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  -