Patterns of Movement Performance and Consistency From Childhood to Old Age

in Motor Control

Click name to view affiliation

Jessica Prebor School of Rehabilitation Sciences, Old Dominion University, Norfolk, VA, USA

Search for other papers by Jessica Prebor in
Current site
Google Scholar
PubMed Close
https://orcid.org/0000-0002-5201-9630 *
,
Brittany Samulski School of Rehabilitation Sciences, Old Dominion University, Norfolk, VA, USA

Search for other papers by Brittany Samulski in
Current site
Google Scholar
PubMed Close
https://orcid.org/0000-0003-4519-3347
,
Cortney Armitano-Lago Department of Exercise and Sport Science, The University of North Carolina at Chapel Hill, Chapel Hill, NC, USA

Search for other papers by Cortney Armitano-Lago in
Current site
Google Scholar
PubMed Close
https://orcid.org/0000-0003-1412-5755
, and
Steven Morrison School of Rehabilitation Sciences, Old Dominion University, Norfolk, VA, USA

Search for other papers by Steven Morrison in
Current site
Google Scholar
PubMed Close
https://orcid.org/0000-0001-7485-0305
DOI:
https://doi.org/10.1123/mc.2022-0006
Keywords:
motor function; U shape; variability; aging
First Published Online:
09 Nov 2022
In Print:
Volume 27: Issue 2
Page Range:
258–274
Restricted access

It is widely accepted that the general process of aging can be reflected by changes in motor function. Typically, optimal performance of a given motor task is observed for healthy young adults with declines being observed for individuals at either end of the lifespan. This study was designed to examine differences in the average and variability (i.e., intraindividual variability) of chewing, simple reaction time, postural control, and walking responses. For this study, 15 healthy children, 15 young adults, and 15 older adults participated. Our results indicated the movement performance for the reaction time and postural sway followed a U shape with young adults having faster reaction times and decreased postural sway compared to the children and older adults. However, this pattern was not preserved across all motor tasks with no age differences emerging for (normalized) gait speed, while chewing rates followed a U-shaped curve with older adults and children chewing at faster rates. Taken together, these findings would indicate that the descriptive changes in motor function with aging are heavily influenced by the nature of the task being performed and are unlikely to follow a singular pattern.

  • Collapse
  • Expand

Motor Control

Cover Motor Control

  • Almotairy, N., Kumar, A., Trulsson, M., & Grigoriadis, A. (2018). Development of the jaw sensorimotor control and chewing—A systematic review. Physiology & Behavior, 194, 456–465. https://doi.org/10.1016/j.physbeh.2018.06.037

    • Search Google Scholar
    • Export Citation

  • Badawi, Y., & Nishimune, H. (2020). Impairment mechanisms and intervention approaches for aged human neuromuscular junctions. Frontiers in Molecular Neuroscience, 13, Article 568426. https://doi.org/10.3389/fnmol.2020.568426

    • PubMed
    • Search Google Scholar
    • Export Citation

  • Bartzokis, G., Beckson, M., Lu, P.H., Nuechterlein, K.H., Edwards, N., & Mintz, J. (2001). Age-related changes in frontal and temporal lobe volumes in men: A magnetic resonance imaging study. Archives of General Psychiatry, 58(5), 461–465. https://doi.org/10.1001/archpsyc.58.5.461

    • Search Google Scholar
    • Export Citation

  • Batterham, P.J., Bunce, D., Mackinnon, A.J., & Christensen, H. (2014). Intra-individual reaction time variability and all-cause mortality over 17 years: A community-based cohort study. Age and Ageing, 43(1), 84–90. https://doi.org/10.1093/ageing/aft116

    • Search Google Scholar
    • Export Citation

  • Bauermeister, S., Sutton, G., Mon-Williams, M., Wilkie, R., Graveson, J., Cracknell, A., Wilkinson, C., Holt, R., & Bunce, D. (2017). Intraindividual variability and falls in older adults. Neuropsychology, 31(1), 20–27. https://doi.org/10.1037/neu0000328

    • PubMed
    • Search Google Scholar
    • Export Citation

  • Bellis, C.J. (1933). Reaction time and chronological age. Proceedings of the Society for Experimental Biology and Medicine, 30(6), 801–803. https://doi.org/10.3181/00379727-30-6682

