TY - JOUR A1 - Nicenboim, Bruno A1 - Vasishth, Shravan A1 - Rösler, Frank T1 - Are words pre-activated probabilistically during sentence comprehension? BT - evidence from new data and a Bayesian random-effects meta-analysis using publicly available data JF - Neuropsychologia : an international journal in behavioural and cognitive neuroscience N2 - Several studies (e.g., Wicha et al., 2003b; DeLong et al., 2005) have shown that readers use information from the sentential context to predict nouns (or some of their features), and that predictability effects can be inferred from the EEG signal in determiners or adjectives appearing before the predicted noun. While these findings provide evidence for the pre-activation proposal, recent replication attempts together with inconsistencies in the results from the literature cast doubt on the robustness of this phenomenon. Our study presents the first attempt to use the effect of gender on predictability in German to study the pre-activation hypothesis, capitalizing on the fact that all German nouns have a gender and that their preceding determiners can show an unambiguous gender marking when the noun phrase has accusative case. Despite having a relatively large sample size (of 120 subjects), both our preregistered and exploratory analyses failed to yield conclusive evidence for or against an effect of pre-activation. The sign of the effect is, however, in the expected direction: the more unexpected the gender of the determiner, the larger the negativity. The recent, inconclusive replication attempts by Nieuwland et al. (2018) and others also show effects with signs in the expected direction. We conducted a Bayesian random-ef-fects meta-analysis using our data and the publicly available data from these recent replication attempts. Our meta-analysis shows a relatively clear but very small effect that is consistent with the pre-activation account and demonstrates a very important advantage of the Bayesian data analysis methodology: we can incrementally accumulate evidence to obtain increasingly precise estimates of the effect of interest. KW - ERP KW - pre-activation KW - predictions KW - grammatical gender KW - Bayesian meta-analysis Y1 - 2020 U6 - https://doi.org/10.1016/j.neuropsychologia.2020.107427 SN - 0028-3932 SN - 1873-3514 VL - 142 PB - Elsevier Science CY - Oxford ER - TY - JOUR A1 - Vasishth, Shravan A1 - Nicenboim, Bruno A1 - Beckman, Mary E. A1 - Li, Fangfang A1 - Kong, Eun Jong T1 - Bayesian data analysis in the phonetic sciences BT - a tutorial introduction JF - Journal of phonetics N2 - This tutorial analyzes voice onset time (VOT) data from Dongbei (Northeastern) Mandarin Chinese and North American English to demonstrate how Bayesian linear mixed models can be fit using the programming language Stan via the R package brms. Through this case study, we demonstrate some of the advantages of the Bayesian framework: researchers can (i) flexibly define the underlying process that they believe to have generated the data; (ii) obtain direct information regarding the uncertainty about the parameter that relates the data to the theoretical question being studied; and (iii) incorporate prior knowledge into the analysis. Getting started with Bayesian modeling can be challenging, especially when one is trying to model one’s own (often unique) data. It is difficult to see how one can apply general principles described in textbooks to one’s own specific research problem. We address this barrier to using Bayesian methods by providing three detailed examples, with source code to allow easy reproducibility. The examples presented are intended to give the reader a flavor of the process of model-fitting; suggestions for further study are also provided. All data and code are available from: https://osf.io/g4zpv. KW - Bayesian data analysis KW - Linear mixed models KW - Voice onset time KW - Gender effects KW - Vowel duration Y1 - 2018 U6 - https://doi.org/10.1016/j.wocn.2018.07.008 SN - 0095-4470 VL - 71 SP - 147 EP - 161 PB - Elsevier CY - London ER - TY - JOUR A1 - Vasishth, Shravan A1 - Nicenboim, Bruno A1 - Engelmann, Felix A1 - Burchert, Frank T1 - Computational Models of Retrieval Processes in Sentence Processing JF - Trends in Cognitive Sciences N2 - 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. Y1 - 2019 U6 - https://doi.org/10.1016/j.tics.2019.09.003 SN - 1364-6613 SN - 1879-307X VL - 23 IS - 11 SP - 968 EP - 982 PB - Elsevier CY - London ER - TY - THES A1 - Nicenboim, Bruno T1 - Dependency resolution as a retrieval process T1 - Dependenzauflösung als ein Gedächtnisabrufsprozess BT - experimental evidence and computational modeling BT - experimentelle Evidenz und komputationelle Modellierung N2 - My thesis focused on the predictions of the activation-based model of Lewis and Vasishth (2005) to investigate the evidence for the use of the memory system