Advertisement

Attention, Perception, & Psychophysics

, Volume 81, Issue 2, pp 533–542 | Cite as

Perceptual-learning evidence for inter-onset-interval- and frequency-specific processing of fast rhythms

  • Ruijing NingEmail author
  • Samuel J. Trosman
  • Andrew T. Sabin
  • Beverly A. Wright
Article

Abstract

Rhythm is fundamental to music and speech, yet little is known about how even simple rhythmic patterns are processed. Here we investigated the processing of isochronous rhythms in the short inter-onset-interval (IOI) range (IOIs < 250–400 ms) using a perceptual-learning paradigm. Trained listeners (n=8) practiced anisochrony detection with a 100-ms IOI marked by 1-kHz tones, 720 trials per day for 7 days. Between pre- and post-training tests, trained listeners improved significantly more than controls (no training; n=8) on the anisochrony-detection condition that the trained listeners practiced. However, the learning on anisochrony detection did not generalize to temporal-interval discrimination with the trained IOI (100 ms) and marker frequency (1 kHz) or to anisochrony detection with an untrained marker frequency (4 kHz or variable frequency vs. 1 kHz), and generalized negatively to anisochrony detection with an untrained IOI (200 ms vs. 100 ms). Further, pre-training thresholds were correlated among nearly all of the conditions with the same IOI (100-ms IOIs), but not between conditions with different IOIs (100-ms vs. 200-ms IOIs). Thus, it appears that some task-, IOI-, and frequency-specific processes are involved in fast-rhythm processing. These outcomes are most consistent with a holistic rhythm-processing model in which a holistic “image” of the stimulus is compared to a stimulus-specific template.

Keywords

Temporal processing Perceptual learning Psychoacoustics 

Notes

Acknowledgments

We thank Paul Reber and Sazzad Nassir for their helpful comments on a preliminary draft of this paper. This work was sponsored in part by NIH/NIDCD, by the Defense Advanced Research Projects Agency (DARPA) Biological Technologies Office (BTO) TNT program under the auspices of Dr. Doug Weber and Tristan McClure-Begley through the Space and Naval Warfare Systems Center, Pacific Grant/Contract No. N66001-17-2-4011, and by a Northwestern University Undergraduate Summer Research Grant.

Disclaimer

Any opinions, findings, and conclusions or recommendations expressed in this publication are those of the author(s) and do not necessarily reflect the views of the Defense Advanced Research Projects Agency (DARPA) Biological Technologies Office (BTO).

