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Spontaneous synchronization to speech reveals neural mechanisms facilitating language learning

Abstract

We introduce a deceptively simple behavioral task that robustly identifies two qualitatively different groups within the general population. When presented with an isochronous train of random syllables, some listeners are compelled to align their own concurrent syllable production with the perceived rate, whereas others remain impervious to the external rhythm. Using both neurophysiological and structural imaging approaches, we show group differences with clear consequences for speech processing and language learning. When listening passively to speech, high synchronizers show increased brain-to-stimulus synchronization over frontal areas, and this localized pattern correlates with precise microstructural differences in the white matter pathways connecting frontal to auditory regions. Finally, the data expose a mechanism that underpins performance on an ecologically relevant word-learning task. We suggest that this task will help to better understand and characterize individual performance in speech processing and language learning.

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Fig. 1: Spontaneous speech synchronization reveals a bimodal distribution.
Fig. 2: Neural distinction between groups: neurophysiological data.
Fig. 3: Structural distinction between groups: anatomical connectivity data.
Fig. 4: Spontaneous speech synchronization test predicts word learning.

Code availability

All computer code used for this study is available upon request.

Data availability

All data needed to evaluate the conclusions in the paper are present in the paper and/or the Supplementary Information. Additional data related to this paper may be requested from the authors.

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Acknowledgements

We thank J. Rowland and J.-R. King for comments and advice. This work was supported by NIH grant 2R01DC05660 (D.P.) and FP7 Ideas: European Research Council grant ERC-StG-313841 (R.d.D.-B.).

Author information

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Authors

Contributions

M.F.A., P.R., J.O., W.M.L., R.d.D.-B. and D.P. designed the research and wrote the manuscript; M.F.A., P.R., J.O. and W.M.L. acquired and analyzed the data.

Corresponding author

Correspondence to M. Florencia Assaneo.

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Competing interests

The authors declare no competing interests.

Additional information

Journal peer review information Nature Neuroscience thanks Sylvain Baillet, Narly Golestani and other anonymous reviewer(s) for their contribution to the peer review of this work.

Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Integrated supplementary information

Supplementary Figure 1 Demographic information.

(a) Age distribution within groups, no significant difference between groups’ age (Mann-Whitney-Wilcoxon test, two-sided p = 0.22). (b) Percentage of female participants within each group, no significant difference in the gender distribution between groups (Fisher’s exact test, p = 0.82). (c) Percentage of early multilingual participants; they learned at least one other language in addition to English before 4 years of age. No significant difference between groups (Fisher’s exact test, p = 0.19). (d) Percentage of late multilingual participants: participants who learned at least one other language in addition to English after 4 years of age. No significant difference between groups (Fisher’s exact test, p = 0.19). (e) Years of music experience: number of years that the participant played at least one instrument, more than 2 hours per week (Mann-Whitney-Wilcoxon test, two-sided p = 0.0032). Double asterisks stands for significant difference between conditions. In all previous panels: Orange/light blue correspond to high/low synchronizers (Nhigh = 43 and Nlow = 41), dots to individual participants, black lines to mean across participants, and shadowed region the SD. (f) Histogram of the years of music experience (N = 75). Participants above one SD were excluded.

Supplementary Figure 2 SSS-test, accelerated version.

(a) Histogram of the PLVs between the envelope of the perceived and produced speech signals, bandpass filtered at 3.5–5.5 Hz. Two clusters were obtained by a kmeans algorithm (black line represents the threshold; individuals above/below this line are labeled as high/low). (b) Produced speech envelopes’ spectrograms. Upper panel: average across high synchronizers (Nhigh = 33); the red trace represents the time evolution of the perceived syllable rate. Lower panel: average across low synchronizers (Nlow = 22). (c) Reported perception. Percent of blocks reported as: ‘The rate of the presented syllables did not change/increased/decreased’. Orange/blue correspond to high/low synchronizers’ answers.

Supplementary Figure 3 SSS-test, online version.

(a) Histogram of the PLVs between the envelope of the perceived and produced speech signals, bandpass filtered at 3.5–5.5 Hz. Two clusters were obtained by a kmeans algorithm (black line represents the threshold; individuals above/below this line are labeled as high/low). (b) Rhythm perception task: participants’ d prime scores. High synchronizers are marginally better than the lows (Nhigh = 35 and Nlow = 34; Mann-Whitney-Wilcoxon test, two-sided p = 0.08). Dots: individual subjects. Black lines: mean across participants. Shadowed region: SD. (c) Rhythm production task: Average spectra of the utterances’ envelopes. Low synchronizers showed more power, although only marginally, than highs for frequencies from 3.6 to 3.7 Hz. Straight lines on top: marginal difference between groups (Nhigh = 31 and Nlow = 44; Wilcoxon signed rank test, two-sided puncorrected < 0.001). No frequency survived a FDR correction under two-sided p = 0.05. Shadowed region: SD.

