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Research ArticleMethods/New Tools, Novel Tools and Methods

Cortical Tracking of Complex Sound Envelopes: Modeling the Changes in Response with Intensity

Denis P. Drennan and Edmund C. Lalor
eNeuro 6 June 2019, 6 (3) ENEURO.0082-19.2019; https://doi.org/10.1523/ENEURO.0082-19.2019
Denis P. Drennan
1School of Engineering, Trinity Centre for Biomedical Engineering and Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin 2, Ireland
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Edmund C. Lalor
1School of Engineering, Trinity Centre for Biomedical Engineering and Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin 2, Ireland
2Department of Biomedical Engineering, Department of Neuroscience, and Del Monte Institute for Neuroscience, University of Rochester, Rochester, NY 14627
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    Figure 1.

    A, B, Example segments of AM BBN and speech stimuli, respectively. C, D, Power spectral densities (PSDs) of AM BBN and speech stimuli, respectively. The AM BBN had a broadband frequency distribution by design, while the male speaker had a frequency distribution that was dominated by frequencies below 5000 Hz. E, F, Amplitude histograms of AM BBN and speech envelopes, respectively. Both envelopes had quite broadly distributed amplitude distributions. Please note that the amplitude distribution of the AM BBN envelope was uniform by design, but after extracting the envelope from the AM BBN signal using the Hilbert transform, it was less so. Also note that the amplitude distribution of the speech envelope was more skewed, with a higher percentage of samples in the higher amplitude bins. G, H, PSDs of AM BBN and speech envelopes, respectively. Both signals had envelopes with a bottom-heavy (right-skewed) frequency distribution indicating that their modulation rates were dominated by low frequencies.

  • Figure 2.
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    Figure 2.

    A, Example segments of the envelope, SPL envelope, and onset envelope stimulus representations. B, Corresponding segment of the AB envelope.

  • Figure 3.
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    Figure 3.

    A, Topographic plot displaying prediction accuracies for the envelope model for the AM BBN dataset and highlighting the channels chosen for analysis. B, Prediction accuracies for each model and subject, including null hypotheses for the envelope model as determined from the permutation tests (in black), and indications of significance as determined from the t tests. Top, middle and bottom rows of asterisks indicate comparisons between AB Env and Env, SPL, and Ons, respectively. ***p < 0.001, **p < 0.01, *p < 0.05.

  • Figure 4.
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    Figure 4.

    Analysis of amplitude-dependent changes at a single representative channel over left central scalp for the AM BBN dataset. A, Group average AB envelope TRF, plotted to minimize the difference between adjacent traces. B, Image plot of group average AB envelope TRF. C, N1 peak latencies across group average AB envelope TRF bins. D, P1-N1 peak-to-peak amplitudes across group average AB envelope TRF bins.

  • Figure 5.
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    Figure 5.

    A, Topographic plot displaying prediction accuracies for the envelope model for the speech dataset and highlighting the channels chosen for analysis. B, Prediction accuracies for each model and subject, including null hypotheses for the envelope model as determined from the permutation tests (in black), and indications of significance as determined from the t tests. Top, middle and bottom rows of asterisks indicate comparisons between AB Env and Env, SPL, and Ons, respectively. ***p < 0.001, **p < 0.01, *p < 0.05.

  • Figure 6.
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    Figure 6.

    Analysis of amplitude-dependent changes at a single representative channels over left central scalp for the speech dataset. A, Group average AB envelope TRF, plotted to minimize the difference between adjacent traces. B, Image plot of group average AB envelope TRF. C, N1 peak latencies across group average AB envelope TRF bins. D, P1-N1 peak-to-peak amplitudes across group average AB envelope TRF bins.

  • Figure 7.
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    Figure 7.

    A, Prediction accuracies for each model and subject for the AM BBN dataset. B, Prediction accuracies for each model and subject for the speech dataset. Top and bottom rows of asterisks indicate comparisons between AB Env + Ons and AB Env, and Ons, respectively. ***p < 0.001, **p < 0.01. C, Group average AB onset envelope TRF for the AM BBN dataset, plotted to minimize the difference between adjacent traces. D, Image plot of group average AB onset envelope TRF for the AM BBN dataset.

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Cortical Tracking of Complex Sound Envelopes: Modeling the Changes in Response with Intensity
Denis P. Drennan, Edmund C. Lalor
eNeuro 6 June 2019, 6 (3) ENEURO.0082-19.2019; DOI: 10.1523/ENEURO.0082-19.2019

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Cortical Tracking of Complex Sound Envelopes: Modeling the Changes in Response with Intensity
Denis P. Drennan, Edmund C. Lalor
eNeuro 6 June 2019, 6 (3) ENEURO.0082-19.2019; DOI: 10.1523/ENEURO.0082-19.2019
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Keywords

  • auditory evoked potential
  • deconvolution
  • electroencephalography
  • encoding model
  • envelope tracking
  • speech

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