Effects of accuracy feedback on fractal characteristics of time estimation

Frontiers in Integrative Neuroscience

Volumn 5, Issue , 2011, Pages

  Kuznetsov, Nikita A ^a   Wallot, Sebastian ^a  

^a UNIVERSITY OF CINCINNATI   (United States)

Author keywords

1 f noise; Accuracy feedback; Embodied cognition; Multifractal; Time estimation

Indexed keywords

ACCURACY; ADULT; ARTICLE; BEHAVIOR; COGNITION; CONTROLLED STUDY; CORRELATION ANALYSIS; FEMALE; FINGER; HUMAN; HUMAN EXPERIMENT; MALE; NORMAL HUMAN; TIME PERCEPTION; VISUAL FEEDBACK; WHITE NOISE;

EID: 82255160741     PISSN: 16625145     EISSN: None     Source Type: Journal    
DOI: 10.3389/fnint.2011.00062     Document Type: Article

References (71)

1. Anderson, M. L. (2010). Neural reuse: a fundamental organizational principle of the brain. Behav. Brain Sci. 33,245-313.
2. Aschwanden, M. (2011). Self-Organized Criticality in Astrophysics: The Statistics of Nonlinear Processes in the Universe. Berlin: Springer-Verlag.
3. Bak, P. (1996). How Nature Works. The Since of Self-Organized Criticality. New York, NY: Copernicus.
4. Bernstein, N. A. (1967). The Coordination and Regulation of Movements. Oxford: Pergamon Press.
5. Block, R. A. (1990). Models of psychological time, in Cognitive Models of Psychological Time, ed. R. A. Block (Hillsdale, NJ: Erlbaum), 1-35.
6. Brainard, D. H. (1997). The psychophysics toolbox. Spat. Vis. 10, 433-436.
7. Brown, C., and Liebovitch, L. (2010). Fractal Analysis. Los Angeles, CA: Sage.
8. Buhusi, C. V., and Meck, W. H. (2009). Relativity theory and time perception: single or multiple clocks? PLoS ONE 4, e6268. doi: 10.1371/jour-nal.pone.0006268
9. Buzsaki, G. (2006). Rhythms of the Brain. New York, NY: Oxford University Press.
10. Castillo, R. D., Van Orden, G. C., and Kloos, H. (2011). The embodiment of time estimation, in Time and Time Perception 2010, eds A. Vatakis, A. Esposito, M. Giagkou, F. Cummins, and G. Papadelis (Heidelberg: Springer-Verlag), 196-206.
11. Chen, Y., Ding, M., and Kelso, J. A. S. (1997). Long memory processes (1/fα type) in human coordination. Phys. Rev. Lett. 79, 4502-4504.
12. Chen, Y., Repp, B., and Patel, A. (2002). Spectral decomposition of variability in synchronization and continuation tapping: comparisons between auditoryand visual pacingand feedback conditions. Hum. Mov. Sci. 21, 515-532.
13. Delignières, D., Lemoine, L., and Torre, K. (2004). Timeintervalsproduction in tapping and oscillatory motion. Hum. Mov. Sci. 23, 87-103.
14. Delignières, D., and Torre, K. (2009). Fractal dynamics of human gait: A reassessment of the 1996 data of Hausdorff et al. J. Appl. Physiol. 106, 1272-1279.
15. Delignières, D., and Torre, K. (2011). Event-based and emergent timing: dichotomyor continuum? Areplyto Repp and Steinman (2010). J. Mot. Behav. 43, 311-318.
16. Delignières, D., Torre, K., and Lemoine, L. (2008). Fractal models for event-based and dynamical timers. Acta Psychol. (Amst.) 127, 382-397.
17. Diniz, A., Wijnants, M. L., Torre, K., Barreiros, J., Crato, N., Bosman, A. M. T., Hasselman, F., Cox, R. F. A., van Orden, G. C., and Delignières, D. (2010). Contemporary theories of 1/f noise in motor control. Hum. Mov. Sci. 30, 889-905.
18. Eke, A., Herman, P., Bassingthwaighte, J. B., Raymound, G. M., Percival, D. B., Cannon, M., Balla, I., and Ikrenyi, C. (2000). Physiological time series: distinguishing fractal noises from motions. Eur. J. Physiol. 439, 403-415.
19. Eke, A., Herman, P., and Kozak, L. R. (2002). Fractal characterization of complexity in temporal physiological signals. Physiol. Meas. 23, R1-R38.
20. Frette, V., Christensen, Malthe-Sørenssen, A., Feder, J., Jøssang, T., and Meakin, P. (1996). Avalanche dynamics in a pile of sand. Nature 379, 49-52.
21. Gibson, J. J. (1966). The Senses Considered as Perceptual Systems. Boston: Houghton Mifflin.
