@phdthesis{Engelmann2016,
  author    = {Engelmann, Felix},
  title     = {Toward an integrated model of sentence processing in reading},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-100864},
  school      = {Universit{\"a}t Potsdam},
  pages     = {xiii, 143},
  year      = {2016},
  abstract  = {In experiments investigating sentence processing, eye movement measures such as fixation durations and regression proportions while reading are commonly used to draw conclusions about processing difficulties. However, these measures are the result of an interaction of multiple cognitive levels and processing strategies and thus are only indirect indicators of processing difficulty. In order to properly interpret an eye movement response, one has to understand the underlying principles of adaptive processing such as trade-off mechanisms between reading speed and depth of comprehension that interact with task demands and individual differences. Therefore, it is necessary to establish explicit models of the respective mechanisms as well as their causal relationship with observable behavior. There are models of lexical processing and eye movement control on the one side and models on sentence parsing and memory processes on the other. However, no model so far combines both sides with explicitly defined linking assumptions. In this thesis, a model is developed that integrates oculomotor control with a parsing mechanism and a theory of cue-based memory retrieval. On the basis of previous empirical findings and independently motivated principles, adaptive, resource-preserving mechanisms of underspecification are proposed both on the level of memory access and on the level of syntactic parsing. The thesis first investigates the model of cue-based retrieval in sentence comprehension of Lewis \& Vasishth (2005) with a comprehensive literature review and computational modeling of retrieval interference in dependency processing. The results reveal a great variability in the data that is not explained by the theory. Therefore, two principles, 'distractor prominence' and 'cue confusion', are proposed as an extension to the theory, thus providing a more adequate description of systematic variance in empirical results as a consequence of experimental design, linguistic environment, and individual differences. In the remainder of the thesis, four interfaces between parsing and eye movement control are defined: Time Out, Reanalysis, Underspecification, and Subvocalization. By comparing computationally derived predictions with experimental results from the literature, it is investigated to what extent these four interfaces constitute an appropriate elementary set of assumptions for explaining specific eye movement patterns during sentence processing. Through simulations, it is shown how this system of in itself simple assumptions results in predictions of complex, adaptive behavior. In conclusion, it is argued that, on all levels, the sentence comprehension mechanism seeks a balance between necessary processing effort and reading speed on the basis of experience, task demands, and resource limitations. Theories of linguistic processing therefore need to be explicitly defined and implemented, in particular with respect to linking assumptions between observable behavior and underlying cognitive processes. The comprehensive model developed here integrates multiple levels of sentence processing that hitherto have only been studied in isolation. The model is made publicly available as an expandable framework for future studies of the interactions between parsing, memory access, and eye movement control.},
  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}
}
@phdthesis{LissonHernandez2022,
  author    = {Liss{\´o}n Hern{\´a}ndez, Paula J.},
  title     = {Computational models of sentence comprehension in aphasia},
  doi       = {10.25932/publishup-55548},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-555487},
  school      = {Universit{\"a}t Potsdam},
  pages     = {vi, 159},
  year      = {2022},
  abstract  = {It is well-known that individuals with aphasia (IWA) have difficulties understanding sentences that involve non-adjacent dependencies, such as object relative clauses or passives (Caplan, Baker, \& Dehaut, 1985; Caramazza \& Zurif, 1976). A large body of research supports the view that IWA's grammatical system is intact, and that comprehension difficulties in aphasia are caused by a processing deficit, such as a delay in lexical access and/or in syntactic structure building (e.g., Burkhardt, Pi{\~n}ango, \& Wong, 2003; Caplan, Michaud, \& Hufford, 2015; Caplan, Waters, DeDe, Michaud, \& Reddy, 2007; Ferrill, Love, Walenski, \& Shapiro, 2012; Hanne, Burchert, De Bleser, \& Vasishth, 2015; Love, Swinney, Walenski, \& Zurif, 2008). The main goal of this dissertation is to computationally investigate the processing sources of comprehension impairments in sentence processing in aphasia. In this work, prominent theories of processing deficits coming from the aphasia literature are implemented within two cognitive models of sentence processing -the activation-based model (Lewis \& Vasishth, 2005) and the direct-access model (McEl- ree, 2000)-. These models are two different expressions of the cue-based retrieval theory (Lewis, Vasishth, \& Van Dyke, 2006), which posits that sentence processing is the result of a series of iterative retrievals from memory. These two models have been widely used to account for sentence processing in unimpaired populations in multiple languages and linguistic constructions, sometimes interchangeably (Parker, Shvarts- man, \& Van Dyke, 2017). However, Nicenboim and Vasishth (2018) showed that when both models are implemented in the same framework and fitted to the same data, the models yield different results, because the models assume different data- generating processes. Specifically, the models hold different assumptions regarding the retrieval latencies. The second goal of this dissertation is to compare these two models of cue-based retrieval, using data from individuals with aphasia and control participants. We seek to answer the following question: Which retrieval mechanism is more likely to mediate sentence comprehension? We model 4 subsets of existing data: Relative clauses in English and German; and control structures and pronoun resolution in German. The online data come from either self-paced listening