt DE, Sosnoff JJ. Aging, complexity, and motor performance. In: Handbook of the Psychology of Aging (Sixth Edition). Elsevier; 2006. p. 163–182.
57. Newell KM, Deutsch KM, Sosnoff JJ, Mayer-Kress G. Variability in motor output as noise: A default and erroneous proposition. In: Davids K, Bennett S, Newell K, editors. Movement System Variability. Human Kinetics; 2006. p. 3–22.
58. Sosnoff JJ, Newell KM. Aging and motor variability: a test of the neural noise hypothesis. Exp Aging Res. 2011;37(4):377–397. doi: 10.1080/0361073X.2011.590754 21800971
59. Vaillancourt DE, Sosnoff JJ, Newell KM. Age-related changes in complexity depend on task dynamics. J Appl Physiol. 2004;97(1):454–5. doi: 10.1152/japplphysiol.00244.2004 15220326
60. Huys R, Studenka BE, Rheaume NL, Zelaznik HN, Jirsa VK. Distinct timing mechanisms produce discrete and continuous movements. PLoS Comput Biol. 2008;4(4).
61. Huys R, Studenka BE, Zelaznik HN, Jirsa VK. Distinct timing mechanisms are implicated in distinct circle drawing tasks. Neurosci Lett. 2010;472(1):24–8. doi: 10.1016/j.neulet.2010.01.047 20117170
62. Ng AV, Kent-Braun JA. Slowed Muscle Contractile Properties Are Not Associated With a Decreased EMG/Force Relationship in Older Humans. J Gerontol A Biol Sci Med Sci. 1999;54(10):B452–B458. doi: 10.1093/gerona/54.10.b452 10568529
63. Ketcham CJ, Stelmach GE. Movement control in the older adult. In: Technology for adaptive aging. Washington (DC): National Academies Press (US); 2004. p. 92.
64. Sosnoff JJ, Newell KM. Age-Related Loss of Adaptability to Fast Time Scales in Motor Variability. J Gerontol Ser B. 2008;63(6):P344–52.
65. Salthouse TA. The processing-speed theory of adult age differences in cognition. Psychol Rev. 1996;103(3):403. doi: 10.1037/0033-295x.103.3.403 8759042
66. Vaillancourt DE, Larsson L, Newell KM. Effects of aging on force variability, single motor unit discharge patterns, and the structure of 10, 20, and 40 Hz EMG activity. Neurobiol Aging. 2003;24(1):25–35. doi: 10.1016/s0197-4580(02)00014-3 12493548
67. Vaillancourt DE, Sosnoff JJ, Newell KM. Age-related changes in complexity depend on task dynamics. J Appl Physiol. 2004;97(1):454–5. doi: 10.1152/japplphysiol.00244.2004 15220326
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