The Effect of Prominence and Cue Association on Retrieval Processes: A Computational Account.

We present a comprehensive empirical evaluation of the ACT-R-based model of sentence processing developed by Lewis and Vasishth (2005) (LV05). The predictions of the model are compared with the results of a recent meta-analysis of published reading studies on retrieval interference in reflexive-/reciprocal-antecedent and subject-verb dependencies (Jäger, Engelmann, & Vasishth, 2017). The comparison shows that the model has only partial success in explaining the data; and we propose that its prediction space is restricted by oversimplifying assumptions. We then implement a revised model that takes into account differences between individual experimental designs in terms of the prominence of the target and the distractor in memory- and context-dependent cue-feature associations. The predictions of the original and the revised model are quantitatively compared with the results of the meta-analysis. Our simulations show that, compared to the original LV05 model, the revised model accounts for the data better. The results suggest that effects of prominence and variable cue-feature associations need to be considered in the interpretation of existing empirical results and in the design and planning of future experiments. With regard to retrieval interference in sentence processing and to the broader field of psycholinguistic studies, we conclude that well-specified models in tandem with high-powered experiments are needed in order to uncover the underlying cognitive processes.

Computational Models of Retrieval Processes in Sentence Processing.

Sentence comprehension requires that the comprehender work out who did what to whom. This process has been characterized as retrieval from memory. This review summarizes the quantitative predictions and empirical coverage of the two existing computational models of retrieval and shows how the predictive performance of these two competing models can be tested against a benchmark data-set. We also show how computational modeling can help us better understand sources of variability in both unimpaired and impaired sentence comprehension.

How the input shapes the acquisition of verb morphology: Elicited production and computational modelling in two highly inflected languages.

The aim of the present work was to develop a computational model of how children acquire inflectional morphology for marking person and number; one of the central challenges in language development. First, in order to establish which putative learning phenomena are sufficiently robust to constitute a target for modelling, we ran large-scale elicited production studies with native learners of Finnish (N = 77; 35-63 months) and Polish (N = 81; 35-59 months), using a novel method that, unlike previous studies, allows for elicitation of all six person/number forms in the paradigm (first, second and third person; singular and plural). We then proceeded to build and test a connectionist model of the acquisition of person/number marking which not only acquires near adult-like mastery of the system (including generalisation to unseen items), but also yields all of the key phenomena observed in the elicited-production studies; specifically, effects of token frequency and phonological neighbourhood density of the target form, and a pattern whereby errors generally reflect the replacement of low frequency targets by higher-frequency forms of the same verb, or forms with the same person/number as the target, but with a suffix from an inappropriate conjugation class. The findings demonstrate that acquisition of even highly complex systems of inflectional morphology can be accounted for by a theoretical model that assumes rote storage and phonological analogy, as opposed to formal symbolic rules.

Exploratory and Confirmatory Analyses in Sentence Processing: A Case Study of Number Interference in German.

Given the replication crisis in cognitive science, it is important to consider what researchers need to do in order to report results that are reliable. We consider three changes in current practice that have the potential to deliver more realistic and robust claims. First, the planned experiment should be divided into two stages, an exploratory stage and a confirmatory stage. This clear separation allows the researcher to check whether any results found in the exploratory stage are robust. The second change is to carry out adequately powered studies. We show that this is imperative if we want to obtain realistic estimates of effects in psycholinguistics. The third change is to use Bayesian data-analytic methods rather than frequentist ones; the Bayesian framework allows us to focus on the best estimates we can obtain of the effect, rather than rejecting a strawman null. As a case study, we investigate number interference effects in German. Number feature interference is predicted by cue-based retrieval models of sentence processing (Van Dyke & Lewis, 2003; Vasishth & Lewis, 2006), but it has shown inconsistent results. We show that by implementing the three changes mentioned, suggestive evidence emerges that is consistent with the predicted number interference effects.

A Computational Investigation of Sources of Variability in Sentence Comprehension Difficulty in Aphasia.

