Dynamics of functional networks for syllable and word-level processing

Abstract

Speech comprehension requires the ability to temporally segment the acoustic input for higher-level linguistic analysis. Oscillation-based approaches suggest that low-frequency auditory cortex oscillations track syllable-sized acoustic information and therefore emphasize the relevance of syllabic-level processing for speech segmentation. Most linguistic approaches, however, focus on mapping from acoustic-phonemic representations to the lexical level. How syllabic processing interacts with higher levels of speech processing, beyond segmentation, including the anatomical and neurophysiological characteristics of the networks involved, is debated. Here we investigate the effects of lexical processing and the interactions with (acoustic) syllable processing by examining MEG data recorded in two experiments using a frequency-tagging paradigm. Participants listened to disyllabic words presented at a rate of 4 syllables/sec. Two conjectures were evaluated: (i) lexical processing of words activates a network that interacts with syllable processing; and (ii) syllable transitions contribute to word-level processing. We show that lexical content activated a left-lateralized frontal and superior and middle temporal network and increased the interaction between left middle temporal areas and auditory cortex (phase-phase coupling). Mere syllable-transition information, in contrast, activated a bilateral superior-, middle temporal and inferior frontal network and increased the interaction between those areas. Word and syllable processing interacted in superior and middle temporal areas (cross-frequency coupling), whereas syllable tracking (cerebro-acoustic coherence) decreased when word-level information was present. The data provide a new perspective on speech comprehension by demonstrating a contribution of an acoustic-syllabic to lexical processing route.\n\nSignificance statementThe comprehension of speech requires integrating information at multiple time scales, including phonemic, syllabic, and word scales. Typically, we think of decoding speech in the service of recognizing words as a process that maps from phonemic units to words. Recent neurophysiological evidence, however, has highlighted the relevance of syllable-sized chunks for segmenting speech. Is there more to recognizing spoken language? We provide neural evidence for brain network dynamics that support an interaction of lexical with syllable-level processing. We identify cortical networks that differ depending on whether lexical-semantic information versus low-level syllable-transition information is processed. Word- and syllable-level processing interact within MTG and STG. The data enrich our understanding of comprehension by implicating a mapping from syllabic to lexical representations.