Skip to main content
SpringerLink
Log in

The Neural Basis of Cognitive Efficiency in Motor Skill Performance from Early Learning to Automatic Stages

  • Chapter
  • First Online:
Neuroergonomics

Part of the book series: Cognitive Science and Technology ((CSAT))

Abstract

Skill acquisition represents a progression from high to low reliance on the conscious control of the action. The ability to produce action without drawing upon limited attentional resources has traditionally been the defining characteristic of skill automaticity. As such, learning represents a progression from low to high efficiency in the cognitive processes needed to plan, execute, and update skilled movement. In this chapter, we summarize neuroimaging findings that illustrate the evolution of such efficiency in terms of the neural adaptations that underlie skill learning automatization. As a backdrop to these findings, we first review the cognitive characteristics of skill automaticity as well as a contemporary theoretical framework for how we perform action based on sequencing movement elements. This provides a vantage point from which neural basis of skill automaticity can be considered in terms of associative and sensorimotor learning processes that provide for more efficient action in terms of cognitive requirements. We then contrast this with a summary of the contextual interference effect, which represents a cautionary account for the negative learning consequences associated with training protocols that appear to expedite skill automaticity.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  • Abernethy, B. (1988). Dual-task methodology and motor skills research: Some methodological constraints. Journal of Human Movement Studies, 14, 101–132.

    Google Scholar 

  • Abrahamse, E. L., Jimenez, L., Verwey, W. B., & Clegg, B. A. (2010). Representing serial action and perception. Psychonomic Bulletin & Review, 17(5), 603–623. https://doi.org/10.3758/PBR.17.5.603.

    Article  Google Scholar 

  • Abrahamse, E. L., & Noordzij, M. L. (2011). Designing training programs for perceptual-motor skills: Practical implications from the serial reaction time task. European Review of Applied Psychology-Revue Europeenne De Psychologie Appliquee, 61(2), 65–76. https://doi.org/10.1016/j.erap.2010.12.001.

    Article  Google Scholar 

  • Abrahamse, E. L., Ruitenberg, M. F. L., de Kleine, E., & Verwey, W. B. (2013). Control of automated behavior: Insights from the discrete sequence production task. Frontiers in Human Neuroscience, 7.

    Google Scholar 

  • Adams, S. G., & Page, A. D. (2000). Effects of selected practice and feedback variables on speech motor learning. Journal of Medical Speech-Language Pathology, 8(4), 215–220.

    Google Scholar 

  • Almåsbakk, B., Whiting, H. T. A., & Helgerud, J. (2001). The efficient learner. Biological Cybernetics, 84(2), 75–83.

    Article  Google Scholar 

  • Ashby, F. G., & Crossley, M. J. (2012). Automaticity and multiple memory systems. Wiley Interdisciplinary Reviews-Cognitive Science, 3(3), 363–376. https://doi.org/10.1002/wcs.1172.

    Article  Google Scholar 

  • Ashby, F. G., Ennis, J. M., & Spiering, B. J. (2007). A neurobiological theory of automaticity in perceptual categorization. Psychological Review, 114(3), 632–656. https://doi.org/10.1037/0033-295x.114.3.632.

    Article  Google Scholar 

  • Ashby, F. G., Turner, B. O., & Horvitz, J. C. (2010). Cortical and basal ganglia contributions to habit learning and automaticity. Trends in Cognitive Sciences, 14(5), 208–215. https://doi.org/10.1016/j.tics.2010.02.001.

    Article  Google Scholar 

  • Bahrick, H. P., Noble, M., & Fitts, P. M. (1954). Extra-task performance as a measure of learning a primary task. Journal of Experimental Psychology, 48, 298–302.

    Article  Google Scholar 

  • Bernacer, J., & Murillo, J. I. (2014). The Aristotelian conception of habit and its contribution to human neuroscience. Frontiers in Human Neuroscience, 8.

    Google Scholar 

  • Bernstein, N. (1967). The Coordination and Regulation of Movements. London: Pergamon Press.

    Google Scholar 

  • Bezzola, L., Merillat, S., Gaser, C., & Jancke, L. (2011). Training-induced neural plasticity in golf novices. Journal of Neuroscience, 31(35), 12444–12448. https://doi.org/10.1523/Jneurosci.1996-11.2011.

    Article  Google Scholar 

  • Brady, F. (1998). A theoretical and empirical review of the contextual interference effect and the learning of motor skills. Quest, 50(3), 266–293.

    Article  Google Scholar 

  • Brady, F. (2004). Contextual interference: A meta-analytic study. Perceptual and Motor Skills, 99(1), 116–126. https://doi.org/10.2466/pms.99.1.116-126.

    Article  Google Scholar 

  • Breton, J., & Robertson, E. M. (2014). Flipping the switch: Mechanisms that regulate memory consolidation. Trends in Cognitive Sciences, 18(12), 629–634. https://doi.org/10.1016/j.tics.2014.08.005.

    Article  Google Scholar 

  • Brown, T. L., & Carr, T. H. (1989). Automaticity in skill acquisition—mechanisms for reducing interference in concurrent performance. Journal of Experimental Psychology-Human Perception and Performance, 15(4), 686–700.

    Article  Google Scholar 

  • Buccino, G., Vogt, S., Ritzl, A., Fink, G. R., Zilles, K., Freund, H. J., et al. (2004). Neural circuits underlying imitation learning of hand actions: An event-related fMRI study. Neuron, 42(2), 323–334. https://doi.org/10.1016/S0896-6273(04)00181-3.

