Open Access
Issue
EPJ Nonlinear Biomed Phys
Volume 3, Number 1, December 2015
Article Number 8
Number of page(s) 15
DOI https://doi.org/10.1140/epjnbp/s40366-015-0022-4
Published online 12 August 2015
  1. Fitts PM. The information capacity of the human motor system in controlling the amplitude of movement. J Exp Psychol. 1954;47(6):381–91. [Google Scholar]
  2. Fitts PM, Peterson JR. Information capacity of discrete motor responses. J Exp Psychol. 1964;67(2):103–12. [Google Scholar]
  3. Shannon C, Weaver W. The mathematical theory of communication. Urbaba, IL: University of Illinois Press; 1949. [Google Scholar]
  4. MacKenzie IS. Fitts’ law as a research and design tool in human-computer interaction. Human-Computer Interaction. 1992;7:91–139. [Google Scholar]
  5. Meyer DE, Kornblum S, Abrams RA, Wright CE, Smith JEK. Optimality in human motor-performance - ideal control of rapid aimed movements. Psychol Rev. 1988;95(3):340–70. doi:10.1037/0033-295x.95.3.340. [Google Scholar]
  6. Schmidt RA, Zelaznik H, Hawkins B, Frank JS, Quinn JT. Motor-output variability - theory for the accuracy of rapid motor acts. Psychol Rev. 1979;86(5):415–51. doi:10.1037//0033-295x.86.5.415. [Google Scholar]
  7. Guiard Y. The problem of consistency in the design of Fitts’ law experiments: consider either target distance and width or movement form and scale. ACM Conference on Human Factors in Computing Systems. New York: Sheridan Press; 2009. p. 1908–18. [Google Scholar]
  8. Welford AT, Norris AH, Shock NW. Speed and accuracy of movement and their changes with age. Acta Psychol. 1969;30:3–15. [Google Scholar]
  9. Buchanan JJ, Park JH, Shea CH. Target width scaling in a repetitive aiming task: switching between cyclical and discrete units of action. Exp Brain Res. 2006;175(4):710–25. doi:10.1007/S00221-006-0589-1. [Google Scholar]
  10. Guiard Y. Fitts’ law in the discrete vs cyclical paradigm. Hum Movement Sci. 1997;16(1):97–131. doi:10.1016/S0167-9457(96)00045-0. [Google Scholar]
  11. Mottet D, Bootsma RJ. The dynamics of goal-directed rhythmical aiming. Biol Cybern. 1999;80(4):235–45. doi:10.1007/S004220050521. [Google Scholar]
  12. Sleimen-Malkoun R, Temprado JJ, Huys R, Jirsa V, Berton E. Is Fitts’ Law continuous in discrete aiming? Plos One. 2012;7(7):e41190. doi:10.1371/journal.pone.0041190. [Google Scholar]
  13. Smits-Engelsman BC, Swinnen SP, Duysens J. The advantage of cyclic over discrete movements remains evident following changes in load and amplitude. Neurosci Lett. 2006;396(1):28–32. doi:10.1016/j.neulet.2005.11.001. [Google Scholar]
  14. Crossman ERFW, Goodeve PJ. Feedback control of hand-movement and Fitts’ law. Q J Exp Psychol. 1963;35A:407–25. [Google Scholar]
  15. Bongers RM, Fernandez L, Bootsma RJ. Linear and logarithmic speed-accuracy trade-offs in reciprocal aiming result from task-specific parameterization of an invariant underlying dynamics. J Exp Psychol Human. 2009;35(5):1443–57. doi:10.1037/A0015783. [Google Scholar]
  16. Guiard Y. On Fitts and Hooke laws - simple harmonic movement in upper-limb cyclical aiming. Acta Psychol. 1993;82(1–3):139–59. doi:10.1016/0001-6918(93)90009-G. [Google Scholar]
  17. Huys R, Fernandez L, Bootsma RJ, Jirsa VK. Fitts’ law is not continuous in reciprocal aiming. P Roy Soc B-Biol Sci. 2010;277(1685):1179–84. doi:10.1098/Rspb.2009.1954. [Google Scholar]
  18. van Mourik AM, Daffertshofer A, Beek PJ. Extracting global and local dynamics from the stochastics of rhythmic forearm movements. J Mot Behav. 2008;40(3):214–31. doi:10.3200/JMBR.40.3.214-231. [Google Scholar]
  19. Strogatz SH. Nonlinear dynamics and chaos: with applications to physics, biology, chemistry, engineering. Cambridge Massachusetts: Perseus Books Publishing, LLC; 1994. [Google Scholar]
  20. Haken H, Kelso JAS, Bunz H. A theoretical-model of phase-transitions in human hand movements. Biol Cybern. 1985;51(5):347–56. doi:10.1007/Bf00336922. [Google Scholar]
  21. Kay BA, Saltzman EL, Kelso JAS, Schöner G. Space-time behavior of single and bimanual rhythmical movements - data and limit-cycle model. J Exp Psychol Human. 1987;13(2):178–92. doi:10.1037//0096-1523.13.2.178. [Google Scholar]
