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29 décembre 2020
- handle: 10670/1.1hptt4
- hal: hal-03089733
- doi: 10.1101/2020.04.04.025684
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info:eu-repo/semantics/altIdentifier/doi/10.1101/2020.04.04.025684
info:eu-repo/semantics/OpenAccess
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Laura Gwilliams et al., « Neural dynamics of phoneme sequencing in real speech jointly encode order and invariant content », HAL-SHS : linguistique, ID : 10.1101/2020.04.04.025684
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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.