    Article  Google Scholar 

  • Burke, R. E. (2007). Sir Charles Sherrington’s the integrative action of the nervous system: A centenary appreciation. Brain, 130, 887–894. https://doi.org/10.1093/brain/awm022.

    Article  Google Scholar 

  • Carter, C. S., Braver, T. S., Barch, D. M., Botvinick, M. M., Noll, D., & Cohen, J. D. (1998). Anterior cingulate cortex, error detection, and the online monitoring of performance. Science, 280(5364), 747–749.

    Article  Google Scholar 

  • Chaney, D. W. (2013). An overview of the first use of the terms cognition and behavior. Behavioral Sciences, 3(1), 143–153.

    Article  Google Scholar 

  • Clegg, B. A., Digirolamo, G. J., & Keele, S. W. (1998). Sequence learning. Trends in Cognitive Sciences, 2(8), 275–281.

    Article  Google Scholar 

  • Cohen, J. D., Servanschreiber, D., & Mcclelland, J. L. (1992). A parallel distributed-processing approach to automaticity. American Journal of Psychology, 105(2), 239–269. https://doi.org/10.2307/1423029.

    Article  Google Scholar 

  • Coynel, D., Marrelec, G., Perlbarg, V., Pelegrini-Issac, M., Van de Moortele, P. F., Ugurbil, K., … Lehericy, S. (2010). Dynamics of motor-related functional integration during motor sequence learning. Neuroimage, 49(1), 759–766. https://doi.org/10.1016/j.neuroimage.2009.08.048.

    Article  Google Scholar 

  • Cross, E. S., Schmitt, P. J., & Grafton, S. T. (2007). Neural substrates of contextual interference during motor learning support a model of active preparation. Journal of Cognitive Neuroscience, 19(11), 1854–1871.

    Article  Google Scholar 

  • Dayan, E., & Cohen, L. G. (2011). Neuroplasticity subserving motor skill learning. Neuron, 72(3), 443–454.

    Article  Google Scholar 

  • Del Rey, P. (1982). Effects of contextual interference on the memory of older females differing in levels of physical activity. Perceptual and Motor Skills, 55(1), 171–180.

    Article  MathSciNet  Google Scholar 

  • Di Paola, M., Caltagirone, C., & Petrosini, L. (2013). Prolonged rock climbing activity induces structural changes in cerebellum and parietal lobe. Human Brain Mapping, 34(10), 2707–2714. https://doi.org/10.1002/hbm.22095.

    Article  Google Scholar 

  • Doyon, J., Bellec, P., Amsel, R., Penhune, V., Monchi, O., Carrier, J., … Benali, H. (2009). Contributions of the basal ganglia and functionally related brain structures to motor learning. Behavioral Brain Research, 199(1), 61–75.

    Article  Google Scholar 

  • Doyon, J., Owen, A. M., Petrides, M., Sziklas, V., & Evans, A. C. (1996). Functional anatomy of visuomotor skill learning in human subjects examined with positron emission tomography. European Journal of Neuroscience, 8(4), 637–648. https://doi.org/10.1111/j.1460-9568.1996.tb01249.x.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • Doyon, J., Song, A. W., Karni, A., Lalonde, F., Adams, M. M., & Ungerleider, L. G. (2002). Experience-dependent changes in cerebellar contributions to motor sequence learning. Proceedings of the National Academy of Sciences of the United States of America, 99(2), 1017–1022. https://doi.org/10.1073/pnas.022615199.

    Article  Google Scholar 

  • Doyon, J., & Ungerleider, L. G. (2002). Functional anatomy of motor skill learning. In R. E. Squire & D. L. Schacter (Eds.), Neuropsychology of memory. New York: Guilford.

    Google Scholar 

  • Engel, K. C., Flanders, M., & Soechting, J. F. (1997). Anticipatory and sequential motor control in piano playing. Experimental Brain Research, 113(2), 189–199.

    Article  Google Scholar 

  • Fendrich, D. W., & Arengo, R. (2004). The influence of string length and repetition on chunking of digit strings. Psychological Research, 68(4), 216–223. https://doi.org/10.1007/s00426-003-0142-9.

    Article  Google Scholar 

  • Fitts, P. M. (1964). Perceptual-motor skills learning. In A. W. Melton (Ed.), Categories of human learning (pp. 243–285). New York: Academic Press.

    Chapter  Google Scholar 

  • Fitts, P. M., & Posner, M. I. (1967). Human performance. Belmont, CA: Brooks/Cole.

    Google Scholar 

  • Florio, T. M., Scarnati, E., Rosa, I., Di Censo, D., Ranieri, B., Cimini, A., … Alecci, M. (2018). The basal ganglia: More than just a switching device. Cns Neuroscience & Therapeutics, 24(8), 677–684. https://doi.org/10.1111/cns.12987.

    Article  Google Scholar 

  • Floyer-Lea, A., & Matthews, P. M. (2005). Distinguishable brain activation networks for short- and long-term motor skill learning. Journal of Neurophysiology, 94(1), 512–518.

    Article  Google Scholar 

  • Friston, K. J., Frith, C. D., Passingham, R. E., Liddle, P. F., & Frackowiak, R. S. (1992). Motor practice and neurophysiological adaptation in the cerebellum: A positron tomography study. Proceedings of the Royal Society B: Biological Sciences, 248(1323), 223–228. https://doi.org/10.1098/rspb.1992.0065.

    Article  Google Scholar 

  • Fuster, J. M. (2004). Upper processing stages of the perception-action cycle. Trends in Cognitive Sciences, 8(4), 143–145. https://doi.org/10.1016/j.tics.2004.02.004.

