Brainstem encoding of speech and musical stimuli in congenital amusia: evidence from Cantonese speakers

Abstract

Congenital amusia is a neurodevelopmental disorder of musical processing that also impacts subtle aspects of speech processing. It remains debated at what stage(s) of auditory processing deficits in amusia arise. In this study, we investigated whether amusia originates from impaired subcortical encoding of speech (in quiet and noise) and musical sounds in the brainstem. Fourteen Cantonese-speaking amusics and 14 matched controls passively listened to six Cantonese lexical tones in quiet, two Cantonese tones in noise (signal-to-noise ratios at 0 and 20 dB), and two cello tones in quiet while their frequency-following responses (FFRs) to these tones were recorded. All participants also completed a behavioral lexical tone identification task. The results indicated normal brainstem encoding of pitch in speech (in quiet and noise) and musical stimuli in amusics relative to controls, as measured by FFR pitch strength, pitch error, and stimulus-to-response correlation. There was also no group difference in neural conduction time or FFR amplitudes. Both groups demonstrated better FFRs to speech (in quiet and noise) than to musical stimuli. However, a significant group difference was observed for tone identification, with amusics showing significantly lower accuracy than controls. Analysis of the tone confusion matrices suggested that amusics were more likely than controls to confuse between tones that shared similar acoustic features. Interestingly, this deficit in lexical tone identification was not coupled with brainstem abnormality for either speech or musical stimuli. Together, our results suggest that the amusic brainstem is not functioning abnormally, although higher-order linguistic pitch processing is impaired in amusia. This finding has significant implications for theories of central auditory processing, requiring further investigations into how different stages of auditory processing interact in the human brain.

Keywords: Cantonese; brainstem; congenital amusia; frequency-following response (FFR); lexical/musical tone; pitch; speech in noise.

FIGURE 1

Time-normalized F0 contours of the six Hong Kong Cantonese tones on the syllable /ji/ T1: high-level, 55, , ‘doctor’; T2: high-rising, 25, , ‘chair’; T3: mid-level, 33, , ‘meaning’; low-falling, 21, , ‘son’; T5: mid-rising, 23, , ‘ear’; T6: low-level, 22, , ‘two.’ F0 ranges: 138–145 Hz, 107–140 Hz, 121–128 Hz, 87–99 Hz, 100–115 Hz, and 96–106 Hz, respectively.

FIGURE 2

Waveforms of the original stimuli /ji/ with six Cantonese tones (A1–F1), and those of the grand-average FFRs of amusics (A2–F2) and controls (A3–F3).

FIGURE 3

Pitch tracks of the grand-average FFRs of amusics (A1–F1) and controls (A2–F2) to the six Cantonese tones. The black and yellow lines indicate pitch tracks of the original stimuli and those of the responses, respectively. The small red dots signify regions where the extracted F₀s were below the noise floor (i.e., SNR was less than one, reflecting the magnitude of the response F₀), and the small blue dots indicate regions where the extracted F₀s were not at the spectral maximum (indicating weak F₀ encoding strengths; Song et al., 2008; Skoe et al., 2013).

FIGURE 4

Grand average waveforms of amusics’ (A1–D1) and controls’ (A2–D2) FFRs to Cantonese Tone 1 and Tone 6 heard in babble noise (SNR = 0 and 20 dB), and the corresponding pitch tracks (A3–D3, A4–D4).

FIGURE 5

Waveforms of the original two cello tones (A1,B1), and grand average waveforms of the FFRs to the cello tones (heard in quiet) of the amusic (A2,B2) and control (A3,B3) groups, and the corresponding pitch tracks (C1,C2,D1,D2).

FIGURE 6

Frequency-following response (FFR) neural lags (A; in ms) and pitch strengths (B; autocorrelations) of amusics and controls under the three experimental conditions (music, speech-in-noise, speech-in-quiet).

FIGURE 7

Frequency-following response pitch errors (A; in Hz) and stimulus-to-response correlations (B) of amusics and controls under the three experimental conditions.

FIGURE 8

Frequency-following response signal-to-noise ratios (A; SNRs) and root-mean-square (B; RMS) amplitudes (in μV) of amusics and controls under the three experimental conditions.

FIGURE 9

Frequency-following response first (A), second (B), and third (C) harmonic amplitudes (in dB) of amusics and controls under the three experimental conditions.

FIGURE 10

Percent-correct scores (A) and reaction times (B; in ms) of amusics and controls for the behavioral tone identification task.