22. Gilden, D. L. (2001). Cognitive emissions of 1/f noise. Psychol. Rev. 108, 33-56.
23. Gilden, D. L., Thornton, T., and Mallon, M. (1995). 1/f noise in human cognition. Science 267, 1837-1839.
24. Haselager, P., van Dijk, J., and van Rooj, I. (2008). A lazy brain? Embodied embedded cognition and cognitive neuroscience, in Handbook of Cognitive Science: An Embodied Approach, eds P. Calvo and T. Gomila (Oxford: Elsevier), 273-287.
25. Hausdorff, J. M., Purdon, P. L., Peng, C.-K., Ladin, Z., Wei, J. Y., and Goldberger, A. L. (1996). Fractal dynamics of human gait: stability of long-range correlations in stride interval fluctuations. J. Appl. Physiol. 80, 1448-1457.
26. Holden, J. G. (2005). Gauging the fractal dimension of response times from cognitive tasks, in Contemporary Nonlinear Methods for Behavioral Scientists, eds M. A. Riley and G. C. Van Orden, 267-318. Available at: http://www.nsf.gov/sbe/bcs/pac/nmbs/nmbs.jsp [Retrieved April 8, 2011].
27. Holden, J. G., Choi, I., Amazeen, P. G., and van Orden, G. C. (2011). Fractal 1/f dynamics suggest entanglement of measurement and human performance. J. Exp. Psychol. Hum. Percept. Perform. 37, 935-948.
28. α fluctuation. J. Exp. Psychol. Gen. 139, 426-463.
29. Ivanov, P. C., Amaral, L. A. N., Gold-berger, A. L., Havlin, S., Rosenblum, M. G., Struzik, Z. R., and Stanley, H. E. (1999). Multifractality in human heartbeat dynamics. Nature 399, 461-465.
30. Järvilehto, T. (1998). The theory of the organism-environment system: I. Description of the theory. Integr. Physiol. Behav. Sci. 33, 321-334.
31. Jazaheri, M., and Shadlen, M. N. (2010). Temporal context calibrates interval timing. Nat. Neurosci. 13, 1020-1026.
32. Jensen, H. J. (1998). Self-Organized Criticality. Cambridge: Cambridge University Press.
33. Kantelhardt, J. W., Zschiegner, S. A., Koscielny-Bunde, E., Havlin, S., Bunde, A., and Stanley, H. E. (2002). Multifractal detrended fluctuation analysis of non stationary time series. Physica A 316, 87-114.
34. Kello, C. T., Anderson, G. G., Holden, J. G., and Van Orden, G. C. (2008). The pervasiveness of 1/f scaling in speech reflects the metastable basis of cognition. Cogn. Sci. 32, 1217-1231.
35. Kello, C. T., Beltz, B., Holden, J. G., and Van Orden, G. C. (2007). The emergent coordination of cognitive function. J. Exp. Psychol. Gen. 136, 551-568.
36. Kello, C. T., Brown, G. D. A., Ferrer-i-Cancho, R., Holden, J. G., Linkenkaer-Hansen, K., Rhodes, T., and Van Orden, G. C. (2010). Scaling laws in cognitive sciences. Trends Cogn. Sci. (Regul. Ed.) 14, 223-232.
37. Kello, C. T., and van Orden, G. C. (2009). Soft-assembly of sensorimotor function. Nonlinear Dynamics Psychol. Life Sci. 13, 57-78.
38. Kelso, J. A. S. (1995). Dynamic Patterns: The Self-Organization of Brain and Behavior. Cambridge, MA: MIT Press.
39. Kiefer, A., Riley, M. A., Shockley, K., Villard, S., and van Orden, G. C. (2009). Walking changes the dynamics of cognitive estimates of time intervals. J. Exp. Psychol. Hum. Percept. Perform. 35, 1532-1541.
40. Kloos, H., and Van Orden, G. C. (2010). Voluntary behavior in cognitive and motor tasks. Mind Matter 8, 19-43.
41. Lemoine, L., Torre, K., and Delignières, D. (2006). Testing for the presence of 1/f noise in continuation tapping data. Can. J. Exp. Psychol. 60, 247-257.
42. Linkenkaer-Hansen, K., Nikouline, V. V., Palva, M. J., and Ilmoniemi, R. J. (2001). Long-range temporal correlations and scaling behavior in human brain oscillations. J. Neurosci. 21, 1370-1377.
43. Madison, G., and Delignières, D. (2009).Auditory feed back affects the long-range correlation of isochronous serial production: support for a closed-loop or memory model of timing. Exp. Brain Res. 193, 519-527.
44. Mandelbrot, B. B. (1997). Fractals and Scaling in Finance. NewYork: Springer-Verlag.
45. Münsterberg, H. (1866). Beiträge zur experimentellen Psychologie, in The Principles of Psychology, Vol. 1, ed. W. James (New York: Henry Holt and Co), 620-627.
