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The influence of metricality and modality on synchronization with a beat

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Abstract

The great majority of the world’s music is metrical, i.e., has periodic structure at multiple time scales. Does the metrical structure of a non-isochronous rhythm improve synchronization with a beat compared to synchronization with an isochronous sequence at the beat period? Beat synchronization is usually associated with auditory stimuli, but are people able to extract a beat from rhythmic visual sequences with metrical structure? We addressed these questions by presenting listeners with rhythmic patterns which were either isochronous or non-isochronous in either the auditory or visual modality, and by asking them to tap to the beat, which was prescribed to occur at 800-ms intervals. For auditory patterns, we found that a strongly metrical structure did not improve overall accuracy of synchronization compared with isochronous patterns of the same beat period, though it did influence the higher-level patterning of taps. Synchronization was impaired in weakly metrical patterns in which some beats were silent. For the visual patterns, we found that participants were generally unable to synchronize to metrical non-isochronous rhythms, or to rapid isochronous rhythms. This suggests that beat perception and synchronization have a special affinity with the auditory system.

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Notes

  1. Importantly, the human uniqueness of BPS is not due to a lack of accurate timekeeping mechanisms in other animals. For example, studies of rabbits (e.g., Moore et al. 1998) show that other mammals are capable of interval timing. Given this fact, it is curious that despite many decades of research in psychology and neuroscience in which animals have been trained to do complex motor tasks, there is to our knowledge not a single published case in which a non-human animal species has been successfully trained to tap or peck in synchrony with an auditory metronome.

  2. We are grateful to Edward Large for confirming these predictions with the coupled-oscillator model of Large and Jones (1999) and with a newer version of this model, using our stimuli as input.

  3. Throughout this paper, the term “synchronization accuracy” refers to the variability of tapping as measured by the variability of tap-to-tone asynchronies or of inter-tap-intervals (ITIs), and not to absolute asynchronies or mean ITIs.

  4. The actual inter-beat interval was 781 ms because the software used for sequence generation (MAX 3.0 running on a Macintosh Quadra 660AV computer) produced output that was 2.4% faster than specified. Throughout the paper, we report the specified or recorded temporal values. Actual values can be obtained, if necessary, by multiplying by .976.

  5. Accents perceived due to grouping rather than due to physical differences between events such as intensity differences.

  6. We did not have the equipment necessary to determine the precise luminance and duration of the flashes. However, we determined informally that a flicker sensation persisted up to rates of about 30 Hz, i.e., a 33-ms IOI.

  7. It should be noted that Povel and Essens (1985), who provided the patterns we used in our study, were interested in a model of rhythm perception based on different coding strategies for metrical and non-metrical sequences, and were not working in an entrainment / attentional-oscillator based framework. Nevertheless, their sequences are useful for exploring predictions of this framework.

  8. It is likely that the recurring long interval also aided synchronization with auditory sequences, especially WM sequences. The difference between auditory SM and WM sequences might have been even more striking if that long interval had not been present. We are currently investigating this issue.

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Acknowledgements

We thank Mari Jones for insightful comments. This research was supported by Neurosciences Research Foundation as part of its program on music and the brain at The Neurosciences Institute, where ADP is the Esther J. Burnham fellow and JRI is the Karp Foundation Fellow, by the H.A. and Mary K. Chapman Charitable Trust, and by National Institutes of Health Grant MH-51230 to BHR.

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  1. The Neurosciences Institute, 10640 John Jay Hopkins Drive, San Diego, CA , 92121, USA

    Aniruddh D. Patel, John R. Iversen & Yanqing Chen

  2. Haskins Laboratories, 270 Crown St., New Haven, CT , 06511, USA

    Bruno H. Repp

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  1. Aniruddh D. Patel
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Correspondence to Aniruddh D. Patel.

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Patel, A.D., Iversen, J.R., Chen, Y. et al. The influence of metricality and modality on synchronization with a beat. Exp Brain Res 163, 226–238 (2005). https://doi.org/10.1007/s00221-004-2159-8

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