    • Search Google Scholar
    • Export Citation

  • Bielak, A.A.M., Cherbuin, N., Bunce, D., & Anstey, K.J. (2014). Intraindividual variability is a fundamental phenomenon of aging: Evidence from an 8-year longitudinal study across young, middle, and older adulthood. Developmental Psychology, 50(1), 143–151. https://doi.org/10.1037/a0032650

    • PubMed
    • Search Google Scholar
    • Export Citation

  • Bielak, A.A.M., Hultsch, D.F., Strauss, E., MacDonald, S.W.S., & Hunter, M.A. (2010). Intraindividual variability is related to cognitive change in older adults: Evidence for within-person coupling. Psychology and Aging, 25(3), 575–586. https://doi.org/10.1037/a0019503

    • PubMed
    • Search Google Scholar
    • Export Citation

  • Bohannon, R.W. (2019). Grip strength: An indispensable biomarker for older adults. Clinical Interventions in Aging, 14, 1681–1691. https://doi.org/10.2147/CIA.S194543

    • PubMed
    • Search Google Scholar
    • Export Citation

  • Casamento-Moran, A., Fleeman, R., Chen, Y.-T., Kwon, M., Fox, E.J., Yacoubi, B., & Christou, E.A. (2018). Neuromuscular variability and spatial accuracy in children and older adults. Journal of Electromyography and Kinesiology, 41, 27–33. https://doi.org/10.1016/j.jelekin.2018.04.011

    • PubMed
    • Search Google Scholar
    • Export Citation

  • Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Routledge. https://doi.org/10.4324/9780203771587

  • Craik, F.I.M., & Bialystok, E. (2006). Cognition through the lifespan: Mechanisms of change. Trends in Cognitive Sciences, 10(3), 131–138. https://doi.org/10.1016/j.tics.2006.01.007

    • PubMed
    • Search Google Scholar
    • Export Citation

  • De Guio, F., Jacobson, S.W., Molteno, C.D., Jacobson, J.L., & Meintjes, E.M. (2012). Functional magnetic resonance imaging study comparing rhythmic finger tapping in children and adults. Pediatric Neurology, 46(2), 94–100. https://doi.org/10.1016/j.pediatrneurol.2011.11.019

    • PubMed
    • Search Google Scholar
    • Export Citation

  • Der, G., & Deary, I.J. (2006). Age and sex differences in reaction time in adulthood: Results from the United Kingdom health and lifestyle survey. Psychology and Aging, 21(1), 62–73. https://doi.org/10.1037/0882-7974.21.1.62

    • PubMed
    • Search Google Scholar
    • Export Citation

  • Deschenes, M.R. (2011). Motor unit and neuromuscular junction remodeling with aging. Current Aging Science, 4(3), 209–220. https://doi.org/10.2174/1874609811104030209

    • PubMed
    • Search Google Scholar
    • Export Citation

  • Doyon, J., Penhune, V., & Ungerleider, L.G. (2003). Distinct contribution of the cortico-striatal and cortico-cerebellar systems to motor skill learning. Neuropsychologia, 41(3), 252–262. https://doi.org/10.1016/S0028-3932(02)00158-6

    • PubMed
    • Search Google Scholar
    • Export Citation

  • Dykiert, D., Der, G., Starr, J.M., & Deary, I.J. (2012). Sex differences in reaction time mean and intraindividual variability across the life span. Developmental Psychology, 48(5), 1262–1276. https://doi.org/10.1037/a0027550

    • PubMed
    • Search Google Scholar
    • Export Citation

  • Enoka, R.M., Christou, E.A., Hunter, S.K., Kornatz, K.W., Semmler, J.G., Taylor, A.M., & Tracy, B.L. (2003). Mechanisms that contribute to differences in motor performance between young and old adults. Journal of Electromyography and Kinesiology, 13(1), 1–12. https://doi.org/10.1016/S1050-6411(02)00084-6

    • Search Google Scholar
    • Export Citation

  • Fagot, D., Mella, N., Borella, E., Ghisletta, P., Lecerf, T., & De Ribaupierre, A. (2018). Intra-individual variability from a lifespan perspective: A comparison of latency and accuracy measures. Journal of Intelligence, 6(1), Article 16. https://doi.org/10.3390/jintelligence6010016