46. Newell, K. M. (1986). Constraints on the development of coordination, in Motor Development in Children: Aspects of Coordination and Control, eds M. Wade and H. Whiting (Dordrecht: Martinus Nijhoff), 341-360.
47. Percival, D. B., and Walden, A. T. (2000). Wavelet Methods for Time Series Analysis. New York, NY: Cambridge University Press.
48. Pressing, J. (1998). Error correction processes in temporal pattern production. J. Math. Psychol. 42, 63-101.
49. Riley, M. A., and Turvey, M. T. (2002). Variability and determinism in motor behavior. J. Mot. Behav. 34, 99-125.
50. Schöner, G. (2002). Timing, clocks, and dynamical systems. Brain Cogn. 48, 31-51.
51. Slifkin, A. B., and Newell, K. M. (1998). Is variabilityin human performance a reflection of system noise? Curr. Dir. Psychol. Sci. 7, 170-177.
52. Stetson, D. A., Albers, J. W., Silverstein, B. A., and Wolfe, R. A. (1992). Effects of age, sex, and anthropometric factors on nerve conduction measures. Muscle Nerve 15, 1095-1104.
53. β noise in self-paced and synchronized tapping: a unifying mechanistic model. Biol. Cybern. 99, 159-170.
54. Torre, K., and Wagenmakers, E. J. (2009). Theories and models of 1/f? noise in human movement science. Hum. Mov. Sci. 28, 297-318.
55. Turvey, M.T. (2007). Action and perception at the level of synergies. Hum. Mov. Sci. 26, 657-697.
56. Van Orden, G. C., Holden, J. G., and Tur-vey, M. T. (2003). Self-organization of cognitive performance. J. Exp. Psychol. Gen. 132, 331-350.
57. Van Orden, G. C., Holden, J. G., and Turvey, M. T. (2005). Human cognition and 1/f scaling. J. Exp. Psychol. Gen. 134, 117-123.
58. Van Orden, G. C., Kello, C. T., and Holden, J. G. (2010). Situated behavior and the place of measurement in psychological theory. Ecol. Psychol. 22, 24-43.
59. van Orden, G. C., Kloos, H., and Wallot, S. (2011). Living in the pink: intentionality, wellbeing, and complexity, in Philosophy of Complex Systems. Handbook of the Philosophy of Science, ed. C. A. Hooker (Amsterdam: Elsevier), 639-684.
60. Vorberg, D., and Wing, A. (1996). Modeling variability and dependence in timing, in Handbook of Perception and Action, Vol. 2, eds H. Heuer and S. W. Keele (London: Academic Press), 181-262.
61. Wagenmakers, E. J., Farrel, S., and Ratcliff, R. (2004). Estimation and interpretation of 1/f-noise in human cognition. Psychon. Bull. Rev. 11, 579-615.
62. Wagenmakers, E. J., Farrell, S., and Ratcliff, R. (2005). Human cognition and a pile of sand: a discussion on serial correlations and self-organized criticality. J. Exp. Psychol. Gen. 135, 108-116.
63. Ward, L. (2002). Dynamical Cognitive Science. Cambridge, MA: MIT Press.
64. Wearden, J. H., and McShane, B. (1988). Interval production as an analogue of the peak procedure: evidence for similarity of human and animal timing processes. Q.J. Exp. Psychol. B 40, 363-375.
65. Werner, G. (2010). Fractals in the nervous system: conceptual implications for theoretical neuroscience. Front. Physiol. 1:15. doi: 10.3389/fphys.2010.00015
66. West, B. J., and Deering, B. (1995). The Lure of Modern Science: Fractal Thinking. Singapore: World Scientific.
67. West, B. J., and Scafetta, N. (2003). A nonlinear dynamical model of human gait. Phys. Rev. E67, 051917.
68. Wijnants, M. L., Bosman, A. M. T., Hasselman, F., Cox, R. F. A., and Van Orden, G. C. (2009). 1/f scaling in movement time changes with practice in precision aiming. Nonlinear Dynamics Psychol. Life Sci. 13, 79-98.
69. Wing, A. M. (1980). The long and short of timing in response sequences, in Tutorials in Motor Behavior, eds G. E. Stelmach and J. Requin (Amsterdam: North Holland), 469-486.
70. Wing, A. M., and Kristofferson, A. B. (1973). Response delays and the timing of discrete motor responses. Percept. Psychophys. 14, 5-12.
71. α fluctuations in a ricepile model. Phys. Rev. E61, 5983-5986.