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Pré-Publication, Document De Travail Année : 2020

Neural dynamics of phoneme sequencing in real speech jointly encode order and invariant content

Résumé

Listeners experience speech as a sequence of discrete words. However, the real input is a continuously varying acoustic signal that blends words and phonemes into one another. Here we recorded two-hour magnetoencephalograms from 21 subjects listening to stories, in order to investigate how the brain concurrently solves three competing demands: 1) processing overlapping acoustic-phonetic information while 2) keeping track of the relative order of phonemic units and 3) maintaining individuated phonetic information until successful word recognition. We show that the human brain transforms speech input, roughly at the rate of phoneme duration, along a temporally-defined representational trajectory. These representations, absent from the acoustic signal, are active earlier when phonemes are predictable than when they are surprising, and are sustained until lexical ambiguity is resolved. The results reveal how phoneme sequences in natural speech are represented and how they interface with stored lexical items.
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Dates et versions

hal-03089733 , version 1 (29-12-2020)

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Laura Gwilliams, Jean-Rémi King, Alec Marantz, David Poeppel. Neural dynamics of phoneme sequencing in real speech jointly encode order and invariant content. 2020. ⟨hal-03089733⟩
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