Neural Representation of Hierarchical Structures in Speech
The most critical attribute of human language is its unbounded combinatorial nature: smaller elements can be combined into larger structures on the basis of a grammatical system, resulting in a hierarchy of linguistic units, such as words, phrases and sentences. Mentally parsing and representing such structures, however, poses challenges for speech comprehension. I will present our recent work which shows that cortical activity of different timescales can concurrently track the time course of abstract linguistic structures at different hierarchical levels, such as words, phrases and sentences. More importantly, neural entrainment to higher level linguistic structures such as phrases and sentences cannot be explained by neural tracking of acoustic features or transitional probability cues between words. I will also discuss preliminary results on the temporal dynamics of neural entrainment to multi-syllable words and how attention differentially modulates neural entrainment to different linguistic structures.