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Summary
This summary is machine-generated.

Sentence processing involves encoding and retrieval, but interference can occur at both stages. This study found evidence for interference during memory encoding, not just retrieval, suggesting a need for updated models of language comprehension.

Keywords:
ACT-Ragreementencodinglong-distance dependenciesretrievalself-organized sentence processingsimilarity-based interferenceworking memory

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Area of Science:

  • Psycholinguistics
  • Cognitive Science
  • Computational Linguistics

Background:

  • Long-distance dependencies in sentences require integrating arguments with verbs.
  • Cue-based retrieval models explain interference when cues match non-target elements (retrieval interference).
  • Encoding interference, occurring during memory formation, is theoretically distinct but empirically challenging to separate from retrieval interference.

Purpose of the Study:

  • To empirically distinguish between encoding and retrieval interference in sentence processing.
  • To investigate the role of subject-verb agreement as a retrieval cue in Italian and English.
  • To propose model augmentations that account for both encoding and retrieval interference.

Main Methods:

  • Two self-paced reading experiments were conducted using Italian and English object relative clauses.
  • Linguistic manipulations focused on subject-verb agreement (gender in Italian, number in English) to create varying retrieval cue strengths.
  • Behavioral data from reading times were analyzed to identify patterns of interference.

Main Results:

  • Both experiments demonstrated similarity-based interference primarily during the encoding phase of sentence processing.
  • Evidence for interference at the retrieval phase was also observed, though less pronounced than encoding interference.
  • The findings highlight that encoding interference significantly impacts sentence comprehension.

Conclusions:

  • Existing cue-based retrieval models (e.g., ACT-R) do not fully account for observed encoding effects.
  • An augmented ACT-R model is proposed to incorporate encoding interference.
  • A novel self-organizing sentence processing (SOSP) model is introduced, offering a unified mechanism for both encoding and retrieval interference.