    Article  Google Scholar 

  • Gentile, A. M. (1972). A working model of skill acquisition with application to teaching. Quest, 17, 3–23.

    Article  Google Scholar 

  • Gentile, A. M. (1998). Implicit and explicit processes during acquisition of functional skills. Scandinavian Journal of Occupational Therapy, 5, 7–16.

    Article  Google Scholar 

  • Gerloff, C., Corwell, B., Chen, R., Hallett, M., & Cohen, L. G. (1997). Stimulation over the human supplementary motor area interferes with the organization of future elements in complex motor sequences. Brain, 120, 1587–1602.

    Article  Google Scholar 

  • Ghilardi, M., Ghez, C., Dhawan, V., Moeller, J., Mentis, M., Nakamura, T., … Eidelberg, D. (2000). Patterns of regional brain activation associated with different forms of motor learning. Brain Research, 871(1), 127-145.

    Article  Google Scholar 

  • Goode, S., & Magill, R. A. (1986). Contextual interference effects in learning three badminton serves. Research Quarterly for Exercise and Sport, 57(4), 308–314.

    Article  Google Scholar 

  • Grafton, S. T., Hazeltine, E., & Ivry, R. (1995). Functional mapping of sequence learning in normal humans. Journal of Cognitive Neuroscience, 7(4), 497–510. https://doi.org/10.1162/jocn.1995.7.4.497.

    Article  Google Scholar 

  • Grafton, S. T., Hazeltine, E., & Ivry, R. B. (2002). Motor sequence learning with the nondominant left hand. A PET functional imaging study. Experimental Brain Research, 146(3), 369–378. https://doi.org/10.1007/s00221-002-1181-y.

    Article  Google Scholar 

  • Grafton, S. T., Mazziotta, J. C., Presty, S., Friston, K. J., Frackowiak, R. S., & Phelps, M. E. (1992). Functional anatomy of human procedural learning determined with regional cerebral blood flow and PET. Journal of Neuroscience, 12(7), 2542–2548.

    Article  Google Scholar 

  • Grafton, S. T., Woods, R. P., & Tyszka, M. (1994). Functional imaging of procedural motor learning: Relating cerebral blood flow with individual subject performance. Human Brain Mapping, 1(3), 221–234. https://doi.org/10.1002/hbm.460010307.

    Article  Google Scholar 

  • Hardwick, R. M., Rottschy, C., Miall, R. C., & Eickhoff, S. B. (2013). A quantitative meta-analysis and review of motor learning in the human brain. Neuroimage, 67, 283–297. https://doi.org/10.1016/j.neuroimage.2012.11.020.

    Article  Google Scholar 

  • Hazeltine, E., Grafton, S. T., & Ivry, R. (1997). Attention and stimulus characteristics determine the locus of motor-sequence encoding—A PET study. Brain, 120, 123–140. https://doi.org/10.1093/brain/120.1.123.

    Article  Google Scholar 

  • Helie, S., Waldschmidt, J. G., & Ashby, F. G. (2010). Automaticity in rule-based and information-integration categorization. Attention, Perception, & Psychophysics, 72(4), 1013–1031. https://doi.org/10.3758/App.72.4.1013.

    Article  Google Scholar 

  • Henry, F. M., & Rogers, D. E. (1960). Increased response latency for complicated movements and a “memory drum” theory of neuromotor reaction. Research Quarterly. American Association for Health, Physical Education and Recreation, 31(3), 448–458.

    Google Scholar 

  • Herdener, M., Esposito, F., di Salle, F., Boller, C., Hilti, C. C., Habermeyer, B., … Cattapan-Ludewig, K. (2010). Musical training induces functional plasticity in human hippocampus. Journal of Neuroscience, 30(4), 1377–1384. https://doi.org/10.1523/jneurosci.4513-09.2010.

    Article  Google Scholar 

  • Hikosaka, O., Nakahara, H., Rand, M. K., Sakai, K., Lu, X., Nakamura, K., … Doya, K. (1999). Parallel neural networks for learning sequential procedures. Trends Neurosci, 22(10), 464–471.

    Article  Google Scholar 

  • Hikosaka, O., Nakamura, K., Sakai, K., & Nakahara, H. (2002). Central mechanisms of motor skill learning. Current Opinion in Neurobiology, 12(2), 217–222.

    Article  Google Scholar 

  • Immink, M. A. (2016). Post-training meditation promotes motor memory consolidation. Frontiers in Psychology, 7. https://doi.org/10.3389/fpsyg.2016.01698.

  • Immink, M. A., Colzato, L. S., Stolte, M., & Hommel, B. (2017). Sequence learning enhancement following single-session meditation is dependent on meta control mode and experienced effort. Journal of Cognitive Enhancement, 1(2), 127–140.

    Article  Google Scholar 

  • Immink, M. A., & Wright, D. L. (1998). Contextual interference: A response planning account. The Quarterly Journal of Experimental Psychology Section A, 51(4), 735–754.

    Article  Google Scholar 

  • Immink, M. A., & Wright, D. L. (2001). Motor programming during practice conditions high and low in contextual interference. Journal of Experimental Psychology: Human Perception and Performance, 27(2), 423–437.

    Google Scholar 

  • James, W. (1890). Principles of psychology (Vol. 1). New York: Holt.

    Google Scholar 

  • Jastrow, O. (1891). The interference of mental processes. American Journal of Psychology, 1891(4), 219–223.

