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Body movement enhances the extraction of temporal structures in auditory sequences

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Abstract

Auditory and motor systems interact in processing auditory rhythms. This study investigated the effect of intuitive body movement, such as head nodding or foot tapping, on listeners’ ability to entrain to the pulse of an auditory sequence. A pulse-finding task was employed using an isochronous sequence of tones in which tones were omitted at pseudorandom positions. Musicians and non-musicians identified their subjectively fitting pulse either using periodic body movement or through listening only. The identified pulse was measured subsequently by finger tapping. Movement appeared to assist pulse extraction especially for non-musicians. The chosen pulse tempi tended to be faster with movement. Additionally, movement led to higher synchronization stabilities of the produced pulse along the sequence, regardless of musical training. These findings demonstrated the facilitatory role of body movement in entraining to auditory rhythms and its interaction with musical training.

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Notes

  1. The terms pulse and beat are often used interchangeably in a musical context. However, beat implies a defined metrical organization based on the alternating strong and weak accentuation (Cooper & Meyer, 1960), which involves the perceptual grouping of pulse, e.g. groups of two or four as in a duple meter, or groups of three as in a waltz meter. Pulse itself, on the other hand, is not confined by metrical specifications; it exists as long as the isochrony is felt by the listener, and is generalizable in processing rhythms across different cultures and musical genres. Therefore, we prefer to use the term pulse here.

  2. A criterion of ITI stability for constituting a ‘pulse’ has not been established in the literature, as it would depend on the task condition and the given stimuli. A study on the perceptual threshold of pulse attribution (Madison & Merker, 2002) found an average 8.6% deviation of the inter-tone intervals in the sequence, beyond which the participants were unable to identify the pulse. Considering the higher difficulty in the present task as the tones in a sequence did not appear regularly, and that the pulse was measured by production, a criterion of 10% was used. This, together with the criterion on inter-pulse interval, appeared to reflect the interaction between musical training and movement well (Fig. 2).

  3. For detailed classification criteria, see Figure S1 and the described procedure in the supplementary material.

  4. Every participant was observed for around 20–30 min during the first experimental block, and also for a shorter while in the beginning of each successive block.

  5. Often two kinds of movement were adopted together by the same participant. The frequency of each employed movement was as follows: head nodding (6), foot tapping (9), and arm swiveling (1).

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Acknowledgments

This work was supported by the doctoral scholarship to the first author from the Bayerische Forschungsstiftung, and the experimental expenses were supported by the Andrea von Braun Foundation. The authors thank Marc Wittmann, Dragan Rangelov, and Björn Merker for earlier discussions of the work, as well as Bruno Repp and an anonymous reviewer for very useful inputs on the manuscript.

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The authors declare no conflict of interest.

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Correspondence to Yi-Huang Su.

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426_2011_346_MOESM1_ESM.eps

Figure S1. The illustration of the procedure and the criteria tree for classifying every ‘unstable trial’ into one of the three types: Type 1 – constantly irregular and unstable ITIs; Type 2 – switching between different pulse levels; Type 3 – missing taps or an unusual pause within an otherwise stable tap series. * We assigned the criterion of ‘not more than 2 outlier ITIs’ in a trial to suggest potential missing taps while the pulse series itself could still be maintained. After a cluster of one or two such outliers was identified, we checked the centroid of this outlier cluster and the centroid of the bigger cluster containing the majority of the ITIs. If the ratio between the bigger centroid and the smaller centroid was bigger than 1.5, suggesting that the outlier ITIs were sufficiently different from most of the other ITIs, then the outliers were likely to be ‘accidental mistakes’ within the taps. If not, then the two clusters were not sufficiently different in ITIs, and the whole tap series would be considered irregular as in Type 1. ** If the ITIs in the bigger cluster, without the outlier ITIs, had a CV less than 10%, then it further confirmed that generally stable pulse was produced in this trial, except for the couple of missing taps or longer pauses, thus classified as Type 3. If the ITIs in the bigger cluster still produced a CV bigger than 10%, then the tap series on the whole was not stable, classified as Type 1. *** If both clusters contained more than two items, then we did not consider the possibility of outlier ITIs. Instead, we checked whether the ratio between the bigger centroid and the smaller centroid was between 1.75 - 2.25, which indicated that one cluster centered around twice the ITI as the other cluster. This would then suggest the possibility of taps switching between two pulse levels, which was further verified by the CV of ITIs within each cluster. If both CVs were no greater than 10%, then it showed that equally stable taps were produced at two different pulse levels, thus classified as Type 2. If not, then we rejected the possibility of switching between pulse levels, and classified it as Type 1. (EPS 5240 kb)

426_2011_346_MOESM2_ESM.eps

Figure S2. Histogram distribution of the produced pulse tempi as the ratio to the stimulus tempo, in each tempo condition. Each row represents data from one participant group. Only the tempi from stable pulse trials are plotted. Bin width = 5% of each stimulus tempo. (EPS 4956 kb)

426_2011_346_MOESM3_ESM.eps

Figure S3. Mean number of stimulus pulse cycles (transformed from RT) as a function of the stimulus tempo, for each participant group. Error bars represent standard errors of the mean. (EPS 3114 kb)

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Su, YH., Pöppel, E. Body movement enhances the extraction of temporal structures in auditory sequences. Psychological Research 76, 373–382 (2012). https://doi.org/10.1007/s00426-011-0346-3

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