experiments, or visual-world eye-tracking experiments. The offline data come from a complementary sentence-picture matching task performed at the end of the trial in both types of experiments. The two competing models of retrieval are implemented in the Bayesian framework, following Nicenboim and Vasishth (2018). In addition, we present a modified version of the direct-acess model that - we argue - is more suitable for individuals with aphasia. This dissertation presents a systematic approach to implement and test verbally- stated theories of comprehension deficits in aphasia within cognitive models of sen- tence processing. The conclusions drawn from this work are that (a) the original direct-access model (as implemented here) cannot account for the full pattern of data from individuals with aphasia because it cannot account for slow misinterpretations; and (b) an activation-based model of retrieval can account for sentence comprehension deficits in individuals with aphasia by assuming a delay in syntactic structure building, and noise in the processing system. The overall pattern of results support an activation-based mechanism of memory retrieval, in which a combination of processing deficits, namely slow syntax and intermittent deficiencies, cause comprehension difficulties in individuals with aphasia.},
  language  = {en}
}
@phdthesis{Yadav2023,
  author    = {Yadav, Himanshu},
  title     = {A computational evaluation of feature distortion and cue weighting in sentence comprehension},
  doi       = {10.25932/publishup-58505},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-585055},
  school      = {Universit{\"a}t Potsdam},
  pages     = {iv, 115},
  year      = {2023},
  abstract  = {Successful sentence comprehension requires the comprehender to correctly figure out who did what to whom. For example, in the sentence John kicked the ball, the comprehender has to figure out who did the action of kicking and what was being kicked. This process of identifying and connecting the syntactically-related words in a sentence is called dependency completion. What are the cognitive constraints that determine dependency completion? A widely-accepted theory is cue-based retrieval. The theory maintains that dependency completion is driven by a content-addressable search for the co-dependents in memory. The cue-based retrieval explains a wide range of empirical data from several constructions including subject-verb agreement, subject-verb non-agreement, plausibility mismatch configurations, and negative polarity items. However, there are two major empirical challenges to the theory: (i) Grammatical sentences' data from subject-verb number agreement dependencies, where the theory predicts a slowdown at the verb in sentences like the key to the cabinet was rusty compared to the key to the cabinets was rusty, but the data are inconsistent with this prediction; and, (ii) Data from antecedent-reflexive dependencies, where a facilitation in reading times is predicted at the reflexive in the bodybuilder who worked with the trainers injured themselves vs. the bodybuilder who worked with the trainer injured themselves, but the data do not show a facilitatory effect. The work presented in this dissertation is dedicated to building a more general theory of dependency completion that can account for the above two datasets without losing the original empirical coverage of the cue-based retrieval assumption. In two journal articles, I present computational modeling work that addresses the above two empirical challenges. To explain the grammatical sentences' data from subject-verb number agreement dependencies, I propose a new model that assumes that the cue-based retrieval operates on a probabilistically distorted representation of nouns in memory (Article I). This hybrid distortion-plus-retrieval model was compared against the existing candidate models using data from 17 studies on subject-verb number agreement in 4 languages. I find that the hybrid model outperforms the existing models of number agreement processing suggesting that the cue-based retrieval theory must incorporate a feature distortion assumption. To account for the absence of facilitatory effect in antecedent-reflexive dependen� cies, I propose an individual difference model, which was built within the cue-based retrieval framework (Article II). The model assumes that individuals may differ in how strongly they weigh a syntactic cue over a number cue. The model was fitted to data from two studies on antecedent-reflexive dependencies, and the participant-level cue-weighting was estimated. We find that one-fourth of the participants, in both studies, weigh the syntactic cue higher than the number cue in processing reflexive dependencies and the remaining participants weigh the two cues equally. The result indicates that the absence of predicted facilitatory effect at the level of grouped data is driven by some, not all, participants who weigh syntactic cues higher than the number cue. More generally, the result demonstrates that the assumption of differential cue weighting is important for a theory of dependency completion processes. This differential cue weighting idea was independently supported by a modeling study on subject-verb non-agreement dependencies (Article III). Overall, the cue-based retrieval, which is a general theory of dependency completion, needs to incorporate two new assumptions: (i) the nouns stored in memory can undergo probabilistic feature distortion, and (ii) the linguistic cues used for retrieval can be weighted differentially. This is the cumulative result of the modeling work presented in this dissertation. The dissertation makes an important theoretical contribution: Sentence comprehension in humans is driven by a mechanism that assumes cue-based retrieval, probabilistic feature distortion, and differential cue weighting. This insight is theoretically important because there is some independent support for these three assumptions in sentence processing and the broader memory literature. The modeling work presented here is also methodologically important because for the first time, it demonstrates (i) how the complex models of sentence processing can be evaluated using data from multiple studies simultaneously, without oversimplifying the models, and (ii) how the inferences drawn from the individual-level behavior can be used in theory development.},
  language  = {en}
}