References

  1. Benjamini, Y., & Hochberg, Y. (1995). Controlling the false discovery rate: a practical and powerful approach to multiple testing. Journal of the Royal Statistical Society. Series B (Methodological), 57(1), 289–300.Google Scholar
  2. Bhatara, A., Tirovolas, A. K., Duan, L. M., Levy, B., & Levitin, D. J. (2011). Perception of emotional expression in musical performance. Journal of Experimental Psychology: Human Perception and Performance, 37(3), 921–934.  https://doi.org/10.1037/a0021922
  3. Drake, C., & Botte, MC. (1993). Tempo sensitivity in auditory sequences: Evidence for a multiple-look model. Perception & Psychophysics, 54(3), 277–286.  https://doi.org/10.3758/BF03205262 CrossRefGoogle Scholar
  4. Fitzgerald, M. B., & Wright, B. A. (2005). A perceptual learning investigation of the pitch elicited by amplitude-modulated noise. The Journal of the Acoustical Society of America, 118(6), 3794–3803.  https://doi.org/10.1121/1.2074687 CrossRefGoogle Scholar
  5. Friberg, A., & Sundberg, J. (1995). Time discrimination in a monotonic, isochronous sequence, The Journal of the Acoustical Society of America, 98(5), 2524–2531.  https://doi.org/10.1121/1.413218 CrossRefGoogle Scholar
  6. Grahn, J. A. (2012). Neural mechanisms of rhythm perception: Current findings and future perspectives. Topics in Cognitive Science, 4(4), 585–606.  https://doi.org/10.1111/j.1756-8765.2012.01213.x
  7. Henry, M. J., & McAuley, J. D. (2009). Evaluation of an imputed pitch velocity model of the auditory kappa effect. Journal of Experimental Psychology: Human Perception and Performance, 35(2), 551–564.  https://doi.org/10.1037/0096-1523.35.2.551
  8. Hibi, S. (1983). Rhythm perception in repetitive sound sequence. Journal of the Acoustical Society of Japan (E), 4(2), 83–95.  https://doi.org/10.1250/ast.4.83
  9. Hirsh, I. J., Monahan, C. B., Grant, K. W., & Singh, P. G. (1990). Studies in auditory timing: 1. Simple patterns. Perception & Psychophysics, 47(3), 215–226.  https://doi.org/10.3758/BF03204997 CrossRefGoogle Scholar
  10. Juslin, P. N., & Laukka, P. (2003). Emotional expression in speech and music. Annals of the New York Academy of Sciences, 1000(1), 279–282.  https://doi.org/10.1196/annals.1280.025
  11. Karmarkar, U. R., & Buonomano, D. V. (2003). Temporal specificity of perceptual learning in an auditory discrimination task. Learning & Memory, 10(2), 141–147.  https://doi.org/10.1101/lm.55503 CrossRefGoogle Scholar
  12. Keele, S. W., Nicoletti, R., Ivry, R. I., & Pokorny, R. A. (1989). Mechanisms of perceptual timing: Beat-based or interval-based judgements? Psychological Research, 50(4), 251–256.  https://doi.org/10.1007/BF00309261 CrossRefGoogle Scholar
  13. Kohno, M. (1992). Two mechanisms of processing sound sequences. In Speech Perception, Production and Linguistic Structure (pp. 287–293). Amsterdam, the Netherlands: IOS Press.Google Scholar
  14. Lake, J. I., LaBar, K. S., & Meck, W. H. (2014). Hear it playing low and slow: How pitch level differentially influences time perception. Acta Psychologica, 149, 169–177.  https://doi.org/10.1016/j.actpsy.2014.03.010 CrossRefGoogle Scholar
  15. Levitt, H. (1971). Transformed up-down methods in psychoacoustics. The Journal of the Acoustical Society of America, 49(2B), 467–477.CrossRefGoogle Scholar
  16. London, J. (2012). Hearing in time: Psychological aspects of musical meter. Oxford, UK: Oxford University Press.Google Scholar
  17. Matell, M. S., & Meck, W. H. (2000). Neuropsychological mechanisms of interval timing behavior. Bioessays, 22(1), 94–103.CrossRefGoogle Scholar
  18. Merker, B. H., Madison, G. S., & Eckerdal, P. (2009). On the role and origin of isochrony in human rhythmic entrainment. Cortex, 45(1), 4–17.  https://doi.org/10.1016/j.cortex.2008.06.011 CrossRefGoogle Scholar
  19. Michon, J. A. (1964). Studies on subjective duration: I. Differential sensitivity in the perception of repeated temporal intervals. Acta Psychologica, 22, 441–450.  https://doi.org/10.1016/0001-6918(64)90032-0 CrossRefGoogle Scholar
  20. Miller, J. L., Grosjean, F., & Lomanto, C. (1984). Articulation rate and its variability in spontaneous speech: A reanalysis and some implications. Phonetica, 41(4), 215–225.  https://doi.org/10.1159/000261728 CrossRefGoogle Scholar
  21. Pashler, H. (2001). Perception and production of brief durations: beat-based versus interval-based timing. Journal of Experimental Psychology: Human Perception and Performance, 27(2), 485.  https://doi.org/10.1037/0096-1523.27.2.485 Google Scholar
