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Models of retrieval in sentence comprehension

  • Research on similarity-based interference has provided extensive evidence that the formation of dependencies between non-adjacent words relies on a cue-based retrieval mechanism. There are two different models that can account for one of the main predictions of interference, i.e., a slowdown at a retrieval site, when several items share a feature associated with a retrieval cue: Lewis and Vasishth’s (2005) activation-based model and McElree’s (2000) direct-access model. Even though these two models have been used almost interchangeably, they are based on different assumptions and predict differences in the relationship between reading times and response accuracy. The activation-based model follows the assumptions of the ACT-R framework, and its retrieval process behaves as a lognormal race between accumulators of evidence with a single variance. Under this model, accuracy of the retrieval is determined by the winner of the race and retrieval time by its rate of accumulation. In contrast, the direct-access model assumes a model ofResearch on similarity-based interference has provided extensive evidence that the formation of dependencies between non-adjacent words relies on a cue-based retrieval mechanism. There are two different models that can account for one of the main predictions of interference, i.e., a slowdown at a retrieval site, when several items share a feature associated with a retrieval cue: Lewis and Vasishth’s (2005) activation-based model and McElree’s (2000) direct-access model. Even though these two models have been used almost interchangeably, they are based on different assumptions and predict differences in the relationship between reading times and response accuracy. The activation-based model follows the assumptions of the ACT-R framework, and its retrieval process behaves as a lognormal race between accumulators of evidence with a single variance. Under this model, accuracy of the retrieval is determined by the winner of the race and retrieval time by its rate of accumulation. In contrast, the direct-access model assumes a model of memory where only the probability of retrieval can be affected, while the retrieval time is drawn from the same distribution; in this model, differences in latencies are a by-product of the possibility of backtracking and repairing incorrect retrievals. We implemented both models in a Bayesian hierarchical framework in order to evaluate them and compare them. The data show that correct retrievals take longer than incorrect ones, and this pattern is better fit under the direct-access model than under the activation-based model. This finding does not rule out the possibility that retrieval may be behaving as a race model with assumptions that follow less closely the ones from the ACT-R framework. By introducing a modification of the activation model, i.e., by assuming that the accumulation of evidence for retrieval of incorrect items is not only slower but noisier (i.e., different variances for the correct and incorrect items), the model can provide a fit as good as the one of the direct-access model. This first ever computational evaluation of alternative accounts of retrieval processes in sentence processing opens the way for a broader investigation of theories of dependency completion.zeige mehrzeige weniger

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Metadaten
Verfasserangaben:Bruno NicenboimORCiDGND, Shravan VasishthORCiDGND
DOI:https://doi.org/10.1016/j.jml.2017.08.004
ISSN:0749-596X
ISSN:1096-0821
Titel des übergeordneten Werks (Englisch):Journal of memory and language
Untertitel (Englisch):a computational evaluation using Bayesian hierarchical modeling
Verlag:Elsevier
Verlagsort:San Diego
Publikationstyp:Wissenschaftlicher Artikel
Sprache:Englisch
Datum der Erstveröffentlichung:25.10.2018
Erscheinungsjahr:2018
Datum der Freischaltung:14.12.2021
Freies Schlagwort / Tag:Bayesian hierarchical modeling; Cognitive modeling; Cue-based retrieval; Sentence processing; Similarity-based interference; Working memory
Band:99
Seitenanzahl:34
Erste Seite:1
Letzte Seite:34
Fördernde Institution:Potsdam Graduate School, the University of Potsdam; Volkswagen FoundationVolkswagen [89953]
Organisationseinheiten:Humanwissenschaftliche Fakultät / Strukturbereich Kognitionswissenschaften / Department Linguistik
DDC-Klassifikation:4 Sprache / 41 Linguistik / 410 Linguistik
Peer Review:Referiert
Publikationsweg:Open Access / Green Open-Access
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