The effect of age and perturbation time on online control during rapid pointing

English version

Autoři: Jessica L. O’Rielly ^aff001; Anna Ma-Wyatt ^aff001
Působiště autorů: School of Psychology, University of Adelaide, Adelaide, South Australia, Australia ^aff001
Vyšlo v časopise: PLoS ONE 14(9)
Kategorie: Research Article
doi: https://doi.org/10.1371/journal.pone.0222219

Souhrn

Visual and proprioceptive information is used differently at different phases of a reach. The time at which a target perturbation occurs during a reach therefore has a significant impact on how an individual can compensate for this perturbation though online control. With healthy ageing, there are notable changes to both sensory and motor control that impact motor performance. However, how the online control process changes with age is not yet fully understood. We used a target perturbation paradigm and manipulated the time at which a target perturbation occurred during the reach to investigate how healthy ageing impacts sensorimotor control. We measured how the latency of the correction and the magnitude of the corrective response changed with perturbation time and quantified the difference across groups using a percentage difference measure. For both groups, online corrections to early perturbations were more easily accounted for than those to late perturbations, despite late perturbations eliciting faster correction latencies. While there was no group difference in accuracy, older participants were slower overall and produced a correction to a change in target location proportionally less often despite similar correction latencies. We speculate that the differences in the time during the reach that the correction is first identified may explain the differences in correction latencies observed between the perturbation time conditions.

Klíčová slova:

Physical sciences – Physics – Classical mechanics – Deceleration – Acceleration – Motion – Velocity – Kinematics – Biology and life sciences – Developmental biology – Organism development – Physiology – Physiological processes – Neuroscience – Sensory systems – Medicine and health sciences – Aging – People and places – Population groupings – Age groups – Ecology and environmental sciences – Soil science – Soil perturbation

Zdroje

1. Elliot D., Hansen S., Grierson L., Lyons J., Bennett S., and Heyes S. Goal directed aiming: two components but multiple processes. Psychology Bulletin. 2011; 136, 1023–44

2. Liu D., Todorov E. Evidence for the flexible sensorimotor strategies predicted by optimal feedback control. Journal of Neuroscience. 2007; 27, 9354–9368. doi: 10.1523/JNEUROSCI.1110-06.2007 17728449

3. Paulignan Y., Mackenzie C., Marteniuk R., Jeannerod M. Selective perturbation of visual input during prehension movements. The effects of changing object position. Experimental Brain Research. 1991b; 83, 502–512. doi: 10.1007/bf00229827 2026193

4. van Beers RJ, Baraduc P, Wolpert DM. Role of uncertainty in sensorimotor control. Philosophical Transactions of the Royal Society of London. Series B: Biological Sciences. 2002 Aug 29;357(1424):1137–45. doi: 10.1098/rstb.2002.1101 12217180

5. Desmurget M, Grafton S. Forward modelling allows feedback control for fast reaching movements. Trends in cognitive sciences. 2000 Nov 1;4(11):423–31. 11058820

6. Owsley C. Aging and vision. Vision research. 2011 Jul 1;51(13):1610–22. doi: 10.1016/j.visres.2010.10.020 20974168

7. Hinton G. Parallel computations for controlling an arm. Journal of motor behavior. 1984 Jun 1;16(2):171–94. doi: 10.1080/00222895.1984.10735317 14713664

8. Flash T, Henis E. Arm trajectory modifications during reaching towards visual targets. Journal of cognitive Neuroscience. 1991 Jul;3(3):220–30. doi: 10.1162/jocn.1991.3.3.220 23964837

9. Hoff B, Arbib MA. Models of trajectory formation and temporal interaction of reach and grasp. Journal of motor behavior. 1993 Sep 1;25(3):175–92. doi: 10.1080/00222895.1993.9942048 12581988

10. Sarlegna F. Impairment of online control of reaching movements with aging: A double-step study. Neuroscience Letters. 2006; 403, 309–314. doi: 10.1016/j.neulet.2006.05.003 16723186

11. Goggin NL, Meeuwsen HJ. Age-related differences in the control of spatial aiming movements. Research Quarterly for Exercise and Sport. 1992 Dec 1;63(4):366–72. doi: 10.1080/02701367.1992.10608758 1439161

12. Kimura D., Kadota K., Kinoshita H. The impact of ageing on the spatial accuracy of quick corrective arm movements in response to sudden target displacement during reaching. Frontiers in Ageing Neuroscience. 2015; 7, 182.

