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  1. The N400 is Elicited by Meaning Changes but not Synonym Substitutions: Evidence From Persian Phrasal Verbs.Kate Stone, Naghmeh Khaleghi & Milena Rabovsky - 2023 - Cognitive Science 47 (12):e13394.
    We tested two accounts of the cognitive process underlying the N400 event‐related potential component: one that it reflects meaning‐based processing and one that it reflects the processing of specific words. The experimental design utilized separable Persian phrasal verbs, which form a strongly probabilistic, long‐distance dependency, ideal for the study of probabilistic processing. In sentences strongly constraining for a particular continuation, we show evidence that between two low‐probability words, only the word that changed the expected meaning of the sentence increased N400 (...)
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  • Memory Versus Expectation: Processing Relative Clauses in a Flexible Word Order Language.Eszter Ronai & Ming Xiang - 2023 - Cognitive Science 47 (1):e13227.
    Memory limitations and probabilistic expectations are two key factors that have been posited to play a role in the incremental processing of natural language. Relative clauses (RCs) have long served as a key proving ground for such theories of language processing. Across three self-paced reading experiments, we test the online comprehension of Hungarian subject- and object-extracted RCs (SRCs and ORCs, respectively). We capitalize on the syntactic properties of Hungarian that allow for a variety of word orders within RCs, which helps (...)
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  • Locality and expectation effects in Hindi preverbal constituent ordering.Sidharth Ranjan, Rajakrishnan Rajkumar & Sumeet Agarwal - 2022 - Cognition 223 (C):104959.
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  • Word Order Typology Interacts With Linguistic Complexity: A Cross‐Linguistic Corpus Study.Himanshu Yadav, Ashwini Vaidya, Vishakha Shukla & Samar Husain - 2020 - Cognitive Science 44 (4):e12822.
    Much previous work has suggested that word order preferences across languages can be explained by the dependency distance minimization constraint (Ferrer‐i Cancho, 2008, 2015; Hawkins, 1994). Consistent with this claim, corpus studies have shown that the average distance between a head (e.g., verb) and its dependent (e.g., noun) tends to be short cross‐linguistically (Ferrer‐i Cancho, 2014; Futrell, Mahowald, & Gibson, 2015; Liu, Xu, & Liang, 2017). This implies that on average languages avoid inefficient or complex structures for simpler structures. But (...)
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  • Lossy‐Context Surprisal: An Information‐Theoretic Model of Memory Effects in Sentence Processing.Richard Futrell, Edward Gibson & Roger P. Levy - 2020 - Cognitive Science 44 (3):e12814.
    A key component of research on human sentence processing is to characterize the processing difficulty associated with the comprehension of words in context. Models that explain and predict this difficulty can be broadly divided into two kinds, expectation‐based and memory‐based. In this work, we present a new model of incremental sentence processing difficulty that unifies and extends key features of both kinds of models. Our model, lossy‐context surprisal, holds that the processing difficulty at a word in context is proportional to (...)
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  • Effects of Early Cues on the Processing of Chinese Relative Clauses: Evidence for Experience‐Based Theories.Fuyun Wu, Elsi Kaiser & Shravan Vasishth - 2018 - Cognitive Science 42 (S4):1101-1133.
    We used Chinese prenominal relative clauses to test the predictions of two competing accounts of sentence comprehension difficulty: the experience-based account of Levy () and the Dependency Locality Theory. Given that in Chinese RCs, a classifier and/or a passive marker BEI can be added to the sentence-initial position, we manipulated the presence/absence of classifiers and the presence/absence of BEI, such that BEI sentences were passivized subject-extracted RCs, and no-BEI sentences were standard object-extracted RCs. We conducted two self-paced reading experiments, using (...)
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  • Category Locality Theory: A unified account of locality effects in sentence comprehension.Shinnosuke Isono - 2024 - Cognition 247 (C):105766.
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