Latent neural dynamics encode temporal context in speech
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Published version
Date
2023-09-15
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Published version
OA Version
Citation
E.P. Stephen, Y. Li, S. Metzger, Y. Oganian, E.F. Chang. 2023. "Latent neural dynamics encode temporal context in speech." Hearing Research, Volume 437, pp.108838-. https://doi.org/10.1016/j.heares.2023.108838
Abstract
Direct neural recordings from human auditory cortex have demonstrated encoding for acoustic-phonetic features of consonants and vowels. Neural responses also encode distinct acoustic amplitude cues related to timing, such as those that occur at the onset of a sentence after a silent period or the onset of the vowel in each syllable. Here, we used a group reduced rank regression model to show that distributed cortical responses support a low-dimensional latent state representation of temporal context in speech. The timing cues each capture more unique variance than all other phonetic features and exhibit rotational or cyclical dynamics in latent space from activity that is widespread over the superior temporal gyrus. We propose that these spatially distributed timing signals could serve to provide temporal context for, and possibly bind across time, the concurrent processing of individual phonetic features, to compose higher-order phonological (e.g. word-level) representations.
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License
© 2023 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/)