    Google Scholar 

  • Jenkins, I. H., Brooks, D. J., Nixon, P. D., Frackowiak, R. S., & Passingham, R. E. (1994). Motor sequence learning: A study with positron emission tomography. Journal of Neuroscience, 14(6), 3775–3790.

    Article  Google Scholar 

  • Jonides, J., Naveh-Benjamin, M., & Palmer, J. (1985). Assessing automaticity. Acta Psychologica, 60(2–3), 157–171. https://doi.org/10.1016/0001-6918(85)90053-8.

    Article  Google Scholar 

  • Jordan, M. I. (1995). The organization of action sequences—Evidence from a relearning task. Journal of Motor Behavior, 27(2), 179–192.

    Article  Google Scholar 

  • Jueptner, M., Frith, C. D., Brooks, D. J., Frackowiak, R. S., & Passingham, R. E. (1997a). Anatomy of motor learning. II. Subcortical structures and learning by trial and error. Journal of Neurophysiology, 77(3), 1325–1337. https://doi.org/10.1152/jn.1997.77.3.1325.

    Article  Google Scholar 

  • Jueptner, M., Stephan, K. M., Frith, C. D., Brooks, D. J., Frackowiak, R. S., & Passingham, R. E. (1997b). Anatomy of motor learning. I. Frontal cortex and attention to action. Journal of Neurophysiology, 77(3), 1313–1324. https://doi.org/10.1152/jn.1997.77.3.1313.

    Article  Google Scholar 

  • Kahneman, D. (1973). Attention and effort. Englewood Cliffs, N.J.: Prentice-Hall.

    Google Scholar 

  • Kantak, S. S., & Winstein, C. J. (2012). Learning-performance distinction and memory processes for motor skills: A focused review and perspective. Behavioural Brain Research, 228(1), 219–231. https://doi.org/10.1016/j.bbr.2011.11.028.

    Article  Google Scholar 

  • Karni, A., Meyer, G., Jezzard, P., Adams, M. M., Turner, R., & Ungerleider, L. G. (1995). Functional MRI evidence for adult motor cortex plasticity during motor skill learning. Nature, 377(6545), 155–158. https://doi.org/10.1038/377155a0.

    Article  Google Scholar 

  • Karni, A., Meyer, G., Rey-Hipolito, C., Jezzard, P., Adams, M. M., Turner, R., et al. (1998). The acquisition of skilled motor performance: Fast and slow experience-driven changes in primary motor cortex. Proceedings of the National Academy of Sciences of the United States of America, 95(3), 861–868.

    Article  Google Scholar 

  • Kawato, M. (1999). Internal models for motor control and trajectory planning. Current Opinion in Neurobiology, 9(6), 718–727.

    Article  Google Scholar 

  • Keele, S. W. (1968). Movement control in skilled motor performance. Psychological Bulletin, 70(6), 387–403.

    Article  Google Scholar 

  • Kim, T., Chen, J., Verwey, W. B., & Wright, D. L. (2018). Improving novel motor learning through prior high contextual interference training. Acta Psychol (Amst), 182, 55–64. https://doi.org/10.1016/j.actpsy.2017.11.005.

    Article  Google Scholar 

  • Klapp, S. T. (1995). Motor response programming during simple choice reaction time: The role of practice. Journal of Experimental Psychology: Human Perception and Performance, 21(5), 1015.

    Google Scholar 

  • Knock, T. R., Ballard, K. J., Robin, D. A., & Schmidt, R. A. (2000). Influence of order of stimulus presentation on speech motor learning: A principled approach to treatment for apraxia of speech. Aphasiology, 14(5–6), 653–668.

    Article  Google Scholar 

  • Koechlin, E., Ody, C., & Kouneiher, F. (2003). The architecture of cognitive control in the human prefrontal cortex. Science, 302(5648), 1181–1185. https://doi.org/10.1126/science.1088545.

    Article  Google Scholar 

  • Kondo, H., Osaka, N., & Osaka, M. (2004). Cooperation of the anterior cingulate cortex and dorsolateral prefrontal cortex for attention shifting. NeuroReport, 23(2), 670–679.

    Google Scholar 

  • Korsgaard, C. M. (2008). Aristotle’s function argument. The constitution of agency (pp. 129–150). Oxford: Oxford University Press.

    Chapter  Google Scholar 

  • Krakauer, J. W., & Mazzoni, P. (2011). Human sensorimotor learning: Adaptation, skill, and beyond. Current Opinion in Neurobiology, 21(4), 636–644. https://doi.org/10.1016/j.conb.2011.06.012.

    Article  Google Scholar 

  • Kubler, A., Dixon, V., & Garavan, H. (2006). Automaticity and reestablishment of executive control-an fMRI study. Journal of Cognitive Neuroscience, 18(8), 1331–1342. https://doi.org/10.1162/jocn.2006.18.8.1331.

    Article  Google Scholar 

  • Kupferschmidt, D. A., Juczewski, K., Cui, G. H., Johnson, K. A., & Lovinger, D. M. (2017). Parallel, but dissociable, processing in discrete corticostriatal Inputs encodes skill learning. Neuron, 96(2), 476–489.

    Google Scholar 

  • LaBerge, D., & Samuels, S. J. (1974). Toward a theory of automatic information processing in reading. Cognitive Psychology, 6, 293–323.

    Article  Google Scholar 

  • Laird, A. R., Fox, P. M., Eickhoff, S. B., Turner, J. A., Ray, K. L., McKay, D. R., … Fox, P. T. (2011). Behavioral interpretations of intrinsic connectivity networks. Journal of Cognitive Neuroscience, 23(12), 4022–4037. https://doi.org/10.1162/jocn_a_00077.