in the formation of non-local dependencies in sentence comprehension. The activation-based model, which follows the Adaptive Control of Thought-Rational framework (ACT-R; Anderson et al., 2004), has been used to explain locality effects and similarity-based interference by assuming that dependencies are resolved by a cue-based retrieval mechanism, and that the retrieval mechanism is affected by decay and interference. Both locality effects and (inhibitory) similarity-based interference cause increased difficulty (e.g., longer reading times) at the site of the dependency completion where a retrieval is assumed: (I) Locality effects are attributed to the increased difficulty in the retrieval of a dependent when the distance from its retrieval site is increased. (II) Similarity-based interference is attributed to the retrieval being affected by the presence of items which have similar features as the dependent that needs to be retrieved. In this dissertation, I investigated some findings problematic to the activation-based model, namely, facilitation where locality effects are expected (e.g., Levy, 2008), and the lack of similarity-based interference from the number feature in grammatical sentences (e.g., Wagers et al., 2009). In addition, I used individual differences in working memory capacity and reading fluency as a way to validate the theories investigated (Underwood, 1975), and computational modeling to achieve a more precise account of the phenomena. Regarding locality effects, by using self-paced reading and eye-tracking-while reading methods with Spanish and German data, this dissertation yielded two main findings: (I) Locality effects seem to be modulated by working memory capacity, with high-capacity participants showing expectation-driven facilitation. (II) Once expectations and other potential confounds are controlled using baselines, with increased distance, high-capacity readers can show a slow-down (i.e., locality effects) and low-capacity readers can show a speedup. While the locality effects are compatible with the activation-based model, simulations show that the speedup of low-capacity readers can only be accounted for by changing some of the assumptions of the activation-based model. Regarding similarity-based interference, two relatively high-powered self-paced reading experiments in German using grammatical sentences yielded a slowdown at the verb as predicted by the activation-based model. This provides evidence in favor of dependency creation via cue-based retrieval, and in contrast with the view that cue-based retrieval is a reanalysis mechanism (Wagers et al., 2009). Finally, the same experimental results that showed inhibitory interference from the number feature are used for a finer grain evaluation of the retrieval process. Besides Lewis and Vasishth’s (2005) activation-based model, also McElree’s (2000) direct-access model can account for inhibitory interference. These two models assume a cue-based retrieval mechanism to build dependencies, but they are based on different assumptions. I present a computational evaluation of the predictions of these two theories of retrieval. The models were compared by implementing them in a Bayesian hierarchical framework. The evaluation of the models reveals that some aspects of the data fit better under the direct access model than under the activation-based model. However, a simple extension of the activation-based model provides a comparable fit to the direct access model. This serves as a proof of concept showing potential ways to improve the original activation-based model. In conclusion, this thesis adds to the body of evidence that argues for the use of the general memory system in dependency resolution, and in particular for a cue-based retrieval mechanism. However, it also shows that some of the default assumptions inherited from ACT-R in the activation-based model need to be revised. N2 - Die vorliegende Dissertation befasst sich mit dem Aktivierungsmodell von Lewis und Vasishth (2005) um die Evidenz für die Verwendung des Arbeitsgedächtnisses bei der Bildung nicht-lokaler Dependenzen in der menschlichen Satzverarbeitung zu untersuchen. Das Aktivierungsmodell, welches auf der ‘Adaptive Control of Thought-Rational’ (ACT-R; Anderson et al., 2004) aufbaut, wird in der Literatur herangezogen, um Lokalitätseffekte und Interferenz durch Ähnlichkeit mit einem von Interferenz und Gedächtnisverfall betroffenen merkmalsbasierten Gedächtnisabrufmechanismus zu erklären. Sowohl Lokalitätseffekte als auch (inhibitorische) Interferenz durch Ähnlichkeit führen zu einer erhöhten Verarbeitungsschwierigkeit (z.B. längere Lesezeiten) an der Stelle, wo die Dependenz gebildet wird und daher ein Gedächtnisabruf anzunehmen ist: (I) Lokalitätseffekte werden durch die erhöhte Schwierigkeit erklärt, die mit dem Abruf des ersten Teils einer Dependenz