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Research ArticleResearch Article: New Research, Sensory and Motor Systems

Auditory Nerve Fiber Discrimination and Representation of Naturally-Spoken Vowels in Noise

Amarins N. Heeringa and Christine Köppl
eNeuro 27 January 2022, 9 (1) ENEURO.0474-21.2021; DOI: https://doi.org/10.1523/ENEURO.0474-21.2021
Amarins N. Heeringa
Cluster of Excellence “Hearing4all” and Research Centre Neurosensory Science, Department of Neuroscience, School of Medicine and Health Science, Carl von Ossietzky University Oldenburg, Oldenburg 26129, Germany
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Christine Köppl
Cluster of Excellence “Hearing4all” and Research Centre Neurosensory Science, Department of Neuroscience, School of Medicine and Health Science, Carl von Ossietzky University Oldenburg, Oldenburg 26129, Germany
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  • Figure 1.
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    Figure 1.

    Characteristics of the three vowels used in the current study. A, Pressure waveform of /bahb/ in quiet (upper panel) and in 5 dB SNR speech-shaped noise (lower panel). The vowel analysis window is highlighted in red. B, Spectrogram of /bahb/ with the vowel analysis window indicated with the white bar. C, The three vowels for which AN-fiber responses were recorded and their corresponding perceptual discriminability as shown by behavioral studies (Jüchter et al., 2021). Colors of the vowels and of each vowel comparison are similar to the colors used in the subsequent figures. D–F, Spectral representation of the naturally-spoken vowels /a:/, /e/, and /i/, respectively. Vowels were derived from the OLLO speech material database and spoken by a female speaker, with /b/ as a flanking consonant. Spectra were generated from the stimulus in the vowel’s corresponding analysis window (see panels A, B and Table 1). Fundamental (f0) and formant frequencies (f1 and f2) are indicated for each vowel. The spectral envelope of each vowel is indicated by a red line. Note that frequency of the vowel spectra is plotted on a linear scale to improve visualization of the f0 harmonics. The spectrum of the frozen ICRA1 speech-shaped noise, presented at 5 dB SNR, is plotted separately indicated in gray for all vowel spectra.

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    Figure 2.

    Single-unit AN-fiber vowel discrimination based on average firing rate. A–C, d’ values for each unit’s firing rate in response to the two vowels that are compared, plotted as a function of the unit’s BF. Low-SR and high-SR fibers are plotted with open and closed symbols, respectively. Dashed horizontal lines indicate a neural discrimination threshold of |d’| = 1. Number of units (of those, number of low-SR units) included in the vowel comparisons are n = 33 (8), n = 24 (4), and n = 23 (4) for panels A, B, and C, respectively. D, Absolute d’ values of all units presented in boxplots. The dashed horizontal line indicates |d’| = 1.

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    Figure 3.

    Single-unit AN-fiber vowel discrimination based on spike timing. A–C, ΔCI values for each unit in response to the two vowels that are compared, plotted as a function of the unit’s BF. Low-SR and high-SR fibers are plotted with open and closed symbols, respectively. Number of units (of those, number of low-SR units) included in the vowel comparisons are n = 33 (8), n = 24 (4), and n = 23 (4) for panels A, B, C, respectively. Note that there are two values per unit in this analysis. D, ΔCI of all units presented in boxplots. Asterisks indicate a significant difference, based on post hoc paired t tests (**p < 0.01, ***p < 0.001).

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    Figure 4.

    Effects of background noise and speaker-specific characteristics on spike-timing-based vowel discrimination. A, ΔCI values for vowel comparisons presented against background noise #1 at 5 dB SNR, spoken by a female speaker of the OLLO database (S01F). Number of units are n = 20 for /a:/ vs /e/, n = 13 for /a:/ vs /i/, and n = 13 for /e/ vs /i/. B, ΔCI values for vowel comparisons presented against noise #2 (5 dB SNR, S01F speaker of the OLLO database). Number of units are n = 13 for /a:/ vs /e/, n = 11 for /a:/ vs /i/, and n = 10 for /e/ vs /i/. C, ΔCI values for vowel comparisons spoken by a male speaker of the OLLO database (S06M), presented against noise #1. Number of units are n = 12 for /a:/ vs /e/, n = 12 for /a:/ vs /i/, and n = 14 for /e/ vs /i/. Asterisks indicate a significant difference, based on post hoc paired t tests after the RM-ANOVA revealed a significant difference between the comparisons (*p < 0.05, **p < 0.01, ***p < 0.001).

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    Figure 5.

    Example of one fiber responding to the three logatomes in quiet and in noise. PSTH of the response to the complete stimulus in quiet (A–C) and in 5 dB SNR speech-shaped ICRA1 noise (D–F). The vowel analysis window is indicated with a horizontal bar. Bin width is 0.49 ms for the graphs in panels A–F. PH of F0 during the vowel analysis window in quiet (G–I) and in 5 dB SNR noise (J–L). PHs were plotted with 64 bins per f0 cycle. This fiber had a BF of 2.2 kHz, a threshold at 28 dB SPL, and a SR of 4.7 spikes/s. Note the remarkably little effect of noise on the shapes of the PHs after the addition of background noise (panels J–L).

  • Figure 6.
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    Figure 6.

