Language in context: Characterizing the comprehension of referential expressions with MEG
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abstract
A critical component of comprehending language in context is identifying the entities that individual linguistic expressions refer to. While previous research has shown that language comprehenders resolve reference quickly and incrementally, little is currently known about the neural basis of successful reference resolution. Using source localized MEG, we provide evidence across 3 experiments and 2 languages that successful reference resolution in simple visual displays is associated with increased activation in the medial parietal lobe. In each trial, participants saw a simple visual display containing three objects which constituted the referential domain. Target referential expressions were embedded in questions about the displays. By varying the displays, we manipulated referential status while keeping the linguistic expressions constant. Follow-up experiments addressed potential interactions of reference resolution with linguistic predictiveness and pragmatic plausibility. Notably, we replicated the effect in Arabic, a language that differs in a structurally informative way from English while keeping referential aspects parallel to our two English studies. Distributed minimum norm estimates of MEG data consistently indicated that reference resolution is associated with increased activity in the medial parietal lobe. With one exception, the timing of the onset of the medial parietal response fell into a mid-latency time-window at 350-500ms after the onset of the resolving word. Through concurrent EEG recordings on a subset of subjects we also describe the EEG topography of the effect of reference resolution, which makes the result available for comparison with a larger existing literature. Our results extend previous reports that medial parietal lobe is involved in referential language processing, indicating that it is relevant for reference resolution to individual referents, and suggests avenues for future research.