Supplementary Figure 4 Word-learning task and accelerated SSS-test, online version.

(a) Histogram of the PLVs between the envelope of the perceived and produced speech signals, bandpass filtered at 3.5–5.5 Hz. Two clusters were obtained by a kmeans algorithm (black line represents the threshold; individuals above/below this line are labeled as high/low). (b) Percent of correct answers for the statistical word-learning task (Nhigh = 25, Nlow=35; r = 0.37, Rank-Biserial Correlation; Mann-Whitney-Wilcoxon test, two-sided p = 0.015). Orange/light blue correspond to high/low synchronizers. * p<0.05. Dots: individual participants. Black lines: mean across participants. Shadowed region: SD. Green dashed line: chance level in a two alternative forced-choice post-learning task.

Supplementary Figure 5 Behavioral results from neurophysiological study.

Syllable detection task, percent of correctly identified syllables (N = 37, Wilcoxon Signed-Rank test, two-sided p = 0.011). Orange/blue correspond to high/low synchronizers. Dots: individual participants. Black lines: mean across participants. Shadowed region: SD. Green dashed line: chance level.

Supplementary Figure 6 Brain-to-stimulus synchronization data from neurophysiological study.

(a) PLV between brain activity and the cochlear envelope of the perceived syllables within each region where high and low synchronizers were significantly different. The aim of the scatter plots is to visualize the magnitude of the effect. Accordingly, the Rank-Biserial correlation for each region is: rBA9/46d = 0.55, rIFJ = 0.52, rBA9/46v = 0.51, rBA44d = 0.52, rIFS = 0.51, rBA45c = 0.52, rBA44v = 0.59, and rBA44op = 0.53. Orange/blue correspond to high/low synchronizers (Nhigh = 18 and Nlow = 19). Dots: individual participants. Black lines: mean across participants. Shadowed region: SD. Green dashed line: chance level. (b) Temporal ROI comprising bilateral superior, middle and posterior temporal gyri. (c) Whole brain surface map showing the PLV differences between groups (PLVhighs - PLVlows).

Supplementary Figure 7 Asymmetry of auditory entrainment results in neurophysiological study.

(a) Auditory asymmetry: comparison between groups. Asymmetry was computed as: (PLVrightPLVleft)/0.5(PLVright + PLVleft). The asymmetry of auditory entrainment was significantly different between groups (r = 0.42, Rank-Biserial Correlation; Mann-Whitney-Wilcoxon test, two-sided p = 0.029). Right inset: ROIs, left and right early auditory regions. (b) Brain-to-stimulus synchrony in each hemisphere averaged within temporal ROIs. The data show that, while the typical rightward lateralization in tracking the speech envelope was present in low synchronizers, this was reduced in the high synchrony group (Wilcoxon signed-rank test, two-sided plow = 0.0013 and phigh = 0.089). (c) Scatter plot of the correlation between structural and neurophysiological values. Mean FA laterality as a function of the auditory entrainment’s asymmetry. There was a significant relationship (N = 36, Spearman r = 0.36, p = 0.026; Skipped Spearman r = 0.38, t = 2.40, CI = 0.04, 0.66) between the neurophysiological auditory asymmetry and the structural laterality of the white matter cluster (see Fig. 3 for the cluster) that differentiates between groups. While the structural leftwards laterality and the reduced rightward asymmetry shown by the high synchronizers might seem counterintuitive, in both cases high synchronizers show a more leftwards pattern of results as compared to low synchronizers (the correlation between structural laterality and auditory asymmetry is positive). Orange/light blue correspond to high/low synchronizers respectively. ** p < 0.005 (Wilcoxon signed-rank test), * p < 0.05 (Mann-Whitney-Wilcoxon test). Dots: individual participants. Black lines: mean across participants. Shadowed region: SD.

Supplementary Figure 8 Tractography results.