    Article  Google Scholar 

  • Lang, C. E., & Bastian, A. J. (2002). Cerebellar damage impairs automaticity of a recently practiced movement. Journal of Neurophysiology, 87(3), 1336–1347. https://doi.org/10.1152/jn.00368.2001.

    Article  Google Scholar 

  • Leavitt, J. L. (1979). Cognitive demands of skating and stickhandling in ice hockey. Canadian Journal Applied Sport Sciences, 4(1), 46–55.

    Google Scholar 

  • Lehericy, S., Benali, H., Van de Moortele, P. F., Pelegrini-Issac, M., Waechter, T., Ugurbil, K., et al. (2005). Distinct basal ganglia territories are engaged in early and advanced motor sequence learning. Proceedings of the National Academy of Sciences of the United States of America, 102(35), 12566–12571.

    Article  Google Scholar 

  • Li, Y., & Wright, D. L. (2000). An assessment of the attention demands during random-and blocked-practice schedules. The Quarterly Journal of Experimental Psychology Section A, 53(2), 591–606.

    Article  Google Scholar 

  • Lin, C.-H. J., Knowlton, B. J., Chiang, M.-C., Iacoboni, M., Udompholkul, P., & Wu, A. D. (2011). Brain–behavior correlates of optimizing learning through interleaved practice. Neuroimage, 56(3), 1758–1772.

    Article  Google Scholar 

  • Little, D. M., Klein, R., Shobat, D. M., McClure, E. D., & Thulborn, K. R. (2004). Changing patterns of brain activation during category learning revealed by functional MRI. Cognitive Brain Research, 22(1), 84–93. https://doi.org/10.1016/j.cogbrainres.2004.07.011.

    Article  Google Scholar 

  • Lohse, K. R., Wadden, K., Boyd, L. A., & Hodges, N. J. (2014). Motor skill acquisition across short and long time scales: A meta-analysis of neuroimaging data. Neuropsychologia, 59, 130–141. https://doi.org/10.1016/j.neuropsychologia.2014.05.001.

    Article  Google Scholar 

  • Magill, R. A., & Hall, K. G. (1990). A review of the contextual interference effect in motor skill acquisition. Human Movement Science, 9(3–5), 241–289.

    Article  Google Scholar 

  • Matsuzaka, Y., Picard, N., & Strick, P. L. (2007). Skill representation in the primary motor cortex after long-term practice. Journal of Neurophysiology, 97(2), 1819–1832. https://doi.org/10.1152/jn.00784.2006.

    Article  Google Scholar 

  • McLeod, P. D. (1980). What can probeRT tell us about the attentional demands ofmovements? In G. E. Stelmach & J. Requin (Eds.), Tutorials in motor behavior (pp. 579–589). Amsterdam: North-Holland.

    Chapter  Google Scholar 

  • Miall, R. C., Reckess, G. Z., & Imamizu, H. (2001). The cerebellum coordinates eye and hand tracking movements. Nature Neuroscience, 4(6), 638–644. https://doi.org/10.1038/88465.

    Article  Google Scholar 

  • Miller, G. A. (1956). The magical number seven, plus or minus two: Some limits on our capacity for processing information. Psychological Review, 63(2), 81–97.

    Article  Google Scholar 

  • Moors, A., & De Houwer, J. (2006). Automaticity: A theoretical and conceptual analysis. Psychological Bulletin, 132(2), 297–326. https://doi.org/10.1037/0033-2909.132.2.297.

    Article  Google Scholar 

  • Nachev, P., Kennard, C., & Husain, M. (2008). Functional role of the supplementary and pre-supplementary motor areas. Nature Reviews Neuroscience, 9(11), 856–869.

    Article  Google Scholar 

  • Nissen, M. J., & Bullemer, P. (1987). Attentional requirements of learning—Evidence from performance-measures. Cognitive Psychology, 19(1), 1–32. https://doi.org/10.1016/0010-0285(87)90002-8.

    Article  Google Scholar 

  • O’Reilly, J. X., Beckmann, C. F., Tomassini, V., Ramnani, N., & Johansen-Berg, H. (2010). Distinct and overlapping functional zones in the cerebellum defined by resting state functional connectivity. Cerebral Cortex, 20(4), 953–965. https://doi.org/10.1093/cercor/bhp157.

    Article  Google Scholar 

  • Ollis, S., Button, C., & Fairweather, M. (2005). The influence of professional expertise and task complexity upon the potency of the contextual interference effect. Acta Psychologica (Amst), 118(3), 229–244. https://doi.org/10.1016/j.actpsy.2004.08.003.

    Article  Google Scholar 

  • Pashler, H. (1994). Dual-task interference in simple tasks—Data and theory. Psychological Bulletin, 116(2), 220–244. https://doi.org/10.1037/0033-2909.116.2.220.

    Article  Google Scholar 

  • Passingham, R. E. (1996). Attention to action. Philosophical Transactions of the Royal Society of London B: Biological Sciences, 351(1346), 1473–1479. https://doi.org/10.1098/rstb.1996.0132.

    Article  Google Scholar 

  • Pauwels, L., Swinnen, S. P., & Beets, I. A. (2014). Contextual interference in complex bimanual skill learning leads to better skill persistence. PLoS ONE, 9(6), e100906. https://doi.org/10.1371/journal.pone.0100906.

    Article  Google Scholar 

  • Pearce, A. J., Thickbroom, G. W., Byrnes, M. L., & Mastaglia, F. L. (2000). Functional reorganisation of the corticomotor projection to the hand in skilled racquet players. Experimental Brain Research, 130(2), 238–243. https://doi.org/10.1007/s002219900236.

