New paper (to appear in Open Mind):

A postdoc in our lab, Dario Paape, has had a paper accepted in the MIT Press open access journal Open Mind, which is one of the few serious open access journals available as an outlet for psycholinguists (another is Glossa Psycholinguistics). Unlike many of the so-called open access journals out there, Open Mind is a credible journal, not least because of its editorial board (the editor in chief is none other than Ted Gibson). The review process was as or more thoughtful and more thorough than I have experience in journals like Journal of Memory and Language (definitely a notch over Cognition). I am hopeful that we as a community can break free from these for-profit publishers and move towards open access journals like Open Mind and Glossa Psycholinguistics.

Download preprint from here: https://psyarxiv.com/2ztgw/

Title: Does local coherence lead to targeted regressions and illusions of grammaticality?

Authors: Dario Paape, Shravan Vasishth, and Ralf Engbert

Abstract: Local coherence effects arise when the human sentence processor is temporarily misled by a locally grammatical but globally ungrammatical analysis ("The coach smiled at THE PLAYER TOSSED A FRISBEE by the opposing team"). It has been suggested that such effects occur either because sentence processing occurs in a bottom-up, self-organized manner rather than being under constant grammatical supervision (Tabor, Galantucci, & Richardson, 2004), or because local coherence can disrupt processing due to readers maintaining uncertainty about previous input (Levy, 2008). We report the results of an eye-tracking study in which subjects read German grammatical and ungrammatical sentences that either contained a locally coherent substring or not and gave binary grammaticality judgments. In our data, local coherence affected on-line processing immediately at the point of the manipulation. There was, however, no indication that local coherence led to illusions of grammaticality (a prediction of self-organization), and only weak, inconclusive support for local coherence leading to targeted regressions to critical context words (a prediction of the uncertain-input approach). We discuss implications for self-organized and noisy-channel models of local coherence.

New paper: Individual differences in cue-weighting in sentence comprehension: An evaluation using Approximate Bayesian Computation

My PhD student Himanshu Yadav has recently submitted this amazing paper for review to a journal. This is the first in a series of papers that we are working on relating to the important topic of individual-level variability in sentence processing, a topic of central concern in our Collaborative Research Center on variability at Potsdam.

Download the preprint from here: https://psyarxiv.com/4jdu5/

Title: Individual differences in cue-weighting in sentence comprehension: An evaluation using Approximate Bayesian Computation

Authors: Himanshu Yadav, Dario Paape, Garrett Smith, Brian Dillon, and Shravan Vasishth

Abstract: Cue-based retrieval theories of sentence processing assume that syntactic dependencies are resolved through a content-addressable search process. An important recent claim is that in certain dependency types, the retrieval cues are weighted such that one cue dominates. This cue-weighting proposal aims to explain the observed average behavior, but here we show that there is systematic individual-level variation in cue weighting. Using the Lewis and Vasishth cue-based retrieval model, we estimated individual-level parameters for processing speed and cue weighting using 13 published datasets; hierarchical Approximate Bayesian Computation (ABC) was used to estimate the parameters. The modeling reveals a nuanced picture of cue weighting: we find support for the idea that some participants weight cues differentially, but not all participants do. Only fast readers tend to have the higher weighting for structural cues, suggesting that reading proficiency might be associated with cue weighting. A broader achievement of the work is to demonstrate how individual differences can be investigated in computational models of sentence processing without compromising the complexity of the model.

New paper: The benefits of preregistration for hypothesis-driven bilingualism research

Download from: here

The benefits of preregistration for hypothesis-driven bilingualism research

Daniela Mertzen, Sol Lago and Shravan Vasishth

Preregistration is an open science practice that requires the specification of research hypoth- eses and analysis plans before the data are inspected. Here, we discuss the benefits of preregis- tration for hypothesis-driven, confirmatory bilingualism research. Using examples from psycholinguistics and bilingualism, we illustrate how non-peer reviewed preregistrations can serve to implement a clean distinction between hypothesis testing and data exploration. This distinction helps researchers avoid casting post-hoc hypotheses and analyses as con- firmatory ones. We argue that, in keeping with current best practices in the experimental sciences, preregistration, along with sharing data and code, should be an integral part of hypothesis-driven bilingualism research.

Freshly minted professor from our lab: Prof. Dr. Titus von der Malsburg

 One of my first PhD students, Titus von der Malsburg, has just been sworn in as a Professor of Psycholinguistics and Cognitive Modeling (tenure track assistant professor) at the Institute of Linguistics, University of Stuttgart in Germany. Stuttgart is one of the most exciting places to be in Germany for computationally oriented scientists.  

Titus is the eighth professor coming out of my lab.  He does very exciting work in psycholinguistics; check out his work here.