    • PubMed
    • Search Google Scholar
    • Export Citation

  • Faul, F., Erdfelder, E., Lang, A.-G., & Buchner, A. (2007). G*Power 3: A flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behavior Research Methods, 39(2), 175–191. https://doi.org/10.3758/BF03193146

    • PubMed
    • Search Google Scholar
    • Export Citation

  • Fjell, A.M., Westlye, L.T., Amlien, I.K., & Walhovd, K.B. (2011). Reduced white matter integrity is related to cognitive instability. The Journal of Neuroscience, 31(49), 18060–18072. https://doi.org/10.1523/JNEUROSCI.4735-11.2011

    • PubMed
    • Search Google Scholar
    • Export Citation

  • Fox, E.J., Moon, H., Kwon, M., Chen, Y.-T., & Christou, E.A. (2014). Neuromuscular control of goal-directed ankle movements differs for healthy children and adults. European Journal of Applied Physiology, 114(9), 1889–1899. https://doi.org/10.1007/s00421-014-2915-9

    • PubMed
    • Search Google Scholar
    • Export Citation

  • Frank, U., van den Engel-Hoek, L., Nogueira, D., Schindler, A., Adams, S., Curry, M., & Huckabee, M.-L. (2019). International standardisation of the test of masticating and swallowing solids in children. Journal of Oral Rehabilitation, 46(2), 161–169. https://doi.org/10.1111/joor.12728

    • PubMed
    • Search Google Scholar
    • Export Citation

  • Hadders-Algra, M. (2018). Early human motor development: From variation to the ability to vary and adapt. Neuroscience and Biobehavioral Reviews, 90, 411–427. https://doi.org/10.1016/j.neubiorev.2018.05.009

    • Search Google Scholar
    • Export Citation

  • Hultsch, D.F., MacDonald, S.W.S., & 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(2), P101–P115. https://doi.org/10.1093/geronb/57.2.P101

    • PubMed
    • Search Google Scholar
    • Export Citation

  • Karlsson, S., Persson, M., & Carlsson, G.E. (1991). Mandibular movement and velocity in relation to state of dentition and age. Journal of Oral Rehabilitation, 18(1), 1–8. https://doi.org/10.1111/j.1365-2842.1991.tb00024.x

    • PubMed
    • Search Google Scholar
    • Export Citation

  • Kennedy, K.M., & Raz, N. (2005). Age, sex and regional brain volumes predict perceptual-motor skill acquisition. Cortex, 41(4), 560–569. https://doi.org/10.1016/S0010-9452(08)70196-5

    • PubMed
    • Search Google Scholar
    • Export Citation

  • Kiliaridis, S., Karlsson, S., & Kjellberg, H. (1991). Characteristics of masticatory mandibular movements and velocity in growing individuals and young adults. Journal of Dental Research, 70(10), 1367–1370. https://doi.org/10.1177/00220345910700101001

    • Search Google Scholar
    • Export Citation

  • Li, E.K., Lee, S., Patel, S.S., & Sereno, A.B. (2018). Age-dependent performance on pro-point and anti-point tasks. Frontiers in Psychology, 9, Article 2519. https://doi.org/10.3389/fpsyg.2018.02519

    • PubMed
    • Search Google Scholar
    • Export Citation

  • Lipsitz, L.A., & Goldberger, A.L. (1992). Loss of “complexity” and aging. Potential applications of fractals and chaos theory to senescence. JAMA, 267(13), 1806–1809. https://doi.org/10.1001/jama.1992.03480130122036

    • PubMed
    • Search Google Scholar
    • Export Citation

  • Ludwig, O., Kelm, J., Hammes, A., Schmitt, E., & Fröhlich, M. (2020). Neuromuscular performance of balance and posture control in childhood and adolescence. Heliyon, 6(7), Article e04541. https://doi.org/10.1016/j.heliyon.2020.e04541

    • PubMed
    • Search Google Scholar
    • Export Citation

  • Luo, N., Sui, J., Abrol, A., Lin, D., Chen, J., Vergara, V.M., Fu, Z., Du, Y., Damaraju, E., Xu, Y., Turner, J.A., & Calhoun, V.D. (2019). Age-related structural and functional variations in 5967 individuals across the adult lifespan. Human Brain Mapping, 41(7), 1725–1737. https://doi.org/10.1002/hbm.24905