(a) Box-plots showing the mean (center line) and SD (grey areas) volumes (corrected for TIV, see tractography methods) for the total left arcuate (sum of the anterior, posterior and long segment volumes; left panel; N = 36, Wilcoxon signed-rank test, two-sided p = 0.0025; r = 0.60, Rank-Biserial correlation; FDR-corrected for multiple comparisons) and the two control tracts (right panel: left IFOF, two-sided p = 0.76, r = 0.06, Rank-Biserial correlation, and left ILF, two-sided p = 0.57, r = 0.11, Rank-Biserial correlation). Even though we cannot specify which exact segment of the arcuate is responsible for these differences (the volume of each of the three segments of the arcuate on their own did not differentiate between high and low synchronizers: long segment, p = 0.21, r = 0.24; anterior segment, p = 1, r = 0; posterior segment, p = 0.079, r = 0.34, Rank-Biserial correlation), the results do show that the dorsal pathway for language processing—connecting temporo-parietal regions with premotor areas and the inferior frontal cortex—is structurally enhanced in high synchronizers as compared to low. (b) Arcuate dissections (long segment in red, anterior in green and posterior in yellow) for representative high (top) and low (bottom) synchronizers. The arcuate dissections for the remaining 30 individuals showed a similar result. The behavioral PLV obtained using the SSS-Test is also shown. (c). Scatter plots display the correlation (N = 36) between the total volume of the left arcuate and the FA laterality values of the TBSS cluster (see Fig. 3 in the main manuscript; negative values imply a leftwards structural lateralization; left panel, an overlap-in yellow- between the TBSS cluster-in red- and a probabilistic atlas of the left arcuate fasciculus-in blue63 is also shown) and also the synchrony of the left inferior/middle frontal gyri with the speech syllable rate (right panel). In other words, the larger the volume of the virtually dissected left arcuate, the more the TBSS FA cluster was lateralized to the left (see Fig. 3 in the main manuscript; Spearman’s r = −0.46, p = 0.0051; Skipped Spearman r = −0.43, t = −2.80, CI = −0.10, −0.72); and the higher the brain-to-stimuli synchrony in frontal regions was (that is, neurophysiology; Spearman´s r = 0.35, p = 0.036; Skipped Spearman r = 0.35, t = 2.18, CI = 0.02, 0.63). In contrast, the volumes of the left IFOF and left ILF did not differentiate between groups and were not correlated with the FA TBSS cluster (IFOF: Spearman´s r = −0.12, p = 0.45; Skipped Spearman r = −0.09, t = −0.52, CI = −0.42, 0.28; ILF: Spearman´s r = −0.18, p = 0.28; Skipped Spearman r = −0.19, t = −1.17, CI = −0.51, 0.15) and the frontal neurophysiological results (IFOF: Spearman´s r = −0.006, p = 0.97; Skipped Spearman r = 0.07, t = 0.46, CI = −0.29, 0.42; ILF: Spearman´s r = −0.10, p = 0.52; Skipped Spearman r = −0.22, t = −1.35, CI = −0.55, 0.13). No significant differences were found for FA or RD measures (all ps > 0.11). Orange/blue, high/low synchronizers. Dots: individual participants. Black lines: mean across participants. Shadowed region: SD.

Supplementary Figure 9 SSS-test, joint bimodal distribution.

For each joint distribution we calculated Hartigans’ dip test statistic for testing unimodality (Hartigan, J.A., Hartigan, P.M. The Dip test of Unimodality. Annals of Statistics, 13, 70–84, 1985) using R (R Core Team. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL http://www.R-project.org/. 2013) and the diptest package (https://cran.r-project.org/web/packages/diptest/index.html). Although Hartigans´s dip test does not directly test for bimodality, it allows to reject the null hypothesis that the tested distribution is unimodal. The figure shows the histogram of the PLVs between the envelope of the perceived and produced speech signals, bandpass filtered at 3.5–5.5 Hz for (a) all the SSS-test experiments pooled together (N = 388; stable rate in-lab, stable rate in-lab replication, stable rate online version, accelerated rate in-lab and accelerated online version); (b) all the SSS-test experiments with a stable rate pooled together (N = 273; stable rate in-lab, stable rate in-lab replication and stable rate online version) and (c) all the SSS-test experiments with an accelerated syllable rate pooled together (N = 155 accelerated rate in-lab and accelerated online version). D, dip tests statistic.

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Supplementary Figures 1–9, Supplementary Table 1

Supplementary Figures 1–9 and Supplementary Table 1.

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Assaneo, M.F., Ripollés, P., Orpella, J. et al. Spontaneous synchronization to speech reveals neural mechanisms facilitating language learning. Nat Neurosci 22, 627–632 (2019). https://doi.org/10.1038/s41593-019-0353-z

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