Neuroscience and Behavioral Physiology

, Volume 41, Issue 2, pp 140–148 | Cite as

Performance of Series of Movements Specified by a Sequence of Sensory Signals. Individual Differences at the Initial State of Sequence Learning

  • A. V. Kurganskii
  • P. P. Grigal

Individual characteristics of the initial stage of sequence learning were studied in a task consisting of reproducing a sequence of movements specified by a sequence of visual stimuli. A total of 20 adult subjects took part in the study; along with the sequence reproduction task, the subjects performed a simple visuomotor reaction, a selection task, and a serial choice response task. Individual relationships between the latent period of performing the sequence and the trial number, i.e., the learning curve, had a characteristic feature: decreases in latent periods, if observed, occurred either rapidly during the first 10 trials to reach a stationary level (the rapid phase) or decreased slowly and essentially linearly throughout the entire block of 60 trials (the slow phase). Individual learning curves were of four types: flat relationships, curves with a rapid phase, curves with a slow phase, and curves in which a rapid phase was followed by a slow phase. The learning curves of all the subjects were thus divided into four groups. Correlation structures of the time parameters (latent periods and durations of intervals between movements) were studied within groups and in terms of the ratios of these parameters with the times taken to perform simple visuomotor reactions, choice reaction times, and the extent of learning in the sequence reaction time task. This analysis revealed significant differences between groups of subjects, indicative of significant functional differences between the groups. It is suggested that individual differences at the initial stage of sequence learning depend mainly on the functional and structural complexity of the internal representation of the sequence, as well as by the working memory processes supporting the identification of a specified sequence of visual stimuli and performing the transformation of abstract representations into sequences of motor commands.

Key words

individual differences sequence learning stages of learning abstract internal representation working memory 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    N. A. Bernshtein, The Construction of Memory [in Russian], Medgiz, Moscow (1947).Google Scholar
  2. 2.
    A. Baddeley, “Working memory: looking back and looking forward,” Nat. Rev. Neurosci., 4, 829–839 (2003).CrossRefPubMedGoogle Scholar
  3. 3.
    R. S. Bapi, K. P. Miyapuram, F. X. Graydon, and K. Doya, “fMRI investigation of cortical and subcortical networks in the learning of abstract and effector-specific representations of motor sequences,” Neuroimage, 32, No. 2, 714–727 (2006).CrossRefPubMedGoogle Scholar
  4. 4.
    R. S. Bapi, V. S. C. Pammi, K. P. Miyapuram, and A. Ahmed, “Investigation of sequence processing: A cognitive and computational neuroscience perspective,” Curr. Sci., 89, No. 10, 1690–1698 (2005).Google Scholar
  5. 5.
    L. S. Beilock and T. H. Carr, “From novice to expert performance. Memory, attention and the control of complex sensorimotor skills,” in Skill Acquisition in Sport, A. M. Williams and N. J. Hodges (eds.), Routledge, UK (2004), Vol. 1, Part 4, pp. 309–327.Google Scholar
  6. 6.
    D. Bullock, “Adaptive neural models of queuing and timing in fluent action,” Trends Cogn. Sci., 8, No. 9, 426–433 (2004).CrossRefPubMedGoogle Scholar
  7. 7.
    J. Doyon and H. Benali, “Reorganization and plasticity in the adult brain during learning of motor skills,” Curr. Opin. Neurobiol., 15, 161–167 (2005).CrossRefPubMedGoogle Scholar
  8. 8.
    U. Eversheim and O. Bock, “Evidence for processing stages in skill acquisition: A dual-task study,” Learn. Mem., 8, 183–189 (2001).CrossRefPubMedGoogle Scholar
  9. 9.
    F. Gobet and F. E. Ritter, “Individual data analysis and Unified Theories of Cognition: A methodological proposal,” in: Proc. 3rd Int. Conf. on Cognitive Modelling, Veenendaal, The Netherlands, University Press (2000), pp. 150–157.Google Scholar
  10. 10.
    S. T. Grafton and A. F. Hamilton, “Evidence for a distributed hierarchy of action representation in the brain,” Hum. Mov. Sci., 26, No. 4, 590–616 (2007).CrossRefPubMedGoogle Scholar
  11. 11.
    S. T. Grafton, E. Hazeltine, and R. B. Ivry, “Abstract and effectorspecific representations of motor sequences identified with PET,” J. Neurosci., 18, No. 22, 9420–9428 (1998).PubMedGoogle Scholar
  12. 12.
    A. Karni, G. Meyer, C. Rey-Hipolito, P. Jezzard, M. Adams, R. Turners, and L. G. Ungerleider, “The acquisition of skilled motor performance: Fast and slow experience-driven changes in primary motor cortex,” Proc. Natl. Acad. Sci. USA, 95, 861–868 (1998).CrossRefPubMedGoogle Scholar
  13. 13.
    S. W. Keele, R. Ivry, U. Mayr, E. Hazeltine, and H. Heuer, “The cognitive and neural architecture of sequence representation,” Psychol. Rev., 110, No. 2, 316–339 (2003).CrossRefPubMedGoogle Scholar
  14. 14.
    M. Korman, N. Raz, T. Flash, and A. Karni, “Multiple shifts in the representation of a motor sequence during the acquisition of skilled performance,” Proc. Natl. Acad. Sci. USA, 100, No. 21, 12492–12497 (2003).CrossRefPubMedGoogle Scholar
  15. 15.
    A. Moore and J. De Houwer, “Automaticity: A theoretical and conceptual analysis,” Psychol. Bull., 132, No. 2, 297–326 (2006).CrossRefGoogle Scholar
  16. 16.
    J. T. Mordkoff and S. Yantis, “An interactive race model of divided attention,” J. Exp. Psychol. Hum. Percept. Perform., 17, No. 2, 520–538 (1991).CrossRefPubMedGoogle Scholar
  17. 17.
    B. J. Rhodes, D. Bullock, W. B. Verwey, B. B. Averbeck, and M. P. A. Page, “Learning and production of movement sequences: Behavioral, neurophysiological, and modeling perspectives,” Hum. Mov. Sci., 23, 699–746 (2004).CrossRefPubMedGoogle Scholar
  18. 18.
    D. A. Rosenbaum, R. A. Carlson, and R. O. Gilmore, “Acquisition of intellectual and perceptual-motor skills,” Ann. Rev. Psychol., 52, 453–470 (2001).CrossRefGoogle Scholar
  19. 19.
    K. Sakai, O. Hikosaka, and K. Nakamura, “Emergence of rhythm during motor learning,” Trends Cogn. Sci., 8, No. 12, 547–553 (2004).CrossRefPubMedGoogle Scholar
  20. 20.
    P. L. Smith and R. Ratcliff, “Psychology and neurobiology of simple decisions,” Trends Neurosci., 27, No. 3, 161–167 (2004).CrossRefPubMedGoogle Scholar
  21. 21.
    D. B. Willingham, “A neuropsychological theory of motor skill learning,” Psychol. Rev., 105, No. 3, 558–584 (1998).CrossRefPubMedGoogle Scholar

Copyright information

© Springer Science+Business Media, Inc. 2011

Authors and Affiliations

  1. 1.Institute of Developmental Physiology, Russian Academy of EducationMoscowRussia

Personalised recommendations