    • Search Google Scholar
    • Export Citation

  • Machek, S.B. (2018). Mechanisms of sarcopenia: Motor unit remodelling and muscle fibre type shifts with ageing. The Journal of Physiology, 596(16), 3467–3468. https://doi.org/10.1113/JP276586

    • PubMed
    • Search Google Scholar
    • Export Citation

  • Magallón, S., Narbona, J., & Crespo-Eguílaz, N. (2016). Acquisition of motor and cognitive skills through repetition in typically developing children. PLoS One, 11(7), Article e0158684. https://doi.org/10.1371/journal.pone.0158684

    • PubMed
    • Search Google Scholar
    • Export Citation

  • Marmon, A.R., Pascoe, M.A., Schwartz, R.S., & Enoka, R.M. (2011). Associations among strength, steadiness, and hand function across the adult life span. Medicine & Science in Sports & Exercise, 43(4), 560–567. https://doi.org/10.1249/MSS.0b013e3181f3f3ab

    • Search Google Scholar
    • Export Citation

  • Maruta, J., Spielman, L.A., Rajashekar, U., & Ghajar, J. (2017). Visual tracking in development and aging. Frontiers in Neurology, 8, Article 640. https://doi.org/10.3389/fneur.2017.00640

    • PubMed
    • Search Google Scholar
    • Export Citation

  • Mcauley, J., Jones, M., Holub, S., Johnston, H., & Miller, N. (2006). The time of our lives: Life span development of timing and event tracking. Journal of Experimental Psychology. General, 135(3), 348–367. https://doi.org/10.1037/0096-3445.135.3.348

    • PubMed
    • Search Google Scholar
    • Export Citation

  • Mella, N., de Ribaupierre, S., Eagleson, R., & de Ribaupierre, A. (2013). Cognitive intraindividual variability and white matter integrity in aging. The Scientific World Journal, 2013, Article 350623. https://doi.org/10.1155/2013/350623

    • PubMed
    • Search Google Scholar
    • Export Citation

  • Mella, N., Fagot, D., & Ribaupierre, A.D. (2016). Dispersion in cognitive functioning: Age differences over the lifespan. Journal of Clinical and Experimental Neuropsychology, 38(1), 111–126. https://doi.org/10.1080/13803395.2015.1089979

    • PubMed
    • Search Google Scholar
    • Export Citation

  • Morrison, S., & Newell, K.M. (2017). Aging and slowing of the neuromotor system. In N.A. Pachana (Ed.), Encyclopedia of geropsychology (pp. 215–226). Springer. https://doi.org/10.1007/978-981-287-082-7_230

    • Search Google Scholar
    • Export Citation

  • Morrison, S., & Newell, K.M. (2019). Intraindividual variability of neuromotor function predicts falls risk in older adults and those with type 2 diabetes. Journal of Motor Behavior, 51(2), 151–160. https://doi.org/10.1080/00222895.2018.1440524

    • PubMed
    • Search Google Scholar
    • Export Citation

  • Newell, K.M., Liu, Y.T., & Mayer-Kress, G. (2001). Time scales in motor learning and development. Psychological Review, 108(1), 57–82. https://doi.org/10.1037/0033-295X.108.1.57

    • PubMed
    • Search Google Scholar
    • Export Citation

  • Newell, K.M., Mayer-Kress, G., & Liu, Y.-T. (2009). Aging, time scales, and sensorimotor variability. Psychology and Aging, 24(4), 809–818. https://doi.org/10.1037/a0017911

    • PubMed
    • Search Google Scholar
    • Export Citation

  • Papargyriou, G., Kjellberg, H., & Kiliaridis, S. (2000). Changes in masticatory mandibular movements in growing individuals: A six-year follow-up. Acta Odontologica Scandinavica, 58(3), 129–134. https://doi.org/10.1080/000163500429262

    • PubMed
    • Search Google Scholar
    • Export Citation

  • Piasecki, M., Ireland, A., Jones, D.A., & McPhee, J.S. (2016). Age-dependent motor unit remodelling in human limb muscles. Biogerontology, 17(3), 485–496. https://doi.org/10.1007/s10522-015-9627-3

    • PubMed
    • Search Google Scholar
    • Export Citation

  • Prebor, J., Samulski, B., Armitano-Lago, C., & Morrison, S. (2021). Chewing entrains cyclical actions but interferes with discrete actions in children. Journal of Motor Behavior, 53(3), 364–372. https://doi.org/10.1080/00222895.2020.1787319

