Contextual influences on spoken-word processing: An electrophysiological approach

Van den Brink, D. (2004). Contextual influences on spoken-word processing: An electrophysiological approach. PhD Thesis, Radboud University Nijmegen, Nijmegen. doi:10.17617/2.57773.
The aim of this thesis was to gain more insight into spoken-word comprehension and the influence of sentence-contextual information on these processes using ERPs. By manipulating critical words in semantically constraining sententes, in semantic or syntactic sense, and examining the consequences in the electrophysiological signal (e.g., elicitation of ERP components such as the N400, N200, LAN, and P600), three questions were tackled: I At which moment is context information used in the spoken-word recognition process? II What is the temporal relationship between lexical selection and integration of the meaning of a spoken word into a higher-order level representeation of the preceding sentence? III What is the time course of the processing of different sources of linguistic information obtained from the context, such as phonological, semantic and syntactic information, during spoken-word comprehension? From the results of this thesis it can be concluded that sentential context already exerts an influence on spoken-word processing at approximately 200 ms after word onset. In addition, semantic integration is attempted before a spoken word can be selected on the basis of the acoustic signal, i.e. before lexical selection is completed. Finally, knowledge of the syntactic category of a word is not needed before semantic integration can take place. These findings, therefore, were interpreted as providing evidence for an account of cascaded spoken-word processing that proclaims an optimal use of contextual information during spoken-word identification. Optimal use is accomplished by allowing for semantic and syntactic processing to take place in parallel after bottom-up activation of a set of candidates, and lexical integration to proceed with a limited number of candidates that still match the acoustic input
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