Children, Young Adults, and Older Adults Choose Different Fast Learning Strategies

in Journal of Aging and Physical Activity

Click name to view affiliation

Dalia Mickeviciene
Search for other papers by Dalia Mickeviciene in
Current site
Google Scholar
PubMedClose
,
Renata Rutkauskaite
Search for other papers by Renata Rutkauskaite in
Current site
Google Scholar
PubMedClose
,
Dovile Valanciene
Search for other papers by Dovile Valanciene in
Current site
Google Scholar
PubMedClose
,
Diana Karanauskiene
Search for other papers by Diana Karanauskiene in
Current site
Google Scholar
PubMedClose
,
Marius Brazaitis
Search for other papers by Marius Brazaitis in
Current site
Google Scholar
PubMedClose
, and
Albertas Skurvydas
Search for other papers by Albertas Skurvydas in
Current site
Google Scholar
PubMedClose
DOI:
https://doi.org/10.1123/japa.2018-0102
Keywords:
age; fast motor learning; intraindividual variability; speed–accuracy task
In Print:
Volume 27: Issue 4
Page Range:
466–472
Restricted access

The aim of the study was to establish whether there were differences in speed–accuracy movement learning strategies between children, young adults, and older adults. A total of 30 boys, 30 young adult men, and 30 older men were seated in a special chair at a table with a Dynamic Parameter Analyzer 1. Participants had to perform a speed–accuracy task with the right-dominant hand. It may be assumed that the motor variables of children are more prone to change during the fast learning process than those of young adults and older adults and that the development of internal models is more changeable in children than in young adults and the older adults during the fast adaptation-based learning process.

Mickeviciene, Brazaitis, and Skurvydas are with the Dept. of Applied Biology and Rehabilitation, Lithuanian Sports University, Kaunas, Lithuania. Rutkauskaite and Karanauskiene are with the Dept. of Health, Physical and Social Education, Lithuanian Sports University, Kaunas, Lithuania. Valanciene, Brazaitis, and Skurvydas are with the Institute of Sport Science and Innovations, Lithuanian Sports University, Kaunas, Lithuania.

Address author correspondence to Dovile Valanciene at dovile.valanciene@lsu.lt.
  • Collapse
  • Expand

Journal of Aging and Physical Activity

Cover Journal of Aging and Physical Activity

  • Anguera, J.A., Reuter-Lorenz, P.A., Willingham, D.T., & Seidler, R.D. (2011). Failure to engage spatial working memory contributes to age-related declines in visuomotor learning. Journal of Cognitive Neuroscience, 23, 11–25. PubMed ID: 20146609 doi:10.1162/jocn.2010.21451

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Bertucco, M., Bhanpuri, N.H., & Sanger, T.D. (2015). Perceived cost and intrinsic motor variability modulate the speed–accuracy trade-off. PLoS ONE, 10(10), 0139988. PubMed ID: 26447874 doi:10.1371/journal.pone.0139988

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Bourgeois, F., & Hay, L. (2003). Information processing and movement optimization during development: kinematics of cyclical pointing in 5- to 11-year-old children. Journal of Motor Behavior, 35(2), 183–195. PubMed ID: 12711588 doi:10.1080/00222890309602132

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Bunce, D., MacDonald, S.W.S., & Hultsch, D.F. (2004). Inconsistency in serial choice decision and motor reaction times dissociate in younger and older adults. Brain and Cognition, 56, 320–327. PubMed ID: 15522770 doi:10.1016/j.bandc.2004.08.006

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Bunce, D., Tzur, M., Ramchurn, A., Gain, F., & Bond, F.W. (2008). Mental health and cognitive function in adults aged 18 to 92 years. The Journals of Gerontology. Series B, Psychological Sciences and Social Sciences, 63, P67–74. doi:10.1093/geronb/63.2.P67

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Dorfberger, S., Adi-Japha, E., & Karni, A. (2009). Sex differences in motor performance and motor learning in children and adolescents: an increasing male advantage in motor learning and consolidation phase gains. Behavioural Brain Research, 198(1), 165–171. doi:10.1016/j.bbr.2008.10.033

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Ehsani, F., Abdollahi, I., Mohseni Bandpei, M.A., Zahiri, N., & Jaberzadeh, S. (2015). Motor learning and movement performance: Older versus younger adults. Basic and Clinical Neuroscience, 6(4), 231–238.

