Sentence comprehension as a cognitive process

Cognitive constraints can dramatically affect real-time sentence interpretation.
A well-known example is erroneous subject-verb or antecedent-reflexive
dependency completion when a distractor noun interrupts a dependency (Cunnings
and Sturt 2018; Jäger et al 2020; Yadav et al., 2022). Another example is
underspecification due to factors such as limited working memory capacity
(von der Malsburg & Vasishth, 2013).

What are these cognitive constraints and how do they impact real-time sentence
comprehension? I will present a series of formal (computational) models of
cognitive processes that can explain a broad range of empirically observed
patterns of difficulty in sentence comprehension. As Brasoveanu and Dotlačil
(2020) have shown, such models are a powerful tool for developing theories of
sentence interpretation processes unfolding over time.

To illustrate the expressive power of the models presented, I will discuss
several important case studies, such as agreement attraction,
modulation of interference effects via individual differences in
cue-weighting, and sources of sentence comprehension difficulty in aphasia.

References

Brasoveanu, A., & Dotlačil, J. (2020). Computational cognitive modeling
and linguistic theory. Springer Nature.
URL: https://library.oapen.org/handle/20.500.12657/39529

Cunnings, I., & Sturt, P. (2018). Retrieval interference and semantic interpretation.
Journal of Memory and Language, 102, 16-27.

Jäger. L, Mertzen, D., Van Dyke J.A., and Vasishth, S.
Interference patterns in subject-verb agreement and reflexives revisited:
A large-sample study. Journal of Memory and Language, 111, 2020.
URL: https://osf.io/reavs/

von der Malsburg, T, and Vasishth, S. Scanpaths reveal syntactic underspecification
and reanalysis strategies. Language and Cognitive Processes, 28(10):1545–1578, 2013.

Vasishth, S. and Engelmann, F. Sentence Comprehension as a Cognitive
Process: A Computational Approach. Cambridge University Press, Cambridge,
UK, 2022.
URL: https://vasishth.github.io/RetrievalModels/

Vasishth, S., Nicenboim, B., Engelmann, F., and Burchert, F.
Computational models of retrieval processes in sentence processing.
Trends in Cognitive Sciences, 23:968–982, 2019.
URL: https://osf.io/qtvxj/

Yadav, H., Paape, D., Smith, G., Dillon, B.W., and Vasishth, S.
Individual differences in cue weighting in sentence
comprehension: An evaluation using Approximate Bayesian Computation.
Open Mind, 2022.
URL: https://doi.org/10.1162/opmi_a_00052