@phdthesis{Laurinavichyute2021,
  author    = {Laurinavichyute, Anna},
  title     = {Similarity-based interference and faulty encoding accounts of sentence processing},
  doi       = {10.25932/publishup-50966},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-509669},
  school      = {Universit{\"a}t Potsdam},
  pages     = {237},
  year      = {2021},
  abstract  = {The goal of this dissertation is to empirically evaluate the predictions of two classes of models applied to language processing: the similarity-based interference models (Lewis \& Vasishth, 2005; McElree, 2000) and the group of smaller-scale accounts that we will refer to as faulty encoding accounts (Eberhard, Cutting, \& Bock, 2005; Bock \& Eberhard, 1993). Both types of accounts make predictions with regard to processing the same class of structures: sentences containing a non-subject (interfering) noun in addition to a subject noun and a verb. Both accounts make the same predictions for processing ungrammatical sentences with a number-mismatching interfering noun, and this prediction finds consistent support in the data. However, the similarity-based interference accounts predict similar effects not only for morphosyntactic, but also for the semantic level of language organization. We verified this prediction in three single-trial online experiments, where we found consistent support for the predictions of the similarity-based interference account. In addition, we report computational simulations further supporting the similarity-based interference accounts. The combined evidence suggests that the faulty encoding accounts are not required to explain comprehension of ill-formed sentences. For the processing of grammatical sentences, the accounts make conflicting predictions, and neither the slowdown predicted by the similarity-based interference account, nor the complementary slowdown predicted by the faulty encoding accounts were systematically observed. The majority of studies found no difference between the compared configurations. We tested one possible explanation for the lack of predicted difference, namely, that both slowdowns are present simultaneously and thus conceal each other. We decreased the amount of similarity-based interference: if the effects were concealing each other, decreasing one of them should allow the other to surface. Surprisingly, throughout three larger-sample single-trial online experiments, we consistently found the slowdown predicted by the faulty encoding accounts, but no effects consistent with the presence of inhibitory interference. The overall pattern of the results observed across all the experiments reported in this dissertation is consistent with previous findings: predictions of the interference accounts for the processing of ungrammatical sentences receive consistent support, but the predictions for the processing of grammatical sentences are not always met. Recent proposals by Nicenboim et al. (2016) and Mertzen et al. (2020) suggest that interference might arise only in people with high working memory capacity or under deep processing mode. Following these proposals, we tested whether interference effects might depend on the depth of processing: we manipulated the complexity of the training materials preceding the grammatical experimental sentences while making no changes to the experimental materials themselves. We found that the slowdown predicted by the faulty encoding accounts disappears in the deep processing mode, but the effects consistent with the predictions of the similarity-based interference account do not arise. Independently of whether similarity-based interference arises under deep processing mode or not, our results suggest that the faulty encoding accounts cannot be dismissed since they make unique predictions with regard to processing grammatical sentences, which are supported by data. At the same time, the support is not unequivocal: the slowdowns are present only in the superficial processing mode, which is not predicted by the faulty encoding accounts. Our results might therefore favor a much simpler system that superficially tracks number features and is distracted by every plural feature.},
  language  = {en}
}
@article{LaurinavichyutevonderMalsburg2022,
  author    = {Laurinavichyute, Anna and von der Malsburg, Titus},
  title     = {Semantic attraction in sentence comprehension},
  series = {Cognitive science},
  volume    = {46},
  journal   = {Cognitive science},
  number    = {2},
  publisher = {Wiley},
  address   = {Hoboken},
  issn      = {0364-0213},
  doi       = {10.1111/cogs.13086},
  pages     = {38},
  year      = {2022},
  abstract  = {Agreement attraction is a cross-linguistic phenomenon where a verb occasionally agrees not with its subject, as required by grammar, but instead with an unrelated noun ("The key to the cabinets were horizontal ellipsis "). Despite the clear violation of grammatical rules, comprehenders often rate these sentences as acceptable. Contenders for explaining agreement attraction fall into two broad classes: Morphosyntactic accounts specifically designed to explain agreement attraction, and more general sentence processing models, such as the Lewis and Vasishth model, which explain attraction as a consequence of how linguistic structure is stored and accessed in content-addressable memory. In the present research, we disambiguate between these two classes by testing a surprising prediction made by the