    • Search Google Scholar
    • Export Citation

  • Graveson, J., Bauermeister, S., McKeown, D., & Bunce, D. (2016). Intraindividual reaction time variability, falls, and gait in old age: a systematic review. The Journals of Gerontology. Series B, Psychological Sciences and Social Sciences, 11, 857–864. doi:10.1093/geronb/gbv027

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Harris, C.M., & Wolpert, D.M. (1998). Signal-dependent noise determines motor planning. Nature, 394(6695), 780–784. PubMed ID: 9723616 doi:10.1038/29528

  • Heitz, R.P., & Schall, J.D. (2012). Neural mechanisms of speed–accuracy tradeoff. Neuron, 76(3), 616–628. doi:10.1016/j.neuron.2012.08.030

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Hosseini, E.A., Nguyen, K.P., & Joiner, W.M. (2017). The decay of motor adaptation to novel movement dynamics reveals an asymmetry in the stability of motion state-dependent learning. PLoS Computational Biology, 13(5), e1005492. doi:10.1371/journal.pcbi.1005492

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Huberdeau, D.M., Krakauer, J.W., & Haith, A.M. (2015). Dual-process decomposition in human sensorimotor adaptation. Current Opinion in Neurobiology, 33, 71–77. PubMed ID: 25827272 doi:10.1016/j.conb.2015.03.003

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Hultsch, D.F., MacDonald, S.W., & Dixon, R.A. (2002). Variability in reaction time performance of younger and older adults. The Journals of Gerontology. Series B, Psychological Sciences and Social Sciences, 57, P101–P115. doi:10.1093/geronb/57.2.P101

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Hunter, S.K. (2014). Sex differences in human fatigability: mechanisms and insight to physiological responses. Acta Physiologica, 210(4), 768–789. doi:10.1111/apha.12234

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Janacsek, K., Fiser, J., & Nemeth, D. (2012). The best time to acquire new skills: age-related differences in implicit sequence learning across the human lifespan. Developmental Science, 15, 496–505. doi:10.1111/j.1467-7687.2012.01150.x

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Jansen-Osmann, P., Richter, S., Konczak, J., & Kalveram, K.T. (2002). Force adaptation transfers to untrained workspace regions in children: evidence for developing inverse dynamic motor models. Experimental Brain Research, 143, 212–220. PubMed ID: 11880897 doi:10.1007/s00221-001-0982-8

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Joseph, J., & Willingham, D.B. (2000). Effect of sex and joystick experience on tracking performance. Journal of Motor Behavior, 32, 45–56. PubMed ID: 11008271 doi:10.1080/00222890009601359

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Kofler, M.J., Rapport, M.D., Sarver, D.E., Raiker, J.S., Orban, S.A., Friedman, L.M., & Kolomeyer, E.G. (2013). Reaction time variability in ADHD: a meta-analytic review of 319 studies. Clinical Psychology Review, 33(6), 795–811. PubMed ID: 23872284 doi:10.1016/j.cpr.2013.06.001

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Kuhtz-Buschbeck, J.P., Stolze, H., Boczek-Funcke, A., Johnk, K., Heinrichs, H., & Illert, M. (1998). Kinematic analysis of apprehension movements in children. Behavioural Brain Research, 93, 131–141. PubMed ID: 9659995 doi:10.1016/S0166-4328(97)00147-2

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Molenaar, P.C. (2008). On the implications of the classical ergodic theorems: analysis of developmental processes has to focus on intra-individual variation. Developmental Psychobiology, 50, 60–69. PubMed ID: 18085558 doi:10.1002/dev.20262

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Porter, M.M., Stuart, S., Boij, M., & Lexell, J. (2002). Capillary supply of the tibialis anterior muscle in young, healthy, and moderately active men and women. Journal of Applied Physiology, 92, 1451–1457. doi:10.1152/japplphysiol.00744.2001

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Rival, C., Olivier, I., & Ceyte, H. (2003). Effects of temporal and/or spatial instructions on the speed–accuracy trade-off of pointing movements in children. Neuroscience Letters, 336(1), 65–69. PubMed ID: 12493603 doi:10.1016/S0304-3940(02)01246-6

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Rothenberg-Cunningham, A., & Newell, K.M. (2013). Children's age-related speed-accuracy strategies in intercepting moving targets in two dimensions. Research Quarterly for Exercise and Sport, 84(1), 79–87. doi:10.1080/02701367.2013.762307

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Salinas, E., Scerra, V.E., Hauser, C.K., Costello, M.G., & Stanford, T.R. (2014). Decoupling speed and accuracy in an urgent decision-making task reveals multiple contributions to their trade-off. Frontiers in Neuroscience, 8, 85. PubMed ID: 24795559 doi:10.3389/fnins.2014.00085

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Shadmehr, R., Smith, M.A., & Krakauer, J.W. (2010). Error correction, sensory prediction, and adaptation in motor control. Annual Review of Neuroscience, 33, 89–108. PubMed ID: 20367317 doi:10.1146/annurev-neuro-060909-153135

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Skurvydas, A., & Brazaitis, M. (2010). Is there a correlation between intraindividual variability in isokinetic knee extension/flexion and muscle fatigue? Isokinetics and Exercise Science, 18, 241–246. doi:10.3233/IES-2010-0394

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Skurvydas, A., Brazaitis, M., Kamandulis, S., & Sipaviciene, S. (2010). Muscle damaging exercise affects isometric force fluctuation as well as intraindividual variability of cognitive function. Journal of Motor Behavior, 42, 179–186. PubMed ID: 20418220 doi:10.1080/00222891003751835

