Implicit Segmentation of a Stream of Syllables Based on Transitional Probabilities: An MEG Study
Statistical segmentation of continuous speech, i.e., the ability to utilise transitional probabilities between syllables in order to detect word boundaries, is reflected in the brain’s auditory event-related potentials (ERPs). The N1 and N400 ERP components are typically enhanced for word onsets compared to random syllables during active listening. We used magnetoencephalography (MEG) to record event-related fields (ERFs) simultaneously with ERPs to syllables in a continuous sequence consisting of ten repeating tri-syllabic pseudowords and unexpected syllables presented between these pseudowords. We found the responses to differ between the syllables within the pseudowords and between the expected and unexpected syllables, reflecting an implicit process extracting the statistical characteristics of the sequence and monitoring for unexpected syllables.
KeywordsStatistical learning Word segmentation MEG N400
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