    Dominant component schemes. A, Response of an AN fiber to the vowel /a:/ plotted in a PH for one period of f0. The FFT of the f0 PH is plotted next to it. The arrow indicates the highest peak in the FFT of the f0 PH at the fourth harmonic of f0 and its relative peak height plotted in number of spikes. This example fiber was a high-SR fiber (46 spikes/s) with a BF at 1.3 kHz. B, All-order ISIH of the same data presented in panel A, accompanied by its FFT. The arrow indicates the highest peak in the FFT, at 1024 Hz, which corresponds to the frequency of the fourth harmonic of f0. C–E, Dominant component schemes plotting the frequency of the highest peak in the FFT of the all-order ISIH (panel B) as a function of the fiber’s BF for responses to the vowels /a:/ [panel C, n = 39 (n = 10 low-SR fibers)], /e/ [panel D, n = 33 (n = 8 low-SR fibers)], and /i/ [panel E, n = 24 (n = 4 low-SR fibers)]. Formant frequencies are indicated on the right and the F = BF line is indicated as a solid black line. Horizontal dotted lines indicate frequencies of f0 harmonics. Symbol size reflects the height of the peak in the ISIH FFT, which is a measure of the strength of the temporal coding at the respective frequency component. F, Frequency distributions of dominant components for responses to /a:/, /e/, and /i/ in blue, red, and yellow, respectively. Data are plotted in a histogram (upper panel) as well as in the form of a cumulative distribution function (CDF; lower panel).

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    Figure 7.

    ALIR schemes. A–C, ALIR schemes plotting the average ISIH FFT amplitude around each harmonic of f0 for fibers with a BF within +/− 0.5 octave of the respective f0 harmonic, for response to the vowels /a:/ (panel A), /e/ (panel B), and /i/ (panel C). Formant frequencies are indicated by dashed lines and f0 is indicated as a dotted line for each vowel ALIR scheme.

  • Figure 8.
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    Figure 8.

    Examples of the PSTH of two fibers during the presentation of the vowel /e/. A, This is an example of a highly fluctuating response. The fiber’s BF is far away from the formant frequencies of the vowel /e/ (at 8.3 kHz). B, This is an example of a flat response, showing little fluctuation. The fiber’s BF is close to f2 (BF = 2.8 kHz, f2 = 2.5 kHz). Both responses derived from high-SR fibers. Fluctuation metrics CV and RC (rate change) are close to twice as high for the fluctuating (panel A) compared with the flat response (panel B). The x-axis represents the time in seconds relative to the start of the complete stimulus. Only the vowel’s analysis window is shown. Bin width is 0.49 ms (1/8 × f0). Bin height represents the average discharge rate.

  • Figure 9.
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    Figure 9.

    Fluctuation amplitude profiles. A–C, CVs of responses to the vowels /a:/ [panel A, n = 39 (n = 10 low-SR fibers)], /e/ [panel B, n = 33 (n = 8 low-SR fibers)], and /i/ [panel C, n = 24 (n = 4 low-SR fibers)] as a function of the fiber’s BF. D–F, Rate change, calculated as the mean absolute difference between each bin height divided by the mean bin height of the PSTH, of the three presented vowels. Vowels and unit numbers for panels D–F are the same as in panels A–C, respectively. Note that the ordinate is plotted in reverse direction, meaning that lower CVs and rate change values, referring to less fluctuation in the PSTH and thus putatively better formant representation, are higher in the graph. Moving averages of high-SR and low-SR fibers are plotted as solid and dashed lines, respectively. Formant frequencies are indicated by dashed vertical lines and f0 as a dotted line for each vowel.

  • Figure 10.
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    Figure 10.

    Rate-based excitation patterns. A–C, Rate-based excitation patterns of AN fiber responses to the vowels /a:/ [panel A, n = 39 (n = 10 low-SR fibers)], /e/ [panel B, n = 33 (n = 8 low-SR fibers)], and /i/ [panel C, n = 24 (n = 4 low-SR fibers)] plotted as a function of the fiber’s BF. Moving averages of high-SR and low-SR fibers are plotted as solid and dashed lines, respectively. Formant frequencies are indicated by dashed vertical lines and f0 as a dotted line for each vowel.

Tables

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    Table 1

    Fundamental and formant frequencies and length of the analysis windows of the presented vowels

    f0 (Hz)f1 (Hz)f2 (Hz)Analysis window (ms)
    F /e/2564002450268
    F /i/2603002575233
    F /a:/2578501275269
    M /e/1073001990121
    M /i/1092202040110
    M /a:/1046501150143
    • Stimuli spoken by the female speaker are marked with F, stimuli spoken by the male speaker are marked with M.

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    Table 2

    Numbers of units from which responses to vowels were recorded

    Single vowels/a://e//i/
    Number of units female speaker393324
    Number of units male speaker131515
    Vowel discriminations/a:/ vs /e//a:/ vs /i//e/ vs /i/
    Number of units female speaker332423
    Number of units male speaker121214
    • Unit numbers are given for the responses to a single vowel (data in Figs. 6, 7, 9, 10) and for responses to a combination of two vowels (data in Figs. 2-4). Unit numbers for responses to vowels spoken by the female and male speaker are presented separately.

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Auditory Nerve Fiber Discrimination and Representation of Naturally-Spoken Vowels in Noise
Amarins N. Heeringa, Christine Köppl
eNeuro 27 January 2022, 9 (1) ENEURO.0474-21.2021; DOI: 10.1523/ENEURO.0474-21.2021

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Auditory Nerve Fiber Discrimination and Representation of Naturally-Spoken Vowels in Noise
Amarins N. Heeringa, Christine Köppl
eNeuro 27 January 2022, 9 (1) ENEURO.0474-21.2021; DOI: 10.1523/ENEURO.0474-21.2021
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Keywords

  • consonant-vowel-consonant logatomes
  • ICRA1 noise
  • Mongolian gerbil
  • OLLO speech material database
  • temporal coding

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