    Article  Google Scholar 

  • Penhune, V. B., & Doyon, J. (2002). Dynamic cortical and subcortical networks in learning and delayed recall of timed motor sequences. Journal of Neuroscience, 22(4), 1397–1406.

    Article  Google Scholar 

  • Penhune, V. B., & Steele, C. J. (2012). Parallel contributions of cerebellar, striatal and M1 mechanisms to motor sequence learning. Behavioural Brain Research, 226(2), 579–591. https://doi.org/10.1016/j.bbr.2011.09.044.

    Article  Google Scholar 

  • Pew, R. W. (1966). Acquisition of hierarchical control over the temporal organization of a skill. Journal of Experimental Psychology, 71(5), 764–771.

    Article  Google Scholar 

  • Poldrack, R. A., Sabb, F. W., Foerde, K., Tom, S. M., Asarnow, R. F., Bookheimer, S. Y., et al. (2005). The neural correlates of motor skill automaticity. Journal of Neuroscience, 25(22), 5356–5364.

    Article  Google Scholar 

  • Porretta, D. L., & O’Brien, K. (1991). The use of contextual interference trials by mildly mentally handicapped children. Research Quarterly for Exercise Sport, 62(2), 240–244.

    Article  Google Scholar 

  • Posner, M. I. (1979). Chronometric explorations of mind. Hillsdale, N.J.: Erlbaum.

    Google Scholar 

  • Posner, M. I., & Keele, S. W. (1969). Attentional demands of movement. In Proceedings of the 16th Congress of Applied Psychology. Amsterdam: Swets and Zeitlinger.

    Google Scholar 

  • Proteau, L., Marteniuk, R. G., & Levesque, L. (1992). A sensorimotor basis for motor learning—evidence indicating specificity of practice. Quarterly Journal of Experimental Psychology Section A-Human Experimental Psychology, 44(3), 557–575. https://doi.org/10.1080/14640749208401298.

    Article  Google Scholar 

  • Puttemans, V., Wenderoth, N., & Swinnen, S. P. (2005). Changes in brain activation during the acquisition of a multifrequency bimanual coordination task: From the cognitive stage to advanced levels of automaticity. Journal of Neuroscience, 25(17), 4270–4278. https://doi.org/10.1523/JNEUROSCI.3866-04.2005.

    Article  Google Scholar 

  • Robertson, E. M. (2007). The serial reaction time task: Implicit motor skill learning? Journal of Neuroscience, 27(38), 10073–10075. https://doi.org/10.1523/Jneurosci.2747-07.2007.

    Article  Google Scholar 

  • Robertson, E. M., Pascual-Leone, A., & Miall, R. C. (2004). Current concepts in procedural consolidation. Nature Reviews Neuroscience, 5(7), 576–582. https://doi.org/10.1038/nrn1426.

    Article  Google Scholar 

  • Sakai, K., Hikosaka, O., & Nakamura, K. (2004). Emergence of rhythm during motor learning. Trends in Cognitive Sciences, 8(12), 547–553. https://doi.org/10.1016/j.tics.2004.10.005.

    Article  Google Scholar 

  • Salmoni, A. W., Schmidt, R. A., & Walter, C. B. (1984). Knowledge of results and motor learning—A review and critical reappraisal. Psychological Bulletin, 95(3), 355–386. https://doi.org/10.1037/0033-2909.95.3.355.

    Article  Google Scholar 

  • Schendan, H. E., Searl, M. M., Melrose, R. J., & Stern, C. (2003). An FMRI study of the role of the medial temporal lobe in implicit and explicit sequence learning. Neuron, 37(6), 1013–1025.

    Article  Google Scholar 

  • Schmidt, R. A. (1975). A schema theory of discrete motor skill learning. Psychological Review, 82, 225–260.

    Article  Google Scholar 

  • Schmidt, R. A. (2003). Motor schema theory after 27 years: Reflections and implications for a new theory. Research Quarterly for Exercise and Sport, 74(4), 366–375.

    Article  Google Scholar 

  • Schmidt, R. A., & Bjork, R. A. (1992). New conceptualizations of practice: Common principles in three paradigms suggest new concepts for training. Psychological Science, 3(4), 207–218.

    Article  Google Scholar 

  • Schmidt, R. A., & Lee, T. D. (2005). Motor control and learning: A behavioural emphasis (4 ed.). Champaign: Human Kinetics.

    Google Scholar 

  • Schneider, W., & Chein, J. M. (2003). Controlled & automatic processing: behavior, theory, and biological mechanisms. Cognitive Science, 27(3), 525–559. https://doi.org/10.1016/S0364-0213(03)00011-9.

    Article  Google Scholar 

  • Schneider, W., & Shiffrin, R. M. (1977). Controlled and automatic human information-processing I: Detection, search, and attention. Psychological Review, 84(1), 1–66. https://doi.org/10.1037/0033-295x.84.1.1.

    Article  Google Scholar 

  • Seidler, R. D., Purushotham, A., Kim, S.-G., Uğurbil, K., Willingham, D., & Ashe, J. (2002). Cerebellum activation associated with performance change but not motor learning. Science, 296(5575), 2043–2046.

    Article  Google Scholar 

  • Seitz, R. J., Canavan, A. G., Yaguez, L., Herzog, H., Tellmann, L., Knorr, U., … Homberg, V. (1994). Successive roles of the cerebellum and premotor cortices in trajectorial learning. Neuroreport, 5(18), 2541–2544.

