Vowels and Consonants in the Brain: Evidence from Magnetoencephalographic Studies on the N1m in Normal-Hearing Listeners

Abstract

Speech sound perception is one of the most fascinating tasks performed by the human brain. It involves a mapping from continuous acoustic waveforms onto the discrete phonological units computed to store words in the mental lexicon. In this article, we review the magnetoencephalographic studies that have explored the timing and morphology of the N1m component to investigate how vowels and consonants are computed and represented within the auditory cortex. The neurons that are involved in the N1m act to construct a sensory memory of the stimulus due to spatially and temporally distributed activation patterns within the auditory cortex. Indeed, localization of auditory fields maps in animals and humans suggested two levels of sound coding, a tonotopy dimension for spectral properties and a tonochrony dimension for temporal properties of sounds. When the stimulus is a complex speech sound, tonotopy and tonochrony data may give important information to assess whether the speech sound parsing and decoding are generated by pure bottom-up reflection of acoustic differences or whether they are additionally affected by top-down processes related to phonological categories. Hints supporting pure bottom-up processing coexist with hints supporting top-down abstract phoneme representation. Actually, N1m data (amplitude, latency, source generators, and hemispheric distribution) are limited and do not help to disentangle the issue. The nature of these limitations is discussed. Moreover, neurophysiological studies on animals and neuroimaging studies on humans have been taken into consideration. We compare also the N1m findings with the investigation of the magnetic mismatch negativity (MMNm) component and with the analogous electrical components, the N1 and the MMN. We conclude that N1 seems more sensitive to capture lateralization and hierarchical processes than N1m, although the data are very preliminary. Finally, we suggest that MEG data should be integrated with EEG data in the light of the neural oscillations framework and we propose some concerns that should be addressed by future investigations if we want to closely line up language research with issues at the core of the functional brain mechanisms.

Decomposing neural responses to melodic surprise in musicians and non-musicians: evidence for a hierarchy of predictions in the auditory system

“…Thus, our results generalize this effect to the spectral content of complex tones in more realistic and complex auditory sequences. Moreover, speech research showing modulations of the N1m component by the acoustic properties of phonemes provides further support to our proposal (Manca & Grimaldi, 2016;Shestakova, Brattico, Soloviev, Klucharev, & Huotilainen, 2004). On the same line, in a previous EEG study reporting an effect similar to the one found here, manipulations of surprise were also confounded with interval size, which is consistent with our data (Koelsch & Jentschke, 2010).…”

Neural representation of vowel formants in tonotopic auditory cortex

“…With regard to vowels specifically, MEG studies have shown differences between vowels in equivalent current dipole localization of the N1m component (Diesch and Luce 1997; Mäkelä et al, 2003; Obleser et al, 2003, 2004; Shestakova et al, 2004; Scharinger et al, 2011, 2012). These studies have shown that vowel pairs that are more dissimilar in F 1 / F 2 space, or that differ by more distinctive features, generally show larger Euclidean distances between their dipole locations (Manca and Grimaldi, 2016). However the specific orientations of differences in dipole locations in relation to formant frequencies have been inconsistent across studies (Manca and Grimaldi, 2016).…”

“…These studies have shown that vowel pairs that are more dissimilar in F 1 / F 2 space, or that differ by more distinctive features, generally show larger Euclidean distances between their dipole locations (Manca and Grimaldi, 2016). However the specific orientations of differences in dipole locations in relation to formant frequencies have been inconsistent across studies (Manca and Grimaldi, 2016). This may reflect the fact that single dipoles are used to model complex patterns of activity that involve the representation of multiple formants on multiple tonotopic gradients, which may be oriented in idiosyncratic ways according to individual anatomy of Heschl’s gyrus and other tonotopically organized regions.…”

“…However, the cortical representation of vowel formants in tonotopic regions has not previously been demonstrated. Magnetoencephalography (MEG) studies have shown differences in source localization between distinct vowels (Obleser et al, 2003, 2004; Scharinger et al, 2011), but findings have been inconsistent across studies (Manca and Grimaldi, 2016), so it is unclear whether any observed differences reflect tonotopic encoding of formants. Neuroimaging studies have almost never reported activation differences between different vowels in univariate subtraction-based analyses (e.g.…”

Phonetic Realisation and Phonemic Categorisation of the Final Reduced Corner Vowels in the Finnic Languages of Ingria

“…They directly correspond to F1 and F2 values, which, in turn, find their straight correlates in regions and types of brain activity. The rounding feature appears more complex, as it requires higher-level information processing and is acoustically less reliable and perceived with significant help from the visual channel (Traunmüller & Öhrström, 2007;Eulitz & Obleser, 2007;Vatakis et al, 2012;Manca & Grimaldi, 2016). One might thus suggest that u is less perceptually robust and salient than i and, therefore, more prompt for reduction, especially in languages with fronting vowel harmony.…”