Low-frequency Cortical Activity Reflects Context-dependent Parsing of Word Sequences

Abstract

During speech listening, it has been hypothesized that the brain builds representations of large linguistic structures such as sentences, which are captured by neural activity tracking the rhythm of these structures. Nevertheless, it has been concerned that the brain may only encode words, and neural activity tracking structures may be confounded by neural activity tracking the predictability or syntactic properties of individual words. Here, to disentangle the neural responses to sentences and words, we design word sequences that are parsed into different sentences in different contexts. By analyzing neural activity recorded by magnetoencephalography, we find that low-frequency neural activity strongly depends on the context - The difference between MEG responses to the same word sequence in two contexts yields a low-frequency signal, most strongly generated in the superior temporal gyrus, which precisely tracks sentences. The predictability and syntactic properties of words can partly explain the neural response in each context but cannot explain the difference between contexts. In summary, low-frequency neural activity encodes sentences and can reliably reflect how the same word sequence is parsed in different contexts.