Rational Sentence Interpretation in Mandarin Chinese.

Previous work has shown that English native speakers interpret sentences as predicted by a noisy-channel model: They integrate both the real-world plausibility of the meaning-the prior-and the likelihood that the intended sentence may be corrupted into the perceived sentence. In this study, we test the noisy-channel model in Mandarin Chinese, a language taxonomically different from English. We present native Mandarin speakers sentences in a written modality (Experiment 1) and an auditory modality (Experiment 2) in three pairs of syntactic alternations. The critical materials are literally implausible but require differing numbers and types of edits in order to form more plausible sentences. Each sentence is followed by a comprehension question that allows us to infer whether the speakers interpreted the item literally, or made an inference toward a more likely meaning. Similar to previous research on related English constructions, Mandarin participants made the most inferences for implausible materials that could be inferred as plausible by deleting a single morpheme or inserting a single morpheme. Participants were less likely to infer a plausible meaning for materials that could be inferred as plausible by making an exchange across a preposition. And participants were least likely to infer a plausible meaning for materials that could be inferred as plausible by making an exchange across a main verb. Moreover, we found more inferences in written materials than spoken materials, possibly a result of a lack of word boundaries in written Chinese. Overall, the fact that the results were so similar to those found in related constructions in English suggests that the noisy-channel proposal is robust.

Pronoun interpretation in Mandarin Chinese follows principles of Bayesian inference.

Successful natural language understanding requires that comprehenders be able to resolve uncertainty in language. One source of potential uncertainty emerges from a speaker's choice to use a pronoun (e.g., he, she, they), since pronouns often do not fully specify the speaker's intended referent. Nevertheless, comprehenders are typically able to interpret pronouns rapidly despite having limited cognitive resources. Here we report three pronoun interpretation experiments that investigate whether comprehenders reverse-engineer a speaker's referential intentions based on Bayesian principles, as documented in previous studies for English. Using Mandarin Chinese, we test the generality of the Bayesian pronoun interpretation theory, and further evaluate the predictions of the theory in ways that are not possible in English. Our results lend both qualitative and quantitative support to a cross-linguistically general Bayesian theory of pronoun interpretation.

Toward a Database of Intracranial Electrophysiology during Natural Language Presentation.

Intracranial electrophysiology (iEEG) studies using cognitive tasks contribute to the understanding of the neural basis of language. However, though iEEG is recorded continuously during clinical treatment, due to patient considerations task time is limited. To increase the usefulness of iEEG recordings for language study, we provided patients with a tablet pre-loaded with media filled with natural language, wirelessly synchronized to clinical iEEG. This iEEG data collected and time-locked to natural language presentation is particularly applicable for studying the neural basis of combining words into larger contexts. We validate this approach with pilot analyses involving words heard during a movie, tagging syntactic properties and verb contextual probabilities. Event-related averages of high-frequency power (70-170Hz) identified bilateral perisylvian electrodes with differential responses to syntactic class and a linear regression identified activity associated with contextual probabilities, demonstrating the usefulness of aligning media to iEEG. We imagine future multi-site collaborations building an 'intracranial neurolinguistic corpus'.