einhergeht, wenn dessen Distanz zu der Stelle, die den Gedächtnisabruf auslöst (d.h. der zweite Teil der Dependenz), vergrößert wird. (II) Interferenz durch Ähnlichkeit wird dadurch erklärt, dass der Gedächtnisabruf von der Anwesenheit von Elementen mit denselben Merkmalen wie die des abzurufenden Teils der Dependenz beeinträchtigt wird. In dieser Dissertation untersuche ich einige Erkenntnisse, die das Aktivierungsmodell herausfordern, namentlich fazilitatorische Effekte an Stellen, wo Lokalitätseffekte zu erwarten wären (z.B. Levy, 2008), sowie die Abwesenheit von Interferenz durch Ähnlichkeit in Experimenten, die den Numerus manipulieren (z.B. Wagers et al., 2009). Des Weiteren verwende ich Messwerte der individuellen Unterschiede in der Arbeitsgedächtnisleistung und in der Leseflüssigkeit um die untersuchten Theorien zu validieren, und komputationale Modellierung um ein genaueres Bild der untersuchten Phänomene zu zeichnen zu können. Was die Lokalitätseffekte angeht, so werden in dieser Dissertation hauptsächlich zwei Erkenntnisse vorgestellt, die auf mit Selbst-gesteuertem-Lesen und Eyetracking erhobenen Daten zum Spanischen und Deutschen basieren. (I) Lokalitätseffekte scheinen von der Arbeitsgedächtniskapazität moduliert zu werden: Probanden mit hoher Arbeitsgedächtniskapazität zeigen erwartungsgesteuerte fazilitatorische Effekte. (II) Wenn Erwartungen und andere potentielle Störvariablen durch geeignete Baselines kontrolliert werden, können bei Probanden mit starkem Arbeitsgedächtnis verlangsamte Lesezeiten (d. h., Lokalitätseffekte) und bei Probanden mit schwachem Arbeitsgedächtnis verkürzte Lesezeiten beobachtet werden. Während Lokalitätseffekte mit dem Aktivierungsmodell vereinbar sind, zeigen Simulationen, dass die fazilitatorischen Effekte der Probanden mit schwächerem Arbeitsgedächtnis nur dann von dem Aktivierungsmodell erklärt werden können, wenn einige der Modellannahmen geändert werden. Was Interferenz durch Ähnlichkeit angeht, so werden in dieser Dissertation zwei Experimente mit Selbst-gesteuertem-Lesen zum Deutschen vorgestellt, die eine relativ hohe statistische Teststärke haben. Grammatische Sätze führen hier zu verlangsamten Lesezeiten am Verb, wie es das Aktivierungsmodell vorhersagt. Diese Ergebnisse sind Evidenz für die Bildung von Dependenzen mittels merkmalsbasiertem Gedächtnisabruf und können nicht durch einen wie von Wagers et al. (2009) vorgeschlagenen Reanalysemechanismus erklärt werden. Letztendlich werden dieselben empirischen Daten, die durch den Numerus ausgelöste inhibitorische Interferenz zeigen, für eine detailliertere, simulationsbasierte Betrachtung des Gedächtnisabrufprozesses verwendet. Neben dem Aktivierungsmodell von Lewis und Vasishth (2005) kann auch das Modell eines direkten Gedächtniszugriffs von McElree (2000) die inhibitorische Interferenz erklären. Beide Modelle nehmen für die Bildung von Dependenzen einen merkmalsbasierten Gedächtniszugriffsmechanismus an, aber sie fußen auf unterschiedlichen Annahmen. Ich stelle eine komputationale Evaluation der Vorhersagen dieser beiden Gedächtniszugriffsmodelle vor. Um die beiden Modelle zu vergleichen, werden sie als Bayessche hierarchische Modelle implementiert. Die Evaluation der Modelle zeigt, dass einige Aspekte der empirischen Daten besser von McElrees Modell als von Lewis’ und Vasishths Modell erklärt werden. Eine einfache Erweiterung des Aktivierungsmodells erklärt die Daten jedoch ähnlich gut wie McElrees Modell. Kurz, diese Dissertation liefert weitere Evidenz für die These, dass das allgemeine Gedächtnissystem — und ein merkmalsbasierter Abrufmechanismus im Besonderen — beim Bilden linguistischer Dependenzen Anwendung findet. Es wird jedoch auch gezeigt, dass einige der Standardannahmen, die das Aktivierungsmodell von der ACT-R-Architektur geerbt hat, überdacht und angepasst werden müssen. KW - linguistics KW - working memory KW - computational modeling KW - Sprachwissenschaft KW - Arbeitsgedächtniss KW - komputationale Modellierung Y1 - 2016 ER - TY - GEN A1 - Paape, Dario L. J. F. A1 - Nicenboim, Bruno A1 - Vasishth, Shravan T1 - Does antecedent complexity affect ellipsis processing? BT - An empirical investigation N2 - In two self-paced reading experiments, we investigated the effect of changes in antecedent complexity on processing times for ellipsis. Pointer- or “sharing”-based approaches to ellipsis processing (Frazier & Clifton 2001, 2005; Martin & McElree 2008) predict no effect of antecedent complexity on reading times at the ellipsis site while other accounts predict increased antecedent complexity to either slow down processing (Murphy 1985) or to speed it up (Hofmeister 2011). Experiment 1 manipulated antecedent complexity and elision, yielding evidence against a speedup at the ellipsis site and in favor of a null effect. In order to investigate possible superficial processing on part of