We present a computational evaluation of three hypotheses about sources of deficit in sentence comprehension in aphasia: slowed processing, intermittent deficiency, and resource reduction. The ACT-R based Lewis and Vasishth (2005) model is used to implement these three proposals. Slowed processing is implemented as slowed execution time of parse steps; intermittent deficiency as increased random noise in activation of elements in memory; and resource reduction as reduced spreading activation. As data, we considered subject vs. object relative sentences, presented in a self-paced listening modality to 56 individuals with aphasia (IWA) and 46 matched controls. The participants heard the sentences and carried out a picture verification task to decide on an interpretation of the sentence. These response accuracies are used to identify the best parameters (for each participant) that correspond to the three hypotheses mentioned above. We show that controls have more tightly clustered (less variable) parameter values than IWA; specifically, compared to controls, among IWA there are more individuals with slow parsing times, high noise, and low spreading activation. We find that (a) individual IWA show differential amounts of deficit along the three dimensions of slowed processing, intermittent deficiency, and resource reduction, (b) overall, there is evidence for all three sources of deficit playing a role, and (c) IWA have a more variable range of parameter values than controls. An important implication is that it may be meaningless to talk about sources of deficit with respect to an abstract verage IWA; the focus should be on the individual's differential degrees of deficit along different dimensions, and on understanding the causes of variability in deficit between participants.

A practical approach to the sensitivity analysis for kinetic Monte Carlo simulation of heterogeneous catalysis.

Lattice kinetic Monte Carlo simulations have become a vital tool for predictive quality atomistic understanding of complex surface chemical reaction kinetics over a wide range of reaction conditions. In order to expand their practical value in terms of giving guidelines for the atomic level design of catalytic systems, it is very desirable to readily evaluate a sensitivity analysis for a given model. The result of such a sensitivity analysis quantitatively expresses the dependency of the turnover frequency, being the main output variable, on the rate constants entering the model. In the past, the application of sensitivity analysis, such as degree of rate control, has been hampered by its exuberant computational effort required to accurately sample numerical derivatives of a property that is obtained from a stochastic simulation method. In this study, we present an efficient and robust three-stage approach that is capable of reliably evaluating the sensitivity measures for stiff microkinetic models as we demonstrate using the CO oxidation on RuO2(110) as a prototypical reaction. In the first step, we utilize the Fisher information matrix for filtering out elementary processes which only yield negligible sensitivity. Then we employ an estimator based on the linear response theory for calculating the sensitivity measure for non-critical conditions which covers the majority of cases. Finally, we adapt a method for sampling coupled finite differences for evaluating the sensitivity measure for lattice based models. This allows for an efficient evaluation even in critical regions near a second order phase transition that are hitherto difficult to control. The combined approach leads to significant computational savings over straightforward numerical derivatives and should aid in accelerating the nano-scale design of heterogeneous catalysts.

Aldosterone Synthase Inhibition Improves Glucose Tolerance in Zucker Diabetic Fatty (ZDF) Rats.

Plasma aldosterone is elevated in type 2 diabetes and obesity in experimental and clinical studies and can act to inhibit both glucose-stimulated insulin secretion by the ß-cell and insulin signaling. Currently mineralocorticoid receptor antagonism is the best characterized treatment to ameliorate aldosterone-mediated effects. A second alternative is inhibition of aldosterone synthase, an approach with protective effects on end-organ damage in heart or kidney in animal models. The effect of aldosterone synthase inhibition on metabolic parameters in type 2 diabetes is not known. Therefore, male Zucker diabetic fatty (ZDF) rats were treated for 11 weeks with the aldosterone synthase inhibitor FAD286, beginning at 7 weeks of age. Results were compared with the mineralocorticoid receptor antagonist eplerenone. Plasma aldosterone was abolished by FAD286 and elevated more than 9-fold by eplerenone. The area under the curve calculated from an oral glucose tolerance test (OGTT) was lower and overall insulin response during OGTT was increased by FAD286. In contrast, eplerenone elevated blood glucose levels and blunted insulin secretion during the OGTT. Fasting glucose was lowered and fasting insulin was increased by FAD286 in the prediabetic state. Glycated hemoglobin was lowered by FAD286, whereas eplerenone showed no effect. We conclude that aldosterone synthase inhibition, in contrast to mineralocorticoid receptor antagonism, has the potential for beneficial effects on metabolic parameters in type 2 diabetes.

