bioRxivNeurosciencePreprint
Interplay between metrical and semantic processing in French: an N400 study.
Noémie te RietmoleniD, Radouane El YagoubiiD, Corine AstésanoiD
Abstract
French accentuation is held to belong to the level of the phrase. Consequently French is considered a language without accent with speakers that are deaf to stress. Recent ERP-studies investigating the French initial accent (IA) however demonstrate listeners to not only discriminate between different stress patterns, but also expect words to be marked with IA early in the process of speech comprehension. Still, as words were presented in isolation, it remains unclear whether the preference applied to the lexical or to the phrasal level. In the current ERP-study, we address this ambiguity and manipulate IA on words embedded in a sentence. Furthermore, we orthogonally manipulate semantic congruity to investigate the interplay between accentuation and later speech processing stages. Results reveal an early fronto-centrally located negative deflection when words are presented without IA, indicating a general dispreference for words presented without IA. Additionally, we found an effect of semantic congruity in the centro-parietal region (the traditional region for N400), which was bigger for words without IA than for words with IA. Furthermore, we observed an interaction between metrical structure and semantic congruity such that {+/-}IA continued to modulate N400 amplitude fronto-centrally, but only in the sentences that were semantically incongruent. The results indicate that presenting word without initial accent hinders semantic conflict resolution. This interpretation is supported by the behavioral data which show that participants were slower and made more errors words had been presented without IA. As participants attended to the semantic content of the sentences, the finding underlines the automaticity of stress processing and indicates that IA may be encoded at a lexical level where it facilitates semantic processing.
- organism: human
- assay: electronic health records
- research focus: cell type annotation
- approach: statistical model
- Citations
- 0
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