participants, Experiment 2 manipulated the amount of attention required to correctly respond to end-of-sentence comprehension probes, yielding evidence against a complexity-induced slowdown at the ellipsis site. Overall, our results are compatible with pointer-based approaches while casting doubt on the notion that changes antecedent complexity lead to measurable differences in ellipsis processing speed. T3 - Zweitveröffentlichungen der Universität Potsdam : Humanwissenschaftliche Reihe - 350 KW - antecedent complexity KW - ellipsis processing KW - memory pointer KW - self-paced reading KW - Bayes factor Y1 - 2017 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-403373 ER - TY - JOUR A1 - Paape, Dario L. J. F. A1 - Nicenboim, Bruno A1 - Vasishth, Shravan T1 - Does antecedent complexity affect ellipsis processing? BT - An empirical investigation JF - Glossa : a journal of general linguistics N2 - In two self-paced reading experiments, we investigated the effect of changes in antecedent complexity on processing times for ellipsis. Pointer- or “sharing”-based approaches to ellipsis processing (Frazier & Clifton 2001, 2005; Martin & McElree 2008) predict no effect of antecedent complexity on reading times at the ellipsis site while other accounts predict increased antecedent complexity to either slow down processing (Murphy 1985) or to speed it up (Hofmeister 2011). Experiment 1 manipulated antecedent complexity and elision, yielding evidence against a speedup at the ellipsis site and in favor of a null effect. In order to investigate possible superficial processing on part of participants, Experiment 2 manipulated the amount of attention required to correctly respond to end-of-sentence comprehension probes, yielding evidence against a complexity-induced slowdown at the ellipsis site. Overall, our results are compatible with pointer-based approaches while casting doubt on the notion that changes antecedent complexity lead to measurable differences in ellipsis processing speed. KW - antecedent complexity KW - ellipsis processing KW - memory pointer KW - self-paced reading KW - Bayes factor Y1 - 2017 U6 - https://doi.org/10.5334/gjgl.290 SN - 2397-1835 VL - 2 IS - 1 SP - 1 EP - 29 PB - Ubiquity Press CY - London ER - TY - JOUR A1 - Nicenboim, Bruno A1 - Vasishth, Shravan A1 - Engelmann, Felix A1 - Suckow, Katja T1 - Exploratory and confirmatory analyses in sentence processing BT - a case study of number interference in German JF - Cognitive science : a multidisciplinary journal of anthropology, artificial intelligence, education, linguistics, neuroscience, philosophy, psychology ; journal of the Cognitive Science Society N2 - 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. KW - Exploratory and confirmatory analyses KW - Sentence processing KW - Bayesian hierarchical modeling KW - Cue-based retrieval KW - Working memory KW - Similarity-based interference KW - Number interference KW - German Y1 - 2018 U6 - https://doi.org/10.1111/cogs.12589 SN - 0364-0213 SN - 1551-6709 VL - 42 SP - 1075 EP - 1100 PB - Wiley CY - Hoboken ER - TY - JOUR A1 - Albert, Aviad A1 - Nicenboim, Bruno T1 - Modeling sonority in terms of pitch intelligibility with the nucleus attraction principle JF - Cognitive science : a multidisciplinary journal of anthropology, artificial intelligence, education, linguistics, neuroscience, philosophy, psychology ; journal of the Cognitive Science Society N2 - Sonority is a fundamental notion in phonetics and phonology, central to many descriptions of the syllable and various useful predictions in phonotactics. Although widely accepted, sonority lacks a clear basis in speech articulation or perception, given that traditional formal principles in linguistic theory are often exclusively based on discrete units in symbolic representation and are typically not designed to be compatible with auditory perception, sensorimotor control, or general cognitive capacities. In addition, traditional sonority principles also exhibit systematic gaps in empirical coverage. Against this backdrop, we propose the incorporation of symbol-based and signal-based models to adequately account for sonority in a complementary manner. We claim that sonority is primarily a perceptual phenomenon related to pitch, driving the optimization of syllables as pitch-bearing units in all language systems. We suggest a measurable acoustic correlate for sonority in terms of periodic energy, and we provide a novel principle that can account for syllabic well-formedness, the nucleus attraction principle (NAP). We present perception experiments that test our two NAP-based models against four traditional sonority models, and we use a Bayesian data analysis approach to test and compare them. Our symbolic NAP model outperforms all the other models we test, while our continuous bottom-up NAP model is at second place, along with the