Testing Low-Frequency Neural Activity in Sentence Understanding

Abstract

Human language has the unique characteristic where we can create infinite and novel phrases or sentences; this stems from the ability of composition, which allows us to combine smaller units into bigger meaningful units. Composition involves us following syntactic rules stored in memory and building well-formed structures incrementally. Research has shown that neural circuits can be associated with cognitive faculties such as memory and language and there is evidence indicating where and when the neural indices of the processing of composition are. However, it is not yet clear "how" neural circuits actually implement compositional processes. This dissertation aims to probe "how" composition of meaning is represented by neural circuits by investigating the role of low-frequency neural activity in carrying out composition. Neuroelectric signals were recorded with Electroencephalography (EEG) to examine the functional interpretation of low-frequency neural activity in the so-called delta band of 0.5 to 3 Hz. Activities in this band have been associated with the processing of syntactic structures (Ding et al. 2016). First, whether these activities are indeed associated with hierarchy remains under debate. This dissertation uses a novel condition in which the same words are presented, but their order is changed to remove the syntactic structure. Only entrainment with syllables was found in this "reversed" condition, supporting the hypothesis that neural activities in the delta band entrain to abstract syntactic structures. Second, we test the timing for language users to combine words and comprehend sentences. How comprehension correlates with this low-frequency neural activity and whether it represents endogenous neural response or evoked response remains unclear. This dissertation manipulates the length of syllables and regularity between syllables to test the hypotheses. The results support the view that this neural activity reflects endogenous response and suggest that it reflects top-down processing. Third, what semantic information modulates this low-frequency neural activity is unknown. This dissertation examines several semantic variables typically associated with different aspects of semantic processing. The stimuli are created by varying the statistical association between words, world knowledge, and the conceptual results of semantic composition. The current results suggest that low-frequency neural activity is not driven by semantic processing. Based on the above findings, we propose that neural activities in the delta band reflect top-down predictive processing that involves syntactic information directly but not semantic information.