Neural representation of vowel formants in tonotopic auditory cortex

Abstract

Speech sounds are encoded by distributed patterns of activity in bilateral superior temporal cortex. However, it is unclear whether speech sounds are topographically represented in cortex, or which acoustic or phonetic dimensions might be spatially mapped. Here, using functional MRI, we investigated the potential spatial representation of vowels, which are largely distinguished from one another by the frequencies of their first and second formants, i.e. peaks in their frequency spectra. This allowed us to generate clear hypotheses about the representation of specific vowels in tonotopic regions of auditory cortex. We scanned participants as they listened to multiple natural tokens of the vowels [ɑ] and [i], which we selected because their first and second formants overlap minimally. Formant-based regions of interest were defined for each vowel based on spectral analysis of the vowel stimuli and independently acquired tonotopic maps for each participant. We found that perception of [ɑ] and [i] yielded differential activation of tonotopic regions corresponding to formants of [ɑ] and [i], such that each vowel was associated with increased signal in tonotopic regions corresponding to its own formants. This pattern was observed in Heschl's gyrus and the superior temporal gyrus, in both hemispheres, and for both the first and second formants. Using linear discriminant analysis of mean signal change in formant-based regions of interest, the identity of untrained vowels was predicted with ∼73% accuracy. Our findings show that cortical encoding of vowels is scaffolded on tonotopy, a fundamental organizing principle of auditory cortex that is not language-specific.

Keywords: Auditory cortex; Formants; Tonotopy; Vowels.

Figure 1

Vowels used in the experiment. (A) Spectrograms and spectra of representative [ɑ] and [i] tokens. (B) Comparison between the [ɑ] and [i] spectra, showing how formant bands were defined.

Figure 2

Tonotopic mapping. Four representative participants are shown. For display purposes, maps were smoothed with 5 surface smoothing steps (approximate FWHM = 2.2 mm) and 3D smoothing of FWHM = 1.5 mm. White outlines show the border of Heschl’s gyrus, derived from automated cortical parcellation.

Figure 3

Responses to vowels [ɑ] and [i] in each formant band within each anatomical ROI. Images show voxels that defined each formant band within each anatomical ROI in one representative participant, i.e. voxels that were tonotopic (amplitude F > 3.03), with a best frequency within one of the four formant bands, which are color coded to match the bar plots. (A) Responses in left Heschl’s gyrus (HG). (B) Responses in right HG. (C) Responses in the left superior temporal gyrus (STG). (D) Responses in the right STG. Error bars show standard error of the mean. Xs show the distribution of the interaction contrast (ROI-defining vowel by presented vowel, i.e. [ɑ] response in [ɑ]-based ROI minus [i] response in [ɑ]-based ROI minus [ɑ] response in [i]-based ROI plus [i] response in [i]-based ROI). Note that the interaction contrast was positive (consistent with our primary hypothesis) for all participants for both the first and second formants in each anatomical region of interest. Statistical significance is indicated by * (paired t-test, p < 0.05).

Figure 4

Classification of untrained vowel blocks on the basis of mean signal change in formant-based regions of interest. HG = Heschl’s gyrus; STG = superior temporal gyrus; L = left; R = right; F₁ = first formant; F₂ = second formant.