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Sleimen-Malkoun, R., Temprado, J.J., & Berton, E. (2013). Age-related dedifferentiation of cognitive and motor slowing: insight from the comparison of Hick-Hyman and Fitts’ laws. Frontiers in Aging Neuroscience, 10, 5–62. doi:10.3389/fnagi.2013.00062

    • Search Google Scholar
    • Export Citation

  • Smith, M.A., Ghazizadeh, A., & Shadmehr, R. (2006). Interacting adaptive processes with different timescales underlie short-term motor learning. PLoS Biology, 4, e179. PubMed ID: 16700627 doi:10.1371/journal.pbio.0040179

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Smits-Engelsman, B.C., Sugden, D., & Duysens, J. (2006). Developmental trends in speed accuracy trade-off in 6–10-year-old children performing rapid reciprocal and discrete aiming movements. Human Movement Science, 25(1), 37–49. PubMed ID: 16442174 doi:10.1016/j.humov.2005.12.002

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Sombric, C.J., Harker, H.M., Sparto, P.J., & Torres-Oviedo, G. (2017). Explicit action switching interferes with the context-specificity of motor memories in older adults. Frontiers in Aging Neuroscience, 9, 1–40. doi:10.3389/fnagi.2017.00040

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Spiegel, M.A., Koester, D., & Schack, T. (2013). The functional role of working memory in the (re) planning and execution of grasping movements. Journal of Experimental Psychology: Human Perception and Performance, 39(5), 1326–1339. PubMed ID: 23339349 doi:10.1037/a0031398

    • Search Google Scholar
    • Export Citation

  • Standage, D., Blohm, G., & Dorris, M.C. (2014). On the neural implementation of the speed–accuracy trade-off. Frontiers in Neuroscience, 13(8), 236. doi:10.3389/fnins.2014.00236

    • Search Google Scholar
    • Export Citation

  • Thura, D., & Cisek, P. (2016). Modulation of premotor and primary motor cortical activity during volitional adjustments of speed–accuracy trade-offs. The Journal of Neuroscience, 36(3), 938–956. PubMed ID: 26791222 doi:10.1523/JNEUROSCI.2230-15.2016

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Ullén, F., Forsman, L., Blom, O., Karabanov, A., & Madison, G. (2008). Intelligence and variability in a simple timing task share neural substrates in the prefrontal white matter. The Journal of Neuroscience, 28, 4238–4243. doi:10.1523/JNEUROSCI.0825-08.2008

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Ungerleider, L.G., Doyon, J., & Karni, A. (2002). Imaging brain plasticity during motor skill learning. Neurobiology of Learning and Memory, 78, 553–564. PubMed ID: 12559834 doi:10.1006/nlme.2002.4091

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Vandermorris, S., Murphy, K.J., & Troyer, A.K. (2013). Age-related elevations in intraindividual variability on associative memory tasks. Neuropsychology, Development, and Cognition. Section B, Aging, Neuropsychology and Cognition, 20(6), 722–734. PubMed ID: 23451864 doi:10.1080/13825585.2013.772557

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Vaquero, E., Cardoso, M.J., Vázquez-Marrufo, M., & Gomez, C.M. (2004). Gender differences in event-related potentials during visual-spatial attention. International Journal of Neuroscience, 114(4), 541–557. PubMed ID: 15195357 doi:10.1080/00207450490422056

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Walsh, E.G., & Wright, G.W. (1987). Inertia, resonant frequency, stiffness and kinetic energy of the human forearm. Quarterly Journal of Experimental Physiology, 72, 161–170. PubMed ID: 3588828 doi:10.1113/expphysiol.1987.sp003060

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Wolpert, D.M., Diedrichsen, J., & Flanagan, J.R. (2011). Principles of sensorimotor learning. Nature Reviews Neuroscience, 12, 739–751. PubMed ID: 22033537 doi:10.1038/nrn3112

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Wolpert, D.M., & Flanagan, J.R. (2016). Computations underlying sensorimotor learning. Current Opinion in Neurobiology, 37, 7–11. PubMed ID: 26719992 doi:10.1016/j.conb.2015.12.003

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Yan, J.H., Thomas, J.R., Stelmach, G.E., & Thomas, K.T. (2000). Developmental features of rapid aiming arm movements across the lifespan. Journal of Motor Behavior, 32, 121–140. PubMed ID: 11005944 doi:10.1080/00222890009601365

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Yao, C., Stawski, R.S., Hultsch, D.F., & MacDonald, S.W. (2016). Selective attrition and intraindividual variability in response time moderate cognitive change. Journal of Clinical and Experimental Neuropsychology, 38(2), 227–237. PubMed ID: 26647008 doi:10.1080/13803395.2015.1102869

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Zuoza, A., Skurvydas, A., Mickeviciene, D., Gutnik, B., Zouziene, D., Penchev, B., & Pencheva, S. (2009). Behavior of dominant and nondominant hands during ballistic protractive target-directed movements. Fiziologija Cheloveka, 35, 62–70.

    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 2221 786 17
Full Text Views 61 2 2
PDF Downloads 35 5 2