Abstract
Single-route models of morphosyntax posit that inflected word processing involves associative memory-based storage, whereas dual-route models propose rule-governed composition as an alternative to storage-based mechanisms. We test these accounts via their divergent predictions on whether word frequency affects processing of regular morphosyntactic inflections (as in the single-route model) or not (dual-route model). To date, the only study to test this using electroencephalography (EEG) comes from Allen, Badecker, and Osterhout (2003), who report no interaction between word grammaticality and word frequency. We conceptually replicate and extend Allen et al. (2003) with generalized additive mixed modeling, which retains per-trial and per-time sample information to avoid loss of statistical power from event-related potential-style averaging of trials while avoiding the assumption that the time course of word processing is identical across all words and individuals. In our EEG study, 51 English native speakers read sentences that either did or did not contain a determiner-noun agreement violation (e.g., this school/*schools) or a subject-verb agreement violation (e.g., the child runs/*run) based on a manipulation of a critical word. We follow the generalized additive mixed modeling procedure from prior research, with word frequency in the British National Corpus as a continuous predictor. We replicated Allen et al.’s (2003) reported main effects of frequency and grammaticality. Critically, we found no significant interaction between frequency and grammaticality. These results support Allen et al. (2003) in aligning with the dual-route model's account of composition-like mechanisms in inflected word processing.
Original language | English (US) |
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Article number | 101137 |
Journal | Journal of Neurolinguistics |
Volume | 67 |
DOIs | |
State | Published - Aug 2023 |
Funding
Versions of this study were presented at the 2021 annual meeting of the Cognitive Neuroscience Society and the 2021 annual meeting of the Society for the Neurobiology of Language. We thank attendees for their helpful comments on the work. We also wish to thank Krishna Bhatia, Gayatri Chavan, Sarah Hassan, Ana Carolina Hernandez, Daniel Henreckson, and Victoria Ogunniyi for their assistance with various aspects of this study. We thank Dr. Ryne Estabrook and Dr. Alexander Demos for their advice regarding the analysis. Thank you also to Dr. Martijn Wieling for his wonderful tutorial on the analysis method presented here as well as for his generosity in sharing advice via email. This work was supported by University of Illinois – Chicago Provost Deiss Award for Graduate Research. Versions of this study were presented at the 2021 annual meeting of the Cognitive Neuroscience Society and the 2021 annual meeting of the Society for the Neurobiology of Language. We thank attendees for their helpful comments on the work. We also wish to thank Krishna Bhatia, Gayatri Chavan, Sarah Hassan, Ana Carolina Hernandez, Daniel Henreckson, and Victoria Ogunniyi for their assistance with various aspects of this study. We thank Dr. Ryne Estabrook and Dr. Alexander Demos for their advice regarding the analysis. Thank you also to Dr. Martijn Wieling for his wonderful tutorial on the analysis method presented here as well as for his generosity in sharing advice via email. This work was supported by University of Illinois – Chicago Provost Deiss Award for Graduate Research.
Keywords
- Electroencephalography
- Morphosyntax
- Psycholinguistics
- Word frequency
ASJC Scopus subject areas
- Experimental and Cognitive Psychology
- Arts and Humanities (miscellaneous)
- Linguistics and Language
- Cognitive Neuroscience