    Article  Google Scholar 

  • Shadmehr, R., & Holcomb, H. H. (1997). Neural correlates of motor memory consolidation. Science, 277(5327), 821–825.

    Article  Google Scholar 

  • Shadmehr, R., & Krakauer, J. W. (2008). A computational neuroanatomy for motor control. Experimental Brain Research, 185(3), 359–381. https://doi.org/10.1007/s00221-008-1280-5.

    Article  Google Scholar 

  • Shaffer, L. H. (1975). Control processes in typing. Quarterly Journal of Experimental Psychology, 27(Aug), 419–432.

    Google Scholar 

  • Shea, J. B., & Morgan, R. L. (1979). Contextual interference effects on the acquisition, retention, and transfer of a motor skill. Journal of Experimental Psychology: Human Learning and Memory, 5(2), 179–187.

    Google Scholar 

  • Sherrington, C. S. (1910). Flexion-reflex of the limb, crossed extension-reflex and reflex stepping and standing. Journal of Physiology, 40, 28–121.

    Article  Google Scholar 

  • Sherrington, C. S. (1974). The integrative action of the nervous system. New Haven, C.T.: Yale University Press.

    Google Scholar 

  • Shmuelof, L., & Krakauer, J. W. (2011). Are we ready for a natural history of motor learning? Neuron, 72(3), 469–476. https://doi.org/10.1016/j.neuron.2011.10.017.

    Article  Google Scholar 

  • Singer, R. N. (2002). Preperformance state, routines, and automaticity: What does it take to realize expertise in self-paced events? Journal of Sport & Exercise Psychology, 24(4), 359–375. https://doi.org/10.1123/jsep.24.4.359.

    Article  Google Scholar 

  • Smith, P. J., & Davies, M. (1995). Applying contextual interference to the Pawlata roll. Journal of Sports Sciences, 13(6), 455–462.

    Article  Google Scholar 

  • Solomons, L., & Stein, G. (1896). Normal motor automatism. Psychological Review, 3, 492–512.

    Article  Google Scholar 

  • Stein, G. (1898). Cultivated motor automatism: A; a study of character in its relation to attention. Psychological Review, 5(3), 295–306.

    Article  Google Scholar 

  • Swinnen, S. P. (2002). Intermanual coordination: From behavioural principles to neural-network interactions. Nature Reviews Neuroscience, 3(5), 350–361. https://doi.org/10.1038/nrn807.

    Article  Google Scholar 

  • Taylor, J. A., & Ivry, R. B. (2012). The role of strategies in motor learning. Year in Cognitive Neuroscience, 1251, 1–12. https://doi.org/10.1111/j.1749-6632.2011.06430.x.

    Article  Google Scholar 

  • Thorn, C. A., Atallah, H., Howe, M., & Graybiel, A. M. (2010). Differential dynamics of activity changes in dorsolateral and dorsomedial striatal loops during learning. Neuron, 66(5), 781–795. https://doi.org/10.1016/j.neuron.2010.04.036.

    Article  Google Scholar 

  • Thorn, C. A., & Graybiel, A. M. (2014). Differential entrainment and learning-related dynamics of spike and local field potential activity in the sensorimotor and associative striatum. Journal of Neuroscience, 34(8), 2845–2859. https://doi.org/10.1523/Jneurosci.1782-13.2014.

    Article  Google Scholar 

  • Toner, J., & Moran, A. (2015). Enhancing performance proficiency at the expert level: Considering the role of’ somaesthetic awareness’. Psychology of Sport and Exercise, 16, 110–117. https://doi.org/10.1016/j.psychsport.2014.07.006.

    Article  Google Scholar 

  • Toni, I., Krams, M., Turner, R., & Passingham, R. E. (1998). The time course of changes during motor sequence learning: A whole-brain fMRI study. Neuroimage, 8(1), 50–61. https://doi.org/10.1006/nimg.1998.0349.

    Article  Google Scholar 

  • Tunovic, S., Press, D. Z., & Robertson, E. M. (2014). A physiological signal that prevents motor skill improvements during consolidation. Journal of Neuroscience, 34(15), 5302–5310. https://doi.org/10.1523/Jneurosci.3497-13.2014.

    Article  Google Scholar 

  • Verwey, W. B. (1999). Evidence for a multistage model of practice in a sequential movement task. Journal of Experimental Psychology-Human Perception and Performance, 25(6), 1693–1708. https://doi.org/10.1037/0096-1523.25.6.1693.

    Article  Google Scholar 

  • Verwey, W. B., Abrahamse, E. L., & de Kleine, E. (2010). Cognitive processing in new and practiced discrete keying sequences. Frontiers in Psychology, 1. https://doi.org/10.3389/fpsyg.20https://doi.org/10.00032.

  • Verwey, W. B., & Dronkers, W. J. (2018). Skill in discrete keying sequences is execution rate specific. Psychological Research-Psychologische Forschung, [Epub ahead of print]. https://doi.org/10.1007/s00426-017-0967-2.

    Article  Google Scholar 

  • Verwey, W. B., Jouen, A. L., Dominey, P. F., & Ventre-Dominey, J. (2018). Explaining the neural activity distribution associated with discrete movement sequences: Evidence for parallel functional systems. Cognitive, Affective, & Behavioral Neuroscience. https://doi.org/10.3758/s13415-018-00651-6.

    Article  Google Scholar 

  • Verwey, W. B., Lammens, R., & van Honk, J. (2002). On the role of the SMA in the discrete sequence production task: A TMS study. Neuropsychologia, 40(8), 1268–1276.

