An ERP study of good production vis-a-vis poor perception of tones in Cantonese: Implications for top-down speech processing
SourcePLoS One, 8, 1, (2013), article e54396
Article / Letter to editor
Display more detailsDisplay less details
SW OZ DCC PL
SubjectDI-BCB_DCC_Theme 1: Language and Communication; Psycholinguistics
This study investigated a theoretically challenging dissociation between good production and poor perception of tones among neurologically unimpaired native speakers of Cantonese. The dissociation is referred to as the near-merger phenomenon in sociolinguistic studies of sound change. In a passive oddball paradigm, lexical and nonlexical syllables of the T1/T6 and T4/T6 contrasts were presented to elicit the mismatch negativity (MMN) and P3a from two groups of participants, those who could produce and distinguish all tones in the language (Control) and those who could produce all tones but specifically failed to distinguish between T4 and T6 in perception (Dissociation). The presence of MMN to T1/T6 and null response to T4/T6 of lexical syllables in the dissociation group confirmed the near-merger phenomenon. The observation that the control participants exhibited a statistically reliable MMN to lexical syllables of T1/T6, weaker responses to nonlexical syllables of T1/T6 and lexical syllables of T4/T6, and finally null response to nonlexical syllables of T4/T6, suggests the involvement of top-down processing in speech perception. Furthermore, the stronger P3a response of the control group, compared with the dissociation group in the same experimental conditions, may be taken to indicate higher cognitive capability in attention switching, auditory attention or memory in the control participants. This cognitive difference, together with our speculation that constant top-down predictions without complete bottom-up analysis of acoustic signals in speech recognition may reduce one’s sensitivity to small acoustic contrasts, account for the occurrence of dissociation in some individuals but not others.
Upload full text
Use your RU credentials (u/z-number and password) to log in with SURFconext to upload a file for processing by the repository team.