Languages (Dec 2023)

Adaptation of Gap Predictions in Filler-Gap Dependency Processing during Reading

  • Emily Atkinson,
  • Akira Omaki

DOI
https://doi.org/10.3390/languages8040285
Journal volume & issue
Vol. 8, no. 4
p. 285

Abstract

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Syntactic adaptation effects have been demonstrated for an expanding list of structure types, but the mechanism underlying this effect is still being explored. In the current work on filler-gap dependency processing, we examined whether exposing participants to a less common gap location—prepositional object (PO) gaps—altered their gap predictions, and whether these effects would transfer across tasks when this input was presented in a quasi-naturalistic way (i.e., by reading stories). In Experiment 1, we demonstrated that comprehenders dampened their direct object (DO) gap predictions following exposure to PO gaps. However, Experiments 2A and 2B suggest that these adaptation effects did not transfer when the quasi-naturalistic exposure phase was presented as a separate task (Experiment 2A) and when they also needed to generalize from a syntactic to a semantic measure of direct object gap predictions (i.e., filled gap vs. plausibility mismatch sentences; Experiment 2B). Overall, these experiments add filler-gap dependency processing, as well as the gap predictions associated with it, to the growing list of structures demonstrating adaptation effects, while also suggesting that this effect may be specific to a singular experimental task environment.

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