TY - JOUR A1 - Mätzig, Paul A1 - Vasishth, Shravan A1 - Engelmann, Felix A1 - Caplan, David A1 - Burchert, Frank T1 - A computational investigation of sources of variability in sentence comprehension difficulty in aphasia JF - Topics in cognitive science N2 - 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. KW - Sentence comprehension KW - Aphasia KW - Computational modeling KW - Cue-based retrieval Y1 - 2018 U6 - https://doi.org/10.1111/tops.12323 SN - 1756-8757 SN - 1756-8765 VL - 10 IS - 1 SP - 161 EP - 174 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 - 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 -