13. Rossit S., Harvey M. Age-related differences in corrected and inhibited pointing movements. Experimental Brain Research. 2008; 185, 1–10. doi: 10.1007/s00221-007-1126-6 17899041

14. Prablanc C., Martin O. Automatic control during hand reaching at undetected two-dimensional target displacements. Journal of Neurophysiology. 1992; 67, 455–469. doi: 10.1152/jn.1992.67.2.455 1569469

15. Ma-Wyatt A., McKee S.P. Visual information throughout a reach determines end point precision. Experimental Brain Research. 2007; 179:55–64. doi: 10.1007/s00221-006-0767-1 17109109

16. Sober S., Sabes P. Flexible strategies for sensory integration during motor planning. Nature Neuroscience. 2005; 8, 490–497. doi: 10.1038/nn1427 15793578

17. Komilis E., Pélisson D., Prablanc C. Error Processing in Pointing at Randomly Feedback-Induced Double-Step Stimuli. Journal of Motor Behaviour. 1993; 25, 299–308.

18. O’Rielly J. l., Ma-Wyatt, A. Changes to online control and eye-hand coordination with healthy ageing. Human Movement Science. 2018; 59, 244–257. doi: 10.1016/j.humov.2018.04.013 29747069

19. Song J H., Nakayama, K. Target selection in visual search as revealed by movement trajectories. Vision Research. 2007; 48, 853–861.

20. Ketcham CJ, Stelmach GE. Motor control of older adults. In: Ekerdt DJ, Applebaum RA, Holden KC, Post SG, Rockwood K, Schulz R, et al editors. Encyclopedia of aging. New York: Macmillan Reference USA; 2002

21. Folstein MF, Folstein SE, McHugh PR. “Mini-mental state”: a practical method for grading the cognitive state of patients for the clinician. Journal of psychiatric research. 1975 Nov 1;12(3):189–98. 1202204

22. Lawton MP, Brody EM. Assessment of older people: self-maintaining and instrumental activities of daily living. The gerontologist. 1969 Oct 1;9(3_Part_1):179–86.

23. Pelli DG, Robson JG. The design of a new letter chart for measuring contrast sensitivity. Clinical Vision Sciences 1988.

24. Snellen H. Letterproeven tot Bepaling der Gezigtsscherpte. In A Bennett. Ophthalmic test types. British Journal of Physiological Optometry. 1962. 22, 238–71

25. The Randot Circles (Stereo Optical, Inc., Chicago, USA http://www.stereooptical.com/)

26. Oldfield R, C. The assessment and analysis of handedness: the Edinburg Inventory Neuropsychologia. 1971, 9, 97–113

27. Brainard D. H. The psychophysics toolbox. Spatial Vision. 1997; 10, 433–436. 9176952

28. Pelli D. The VideoToolbox software for visual psychophysics: Transforming numbers into movies. Spatial Vision. 1997; 10, 437–442. 9176953

29. Atkeson C., Hollerbach J. Kinematic features of unrestrained vertical arm movements. The Journal of Neuroscience. 1985; 5, 2318–2330. 4031998

30. Leys C., Ley C., Klein O., Bernard P., Licata L. Detecting outliers: Do not use standard deviation around the mean, use absolute deviation around the median. Journal of Experimental Social Psychology. 2013; 49, 764–766.

31. Verneau M., van der Kamp J., de Looze Geert M., Savelsbergh J. Age effects on voluntary and automatic adjustments in anti-pointing tasks. Experimental Brain Research. 2016; 234, 419–428. doi: 10.1007/s00221-015-4459-6 26497989

32. Cressman EK, Cameron BD, Lam MY, Franks IM, Chua R Movement duration does not affect automatic online control. Human Movement Sciience. 2010. 29(6):871–881

33. Oostwoud Wijdenes L. O., Brenner E. M., Smeets J. B. Analysis of methods to determine the latency of online movement adjustments. Behavioural Research Methods. 2014a; 46, 131–139.

