Memory Retrieval in Online Sentence Parsing: Empirical Evidence, Computational Modelling, and Simulations.

This paper reports two experiments (Experiments 1 and 2) and computational simulations designed to investigate and model memory retrieval processes during real-time sentence processing. Central to this study is the hypothesis that linguistic information serves as a cue to retrieve target representations from memory during dependency formation. The basis for this cue-based memory retrieval stems from research showing that non-target representations that match a set of retrieval cues interfere with target retrieval. The susceptibility to this similarity-based interference has been debated in the sentence processing literature, and various hypotheses and models have been formulated and developed. This issue is addressed empirically in Experiments 1 and 2, which investigated similarity-based interference in sentences with a floating quantifier. Bayesian linear mixed models and Bayes factor analyses suggested similarity-based interference. However, the patterns of interference were not consistent with existing theories and models. To reconcile these findings within the framework of cue-based memory retrieval, this paper implements