  22. Rammsayer, T. H., & Altenmüller, E. (2006). Temporal information processing in musicians and nonmusicians. Music Perception: An Interdisciplinary Journal, 24(1), 37–48.  https://doi.org/10.1525/mp.2006.24.1.37 CrossRefGoogle Scholar
  23. Rammsayer, T. H., & Brandler, S. (2004). Aspects of temporal information processing: A dimensional analysis. Psychological Research, 69(1–2), 115–123.  https://doi.org/10.1007/s00426-003-0164-3 CrossRefGoogle Scholar
  24. Ravignani, A., & Madison, G. (2017). The paradox of isochrony in the evolution of human rhythm. Frontiers in Psychology, 8, 1820.  https://doi.org/10.3389/fpsyg.2017.01820
  25. Regan, D., & Beverley, K. I. (1985). Postadaptation orientation discrimination. Journal of the Optical Society of America A, 2(2), 147–155.  https://doi.org/10.1364/JOSAA.2.000147 CrossRefGoogle Scholar
  26. Ritter, F. E., & Schooler, L. J. (2001). The learning curve. In International Encyclopedia of the Social and Behavioral Sciences (Vol.13, pp. 8602–8605). Amsterdam, the Netherlands: Pergamon.Google Scholar
  27. Sabin, A. T., Eddins, D. A., & Wright, B. A. (2012). Perceptual learning evidence for tuning to spectrotemporal modulation in the human auditory system. Journal of Neuroscience, 32(19), 6542–6549.  https://doi.org/10.1523/JNEUROSCI.5732-11.2012 CrossRefGoogle Scholar
  28. Schulze, HH. (1978). The detectability of local and global displacements in regular rhythmic patterns. Psychological Research, 40(2), 173–181.  https://doi.org/10.1007/BF00308412 CrossRefGoogle Scholar
  29. Sussman, E. S., & Gumenyuk, V. (2005). Organization of sequential sounds in auditory memory. Neuroreport, 16(13), 1519–1523.  https://doi.org/10.1097/01.wnr.0000177002.35193.4c CrossRefGoogle Scholar
  30. ten Hoopen, G., Berg, S. V. D., Memelink, J., Bocanegra, B., & Boon, R. (2011). Multiple-look effects on temporal discrimination within sound sequences. Attention, Perception, & Psychophysics, 73(7), 2249–2269.  https://doi.org/10.3758/s13414-011-0171-1 CrossRefGoogle Scholar
  31. ten Hoopen, G., Boelaarts, L., Gruisen, A., Apon, I., Donders, K., Mul, N., & Akerboom, S. (1994). The detection of anisochrony in monaural and interaural sound sequences. Perception & Psychophysics, 56(1), 110–120.  https://doi.org/10.3758/BF03211694 CrossRefGoogle Scholar
  32. ten Hoopen, G., Hartsuiker, R., Sasaki, T., Nakajima, Y., Tanaka, M., & Tsumura, T. (1995). Auditory isochrony: Time shrinking and temporal patterns. Perception, 24(5), 577–593.  https://doi.org/10.1068/p240577 CrossRefGoogle Scholar
  33. Thaut, M. (2013). Rhythm, Music, and the Brain: Scientific Foundations and Clinical Applications. New York, NY: Routledge.  https://doi.org/10.4324/9780203958827
  34. Torchiano, M. (2017). effsize: Efficient effect size computation (R package version 0.7.1). Retrieved from https://CRAN.R-project.org/package=effsize
  35. Treisman, M. (1963). Temporal discrimination and the indifference interval: Implications for a model of the internal clock. Psychological Monographs: General and Applied, 77(13), 1–31.  https://doi.org/10.1037/h0093864
  36. Warren, B. M., & Ackroff, J. M. (1976). Two types of auditory sequence perception. Perception & Psychophysics, 20(5), 387–394.  https://doi.org/10.3758/BF03199420 CrossRefGoogle Scholar
  37. Wright, B. A., Buonomano, D. V., Mahncke, H. W., & Merzenich, M. M. (1997). Learning and generalization of auditory temporal-interval discrimination in humans. Journal of Neuroscience, 17(10), 3956–3963.  https://doi.org/10.1523/JNEUROSCI.17-10-03956.1997 CrossRefGoogle Scholar
  38. Wright, B. A., Lombardino, L. J., King, W. M., Puranik, C. S., Leonard, C. M., & Merzenich, M. M. (1997). Deficits in auditory temporal and spectral resolution in language-impaired children. Nature, 387(6629), 176–178.  https://doi.org/10.1038/387176a0 CrossRefGoogle Scholar
  39. Wright, B. A., & Fitzgerald, M. B. (2004). The time course of attention in a simple auditory detection task. Perception & Psychophysics, 66(3), 508–516.  https://doi.org/10.3758/BF03194897 CrossRefGoogle Scholar

Copyright information

© The Psychonomic Society, Inc. 2018

Authors and Affiliations

  • Ruijing Ning
    • 1
    Email author
  • Samuel J. Trosman
    • 1
  • Andrew T. Sabin
    • 1
  • Beverly A. Wright
    • 1
    • 2
    • 3
  1. 1.Department of Communication Sciences and DisordersNorthwestern UniversityEvanstonUSA
  2. 2.Knowles Hearing CenterNorthwestern UniversityEvanstonUSA
  3. 3.Northwestern University Institute for NeuroscienceNorthwestern UniversityEvanstonUSA

Personalised recommendations