34. Fisk J., Goodale M. The organization of eye and limb movements during unrestricted reaching to targets in contralateral and ipsilateral visual space. Experimental Brain Research. 1985; 60, 15–178.

35. Carey D., Hargreaves E., Goodale M. Reaching to ipsilateral or contralateral targets: within-hemisphere visuomotor processing cannot explain hemispatial differences in motor control. Experimental Brain Research. 1996; 112:496–504. doi: 10.1007/bf00227955 9007551

36. Wilson P., Hyde C. The development of rapid online control in children aged 6–12 years: Reaching performance. Human Movement Science. 2013; 32, 1138–1150. doi: 10.1016/j.humov.2013.02.008 23932022

37. IBM Corp. IBM SPSS Statistics for Windows. 2017. Version 25.0. Armonk, NY: IBM Corp.

38. Cheterikov A., Filippova M. How to tell a wife from a hat: Affective feedback in perceptual categorization. Acta Psychologica. 2014; 151, 206–213. doi: 10.1016/j.actpsy.2014.06.012 25051145

39. Snijders T., Bosker R. Multilevel analysis: An introduction to basic and advanced multilevel modelling. London: Sage Publications. 1999.

40. Nakagawa S., Schielzeth H. A general and simple method for obtaining R2 from generalized linear mixed-effects models. Methods in Ecology and Evolution. 2013; 4, 133–142.

41. Johnson P. Extension of Nakagawa Schielzeth’s R2GLMM to random slopes models. Methods in Ecology and Evolution. 2014; 5, 944–946. doi: 10.1111/2041-210X.12225 25810896

42. Jamovi Project. Jamovi. 2017. Version 0.9.1.9 [Computer Software] Available from https://www.jamovi.org.

43. Fitts PM. The information capacity of the human motor system in controlling the amplitude of movement. Journal of experimental psychology. 1954 Jun;47(6):381. 13174710

44. Sarlegna F., Mutha P. The influence of visual target information on the online control of movements. Vision Research. 2015; 110, 144–154. doi: 10.1016/j.visres.2014.07.001 25038472

45. Teeken J., Adam J., Pass F., van Boxtel M. Effects of age and gender on discrete and reciprocal aiming movements. Psychology and Aging. 1996; 11, 195–198. 8795047

46. Chua R., Elliott D. Visual regulation of manual aiming. Human Movement Science. 1993; 12, 365–401.

47. Welsh T., Higgings L., Elliot D. Are there age related differences in learning to optimize speed, accuracy and energy expenditure? Human Movement Science. 2007; 26, 892912.

48. Ketcham C., Stelmach G. Age- related declines in motor control, in The handbook of the Psychology of Aging, 5th ed., Birren J. Eand Schaie K. W., Eds., Academic, San Diego, CA, pp. 313–348; 2011.

49. Saunders J. A., Knill D. C. Humans use continuous visual feedback from the hand to control both the direction and distance of pointing movements. Experimental Brain Research. 2005; 162, 458–473. doi: 10.1007/s00221-004-2064-1 15754182

50. Yan J. H., Thomas J. R., Stelmach G. E., Thomas K. T. Developmental features of rapid aiming arm movements across the lifespan. Journal Motor Behaviour. 2000. 32, 121–140.

51. Salthouse T. Ageing and measures of processing speed. Biological Psychology. 2000. 54, 25–54.

52. Seidler R., Bernard J., Burutolu T., Fling B., Gordon M., Gwin J., et al. Motor Control and Ageing: Links to Age-related Brain Structural, Functional, and Biochemical Effects. Neuroscience and Biobehavioural Reviews. 2010, 23, 721–733.

53. Morgan M, Phillips JG, Bradshaw JL, Mattingley JB, Iansek R, Bradshaw JA. Age-related motor slowness: Simply strategic?. Journal of gerontology. 1994 May 1;49(3):M133–9. doi: 10.1093/geronj/49.3.m133 8169335

The effect of age and perturbation time on online control during rapid pointing

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