Lewis and Vasishth model but not by the morphosyntactic accounts, namely, that attraction should not be limited to morphosyntax, but that semantic features of unrelated nouns equally induce attraction. A recent study by Cunnings and Sturt provided initial evidence that this may be the case. Here, we report three single-trial experiments in English that compared semantic and agreement attraction and tested whether and how the two interact. All three experiments showed strong semantically induced attraction effects closely mirroring agreement attraction effects. We complement these results with computational simulations which confirmed that the Lewis and Vasishth model can faithfully reproduce the observed results. In sum, our findings suggest that attraction is a more general phenomenon than is commonly believed, and therefore favor more general sentence processing models, such as the Lewis and Vasishth model.},
  language  = {en}
}
@phdthesis{Mertzen2022,
  author    = {Mertzen, Daniela},
  title     = {A cross-linguistic investigation of similarity-based interference in sentence comprehension},
  doi       = {10.25932/publishup-55668},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-556685},
  school      = {Universit{\"a}t Potsdam},
  pages     = {xvii, 129},
  year      = {2022},
  abstract  = {The aim of this dissertation was to conduct a larger-scale cross-linguistic empirical investigation of similarity-based interference effects in sentence comprehension. Interference studies can offer valuable insights into the mechanisms that are involved in long-distance dependency completion. Many studies have investigated similarity-based interference effects, showing that syntactic and semantic information are employed during long-distance dependency formation (e.g., Arnett \& Wagers, 2017; Cunnings \& Sturt, 2018; Van Dyke, 2007, Van Dyke \& Lewis, 2003; Van Dyke \& McElree, 2011). Nevertheless, there are some important open questions in the interference literature that are critical to our understanding of the constraints involved in dependency resolution. The first research question concerns the relative timing of syntactic and semantic interference in online sentence comprehension. Only few interference studies have investigated this question, and, to date, there is not enough data to draw conclusions with regard to their time course (Van Dyke, 2007; Van Dyke \& McElree, 2011). Our first cross-linguistic study explores the relative timing of syntactic and semantic interference in two eye-tracking reading experiments that implement the study design used in Van Dyke (2007). The first experiment tests English sentences. The second, larger-sample experiment investigates the two interference types in German. Overall, the data suggest that syntactic and semantic interference can arise simultaneously during retrieval. The second research question concerns a special case of semantic interference: We investigate whether cue-based retrieval interference can be caused by semantically similar items which are not embedded in a syntactic structure. This second interference study builds on a landmark study by Van Dyke \& McElree (2006). The study design used in their study is unique in that it is able to pin down the source of interference as a consequence of cue overload during retrieval, when semantic retrieval cues do not uniquely match the retrieval target. Unlike most other interference studies, this design is able to rule out encoding interference as an alternative explanation. Encoding accounts postulate that it is not cue overload at the retrieval site but the erroneous encoding of similar linguistic items in memory that leads to interference (Lewandowsky et al., 2008; Oberauer \& Kliegl, 2006). While Van Dyke \& McElree (2006) reported cue-based retrieval interference from sentence-external distractors, the evidence for this effect was weak. A subsequent study did not show interference of this type (Van Dyke et al., 2014). Given these inconclusive findings, further research is necessary to investigate semantic cue-based retrieval interference. The second study in this dissertation provides a larger-scale cross-linguistic investigation of cue-based retrieval interference from sentence-external items. Three larger-sample eye-tracking studies in English, German, and Russian tested cue-based interference in the online processing of filler-gap dependencies. This study further extends the previous research by investigating interference in each language under varying task demands (Logačev \& Vasishth, 2016; Swets et al., 2008). Overall, we see some very modest support for proactive cue-based retrieval interference in English. Unexpectedly, this was observed only under a low task demand. In German and Russian, there is some evidence against the interference effect. It is possible that interference is attenuated in languages with richer case marking. In sum, the cross-linguistic experiments on the time course of syntactic and semantic interference from sentence-internal distractors support existing evidence of syntactic and semantic interference during sentence comprehension. Our data further show that both types of interference effects can arise simultaneously. Our cross-linguistic experiments investigating semantic cue-based retrieval interference from sentence-external distractors suggest that this type of interference may arise only in specific linguistic contexts.},
  language  = {en}
}