Poster E73, Thursday, August 22, 2019, 3:45 – 5:30 pm, Restaurant Hall
Tracking the implicit phonological learning of speech using EEG
Manli Zhang1, Lars Riecke1, Milene Bonte1;1Maastricht University
Statistical learning, or the ability to extract statistical regularities from the sensory environment, plays a critical role in language acquisition and reading development. Recent studies have shown that the acquisition of novel word structures can be tracked over time via EEG. It is currently unclear (1) how different phonological units, such as syllables and words, are encoded throughout the learning process; (2) whether the outcome of implicit phonological learning resembles the neural representation of pre-existing word structures and (3) how this tracking and learning of speech units relates to individual differences in reading and phonological abilities. To address these questions, the current study measures EEG while participants listened to (a) a structured stream with repetitions of tri-syllabic nonwords, (b) a random stream of syllables, and (c) a series of tri-syllabic real Dutch words. We analyzed inter-trial coherence (ITC) at the frequency of repeating (non)words and individual syllables, as well as the N400 component time-locked to (non)word/triplet onsets. Behavioral measures of structured nonword recognition, as well as reading and phonological skills were assessed after training. We found that syllable tracking was present and stayed stable across blocks in both the random and structured conditions. In contrast, nonword tracking started to emerge and approximated the neural encoding of real words as exposure accumulated, and was only observed in the structured condition. (Non)word onsets in the structured and real word conditions were observed to elicit larger N400 amplitudes compared to the triplet onsets in the random condition, indicating successful cortical segmentation of the continuous speech stream. Furthermore, nonword-rate ITC in the first two blocks of the structured condition correlated with individuals’ phonological awareness and naming speed, which may imply that participants who are more skilled in phonological processing and visual-verbal conversion would be more sensitive to statistical regularities at an early stage of learning. Our results provide two neural indicators, word-rate ITC and N400, to track the progression of implicit phonological learning. Finally, reading and phonological abilities appear to be closely related to the quick detection of statistical linguistic patterns. Currently acquired data from dyslexic participants are expected to further reveal such an association.
Themes: Speech Perception, Reading
Method: Electrophysiology (MEG/EEG/ECOG)