    • PubMed
    • Search Google Scholar
    • Export Citation

  • Rafiei, F., & Rahnev, D. (2021). Qualitative speed-accuracy tradeoff effects that cannot be explained by the diffusion model under the selective influence assumption. Scientific Reports, 11(1), 45. https://doi.org/10.1038/s41598-020-79765-2

    • PubMed
    • Search Google Scholar
    • Export Citation

  • Rosano, C., Aizenstein, H., Brach, J., Longenberger, A., Studenski, S., & Newman, A.B. (2008). Special article: Gait measures indicate underlying focal gray matter atrophy in the brain of older adults. The Journals of Gerontology. Series A, Biological Sciences and Medical Sciences, 63(12), 1380–1388. https://doi.org/10.1093/gerona/63.12.1380

    • PubMed
    • Search Google Scholar
    • Export Citation

  • Salat, D.H., Buckner, R.L., Snyder, A.Z., Greve, D.N., Desikan, R.S.R., Busa, E.J.C., Morris, A.M., Dale, A.M., & Bruce, F. (2004). Thinning of the cerebral cortex in aging. Cerebral Cortex, 14(7), 721–730. https://doi.org/10.1093/cercor/bhh032

    • PubMed
    • Search Google Scholar
    • Export Citation

  • Salthouse, T.A. (1979). Adult age and the speed-accuracy trade-off. Ergonomics, 22(7), 811–821. https://doi.org/10.1080/00140137908924659

  • Samulski, B., Prebor, J., Armitano, C., & Morrison, S. (2019). Coupling of motor oscillators—What really happens when you chew gum and walk? Neuroscience Letters, 698, 90–96. https://doi.org/10.1016/j.neulet.2019.01.016

    • PubMed
    • Search Google Scholar
    • Export Citation

  • Samulski, B., Prebor, J., Armitano-Lago, C., & Morrison, S. (2020). Age-related changes in neuromotor function when performing a concurrent motor task. Experimental Brain Research, 238, 565–574. https://doi.org/10.1007/s00221-020-05736-8

    • PubMed
    • Search Google Scholar
    • Export Citation

  • Seidler, R.D., Bernard, J.A., Burutolu, T.B., Fling, B.W., Gordon, M.T., Gwin, J.T., Kwak, Y., & Lipps, D.B. (2010). Motor control and aging: Links to age-related brain structural, functional, and biochemical effects. Neuroscience and Biobehavioral Reviews, 34(5), 721–733. https://doi.org/10.1016/j.neubiorev.2009.10.005

    • PubMed
    • Search Google Scholar
    • Export Citation

  • Siegler, R.S. (1994). Cognitive variability: A key to understanding cognitive development. Current Directions in Psychological Science, 3(1), 1–5. https://doi.org/10.1111/1467-8721.ep10769817

    • Search Google Scholar
    • Export Citation

  • Simonsohn, U. (2018). Two lines: A valid alternative to the invalid testing of U-shaped relationships with quadratic regressions. Advances in Methods and Practices in Psychological Science, 1(4), 538–555. https://doi.org/10.1177/2515245918805755

    • Search Google Scholar
    • Export Citation

  • Stergiou, N., & Decker, L.M. (2011). Human movement variability, nonlinear dynamics, and pathology: Is there a connection? Human Movement Science, 30(5), 869–888. https://doi.org/10.1016/j.humov.2011.06.002

    • Search Google Scholar
    • Export Citation

  • Sullivan, E.V., Rohlfing, T., & Pfefferbaum, A. (2010). Quantitative fiber tracking of lateral and interhemispheric white matter systems in normal aging: Relations to timed performance. Neurobiology of Aging, 31(3), 464–481. https://doi.org/10.1016/j.neurobiolaging.2008.04.007

    • PubMed
    • Search Google Scholar
    • Export Citation

  • Sullivan, E.V., Rose, J., Rohlfing, T., & Pfefferbaum, A. (2009). Postural sway reduction in aging men and women: Relation to brain structure, cognitive status, and stabilizing factors. Neurobiology of Aging, 30(5), 793–807. https://doi.org/10.1016/j.neurobiolaging.2007.08.021