best performing traditional models. We interpret the results as providing strong support for our proposals: (i) the designation of periodic energy as the acoustic correlate of sonority; (ii) the incorporation of continuous entities in phonological models of perception; and (iii) the dual-model strategy that separately analyzes symbol-based top-down processes and signal-based bottom-up processes in speech perception. KW - Sonority KW - Pitch intelligibility KW - Periodic energy KW - Bayesian data KW - analysis KW - Speech perception KW - Phonetics and phonology Y1 - 2022 U6 - https://doi.org/10.1111/cogs.13161 SN - 0364-0213 SN - 1551-6709 VL - 46 IS - 7 PB - Wiley CY - Hoboken ER - TY - JOUR A1 - Nicenboim, Bruno A1 - Vasishth, Shravan T1 - Models of retrieval in sentence comprehension BT - a computational evaluation using Bayesian hierarchical modeling JF - Journal of memory and language N2 - Research on similarity-based interference has provided extensive evidence that the formation of dependencies between non-adjacent words relies on a cue-based retrieval mechanism. There are two different models that can account for one of the main predictions of interference, i.e., a slowdown at a retrieval site, when several items share a feature associated with a retrieval cue: Lewis and Vasishth’s (2005) activation-based model and McElree’s (2000) direct-access model. Even though these two models have been used almost interchangeably, they are based on different assumptions and predict differences in the relationship between reading times and response accuracy. The activation-based model follows the assumptions of the ACT-R framework, and its retrieval process behaves as a lognormal race between accumulators of evidence with a single variance. Under this model, accuracy of the retrieval is determined by the winner of the race and retrieval time by its rate of accumulation. In contrast, the direct-access model assumes a model of memory where only the probability of retrieval can be affected, while the retrieval time is drawn from the same distribution; in this model, differences in latencies are a by-product of the possibility of backtracking and repairing incorrect retrievals. We implemented both models in a Bayesian hierarchical framework in order to evaluate them and compare them. The data show that correct retrievals take longer than incorrect ones, and this pattern is better fit under the direct-access model than under the activation-based model. This finding does not rule out the possibility that retrieval may be behaving as a race model with assumptions that follow less closely the ones from the ACT-R framework. By introducing a modification of the activation model, i.e., by assuming that the accumulation of evidence for retrieval of incorrect items is not only slower but noisier (i.e., different variances for the correct and incorrect items), the model can provide a fit as good as the one of the direct-access model. This first ever computational evaluation of alternative accounts of retrieval processes in sentence processing opens the way for a broader investigation of theories of dependency completion. KW - Cognitive modeling KW - Sentence processing KW - Working memory KW - Cue-based retrieval KW - Similarity-based interference KW - Bayesian hierarchical modeling Y1 - 2018 U6 - https://doi.org/10.1016/j.jml.2017.08.004 SN - 0749-596X SN - 1096-0821 VL - 99 SP - 1 EP - 34 PB - Elsevier CY - San Diego ER - TY - JOUR A1 - Vasishth, Shravan A1 - Nicenboim, Bruno T1 - Statistical Methods for Linguistic Research: Foundational Ideas - Part I JF - Language and linguistics compass N2 - We present the fundamental ideas underlying statistical hypothesis testing using the frequentist framework. We start with a simple example that builds up the one-sample t-test from the beginning, explaining important concepts such as the sampling distribution of the sample mean, and the iid assumption. Then, we examine the meaning of the p-value in detail and discuss several important misconceptions about what a p-value does and does not tell us. This leads to a discussion of Type I, II error and power, and Type S and M error. An important conclusion from this discussion is that one should aim to carry out appropriately powered studies. Next, we discuss two common issues that we have encountered in psycholinguistics and linguistics: running experiments until significance is reached and the ‘garden-of-forking-paths’ problem discussed by Gelman and others. The best way to use frequentist methods is to run appropriately powered studies, check model assumptions, clearly separate exploratory data analysis from planned comparisons decided upon before the study was run, and always attempt to replicate results. Y1 - 2016 U6 - https://doi.org/10.1111/lnc3.12201 SN - 1749-818X VL - 10 SP - 349 EP - 369 PB - Wiley-Blackwell CY - Hoboken ER -