  22. Daffertshofer A, van Veen B, Ton R, Huys R. Discrete and rhythmic movements - just a bifurcation apart? IEEE International Conference on Systems, Man and Cybernetics; San Diego. CA: IEEE; 2014. p. 778–83. [Google Scholar]
  23. Kay BA. The dimensionality of movement trajectories and the degrees of freedom problem - a tutorial. Hum Movement Sci. 1988;7(2–4):343–64. doi:10.1016/0167-9457(88)90016-4. [Google Scholar]
  24. Jirsa VK, Kelso JAS. The excitator as a minimal model for the coordination dynamics of discrete and rhythmic movement generation. J Mot Behav. 2005;37(1):35–51. doi:10.3200/Jmbr.37.1.35-51. [Google Scholar]
  25. Schöner G. A dynamic theory of coordination of discrete movement. Biol Cybern. 1990;63(4):257–70. doi:10.1007/Bf00203449. [Google Scholar]
  26. Buchanan JJ, Park JH, Shea CH. Systematic scaling of target width: dynamics, planning, and feedback. Neurosci Lett. 2004;367(3):317–22. doi:10.1016/J.Neulet.2004.06.028. [Google Scholar]
  27. Thompson SG, McConnell DS, Slocum JS, Bohan M. Kinematic analysis of multiple constraints on a pointing task. Hum Movement Sci. 2007;26(1):11–26. doi:10.1016/J.Humov.2006.09.001. [Google Scholar]
  28. Sleimen-Malkoun R, Temprado JJ, Berton E. Age-related changes of movement patterns in discrete Fitts’ task. BMC Neurosci. 2013;14:145. doi:10.1186/1471-2202-14-145. [Google Scholar]
  29. Perdikis D, Huys R, Jirsa VK. Complex processes from dynamical architectures with time-scale hierarchy. PLoS One. 2011;6(2):e16589. doi:10.1371/journal.pone.0016589. [Google Scholar]
  30. Feldman AG. Once more on the equilibrium-point hypothesis (lambda-model) for motor control. J Mot Behav. 1986;18(1):17–54. [Google Scholar]
  31. Kugler PN, Kelso JAS, Turvey MT. On the concept of coordinative structures as dissipative structures: I. Theoretical lines of convergence. Advances in psychology: Vol.1. Tutorials in motor behavior. Amsterdam, the Netherlands: Elsevier B.V; 1980. p. 3–47. [Google Scholar]
  32. Saltzman EL, Munhall KG. Skill acquisition and development: the roles of state-, parameter, and graph dynamics. J Mot Behav. 1992;24(1):49–57. doi:10.1080/00222895.1992.9941600. [Google Scholar]
  33. Harris CM, Wolpert DM. Signal-dependent noise determines motor planning. Nature. 1998;394(6695):780–4. doi:10.1038/29528. [Google Scholar]
  34. Robertson SD, Zelaznik HN, Lantero DA, Bojczyk KG, Spencer RM, Doffin JG, et al. Correlations for timing consistency among tapping and drawing tasks: evidence against a single timing process for motor control. J Exp Psychol Human. 1999;25(5):1316–30. doi:10.1037/0096-1523.25.5.1316. [Google Scholar]
  35. Guiard Y, Olafsdottir H, Perrault S, editors. Fitts’ law as an explicit time/error trade-off. ACM Conference on Human Factors in Computing Systems, 2011. [Google Scholar]
  36. Kostrubiec V, Zanone PG, Fuchs A, Kelso JAS. Beyond the blank slate: routes to learning new coordination patterns depend on the intrinsic dynamics of the learner-experimental evidence and theoretical model. Front Hum Neurosci. 2012;6:Artn 222. doi:10.3389/Fnhum.2012.00222. [Google Scholar]
  37. Plamondon R, Alimi AM. Speed/accuracy trade-offs in target-directed movements. Behav Brain Sci. 1997;20(2):279–303. [Google Scholar]
  38. Welford AT. Fundamentals of skill. London, UK: Methuen; 1968. [Google Scholar]
  39. Peinke J, Friedrich R, Chilla F, Chabaud B, Naert A. Statistical dependency of eddies of different sizes in turbulence. Z Phys B Con Mat. 1996;101(2):157–9. doi:10.1007/S002570050194. [Google Scholar]
  40. van Mourik AM, Daffertshofer A, Beek PJ. Estimating Kramers-Moyal coefficients in short and non-stationary data sets. Phys Lett A. 2006;351(1–2):13–7. doi:10.1016/J.Physleta.2005.10.066. [Google Scholar]
  41. Huys R, Studenka BE, Rheaume NL, Zelaznik HN, Jirsa VK. Distinct timing mechanisms produce discrete and continuous movements. PLoS Comput Biol. 2008;4(4):Artn E1000061. doi:10.1371/Journal.Pcbi.1000061. [Google Scholar]

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