    • PubMed
    • Search Google Scholar
    • Export Citation

  • Takahashi, C.D., Nemet, D., Rose-Gottron, C.M., Larson, J.K., Cooper, D.M., & Reinkensmeyer, D.J. (2003). Neuromotor noise limits motor performance, but not motor adaptation, in children. Journal of Neurophysiology, 90(2), 703–711. https://doi.org/10.1152/jn.01173.2002

    • Search Google Scholar
    • Export Citation

  • Tamnes, C.K., Fjell, A.M., Westlye, L.T., Østby, Y., & Walhovd, K.B. (2012). Becoming consistent: Developmental reductions in intraindividual variability in reaction time are related to white matter integrity. The Journal of Neuroscience, 32(3), 972–982. https://doi.org/10.1523/JNEUROSCI.4779-11.2012

    • PubMed
    • Search Google Scholar
    • Export Citation

  • Tudoraşcu, I., Sfredel, V., Riza, A.L., Dănciulescu Miulescu, R., Ianoşi, S.L., & Dănoiu, S. (2014). Motor unit changes in normal aging: A brief review. Romanian Journal of Morphology and Embryology, 55(4), 1295–1301.

    • PubMed
    • Search Google Scholar
    • Export Citation

  • Turesky, T.K., Olulade, O.A., Luetje, M.M., & Eden, G.F. (2018). An fMRI study of finger tapping in children and adults. Human Brain Mapping, 39(8), 3203–3215. https://doi.org/10.1002/hbm.24070

    • PubMed
    • Search Google Scholar
    • Export Citation

  • University of Düsseldorf. (n.d.). G*Power. Retrieved from October 15, 2022. https://www.psychologie.hhu.de/arbeitsgruppen/allgemeine-psychologie-und-arbeitspsychologie/gpower

    • Search Google Scholar
    • Export Citation

  • Vaillancourt, D.E., & Newell, K.M. (2002). Changing complexity in human behavior and physiology through aging and disease. Neurobiology of Aging, 23(1), 1–11. https://doi.org/10.1016/S0197-4580(01)00247-0

    • PubMed
    • Search Google Scholar
    • Export Citation

  • van Geert, P., & van Dijk, M. (2002). Focus on variability: New tools to study intra-individual variability in developmental data. Infant Behavior and Development, 25(4), 340–374. https://doi.org/10.1016/S0163-6383(02)00140-6

    • Search Google Scholar
    • Export Citation

  • Vieluf, S., Aschersleben, G., & Panzer, S. (2017). Lifespan development of the bilateral deficit in a simple reaction time task. Experimental Brain Research, 235(4), 985–992. https://doi.org/10.1007/s00221-016-4856-5

    • Search Google Scholar
    • Export Citation

  • Webb, S.J., Monk, C.S., & Nelson, C.A. (2001). Mechanisms of postnatal neurobiological development: Implications for human development. Developmental Neuropsychology, 19(2), 147–171. https://doi.org/10.1207/S15326942DN1902_2

    • PubMed
    • Search Google Scholar
    • Export Citation

  • Williams, B.R., Hultsch, D.F., Strauss, E.H., Hunter, M.A., & Tannock, R. (2005). Inconsistency in reaction time across the life span. Neuropsychology, 19(1), 88–96. https://doi.org/10.1037/0894-4105.19.1.88

    • PubMed
    • Search Google Scholar
    • Export Citation

  • Wintergerst, A.M., Throckmorton, G.S., & Buschang, P.H. (2008). Effects of bolus size and hardness on within-subject variability of chewing cycle kinematics. Archives of Oral Biology, 53(4), 369–375. https://doi.org/10.1016/j.archoralbio.2007.10.012

    • PubMed
    • Search Google Scholar
    • Export Citation

  • Wu, T., & Hallett, M. (2005). A functional MRI study of automatic movements in patients with Parkinson’s disease. Brain: A Journal of Neurology, 128(10), 2250–2259. https://doi.org/10.1093/brain/awh569

    • PubMed
    • Search Google Scholar
    • Export Citation

  • Zahr, N.M., Rohlfing, T., Pfefferbaum, A., & Sullivan, E.V. (2009). Problem solving, working memory, and motor correlates of association and commissural fiber bundles in normal aging: A quantitative fiber tracking study. NeuroImage, 44(3), 1050–1062. https://doi.org/10.1016/j.neuroimage.2008.09.046

    • PubMed
    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 889 889 155
Full Text Views 32 32 1
PDF Downloads 46 46 2