    Article  Google Scholar 

  • Verwey, W. B., Shea, C. H., & Wright, D. L. (2015). A cognitive framework for explaining serial processing and sequence execution strategies. Psychonomic Bulletin & Review, 22(1), 54–77. https://doi.org/10.3758/s13423-014-0773-4.

    Article  Google Scholar 

  • Verwey, W. B., & Wright, D. L. (2014). Learning a keying sequence you never executed: Evidence for independent associative and motor chunk learning. Acta Psychologica (Amst), 151, 24–31. https://doi.org/10.1016/j.actpsy.2014.05.017.

    Article  Google Scholar 

  • Walker, M. P., & Stickgold, R. (2004). Sleep-dependent learning and memory consolidation. Neuron, 44(1), 121–133. https://doi.org/10.1016/j.neuron.2004.08.031.

    Article  Google Scholar 

  • Wambaugh, J. L., Nessler, C., Wright, S., & Mauszycki, S. C. (2014). Sound production treatment: effects of blocked and random practice. American Journal of Speech-Language Pathology, 23(2), 225–245.

    Article  Google Scholar 

  • Whitaker, H. A. (1983). Towards a brain model of automatization: A short essay. In R. A. Magill (Ed.), Memory and control of action (pp. 199–214). Amsterdam: North-Holland.

    Chapter  Google Scholar 

  • Wolpert, D. M., Miall, R. C., & Kawato, M. (1998). Internal models in the cerebellum. Trends in Cognitive Sciences, 2(9), 338–347.

    Article  Google Scholar 

  • Wright, D., Verwey, W., Buchanen, J., Chen, J., Rhee, J., & Immink, M. (2016). Consolidating behavioral and neurophysiologic findings to explain the influence of contextual interference during motor sequence learning. Psychonomic Bulletin & Review, 23(1), 1–21. https://doi.org/10.3758/s13423-015-0887-3.

    Article  Google Scholar 

  • Wright, D. L., Black, C. B., Immink, M. A., Brueckner, S., & Magnuson, C. (2004). Long-term motor programming improvements occur via concatenation of movement sequences during random but not during blocked practice. Journal of Motor Behavior, 36(1), 39–50.

    Article  Google Scholar 

  • Wright, D. L., & Kemp, T. (1992). The dual-task methodology and assessing the attentional demands of ambulation with walking devices. Physical Therapy, 72, 306–312.

    Article  Google Scholar 

  • Wright, D. L., Magnuson, C. E., & Black, C. B. (2005). Programming and reprogramming sequence timing following high and low contextual interference practice. Research Quarterly for Exercise and Sport, 76(3), 258–266. https://doi.org/10.1080/02701367.2005.10599297.

    Article  Google Scholar 

  • Wu, T., Chan, P., & Hallett, M. (2008). Modifications of the interactions in the motor networks when a movement becomes automatic. Journal of Physiology-London, 586(17), 4295–4304.

    Article  Google Scholar 

  • Wu, T., & Hallett, M. (2005). The influence of normal human ageing on automatic movements. Journal of Physiology-London, 562(2), 605–615.

    Article  Google Scholar 

  • Wu, T., Kansaku, K., & Hallett, M. (2004). How self-initiated memorized movements become automatic: A functional MRI study. Journal of Neurophysiology, 91(4), 1690–1698. https://doi.org/10.1152/jn.01052.2003.

    Article  Google Scholar 

  • Wu, T., Liu, J., Zhang, H., Hallett, M., Zheng, Z., & Chan, P. (2015). Attention to Automatic Movements in Parkinson’s Disease: Modified Automatic Mode in the Striatum. Cerebral Cortex, 25(10), 3330–3342. https://doi.org/10.1093/cercor/bhu135.

    Article  Google Scholar 

  • Wymbs, N. F., & Grafton, S. T. (2009). Neural substrates of practice structure that support future off-line learning. Journal of Neurophysiology, 102(4), 2462–2476. https://doi.org/10.1152/jn.00315.2009.

    Article  Google Scholar 

  • Yin, H. H., & Knowlton, B. J. (2006). The role of the basal ganglia in habit formation. Nature Reviews Neuroscience, 7(6), 464–476. https://doi.org/10.1038/nrn1919.

    Article  Google Scholar 

  • Yin, H. H., Mulcare, S. P., Hilario, M. R. F., Clouse, E., Holloway, T., Davis, M. I., … Costa, R. M. (2009). Dynamic reorganization of striatal circuits during the acquisition and consolidation of a skill. Nature Neuroscience, 12(3), 333–341. https://doi.org/10.1038/nn.2261.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. University of South Australia, Adelaide, Australia

    Maarten A. Immink

  2. University of Twente, Enschede, The Netherlands

    Willem B. Verwey

  3. Texas A&M University, College Station, USA

    Willem B. Verwey & David L. Wright

Authors
  1. Maarten A. Immink
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Willem B. Verwey
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. David L. Wright
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Maarten A. Immink .

Editor information

Editors and Affiliations

  1. Department of Industrial and Systems Engineering, North Carolina State University, Raleigh, NC, USA

    Chang S. Nam

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Immink, M.A., Verwey, W.B., Wright, D.L. (2020). The Neural Basis of Cognitive Efficiency in Motor Skill Performance from Early Learning to Automatic Stages. In: Nam, C. (eds) Neuroergonomics. Cognitive Science and Technology. Springer, Cham. https://doi.org/10.1007/978-3-030-34784-0_12

Download citation

Publish with us

Policies and ethics

Search

Navigation