Top-down information shapes lexical processing when listening to continuous speech

Laura Gwilliams, Alec Marantz, David Poeppel, Jean Remi King

Research output: Contribution to journalArticlepeer-review

Abstract

Speech is often structurally and semantically ambiguous. Here we study how the human brain uses sentence context to resolve lexical ambiguity. Twenty-one participants listened to spoken narratives while magneto-encephalography (MEG) was recorded. Stories were annotated for grammatical word class (noun, verb, adjective) under two hypothesised sources of information: “bottom-up”: the most common word class given the word’s phonology; “top-down”: the correct word class given the context. We trained a classifier on trials where the hypotheses matched (about 90%) and tested the classifier on trials where they mismatched. The classifier predicted top-down word class labels, and anti-correlated with bottom-up labels. Effects peaked ∼100 ms after word onset over mid-frontal MEG sensors. Phonetic information was encoded in parallel, though peaking later (∼200 ms). Our results support that lexical representations are built in a context-sensitive manner, which precedes sensory phonetic processing. We showcase multivariate analyses for teasing apart subtle representational distinctions from neural time series.

Original languageEnglish (US)
JournalLanguage, Cognition and Neuroscience
DOIs
StateAccepted/In press - 2023

Keywords

  • MEG
  • decoding
  • neural processing
  • part of speech
  • word class

ASJC Scopus subject areas

  • Language and Linguistics
  • Experimental and Cognitive Psychology
  • Linguistics and Language
  • Cognitive Neuroscience

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