Retrieval interference in reflexive processing: experimental evidence from Mandarin, and computational modeling.

We conducted two eye-tracking experiments investigating the processing of the Mandarin reflexive ziji in order to tease apart structurally constrained accounts from standard cue-based accounts of memory retrieval. In both experiments, we tested whether structurally inaccessible distractors that fulfill the animacy requirement of ziji influence processing times at the reflexive. In Experiment 1, we manipulated animacy of the antecedent and a structurally inaccessible distractor intervening between the antecedent and the reflexive. In conditions where the accessible antecedent mismatched the animacy cue, we found inhibitory interference whereas in antecedent-match conditions, no effect of the distractor was observed. In Experiment 2, we tested only antecedent-match configurations and manipulated locality of the reflexive-antecedent binding (Mandarin allows non-local binding). Participants were asked to hold three distractors (animate vs. inanimate nouns) in memory while reading the target sentence. We found slower reading times when animate distractors were held in memory (inhibitory interference). Moreover, we replicated the locality effect reported in previous studies. These results are incompatible with structure-based accounts. However, the cue-based ACT-R model of Lewis and Vasishth (2005) cannot explain the observed pattern either. We therefore extend the original ACT-R model and show how this model not only explains the data presented in this article, but is also able to account for previously unexplained patterns in the literature on reflexive processing.

A framework for modeling the interaction of syntactic processing and eye movement control.

We explore the interaction between oculomotor control and language comprehension on the sentence level using two well-tested computational accounts of parsing difficulty. Previous work (Boston, Hale, Vasishth, & Kliegl, 2011) has shown that surprisal (Hale, 2001; Levy, 2008) and cue-based memory retrieval (Lewis & Vasishth, 2005) are significant and complementary predictors of reading time in an eyetracking corpus. It remains an open question how the sentence processor interacts with oculomotor control. Using a simple linking hypothesis proposed in Reichle, Warren, and McConnell (2009), we integrated both measures with the eye movement model EMMA (Salvucci, 2001) inside the cognitive architecture ACT-R (Anderson et al., 2004). We built a reading model that could initiate short "Time Out regressions" (Mitchell, Shen, Green, & Hodgson, 2008) that compensate for slow postlexical processing. This simple interaction enabled the model to predict the re-reading of words based on parsing difficulty. The model was evaluated in different configurations on the prediction of frequency effects on the Potsdam Sentence Corpus. The extension of EMMA with postlexical processing improved its predictions and reproduced re-reading rates and durations with a reasonable fit to the data. This demonstration, based on simple and independently motivated assumptions, serves as a foundational step toward a precise investigation of the interaction between high-level language processing and eye movement control.

What eye movements can tell us about sentence comprehension.

Eye movement data have proven to be very useful for investigating human sentence processing. Eyetracking research has addressed a wide range of questions, such as recovery mechanisms following garden-pathing, the timing of processes driving comprehension, the role of anticipation and expectation in parsing, the role of semantic, pragmatic, and prosodic information, and so on. However, there are some limitations regarding the inferences that can be made on the basis of eye movements. One relates to the nontrivial interaction between parsing and the eye movement control system which complicates the interpretation of eye movement data. Detailed computational models that integrate parsing with eye movement control theories have the potential to unpack the complexity of eye movement data and can therefore aid in the interpretation of eye movements. Another limitation is the difficulty of capturing spatiotemporal patterns in eye movements using the traditional word-based eyetracking measures. Recent research has demonstrated the relevance of these patterns and has shown how they can be analyzed. In this review, we focus on reading, and present examples demonstrating how eye movement data reveal what events unfold when the parser runs into difficulty, and how the parsing system interacts with eye movement control. WIREs Cogn Sci 2013, 4:125-134. doi: 10.1002/wcs.1209 For further resources related to this article, please visit the WIREs website.